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While cognitive theory has advanced several candidate frameworks to explain attentional entrainment, the neural basis for the temporal allocation of attention is unknown. Here we present a new model of attentional entrainment guided by empirical evidence obtained using a cohort of 50 artificial brains. These brains were evolved in silico to perform a duration judgment task similar to one where human subjects perform duration judgments in auditory oddball paradigms. We found that the artificial brains display psychometric characteristics remarkably similar to those of human listeners and exhibit similar patterns of distortions of perception when presented with out-of-rhythm oddballs. A detailed analysis of mechanisms behind the duration distortion suggests that attention peaks at the end of the tone, which is inconsistent with previous attentional entrainment models. Instead, the new model of entrainment emphasizes increased attention to those aspects of the stimulus that the brain expects to be highly informative.
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Cardiovascular diseases remain one of the main threats to human health, significantly affecting the quality and life expectancy. Effective and prompt recognition of these diseases is crucial. This research aims to develop an effective novel hybrid method for automatically detecting dangerous arrhythmias based on cardiac patients' short electrocardiogram (ECG) fragments. This study suggests using a continuous wavelet transform (CWT) to convert ECG signals into images (scalograms) and examining the task of categorizing short 2-s segments of ECG signals into four groups of dangerous arrhythmias that are shockable, including ventricular flutter (C1), ventricular fibrillation (C2), ventricular tachycardia torsade de pointes (C3), and high-rate ventricular tachycardia (C4). We propose developing a novel hybrid neural network with a deep learning architecture to classify dangerous arrhythmias. This work utilizes actual electrocardiogram (ECG) data obtained from the PhysioNet database, alongside artificially generated ECG data produced by the Synthetic Minority Over-sampling Technique (SMOTE) approach, to address the issue of imbalanced class distribution for obtaining an accuracy-trained model. Experimental results demonstrate that the proposed approach achieves high accuracy, sensitivity, specificity, precision, and an F1-score of 97.75%, 97.75%, 99.25%, 97.75%, and 97.75%, respectively, in classifying all the four shockable classes of arrhythmias and are superior to traditional methods. Our work possesses significant clinical value in real-life scenarios since it has the potential to significantly enhance the diagnosis and treatment of life-threatening arrhythmias in individuals with cardiac disease. Furthermore, our model also has demonstrated adaptability and generality for two other datasets.
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Systemic amyloidosis is a rare protein misfolding and deposition condition that causes slow organ failure. Each of the more than 15 exclusive sorts of systemic amyloidosis, which encourage amyloid production and tissue deposition, is introduced by a unique precursor protein. Amyloidosis can affect various organs, including the heart, kidneys, liver, nerves, gastrointestinal tract, lungs, muscles, skin, and soft tissues. It can either be acquired or hereditary. Insidious and doubtful signs often cause a put-off in diagnosis. In the closing decade, noteworthy progressions have been made in the identity, prediction, and handling of amyloidosis. Shotgun proteomics based on mass spectrometry has revolutionized amyloid typing and enabled the identification of novel amyloid forms. It is critical to correctly identify the precursor protein implicated in amyloidosis because the kind of protein influences the proper treatment strategy. Cardiac amyloidosis is a disorder characterized by the systemic accumulation of amyloid protein in the myocardium's extracellular space, which causes a variety of symptoms. The buildup of amyloid aggregates precipitates myocardial thickening and stiffening, culminating in diastolic dysfunction and, in due course, heart failure. We examine every kind of systemic amyloidosis in this text to offer practitioners beneficial equipment for diagnosing and treating those unusual diseases. This review presents a comprehensive analysis of cardiac amyloidosis and consolidates current methods for screening, diagnosis, evaluation, and treatment alternatives.
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Introduction Gout, a chronic inflammatory joint disease, is increasingly prevalent worldwide, mainly affecting men, young females, and post-menopausal women. This study aims to investigate gout epidemiology in Al-Baha, Saudi Arabia, addressing the dearth of localized data on prevalence, risk factors, and management practices. Methods A cross-sectional analysis was conducted at King Fahad Hospital, Al-Baha, Saudi Arabia, covering 116 patients from March 2016 to November 2017. Data encompassed demographics, clinical presentations, and biochemical markers relevant to gout. Results Among 116 patients, 41 (35.3%) were diagnosed with gout, with males exhibiting a significantly higher prevalence than females (43.9% vs. 24%). Significant associations were found between gout prevalence and residency, occupational status, education level, clinical presentations (podagra, arthralgia/arthritis), and biochemical markers. Conclusion This study enriches global knowledge by providing localized insights into gout's epidemiology and highlighting demographic influences and clinical presentations specific to the Saudi context. The findings underscore the importance of tailored approaches in gout management, considering regional variations in prevalence, risk factors, and clinical manifestations.
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Gastrointestinal stromal tumors (GISTs) are considered the most common mesenchymal tumors of the digestive system. However, they make up less than 1% of all GI tumors. GISTs arise from the interstitial cells of Cajal and are commonly found in the stomach and small intestine, and rarely in the colon and esophagus. In this case report, we present a 57-year-old male, a known diabetic, who complained of abdominal pain. He was diagnosed with cholelithiasis and a GIST in the jejunum, which was managed laparoscopically without complications. Most of the time, patients with GIST present with vague symptoms, or sometimes, they are asymptomatic. The most common symptoms are abdominal pain, GI bleeding, and an abdominal mass. These symptoms are usually related to the site of tumor growth, tumor size, and tumor rupture or perforation. Regardless of the tumor location, surgical excision is the gold standard for treating GISTs.
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Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound care requires precise and reliable wound measurement to optimize patient treatment and outcomes according to evidence-based best practices. Images are used to objectively assess wound state by quantifying key healing parameters. Nevertheless, the robust segmentation of wound images is complex because of the high diversity of wound types and imaging conditions. This study proposes and evaluates a novel hybrid model developed for wound segmentation in medical images. The model combines advanced deep learning techniques with traditional image processing methods to improve the accuracy and reliability of wound segmentation. The main objective is to overcome the limitations of existing segmentation methods (UNet) by leveraging the combined advantages of both paradigms. In our investigation, we introduced a hybrid model architecture, wherein a ResNet34 is utilized as the encoder, and a UNet is employed as the decoder. The combination of ResNet34's deep representation learning and UNet's efficient feature extraction yields notable benefits. The architectural design successfully integrated high-level and low-level features, enabling the generation of segmentation maps with high precision and accuracy. Following the implementation of our model to the actual data, we were able to determine the following values for the Intersection over Union (IOU), Dice score, and accuracy: 0.973, 0.986, and 0.9736, respectively. According to the achieved results, the proposed method is more precise and accurate than the current state-of-the-art.
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Glass ionomer cement (GIC) is a self-adhesive dental restorative material composed of a polyacrylic acid liquid and fluoro-aluminosilicate glass powder. It is commonly used for cementation during dental restoration. This study aimed to systematically review the existing literature regarding the clinical performance of GIC in load-bearing dental restorations. A comprehensive literature search was conducted in EBSCO, PubMed, Embrace, and Cochrane databases. Only randomized controlled trials (RCTs) were included in the search, and a broad search technique was used, where inclusion and exclusion criteria were applied. After a thorough evaluation, 12 RCTs were extensively reviewed, and whether GIC is suitable for load-bearing restorations was determined. Significant variations in staining surface or margin, color match, translucency, esthetic anatomical form, retention, material fracture, marginal adaptation, surface luster, occlusal contour, wear, and approximal anatomical form indicated the unsuitability of GIC. By contrast, significance differences in patient view and periodontal response indicated that GIC is suitable. No significant differences in postoperative sensitivity, recurrence of caries, or tooth integrity were observed. Nevertheless, the results of the review demonstrated that the clinical performance of GIC is comparable to that of traditional restorative materials with regard to the parameters analyzed. GIC is a suitable restorative material for load-bearing restorations regarding surface margin, esthetic anatomical form, material retention and fracture, marginal adaptation, occlusal contour, wear, and approximal anatomical form. It reduces other parameters, such as postoperative sensitivity, recurrence of caries, and tooth integrity.
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Restauración Dental Permanente , Cementos de Ionómero Vítreo , Humanos , Cementos de Ionómero Vítreo/química , Cementos de Ionómero Vítreo/uso terapéutico , Restauración Dental Permanente/métodos , Ensayos Clínicos Controlados Aleatorios como Asunto , Caries Dental/terapiaRESUMEN
BACKGROUND: As the impacts of diabetes-induced reproductive damage are now evident in young people, we are now in urgent need to devise new ways to protect and enhance the reproductive health of diabetic people. The present study aimed to evaluate the protective effects of enalapril (an ACE inhibitor) and paricalcitol (a vitamin D analog), individually or in combination, on streptozotocin (STZ)-diabetes-induced testicular dysfunction in rats and to identify the possible mechanisms for this protection. MATERIAL AND METHODS: This study was carried out on 50 male Sprague-Dawley rats; 10 normal rats were allocated as a non-diabetic control group. A total of 40 rats developed diabetes after receiving a single dose of STZ; then, the diabetic rats were divided into four groups of equivalent numbers assigned as diabetic control, enalapril-treated, paricalcitol-treated, and combined enalapril-and-paricalcitol-treated groups. The effects of mono and combined therapy with paricalcitol and enalapril on testicular functions, sperm activity, glycemic state oxidative stress, and inflammatory parameters, as well as histopathological examinations, were assessed in comparison with the normal and diabetic control rats. RESULTS: As a result of diabetes induction, epididymal sperm count, sperm motility, serum levels of testosterone, follicle-stimulating hormone (FSH) as well as luteinizing hormone (LH), and the antioxidant enzyme activities, were significantly decreased, while abnormal sperm (%), insulin resistance, nitric oxide (NO), malondialdehyde (MDA), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were significantly increased, along with severe distortion of the testicular structure. Interestingly, treatment with paricalcitol and enalapril, either alone or in combination, significantly improved the sperm parameters, increased antioxidant enzyme activities in addition to serum levels of testosterone, FSH, and LH, reduced insulin resistance, IL-6, and TNF-α levels, and finally ameliorated the diabetes-induced testicular oxidative stress and histopathological damage, with somewhat superior effect for paricalcitol monotherapy and combined therapy with both drugs compared to monotherapy with enalapril alone. CONCLUSIONS: Monotherapy with paricalcitol and its combination therapy with enalapril has a somewhat superior effect in improving diabetes-induced testicular dysfunction (most probably as a result of their hypoglycemic, antioxidant, anti-inflammatory, and anti-apoptotic properties) compared with monotherapy with enalapril alone in male rats, recommending a synergistic impact of both drugs.
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Cancer is a major public health concern worldwide in terms of mortality. The exact reason behind the development of cancer is not understood clearly, but it is evidenced that alcohol consumption, radiation, and exposure to chemicals are main players in this pathogenesis. The current mode of treatments such as surgery, chemotherapy, and radiotherapy are effective, but, still, cancer is a major problem leading to death and other side effects. However, safer and effective treatment modules are needed to overcome the adverse effects of current treatment modules. In this regard, natural compounds have been recognized to ameliorate diseases by exerting anti-inflammatory, anti-oxidative, and anti-tumor potential through several mechanisms. Mangiferin, a xanthone C-glucoside, is found in several plant species including Mangifera indica (mango), and its role in disease prevention has been confirmed through its antioxidant and anti-inflammatory properties. Furthermore, its anti-cancer-potential mechanism has been designated through modulation of cell signaling pathways such as inflammation, angiogenesis, PI3K/AKT, apoptosis, and cell cycle. This article extensively reviews the anticancer potential of mangiferin in different cancers through the modulation of cell signaling pathways. Moreover, the synergistic effects of this compound with some commonly used anti-cancer drugs against different cancer cells are discussed. More clinical trials should be performed to reconnoiter the anti-cancer potential of this compound in human cancer treatment. Further, understanding of mechanisms of action and the safety level of this compound can help to manage diseases, including cancer.
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In this study, we investigated both meat-derived and methicillin-resistant Staphylococcus aureus (MRSA), exploring their genetic relatedness to patient-derived MRSA isolates in Saudi Arabia. We collected 250 meat samples and identified 53 S. aureus isolates, with 79% being methicillin-sensitive Staphylococcus aureus (MSSA) and 21% being MRSA. Moreover, we included 80 clinically confirmed patient-derived MRSA isolates. We identified the most common S. aureus clone in both patients and retail meat. In meat, ST6 and ST97 were the most common clones in 55% of the MRSA isolates, and ST1153 and ST672 were the most common in 21% and 17% of the MSSA isolates. In patients, ST5 and ST6 were the predominant clones in 46% of the S. aureus isolates. CC5/ST5-SCCmecVc-t311 and CC361/ST672-SCCmecV-t3841 were common MRSA clones in both meat and patients. CC97 and CC361 clones were the second most prevalent S. aureus clones in meat and were relatively common in patients. Furthermore, we sequenced and characterized novel S. aureus strains ST8109, ST8110, and ST8111. The genomic similarities between meat- and patient-derived S. aureus isolates suggest that retail meat might be a reservoir for S.aureus and MRSA transmission. Therefore, a structured One Health approach is recommended for S. aureus dissemination, genetic characterization, antibiotic resistance, and impact on human health.
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Background: Diabetes mellitus is a chronic disease that needs long-term management. Mobile health is an emerging field that is being used for diabetes self-management. Aim: Evaluate the effect of a diabetes self-management mobile application on self-efficacy, self-care agency, and self-care management among 128 Jordanian patients with Type 1 Diabetes Mellitus. Methods: The study utilized a non-equivalent controlled groups quasi-experimental design, with 64 patients in the control and in the intervention groups. Results: There was significant improvement in mean self-efficacy in the intervention group, improved self-care agency between the groups, and improved self-care management both within the intervention group and between the groups, after controlling for self-efficacy and self-care agency. Conclusion: Using a diabetes self-management mobile application may help improve patients' confidence in managing diabetes, and better commitment to and performance of self-care activities.
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Diabetes Mellitus Tipo 1 , Aplicaciones Móviles , Automanejo , Humanos , Autoeficacia , AutocuidadoRESUMEN
Breast cancer, a leading cause of female mortality worldwide, poses a significant health challenge. Recent advancements in deep learning techniques have revolutionized breast cancer pathology by enabling accurate image classification. Various imaging methods, such as mammography, CT, MRI, ultrasound, and biopsies, aid in breast cancer detection. Computer-assisted pathological image classification is of paramount importance for breast cancer diagnosis. This study introduces a novel approach to breast cancer histopathological image classification. It leverages modified pre-trained CNN models and attention mechanisms to enhance model interpretability and robustness, emphasizing localized features and enabling accurate discrimination of complex cases. Our method involves transfer learning with deep CNN models-Xception, VGG16, ResNet50, MobileNet, and DenseNet121-augmented with the convolutional block attention module (CBAM). The pre-trained models are finetuned, and the two CBAM models are incorporated at the end of the pre-trained models. The models are compared to state-of-the-art breast cancer diagnosis approaches and tested for accuracy, precision, recall, and F1 score. The confusion matrices are used to evaluate and visualize the results of the compared models. They help in assessing the models' performance. The test accuracy rates for the attention mechanism (AM) using the Xception model on the "BreakHis" breast cancer dataset are encouraging at 99.2% and 99.5%. The test accuracy for DenseNet121 with AMs is 99.6%. The proposed approaches also performed better than previous approaches examined in the related studies.
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Human pathogenic fungi and bacteria pose a huge threat to human life, accounting for high rates of mortality every year. Unfortunately, the past few years have seen an upsurge in multidrug resistance pathogens. Consequently, finding an effective alternative antimicrobial agent is of utmost importance. Hence, this study aimed to phytofabricate silver nanoparticles (AgNPs) using aqueous extracts of the solid endosperm of Cocos nucifera L, also known as coconut meat (Cm). Green synthesis is a facile, cost-effective and eco-friendly methods which has several benefits over other physical and chemical methods. The synthesized nanoparticles were characterized by UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and dynamic light scattering (DLS). The Cm-AgNPs showed a UV-Vis peak at 435 nm and were crystalline and quasi-spherical, with an average size of 15 nm. The FTIR spectrum displayed functional groups of phenols, alkaloids, sugars, amines, and carbonyl compounds, which are vital in the reduction and capping of NPs. The antibacterial and anticandidal efficacy of the Cm-AgNPs was assessed by the agar-well diffusion method and expressed as a zone of inhibition (ZOI). Amongst all the test isolates, Staphylococcus epidermidis, Candida auris, and methicillin-resistant Staphylococcus epidermidis were more susceptible to the NPs with a ZOI of 26.33 ± 0.57 mm, 19.33 ± 0.57 mm, and 18 ± 0.76 mm. The MIC and MFC values for Candida spp. were higher than the bacterial test isolates. Scanning electron microscopic studies of all the test isolates at their MIC concentrations showed drastically altered cell morphology, indicating that the NPs could successfully cross the cell barrier and damage the cell integrity, causing cell death. This study reports the efficacy of Cm-AgNPs against several Candida and bacterial strains, which had not been reported in earlier studies. Furthermore, the synthesized AgNPs exhibited significant antioxidant activity. Thus, the findings of this study strongly imply that the Cm-AgNPs can serve as promising candidates for therapeutic applications, especially against multidrug-resistant isolates of Candida and bacteria. However, further investigation is needed to understand the mode of action and biosafety.
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Antiinfecciosos , Nanopartículas del Metal , Staphylococcus aureus Resistente a Meticilina , Humanos , Cocos , Antioxidantes/farmacología , Plata/farmacología , Antiinfecciosos/farmacología , Candida , CarneRESUMEN
In this research, the treatment of diabetic nephropathy in rats induced by streptozotocin with L. sativium whole-plant aqueous extract was examined, and the mechanism of action was proposed. Adult male rats were grouped into: control, L. sativum, T1DM, and T1DM + L. sativum-treated groups. For 8 weeks, L. sativum S was given to rats at a final dose of 250 mg/kg. Treatment with L. sativum reduced the amount of fasting glucose, increased the amount of fasting insulin, and diminished the increase in hepatic and serum cholesterol, free fatty acid, and triglyceride levels. The level of serum LDL-c was reduced. At the level of the kidney, L. sativum reduced urine volume and albumin excretion and spiked creatinine excretion. It also attenuated the tubular damage in the rats' kidneys and reduced the amounts of major inflammatory markers, including nuclear factor-kappaα (NF-κB), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6). Interestingly, L. sativium reduced the amount of mRNA transforming growth factor-ß1 (TGF-ß1), stimulated mRNA superoxide dismutase (SOD) and catalase (CAT), reduced lipid peroxide levels (MDA), and increased the glutathione (GSH), SOD, and CAT in the rat kidneys of the control and T1DM-treated group. In conclusion, L. sativum is a novel therapy against DN owing to its hypoglycemic effect, insulin-releasing, and antioxidant potential.
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Unmanned aerial vehicle (UAV) networks offer a wide range of applications in an overload situation, broadcasting and advertising, public safety, disaster management, etc. Providing robust communication services to mobile users (MUs) is a challenging task because of the dynamic characteristics of MUs. Resource allocation, including subchannels, transmit power, and serving users, is a critical transmission problem; further, it is also crucial to improve the coverage and energy efficacy of UAV-assisted transmission networks. This paper presents an Enhanced Slime Mould Optimization with Deep-Learning-based Resource Allocation Approach (ESMOML-RAA) in UAV-enabled wireless networks. The presented ESMOML-RAA technique aims to efficiently accomplish computationally and energy-effective decisions. In addition, the ESMOML-RAA technique considers a UAV as a learning agent with the formation of a resource assignment decision as an action and designs a reward function with the intention of the minimization of the weighted resource consumption. For resource allocation, the presented ESMOML-RAA technique employs a highly parallelized long short-term memory (HP-LSTM) model with an ESMO algorithm as a hyperparameter optimizer. Using the ESMO algorithm helps properly tune the hyperparameters related to the HP-LSTM model. The performance validation of the ESMOML-RAA technique is tested using a series of simulations. This comparison study reports the enhanced performance of the ESMOML-RAA technique over other ML models.
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An appendiceal mucocele is a rare disease characterized by the dilation of the appendix lumen with mucus accumulation. Although this disease is often found incidentally during appendectomy, it is crucial to differentiate it from acute appendicitis preoperatively to select adequate surgical management. We present a case of a 31-year-old male, medically free, with right-sided abdominal pain associated with nausea and vomiting. He was diagnosed with appendiceal mucocele and underwent laparoscopic appendectomy. The absence of a distinct clinical presentation and biochemical parameters necessitates a comprehensive and collaborative diagnostic approach for mucocele of the appendix. Achieving an accurate diagnosis prior to surgery is imperative to ensure the appropriate surgical technique is chosen, thereby minimizing the risk of serious intraoperative and postoperative complications such as pseudomyxoma peritonei.
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Aim: Parafunctional habits cause movements indicating their effect as functional and structural disorders such as malocclusion and temporomandibular joint changes in the oral and dental organs. This cross-sectional study was conducted to investigate the prevalence and factors associated with parafunctional habits in 6-12-year-old children in Qom, Iran. Materials and methods: This analytical cross-sectional study was performed on 403 6-12-year-old schoolchildren of Qom, Iran. Data collection tools included a demographic questionnaire and a checklist prepared along with a clinical examination. Data were analyzed using the Statistical Package for the Social Sciences (SPSS), with chi-square and analysis of variance (ANOVA) tests. Results: The mean age of children was 8.9 ± 2.03 years. Bruxism was more common than other parafunctional habits (22.6%). There was a significant relationship between oral habits with children's gender and age (p <0.001). However, there was no significant relationship between oral habits and other variables such as underlying disease, economic status and parent's smoking (p >0.05). Conclusions: Given the relatively high prevalence of parafunctional habits in children, it seems that children should be investigated for the presence of such habits in order to provide the necessary education to parents and perform dental interventions to prevent complications from oral habits. Dental interventions at a younger age are easier to conduct and have a more effective preventive role. How to cite this article: Mehdipour A, Aghaali M, Janatifar Z, et al. Prevalence of Oral Parafunctional Habits in Children and Related Factors: an Observational Cross-sectional Study. Int J Clin Pediatr Dent 2023;16(2):308-311.
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INTRODUCTION: Testicular cancer (TC) is a serious health issue, which requires early detection through testicular self-examination (TSE). OBJECTIVES: To investigate Saudi nursing students' health beliefs about TC and TSE using the Health Belief Model (HBM) scale and assess the validity and reliability of the HBM scale. METHODS: This cross-sectional study recruited a convenience sample of 374 nursing students from six nursing colleges in different cities in Saudi Arabia. Data were collected through self-report questionnaires that included demographic and academic information, as well as a valid and reliable HBM scale for TC and TSE. RESULTS: Most participants were single (88.8 %), in their third year of nursing education (43.9 %), had excellent or very good health (83.2%), had no family history of TC (88.9%), and had no medical problems with their testicles (92.8%). The participants had low susceptibility to TC and moderate beliefs about the seriousness of TC. Furthermore, participants reported moderate levels of perceived benefits and health motivation for preventing TC and practicing TSE, but high levels of perceived barriers and low levels of self-efficacy for practicing TSE. The internal reliability (Cronbach's alpha) of susceptibility, benefits and health motivation, seriousness, barriers, self-efficacy, and health motivation and promotion sub-scales was 0.91, 0.89, 0.88, 0.84, 0.67, and 0.65, respectively. Significant relationship between students' performing TSE and their health beliefs about Susceptibility (t=1.93, p=0.04) and Seriousness of having TC (t=2.88, p=0.03), and self-efficacy (t=3.91, p<0.001) and barriers (t=-2.51, p=0.04) to practice TSE. CONCLUSION: The study concluded that Saudi nursing students had moderate levels of health beliefs about TC and TSE, with high perceived barriers and low levels of self-efficacy for practicing TSE.
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Estudiantes de Enfermería , Neoplasias Testiculares , Masculino , Humanos , Neoplasias Testiculares/diagnóstico , Estudios Transversales , Reproducibilidad de los Resultados , Arabia Saudita , Conocimientos, Actitudes y Práctica en Salud , Autoexamen , Encuestas y CuestionariosRESUMEN
This study evaluated the cholesterol-alleviating effect and underlying mechanisms of chitosan-oligosaccharide (COS) in hypercholesterolemic hamsters. Male hamsters (n = 24) were divided into three groups in a random fashion, and each group was fed one particular diet, namely a non-cholesterol diet (NCD), a high-cholesterol diet (HCD), and an HCD diet substituting 5% of the COS diet for six weeks. Subsequently, alterations in fecal bile acids (BAs), short-chain fatty acids (SCFAs), and gut microflora (GM) were investigated. COS intervention significantly reduced and increased the plasma total cholesterol (TC) and high-density lipoprotein-cholesterol (HDL-C) levels in hypercholesteremic hamsters. Furthermore, Non-HDL-C and total triacylglycerols (TG) levels were also reduced by COS supplementation. Additionally, COS could reduce and increase food intake and fecal SCFAs (acetate), respectively. Moreover, COS had beneficial effects on levels of BAs and GM related to cholesterol metabolism. This study provides novel evidence for the cholesterol-lowering activity of COS.
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Quitosano , Microbioma Gastrointestinal , Hipercolesterolemia , Animales , Cricetinae , Masculino , Ácidos y Sales Biliares , Quitosano/farmacología , Colesterol , Ácidos Grasos Volátiles , Hígado/metabolismo , Mesocricetus , Oligosacáridos/farmacologíaRESUMEN
The domestication of animals and the cultivation of crops have been essential to human development throughout history, with the agricultural sector playing a pivotal role. Insufficient nutrition often leads to plant diseases, such as those affecting rice crops, resulting in yield losses of 20-40% of total production. These losses carry significant global economic consequences. Timely disease diagnosis is critical for implementing effective treatments and mitigating financial losses. However, despite technological advancements, rice disease diagnosis primarily depends on manual methods. In this study, we present a novel self-attention network (SANET) based on the ResNet50 architecture, incorporating a kernel attention mechanism for accurate AI-assisted rice disease classification. We employ attention modules to extract contextual dependencies within images, focusing on essential features for disease identification. Using a publicly available rice disease dataset comprising four classes (three disease types and healthy leaves), we conducted cross-validated classification experiments to evaluate our proposed model. The results reveal that the attention-based mechanism effectively guides the convolutional neural network (CNN) in learning valuable features, resulting in accurate image classification and reduced performance variation compared to state-of-the-art methods. Our SANET model achieved a test set accuracy of 98.71%, surpassing that of current leading models. These findings highlight the potential for widespread AI adoption in agricultural disease diagnosis and management, ultimately enhancing efficiency and effectiveness within the sector.