Search Results (22)

Accurate diagnosis of sinusitis is essential due to its widespread prevalence and its considerable impact on patient quality of life. While multiple imaging techniques are available for detecting maxillary sinus, computed tomography (CT) remains the preferred modality because of its high sensitivity and spatial resolution. Although recent advances in deep learning have led to the development of automated methods for sinusitis classification, many existing models perform poorly in the presence of complex pathological features and offer limited interpretability, which hinders their integration into clinical workflows. In this study, we propose a hybrid deep learning framework that combines EfficientNetB0, a convolutional neural network, with the Swin Transformer, a vision transformer, to improve feature representation. An attention-based fusion module is used to integrate both local and global information, thereby enhancing diagnostic accuracy. To improve transparency and support clinical adoption, the model incorporates explainable artificial intelligence (XAI) techniques using Gradient-weighted Class Activation Mapping (Grad-CAM). This allows for visualization of the regions influencing the model’s predictions, helping radiologists assess the clinical relevance of the results. We evaluate the proposed method on a curated maxillary sinus CT dataset covering four diagnostic categories: Normal, Opacified, Polyposis, and Retention Cysts. The model achieves a classification accuracy of 95.83%, with precision, recall, and F1 score all at 95%. Grad-CAM visualizations indicate that the model consistently focuses on clinically significant regions of the sinus anatomy, supporting its potential utility as a reliable diagnostic aid in medical practice. Full article

The omega-3 polyunsaturated fatty acids (n-3 PUFA) in animal-derived foods are increasingly important for human health. Sacha inchi (Plukenetia volubilis L.), rich in n-3 PUFA, is a promising feedstuff for producing n-3 PUFA-enriched animal products. However, research on dietary Sacha inchi oil (SIO) supplementation in laying hens remains limited. Therefore, this study aimed to evaluate the effects of SIO on production performance, egg quality, and yolk fatty acid (FA) composition in laying hens. A total of 192 hybrid hens [(♂ White Leghorn × ♀ Egyptian Fayoumi); initial body weight: 1910 ± 22.14 g; age: 25 weeks old] were randomly assigned one of the four diets: a basal diet (CONT), and three tested diets based on CONT with the addition of 1.5%, 3.0%, and 4.5% SIO (as-feed basis) (SI15, SI30, and SI45, respectively). Each dietary treatment included 48 hens housed in 12 battery cages for 56 days with 4 birds per cage. Increasing dietary SIO levels significantly reduced average daily feed intake (p < 0.05). Egg yolk weight linearly increased (p < 0.05) with higher SIO inclusion, while other egg quality traits were unaffected. SIO supplementation significantly increased (p = 0.001) yolk n-3 PUFA level (from 0.79% to 8.29% on day 28, and from 0.87% to 9.13% on day 56) and substantially reduced the n-6/n-3 PUFA ratio by about nine-fold on both 28 and 56 days. In conclusion, SIO is a promising n-3 PUFA-rich feed ingredient for egg production. Adding 3.0–4.5% SIO in laying hen diets can enhance egg yolk weight and n-3 PUFA level while reducing feed intake without negatively affecting egg production or quality. Full article

Many breast cancer patients follow a self-managed treatment pathway, which may lead to gaps in the data available to healthcare professionals, such as information about patients’ everyday symptoms at home. Mobile apps have the potential to bridge this information gap, leading to more effective treatments and interventions, as well as helping breast cancer patients monitor and manage their symptoms. In this paper, we elicit design requirements for breast cancer symptom-management mobile apps using a systematic review following the PRISMA framework. We then evaluate existing cancer symptom-management apps found on the Apple store according to the extent to which they meet these requirements. We find that, whilst some requirements are well supported (such as functionality to record multiple symptoms and provision of information), others are currently not being met, particularly interoperability, functionality related to responses from healthcare professionals, and personalisation. Much work is needed for cancer patients and healthcare professionals to experience the benefits of digital health innovation. The article demonstrates a formal requirements model, in which requirements are categorised as functional and non-functional, and presents a proposal for conceptual design for future mobile apps. Full article

Understanding genetic diversity, runs of homozygosity (ROH), and selection signatures is critical for the conservation and breeding management of native Japanese chickens. In this study, genetic diversity, ROH, and selection signatures in 11 populations of seven native Japanese breeds and three foreign breeds with different genetic and behavioral backgrounds were investigated using 11,493 SNPs identified through restriction-site-associated DNA sequencing. The Oh-Shamo (OSM), an aggressive cockfighting breed, exhibited the highest genetic diversity. Six native Japanese breeds, Ingie (IG), Ryujin-Jidori (RYU), Tosa-Jidori (TJI), Tosa-Kukin (TKU), Nagoya (NAG), and Ukkokei (UK), showed intermediate levels of genetic diversity and ROH. Population analyses grouped the 11 populations into four distinct clusters: (1) five populations comprising three foreign breeds (the Fayoumi inbred line, closed-colony G line of White Leghorn, commercial T line of WL, and White Plymouth Rock) and the IG Japanese breed; (2) OSM and two old Jidori breeds (RYU and TJI); (3) TKU and UK; and (4) the meat-type Nagoya breed. ROH and Fst analyses identified seven SNPs on chromosomes 13, 17, 20, 24, and 26, five of which were candidate genetic variants for fear-related behavior. These findings provide insights into genetic diversity and conserved genomic segments valuable for breeding and conservation in Japanese chicken breeds. Full article

Russian Snow White (RSW) chickens are characterized by high egg production, extreme resistance to low temperatures, disease resistance, and by the snow-white color of the day-old chicks. Studying the genome of this unique chicken breed will reveal its evolutionary history and help to understand the molecular genetic mechanisms underlying the unique characteristics of this breed, which will open new breeding opportunities and support future studies. We have sequenced and made a de novo assembly of the whole RSW genome using deep sequencing (250×) by the short reads. The genome consists of 40 chromosomes with a total length of 1.1 billion nucleotide pairs. Phylogenetic analysis placed the RSW near the White Leghorn, Fayoumi, and Houdan breeds. Comparison with other chicken breeds revealed a wide pool of mutations unique to the RSW. The functional annotation of these mutations showed the adaptation of genes associated with the development of the nervous system, thermoreceptors, purine receptors, and the TGF-beta pathway, probably caused by selection for low temperatures. We also found adaptation of the immune system genes, likely driven by selection for resistance to viral diseases. Integration with previous genome-wide association studies (GWAS) suggested several causal single nucleotide polymorphisms (SNPs). Specifically, we identified an RSW-specific missense mutation in the RALYL gene, presumably causing the snow-white color of the day-old chicks, and an RSW-specific missense mutation in the TLL1 gene, presumably affecting the egg weight. Full article

Tribolium castaneum is a challenging pest of stored products, causing significant economic losses. The present study explored the efficacy of Coridothymus capitatus essential oil and its primary constituent, carvacrol, as eco-friendly alternatives for managing this pest. To evaluate their insecticidal potential, repellency, fumigant toxicity, and antifeedant properties, progeny inhibition assays were performed. Carvacrol exhibited superior repellency compared to the essential oil, achieving a 92% repellency rate at 2 mg/cm². Both compounds demonstrated significant fumigant toxicity against T. castaneum, with LC₅₀ values of 168.47 and 106.5 μL/L for the essential oil and carvacrol, respectively, after 24 h. Carvacrol also outperformed the essential oil in antifeedant activity, inducing an 80.7% feeding deterrence at 1.17 mg/g. Moreover, both treatments effectively suppressed the development of the pest’s progeny. These results collectively underscore the potent insecticidal properties of C. capitatus essential oil and carvacrol, particularly carvacrol, as promising candidates for the sustainable management of T. castaneum in stored product protection. Full article

This study investigated the effects of the β-mannanase enzyme and soyhulls on production performance, economics, egg quality, hematology and serum biochemistry, nutrient digestibility, gut morphology, digesta viscosity, and excreta consistency in laying hens during the late peak production phase (37 to 40 weeks of age). Golden brown hens (RIR × Fayoumi; n = 200) were fed a control diet (no soyhulls or enzymes) and diets containing four combinations, i.e., 3% soyhulls with 20 mg/kg β-mannanase (D1), 3% soyhulls with 30 mg/kg β-mannanase (D2), 9% soyhulls with 20 mg/kg β-mannanase (D3), and 9% soyhulls with 30 mg/kg β-mannanase (D4), for four weeks in four replicates of 10 birds each. Overall, a significantly higher (p < 0.05) feed intake, weight gain, feed conversion ratio, and water intake were calculated in the D2 group as compared to the control and remaining combinations of soyhulls and β-mannanase. No mortality was recorded during the entire experiment. Economically, the D1 and D2 groups showed the best results as compared to the D3 and D4 groups. Egg quality parameters like egg weight, shell weight and shell thickness, yolk weight, albumen weight and height, and the Haugh unit remained unchanged (p > 0.05). Similarly, the D2 group showed significantly lower total cholesterol, LDL, and VLDL levels and enhanced gut morphology with greater villus width, height, crypt depth, and surface area across intestinal segments. Crude protein (CP), crude fiber (CF), crude fat, and ash digestibility were higher (p < 0.05) in the D1 and D2 groups compared to the control. Digesta viscosity, excreta consistency, and other egg quality parameters remained unaffected. In conclusion, the dietary inclusion of a combination of 3% soyhulls and 30 mg/kg β-mannanase may have potential benefits for laying hens by improving some production performance and egg quality indicators and economics, lowering blood cholesterol, LDL, and VLDL levels, enhancing nutrient digestibility, and improving gut morphology without affecting egg quality. Full article

Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate the use of deep learning techniques, particularly generative adversarial networks (GANs), in combination with convolutional neural networks (CNNs), for the classification of sinus pathologies in medical imaging data. The dataset is composed of images obtained through computed tomography (CT) scans, covering cases classified into “Moderate”, “Severe”, and “Normal” classes. The lightweight GAN is applied to augment a dataset by creating synthetic images, which are then used to train and test the ResNet-50 and ResNeXt-50 models. The model performance is optimized using random search to perform hyperparameter tuning, and the evaluation is conducted extensively for various metrics like accuracy, precision, recall, and the F1-score. The results demonstrate the effectiveness of the proposed approach in accurately classifying sinus pathologies, with the ResNeXt-50 model achieving superior performance with accuracy: 91.154, precision: 0.917, recall: 0.912, and F1-score: 0.913 compared to ResNet-50. This study highlights the potential of GAN-based data augmentation and deep learning techniques in enhancing the diagnosis of maxillary sinus diseases. Full article

This study investigated the anticoccidial activity of spinach (Spinacia oleracea) whole-plant extract against Eimeria tenella, both in vitro and in vivo. For this purpose, one hundred 8-day-old broiler chicks of both sexes were divided into four groups (n = 25 in each group). Chicks in the first group served as the negative control (non-treated–non-infected). Chicks in the second group were challenged at 18 days old with 5 × 10⁴ E. tenella sporulated oocysts. The third group was challenged with 5 × 10⁴ sporulated E. tenella oocysts at 18 days old after receiving spinach extract at a dose of 50 mg/kg at 8 days old. The fourth group received 0.2 mg/kg diclazuril (Coxiril^® 0.2%) in their diet two days before being orally infected with 5 × 10⁴ sporulated E. tenella oocysts and this continued till day 10 post-infection (PI). The growth performance, clinical symptoms, oocyst shedding, histological findings, and biochemical parameters were used to evaluate the efficacy on day 8 PI when the infection was at its peak. A gas chromatography examination revealed that omega-3 fatty acids were the main constituents of the spinach extract, followed by oleic acid, palmitic acid, and phytol, with amounts of 23.37%, 17.53%, 11.26%, and 7.97%, respectively. The in vitro investigation revealed that the spinach extract at concentrations of 10% and 5% inhibited the oocyst sporulation by 52.1% and 45.1%, respectively. The 5% concentration was selected for the in vivo trial based on the results of the in vitro study. The infected–untreated group showed high levels of OPG; lower body weight; a greater number of parasite stages; few goblet cells; decreased SOD, CAT, and GPX levels; and increased MDA and NO levels. The spinach-treated group, on the other hand, showed a significant decrease in oocyst output per gram of feces (OPG), increased body weight, decreased parasitic stages, and a nearly normal number of goblet cells. Additionally, it reduced malondialdehyde (MDA) and nitric oxide (NO), while increasing superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX). In conclusion, spinach produced significant antioxidant effects, increased body weight, reduced the number of oocysts and parasite stages in the caecum, and restored the number of goblet cells relative to those of an uninfected control. Furthermore, spinach extract inhibits the sporulation percentage of E. tenella oocysts. The ethanolic extract of S. oleracea (whole plant) contained high concentrations of fatty acids, palmitic acid, Phytol, betulin, and ursolic aldehyde, all of which are known to regulate the antioxidant pathway and modulate inflammatory processes and may be the main reason for its anticoccidial activity. Full article

Traffic flow monitoring plays a crucial role in Intelligent Transportation Systems (ITS) by dealing with real-time data on traffic situations and allowing effectual traffic management and optimization. A typical approach used for traffic flow monitoring frequently depends on collection and analysis of the data through a manual process that is not only resource-intensive, but also a time-consuming process. Recently, Artificial Intelligence (AI) approaches like ensemble learning demonstrate promising outcomes in numerous ITS applications. With this stimulus, the current study proposes an Improved Artificial Rabbits Optimization with Ensemble Learning-based Traffic Flow Monitoring System (IAROEL-TFMS) for ITS. The primary intention of the proposed IAROEL-TFMS technique is to employ the feature subset selection process with optimal ensemble learning so as to predict the traffic flow. In order to accomplish this, the IAROEL-TFMS technique initially designs the IARO-based feature selection approach to elect a set of features. In addition, the traffic flow is predicted using the ensemble model that comprises a Gated Recurrent Unit (GRU), Long Short-term Memory (LSTM), and Bidirectional Gated Recurrent Unit (BiGRU). Finally, the Grasshopper Optimization Algorithm (GOA) is applied for the adjustment of the optimum hyperparameters of all three DL models. In order to highlight the improved prediction results of the proposed IAROEL-TFMS algorithm, an extensive range of simulations was conducted. The simulation outcomes imply the supremacy of the IAROEL-TFMS methodology over other existing approaches with a minimum RMSE of 16.4539. Full article

Alzheimer’s disease (AD) is a progressive neurological illness characterized by memory loss and cognitive deterioration. Dapagliflozin was suggested to attenuate the memory impairment associated with AD; however, its mechanisms were not fully elucidated. This study aims to examine the possible mechanisms of the neuroprotective effects of dapagliflozin against aluminum chloride (AlCl₃)-induced AD. Rats were distributed into four groups: group 1 received saline, group 2 received AlCl₃ (70 mg/kg) daily for 9 weeks, and groups 3 and 4 were administered AlCl₃ (70 mg/kg) daily for 5 weeks. Dapagliflozin (1 mg/kg) and dapagliflozin (5 mg/kg) were then given daily with AlCl₃ for another 4 weeks. Two behavioral experiments were performed: the Morris Water Maze (MWM) and the Y-maze spontaneous alternation (Y-maze) task. Histopathological alterations in the brain, as well as changes in acetylcholinesterase (AChE) and amyloid β (Aβ) peptide activities and oxidative stress (OS) markers, were all evaluated. A western blot analysis was used for the detection of phosphorylated 5’ AMP-activated protein kinase (p-AMPK), phosphorylated mammalian target of Rapamycin (p-mTOR) and heme oxygenase-1 (HO-1). Tissue samples were collected for the isolation of glucose transporters (GLUTs) and glycolytic enzymes using PCR analysis, and brain glucose levels were also measured. The current data demonstrate that dapagliflozin represents a possible approach to combat AlCl₃-induced AD in rats through inhibiting oxidative stress, enhancing glucose metabolism and activating AMPK signaling. Full article

Parental exposure to insults was initially considered safe if stopped before conception. In the present investigation, paternal or maternal preconception exposure to the neuroteratogen chlorpyrifos was investigated in a well-controlled avian model (Fayoumi) and compared to pre-hatch exposure focusing on molecular alterations. The investigation included the analysis of several neurogenesis, neurotransmission, epigenetic and microRNA genes. A significant decrease in the vesicular acetylcholine transporter (SLC18A3) expression was detected in the female offspring in the three investigated models: paternal (57.7%, p < 0.05), maternal (36%, p < 0.05) and pre-hatch (35.6%, p < 0.05). Paternal exposure to chlorpyrifos also led to a significant increase in brain-derived neurotrophic factor (BDNF) gene expression mainly in the female offspring (27.6%, p < 0.005), while its targeting microRNA, miR-10a, was similarly decreased in both female (50.5%, p < 0.05) and male (56%, p < 0.05) offspring. Doublecortin’s (DCX) targeting microRNA, miR-29a, was decreased in the offspring after maternal preconception exposure to chlorpyrifos (39.8%, p < 0.05). Finally, pre-hatch exposure to chlorpyrifos led to a significant increase in protein kinase C beta (PKCß; 44.1%, p < 0.05), methyl-CpG-binding domain protein 2 (MBD2; 44%, p < 0.01) and 3 (MBD3; 33%, p < 0.05) genes expression in the offspring. Although extensive studies are required to establish a mechanism–phenotype relationship, it should be noted that the current investigation does not include phenotype assessment in the offspring. Full article

This study was conducted to evaluate the effect of dietary supplementation with Spirulina platensis (SP) on the productive performance, carcass characteristics, behavior, blood serum metabolites, hematological indices, and economic efficiency of Fayoumi broiler chickens for a 56-day. In total, 120 one-day-old broiler chicks were randomly distributed among four dietary treatments with three replicates (n = 10/group) for 8 weeks. The dietary treatments were a control basal diet without SP and the same basal diets supplemented with 0.25, 0.5, or 1.0% SP. Birds fed 1% Spirulina-supplemented diets recorded significantly (p < 0.05) higher body weight, weight gain, and feed conversion ratio and less overall feed intake and feeding behavior than those in the control group. No significant changes (p > 0.05) were recorded in the dressing percentage or the relative weights of internal organs among the different experimental groups, except for the thymus. Diets containing 0.5 or 1.0% SP saw an increase (p < 0.05) in serum total protein and globulin and a reduction (p < 0.05) in serum cholesterol concentration. The lymphocyte percentage in birds fed SP diets was significantly (p < 0.05) higher than in birds fed the control diet. These results suggest that adding SP up to 1% to the broiler diets could positively affect some important blood biochemical parameters, enhance their immunity response, and improve their growth performance. However, from an economic point of view, supplementation with 0.25% of SP is recommended for Fayoumi broiler chickens. Full article

We investigated the scientific research dissemination by analyzing the publications and citation data, implying that not all citations are significantly important. Therefore, as alluded to existing state-of-the-art models that employ feature-based techniques to measure the scholarly research dissemination between multiple entities, our model implements the convolutional neural network (CNN) with fastText-based pre-trained embedding vectors, utilizes only the citation context as its input to distinguish between important and non-important citations. Moreover, we speculate using focal-loss and class weight methods to address the inherited class imbalance problems in citation classification datasets. Using a dataset of 10 K annotated citation contexts, we achieved an accuracy of 90.7% along with a 90.6% f1-score, in the case of binary classification. Finally, we present a case study to measure the comprehensiveness of our deployed model on a dataset of 3100 K citations taken from the ACL Anthology Reference Corpus. We employed state-of-the-art graph visualization open-source tool Gephi to analyze the various aspects of citation network graphs, for each respective citation behavior. Full article