newcastle disease (ND) is an economically significant and extremely spreadable viral illness affecting a wide variety of avian species. ND can rapidly spread within poultry farms and result in considerable economic losses for the global poultry industry. This disease is endemic in Iran, and despite intensive vaccination efforts in the poultry industry, outbreaks of ND occur unexpectedly. This study aimed to isolate the newcastle disease virus (NDV) from poultry farms with breathing problems in Markazi province, Iran, and investigate the evolutionary relationship and molecular characteristics of the isolates during 2017-2019. To this end, tissue samples (lung, brain, and trachea) were taken from 42 broiler farms exhibiting respiratory symptoms. The samples were inoculated into 9-11-day-old embryonated eggs, and the virus was isolated from 20 (47.6%) of the 42 farms. Subsequently, RT-PCR was used to amplify partial fusion gene sequences from the new isolates. The amplified products were sequenced and compared phylogenetically to the standard pilot dataset (125 selected sequences) generated by the NDV consortium. As determined by phylogenetic analysis, all nine isolates belonged to subgenotype VII.1.1 of genotype VII and were highly similar to isolates from other parts of Iran and China. Moreover, all isolates possessed a polybasic cleavage site motif (112RRQKRF117), characteristic of virulent strains. Furthermore, the present isolates shared a high nucleotide identity (96%) with viruses previously isolated from other provinces of Iran, as determined by BLAST searches and multiple alignments. In addition, they shared a high degree of sequence similarity but were distinct from the existing NDV vaccines. Therefore, the genetic dissimilarity between current vaccine strains and circulating NDVs must be considered in vaccination programs.

The present reserach aimed to detect and isolate the genes involved in the staphylococcal enterotoxins (SEs) production in strains isolated from unprocessed cow’s milk and to examine the impact of Bifidobacterium bifidum probiotic cell-free supernatant (CFS) on their expression. Standard techniques were used for isolation and identification of Staphylococci strains in unprocessed milk. The PCR was used to identify strains carrying enterotoxin genes. The B. bifidum CFS was applied to strains containing the target genes, and the genes expression levels were quantified using Real-time PCR. Using 16SrDNA sequencing, the phylogenic relationship of the isolated strains was determined. Analysis revealed that bacteria such as Staphylococcus species were found in the 72% of the samples. The PCR test showed the presence of various SE superantigens, including SEA (16.7%), SEC (11.7%), SED (8.3%), SEE (6.7%), and SEB (1.7%) in isolated strains. The B. bifidum CFS had obvious antimicrobial activity against strains 24, 51, 54, and 35 of Staphylococcus species, and the minimum inhibitory concentration and minimum bactericidal concentration values for these strains treated with B. bifidum CFS were in the range of 31.25-125 μg/ml. Strains 51 and 24 were clustered with S.aureus ATCC 25923, and strains 54 and 35 were clustered with S.aureus ATCC 12600, respectively. The RT-PCR exhibited that probiotics CFS suppressed the expression of SEA, SEB, SEC, and SEE genes (P<0.05). The average fold change for SEA, SEB, SEC, and SED genes was -1.681, -1.28, -1.52, and -0.84, respectively. The research demonstrated that probiotic bacteria can lower enterotoxin production by downregulating the expression of SEs genes.

Technology stands as one of the most pivotal elements driving change in the strategic landscape of the media industry and its destiny is fundamentally intertwined with technology. The rapid influx and progression of new technologies, particularly information and communication technologies within media organizations, have significantly impacted the societal and cultural dimensions of media existence over recent decades and has prompted significant foundational changes in the environment, structure and management approaches of media organizations. Consequently, identifying success factors in the implementation of new technologies within the media industry becomes imperative. To achieve this objective, dimensions, components and initial indicators were identified through reviewing existing studies, and to validate and indigenize the obtained indicators, a fuzzy Delphi method was employed, drawing on expert opinions. Ultimately, 166 relevant indicators were identified across eight influential dimensions: big data infrastructure, digital literacy of managers and employees, innovation in technology and content, technological capabilities of new media, media communication management, semiotics in the media industry, audience engagement and technology-based business strategy along with 33 components. These dimensions and components with incorporating relevant indicators can serve as a roadmap and guideline for any media entity intending to implement new technologies within its organizational framework.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammatory processes that result in joint swelling, inflammation, and the onset of pain. This discomfort and pathological condition exhibit a gradual rise in scale and become more intense. Even though pharmacotherapy like disease-modifying antirheumatic drugs (DMARDs) and biologics has improved, there is still a need for more focused treatments that cause less harm. This study examines how treatments for RA have changed over time, focusing on the shift from traditional medicines to new, creative ways to combine medicine with immune-engineering therapies. DMARDs are still the most common way to treat RA. On the other hand, biologics and Janus kinase inhibitors are options for people who do not react to their first medications. The development of nanomedicines and hydrogels is an exciting new area of study because they make it possible for more precise spread and less overall toxicity of the medicine. The early research suggests that these innovative approaches could greatly improve the effectiveness of therapy by delivering drugs directly to the site of inflammation while also reducing the severity of any side effects that might occur. RA care is quickly expanding beyond the traditional use of drugs to include more modern ways of managing medications and also personalized healing methods.

Trichomonas gallinae is a flagellated protozoan parasite that affects numerous avian species worldwide, causing a range of diseases collectively termed trichomonosis. This review study aimed to present a comprehensive analysis of the prevalence of T. gallinae in birds of Iran, along with an exploration of its associated pathological findings. Through an extensive search of published studies, scientific databases, and relevant literature, we identified several studies conducted in Iran that focused on the prevalence of T. gallinae in different bird populations as well as their pathological effect. These studies utilized a variety of techniques, including direct microscopic examination, culture methods, and molecular tools to detect and identify the presence of this parasite. This review study indicates that T. gallinae infections are prevalent among various bird species in Iran, including Domestic pigeons, Zebra Finches and Turkey. The prevalence rates reported showed significant differences among various regions and bird species, ranging from as low as 2.5% in zebra finches to as high as 70% in pigeons. The clinical signs of infected birds varied from no clinical signs to visible yellowish-white masses of caseous necrotic material, hyperplasia of mucous cells and significant congestion of lung. These findings underline the importance of T. gallinae as a significant pathogen affecting avian populations in Iran. Using at least two techniques such as culture or PCR in addition to direct smear is recommended for better diagnosis of infection. The study highlights the need for further epidemiological studies to better understand the risk factors associated with T. gallinae transmission and to develop effective prevention and control strategies.

Mycotoxins are the toxins produced by various types of fungi, including Fusarium, which can produce different types of mycotoxins such as Deoxynivalenol (DON), Zearalenone (ZEN), T-2 toxin, and Fumonisins (FUM). Mycotoxins have the potential to reduce the quality of crops and pose health risks to both humans and animals. This can result in reduced animal production and substantial economic consequences on a global scale. Extensive research has been carried out to investigate the high incidence of contamination in grains by Fusarium fungi. In this study, 80 samples of maize from silos of dairy farms in Fars province, Iran were taken and examined for fungal contamination by Fusarium and potential production of DON and FUM. For this purpose, identification using specific primers for different genes was carried out by PCR test and gel electrophoresis with agarose (1%). Among different counties, the silos in Kharameh with 47.05% and Jahrom with 46.15% had the highest contamination rate, and the lowest contamination rate belonged to Kazeroon with 27.27%. Out of the 30 positive samples contaminated by Fusarium, 21 produced FUM, four produced DON, and five produced both toxins. Fusarium species that contaminated the maize samples were also identified, including 13, 10, and 7 samples contaminated by F. proliferatum, F. verticillioides, and F. graminearum, respectively. As a conclusion, the findings of the study indicate that 37.5% of the corn samples from dairy farm silos in Fars province were contaminated with the Fusarium fungus, which had the potential to produce the toxic mycotoxins, deoxynivalenol and fumonisins.

Nature is a valuable resource, supplying remedies for the treatment of all diseases. Plant kingdom stands for a plethora of natural compounds that are well known for their utilization in therapeutic applications. They may pave the way for the development of new mediators with appropriate efficacy in many pathological disorders in the future. In India and throughout the world, herbs have become a principle and popular medicine. Recognized green medicines are better than synthetic ones and have fewer side effects. Since ancient times, plants have been intended for their medicinal properties for treating various diseases owing to their fewer side effects, availability of the agent, cost-efficiency, and potential effectiveness. The medicinal value of plants stems from various vegetative parts of the plant, including flowers, fruit, bark, roots, leaves, seeds, and its modified parts. The Indian forests are the major repository of remedial and aromatic medicinal plants, which can be used for the production of a plethora of remedies against various diseases. Butea monosperma is one of the traditional Ayurvedic medicinal plants considered a rich source of ingredients that can be used in drug development as home remedies to treat various diseases, such as diarrhea, constipation, hypertension, dehydration, bronchial asthma, leucorrhea, cancer, infection, as well as liver and stomach disorders. The seed powder is known for its notable medicinal, pharmaceutical, and insecticidal activities. This study highlights the traditional Ayurvedic importance of an eminent medicinal plant, B. monosperma, with its active chemical constituents, as well as pharmacological, environmental, ecological, economical, and agricultural significance. This plant can be planted everywhere to take advantage of its versatile applications.

Misdiagnosis of skin diseases is a common occurrence. Psoriasis is a skin disease that has many similarities with other diseases, and its incorrect diagnosis causes many problems in the treatment process. Misdiagnosis of this disease causes doctors to face problems during treatment. The lack of images of the disease and the database of skin diseases reduces the diagnosis and the coordination of diagnostic methods, therefore, diagnosis using different images is very useful. Today, diagnosis methods using deep features in medical images have received much attention. Artificial intelligence is one of the automatic methods of diagnosis. These methods can detect new data entering the system and keep it in memory. Therefore, in this article, two different groups of data have been identified using deep features based on artificial intelligence. In this method, the data of the first group in the form of training and testing and the data of the second group are studied gradually. If they are correctly identified, the next 0.1 chunks of data enter the network without testing. If they are wrongly recognized, they enter the training section and this reduces the training process. In this work, by training 20% of the data, i.e. the first 10% and the fourth 10%, there was no need for training because the accuracy was not less than98%. In this article, deep features of images were first extracted using convolutional neural network, and then psoriasis and eczema were diagnosed with average accuracy of98.3%and sensitivity of 97.9% in skin images using artificial intelligence.

To address computational complexity in heating, ventilating, and air conditioning systems, two general reduced multiple model control designs based on gap metric, stability margin, and model order reduction are proposed. The difference between two designs lies in the sequence of implementing model order reduction and multiple model techniques, resulting in distinct control approaches. As the number and location of reduced multiple models are not necessarily the same in two cases, the selected models will also be different. This could make one approach preferable to another in terms of closed-loop performance. Therefore, we introduce a model selection criterion to predict the most suitable approach for improving indoor thermal comfort and air quality in considered system. This criterion is based on maximum gap metric, maximum stability margin, and number of nominal models. Finally, two new approaches called OR-MM and MM-OR and a new criterion called MSC are proposed. To validate the effectiveness of our method, we conduct computer simulations that demonstrate their achievements.