Omega-3 and omega-6 polyunsaturated fatty acids and their potential therapeutic role in protozoan infections.

Protozoa exert a serious global threat of growing concern to human, and animal, and there is a need for the advancement of novel therapeutic strategies to effectively treat or mitigate the impact of associated diseases. Omega polyunsaturated fatty acids (ω-PUFAs), including Omega-3 (ω-3) and omega-6 (ω-6), are constituents derived from various natural sources, have gained significant attention for their therapeutic role in parasitic infections and a variety of essential structural and regulatory functions in animals and humans. Both ω-3 and ω-6 decrease the growth and survival rate of parasites through metabolized anti-inflammatory mediators, such as lipoxins, resolvins, and protectins, and have both in vivo and in vitro protective effects against various protozoan infections. The ω-PUFAs have been shown to modulate the host immune response by a commonly known mechanism such as (inhibition of arachidonic acid (AA) metabolic process, production of anti-inflammatory mediators, modification of intracellular lipids, and activation of the nuclear receptor), and promotion of a shift towards a more effective immune defense against parasitic invaders by regulation the inflammation like prostaglandins, leukotrienes, thromboxane, are involved in controlling the inflammatory reaction. The immune modulation may involve reducing inflammation, enhancing phagocytosis, and suppressing parasitic virulence factors. The unique properties of ω-PUFAs could prevent protozoan infections, representing an important area of study. This review explores the clinical impact of ω-PUFAs against some protozoan infections, elucidating possible mechanisms of action and supportive therapy for preventing various parasitic infections in humans and animals, such as toxoplasmosis, malaria, coccidiosis, and chagas disease. ω-PUFAs show promise as a therapeutic approach for parasitic infections due to their direct anti-parasitic effects and their ability to modulate the host immune response. Additionally, we discuss current treatment options and suggest perspectives for future studies. This could potentially provide an alternative or supplementary treatment option for these complex global health problems.

Validation of a modified problematic use of mobile phones scale to examine problematic smartphone use and dependence.

Over the past decade, the world population has experienced rapid and widespread adoption of smartphones due to their usefulness and convenience. However, researchers have identified a range of adverse behaviours associated with the adoption of smartphones and their higher use. These behaviours are collectively described as Problematic Smartphone Use and Dependence (PSUD). Despite growing research, the underlying processes and drivers leading to these behaviours are inadequately understood. This can partly be attributed to the absence of developed statistical tools and measures that allow researchers to build a comprehensive conceptual understanding of PSUD. To address this issue, this study proposes and evaluates a validated extension to the Problematic Use of Mobile Phones (PUMP) scale. The extension of this tool incorporates factors associated with substance dependence outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), including additional items to measure PSUD accurately, referred to as the modified problematic use of mobile phones (MPUMP) scale. The newly developed tool was used in a cross-sectional online survey during September and October 2022, drawing on 1018 adult Australian participants. Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) were conducted to derive the underlying factors. The EFA revealed two distinct factors: Distraction and Dysregulation. Both factors exhibited high internal consistency, with Cronbach's Alpha coefficients of 0.92 and 0.86, respectively. A one-way analysis of variance (ANOVA) revealed significant variations inthe identified factors' mean scores across different socio-demographic characteristics. The study provides evidence that the MPUMP scale is a validated and reliable measure for accurately assessing PSUD. The study findings offer novel insights into the psychosocial and physical aspects of PSUD, providing a foundation for exploring the causes and potential interventions for PSUD.

Effect of nutritional and environmental conditions on biofilm formation of avian pathogenic Escherichia coli.

AIMS: To study the effects of environmental stress and nutrient conditions on biofilm formation of avian pathogenic Escherichia coli (APEC). METHODS AND RESULTS: The APEC strain DE17 was used to study biofilm formation under various conditions of environmental stress (including different temperatures, pH, metal ions, and antibiotics) and nutrient conditions (Luria-Bertani [LB] and M9 media, with the addition of different carbohydrates, if necessary). The DE17 biofilm formation ability was strongest at 25°C in LB medium. Compared to incubation at 37°C, three biofilm-related genes (csgD, dgcC, and pfs) were significantly upregulated and two genes (flhC and flhD) were downregulated at 25°C, which resulted in decreased motility. However, biofilm formation was strongest in M9 medium supplemented with glucose at 37°C, and the number of live bacteria was the highest as determined by confocal laser scanning microscopy. The bacteria in the biofilm were surrounded by a thick extracellular matrix, and honeycomb-like or rough surfaces were observed by scanning electron microscopy. Moreover, biofilm formation of the DE17 strain was remarkably inhibited under acidic conditions, whereas neutral and alkaline conditions were more suitable for biofilm formation. Biofilm formation was also inhibited at specific concentrations of cations (Na+ , K+ , Ca2+ , and Mg2+ ) and antibiotics (ampicillin, chloramphenicol, kanamycin, and spectinomycin). The real-time quantitative reverse transcription PCR showed that the transcription levels of biofilm-related genes change under different environmental conditions. CONCLUSIONS: Nutritional and environmental factors played an important role in DE17 biofilm development. The transcription levels of biofilm-related genes changed under different environmental and nutrient conditions. SIGNIFICANCE AND IMPACT OF THE STUDY: The findings suggest that nutritional and environmental factors play an important role in APEC biofilm development. Depending on the different conditions involved in this study, it can serve as a guide to treating biofilm-related infections and to eliminating biofilms from the environment.

Evaluating the impact of roads on the diversity pattern and density of trees to improve the conservation of species.

Roadside trees alter biotic and abiotic factors of plants diversity in an ecosystem. Rows of plants grow along the roadside due to the interplay between the arrival of propagule and seedling establishment, which depends on the road's specifications, land pattern, and road administration and protection practices. A field study was conducted to measure the roadside tree diversity in the city of Karachi (Pakistan). A total of 180 plots, divided into three primary road groups, were surveyed. The highest quantity of tree biomass per unit area was found on wide roads, followed by medium roads. On narrow roads, the least biomass was detected. A single species or a limited number of species dominated the tree community. Conocarpus erectus was the most dominant non-native species on all types of sidewalks or roadsides, followed by Guaiacum officinale. A total of 76 species (32 non-natives and 44 natives) that were selectively spread along the roadsides of the city were studied. There was a significant difference in phylogenetic diversity (PD), phylogenetic mean pairwise distance (MPD), and phylogenetic mean nearest taxon distance (MNTD) among wide, medium, and narrow roads. Management practices have a significant positive correlation with diversity indices. Our study identified patterns of diversity in roadside trees in Karachi. It provides the basis for future planning for plant protection, such as the protection of plant species, the maintenance of plant habitats, and the coordination of plant management in Karachi.

AI-based object detection latest trends in remote sensing, multimedia and agriculture applications.

Object detection is a vital research direction in machine vision and deep learning. The object detection technique based on deep understanding has achieved tremendous progress in feature extraction, image representation, classification, and recognition in recent years, due to this rapid growth of deep learning theory and technology. Scholars have proposed a series of methods for the object detection algorithm as well as improvements in data processing, network structure, loss function, and so on. In this paper, we introduce the characteristics of standard datasets and critical parameters of performance index evaluation, as well as the network structure and implementation methods of two-stage, single-stage, and other improved algorithms that are compared and analyzed. The latest improvement ideas of typical object detection algorithms based on deep learning are discussed and reached, from data enhancement, a priori box selection, network model construction, prediction box selection, and loss calculation. Finally, combined with the existing challenges, the future research direction of typical object detection algorithms is surveyed.

Effect of Antibiotics on the Colonization of Live Attenuated Salmonella Enteritidis Vaccine in Chickens.

Salmonellosis, caused by Salmonella Enteritidis, is a prevalent zoonosis that has serious consequences for human health and the development of the poultry sector. The Salmonella Enteritis live vaccine (Sm24/Rif12/Ssq strain) is used to prevent Salmonella Enteritidis around the world. However, in some parts of the world, poultry flocks are frequently raised under intensive conditions, with significant amounts of antimicrobials to prevent and treat disease and to promote growth. To investigate whether antibiotic use influences the colonization of orally administered Salmonella live vaccines, 240 1-day-old specific pathogen-free chicks were randomly divided into 24 groups of 10 animals for this study. The different groups were treated with different antibiotics, which included ceftiofur, amoxicillin, enrofloxacin, and lincomycin-spectinomycin. Each group was immunized 2, 3, 4, and 5 days after withdrawal, respectively. At 5 days after immunization, the blood, liver, and ceca with contents were collected for the isolation of the Salmonella live vaccine strain. The result showed that no Salmonella vaccine strain was isolated in the blood and liver of the chicks in those groups. The highest number of Salmonella vaccine strains was isolated in the cecum from chicks vaccinated 2 days after ceftiofur withdrawal, and no Salmonella vaccine strain was isolated from the cecum in chicks immunized 3 days after ceftiofur withdrawal. Among the chickens immunized 4 days after the withdrawal of amoxicillin, enrofloxacin, and lincomycin-spectinomycin, the number of Salmonella vaccine colonization in the cecum was the highest, which was higher than that of the chickens immunized at other withdrawal interval (2, 3, and 5 days) groups and was higher than that of the chickens without treatment (P < 0.05). This study provides a reference for the effective use of the Salmonella Enteritidis live vaccine and key antibiotics commonly utilized in the poultry industry.

A hybrid approach to forecast the COVID-19 epidemic trend.

Studying the progress and trend of the novel coronavirus pneumonia (COVID-19) transmission mode will help effectively curb its spread. Some commonly used infectious disease prediction models are introduced. The hybrid model is proposed, which overcomes the disadvantages of the logistic model's inability to predict the number of confirmed diagnoses and the drawbacks of too many tuning parameters of the SEIR (Susceptible, Exposed, Infectious, Recovered) model. The realization and superiority of the prediction of the proposed model are proven through experiments. At the same time, the influence of different initial values of the parameters that need to be debugged on the hybrid model is further studied, and the mean error is used to quantify the prediction effect. By forecasting epidemic size and peak time and simulating the effects of public health interventions, this paper aims to clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviours are critical to slow down the epidemic.

Advance hybrid medical watermarking algorithm using speeded up robust features and discrete cosine transform.

In the continuous development of computer network technology, multimedia technology and information technology, digitization has become the main means of displaying information, thus facilitating the storage, copying and dissemination of digital multimedia information. In this context, there are no restrictions on arbitrary editing, copying, modification, and dissemination of digital images, music, etc., which leads to various social problems such as information security, copyright disputes, and piracy. With the advancement of networks and multimedia, digital watermarking technology has received worldwide attention as an effective method of copyright protection. Improving the anti-geometric attack ability of digital watermarking algorithms using image feature-based algorithms have received extensive attention. This paper proposes a novel robust watermarking algorithm based on SURF-DCT perceptual hashing (Speeded Up Robust Features and Discrete Cosine Transform), namely blind watermarking. The algorithm firstly uses the affine transformation with a feature matrix and chaotic encryption technology to preprocess the watermark image, enhance the confidentiality of the watermark, and perform block and DCT coefficients extraction on the carrier image, and then uses the positive and negative quantization rules to modify the DCT coefficients. The embedding of the watermark is completed, and the blind extraction of the watermark realized. Experiments show that the algorithm has good invisibility and strong robustness against conventional and geometric attacks and can effectively protect the security of images with NC value more than 90%.