Asthma, a prevalent chronic condition in children, poses significant challenges in management. While conventional treatments like inhaled corticosteroids and beta-agonists are standard, there is increasing interest in the role of herbal medicine and probiotics as complementary therapies. This paper reviews the impact of herbal remedies—such as Butterbur, Ginger, Turmeric, Boswellia, Licorice, and Ephedra—and probiotics on pediatric asthma. Evidence suggests these therapies may reduce inflammation and improve respiratory function, potentially benefiting asthma management. However, variability in product quality and study designs necessitates further research. Future studies should focus on validating these interventions through rigorous clinical trials to better integrate herbal medicine and probiotics into comprehensive asthma care for children.

Inborn errors of immunity (IEIs) necessitate a well-funded healthcare system and substantial financial resources for diagnosis and treatment. More than that, these diseases and socioeconomic status are inversely related. Immune deficiencies are better managed by those with higher socioeconomic position, but the emotional and financial tolls of living with a compromised immune system can be devastating for patients and their families, causing them to struggle financially for years to come. For a long time, the patient and people close to her are impacted by these conditions. Conversely, the national healthcare system and patients' socioeconomic situation determine the likelihood of early diagnosis and successful treatment. The development of the immune system throughout infancy is crucial. Fetal development is regulated by maternal nutrition, psychological stress, the mother's mental health, and supporting social networks. The immune system develops from conception and matures during neonatal and early childhood. Effective IEI management and therapy require genetic and social factors to interact. Geneticists, immunologists, healthcare providers, and politicians must collaborate to address IEIs. Insufficient resources for complete newborn screening and genetic testing for all patients make treating the increased incidence of autosomal recessive and genetic diseases in MENA problematic. Primary immunodeficiency treatments including stem cell transplantation and gene therapy are limited in Latin America and Africa. Parental comprehension, awareness, and attitudes of PID genetic testing depend on service accessibility, familial history, and individual circumstances. Patients resist genetic therapy due to financial constraints, notably the high cost of genetic testing. HSCT may treat nonmalignant lymphohematopoietic diseases, myeloid and lymphoid malignancies, immunological deficits, genetic disorders, and inborn metabolic problems. Improving PID outcomes requires correcting these discrepancies. This review aims to underscore the critical need for heightened awareness and improved diagnostic methods for IEIs by analyzing the interplay between genetic factors and societal influences.

At the beginning of 2020, the pneumonia-like covid-19 virus spread rapidly worldwide. With the emergence of this dangerous virus, work and daily life have become very difficult. In order to control this virus, all the centers are closed and quarantined by the government and the countries of the world. Every day, many people from all over the world die due to covid-19. Many efforts are being made in all fields to diagnose and treat people infected with this virus. For this reason, many researchers started working on identifying this virus and its types. The Scientifics, in computer science, did not sit idle either. In some studies, different image processing methods and algorithms have been used to extract the edge features of the CT images of lungs. Edge detection is the purpose of this article to reach the highest accuracy rate. Consequently, a classification method with CNN -AlexNet architecture was used. Therefore, the proposed method helps physicians for improving disease diagnosis from CT images of the lungs. It can help to more accurate detection of the infected lungs. The results show that the average accuracy rate of image edge extraction with a threshold value of 0.1 is 93% and the accuracy rate of AlexNet architecture classification is 100%.

No Abstract