Human CMV (HCMV) is a major cause of morbidity and mortality in both congenitally infected and immunocompromised individuals. Development of an effective HCMV vaccine would help protect these vulnerable groups. NK group 2, member D (NKG2D) is a potent activating receptor expressed by cells of the innate and adaptive immune systems. Its importance in HCMV immune surveillance is indicated by the elaborative evasion mechanisms evolved by the virus to avoid NKG2D. In order to study this signaling pathway, we engineered a recombinant mouse CMV expressing the high-affinity NKG2D ligand RAE-1γ (RAE-1γMCMV). Expression of RAE-1γ by MCMV resulted in profound virus attenuation in vivo and lower latent viral DNA loads. RAE-1γMCMV infection was efficiently controlled by immunodeficient hosts, including mice lacking type I interferon receptors or immunosuppressed by sublethal γ-irradiation. Features of MCMV infection in neonates were also diminished. Despite tight innate immune control, RAE-1γMCMV infection elicited strong and long-lasting protective immunity. Maternal RAE-1γMCMV immunization protected neonatal mice from MCMV disease via placental transfer of antiviral Abs. Despite strong selective pressure, the RAE-1γ transgene did not exhibit sequence variation following infection. Together, our results indicate that use of a recombinant virus encoding the ligand for an activating NK cell receptor could be a powerful approach to developing a safe and immunogenic HCMV vaccine.

COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been made by researchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets mostly used in research in the field of COVID-19 regression modeling as well as present current literature based on Artificial Intelligence (AI) methods for regression tasks, like disease spread. Moreover, we discuss the applicability of Machine Learning (ML) and Evolutionary Computing (EC) methods that have focused on regressing epidemiology curves of COVID-19, and provide an overview of the usefulness of existing models in specific areas. An electronic literature search of the various databases was conducted to develop a comprehensive review of the latest AI-based approaches for modeling the spread of COVID-19. Finally, a conclusion is drawn from the observation of reviewed papers that AI-based algorithms have a clear application in COVID-19 epidemiological spread modeling and may be a crucial tool in the combat against coming pandemics.

Head and neck cancer encompass different malignancies that develop in and around the throat, larynx, nose, sinuses and mouth. Most head and neck cancers are squamous cell carcinomas (HNSCC) that arise in the flat squamous cells that makeup the thin layer of tissue on the surface of anatomical structures in the head and neck. Each year, HNSCC is diagnosed in more than 600,000 people worldwide, with about 50,000 new cases. HNSCC is considered extremely curable if detected early. But the problem remains in treatment of inoperable cases, residues or late stages. Circadian rhythm regulation has a big role in developing various carcinomas, and head and neck tumors are no exception. A number of studies have reported that alteration in clock gene expression is associated with several cancers, including HNSCC. Analyses on circadian clock genes and their association with HNSCC have shown that expression of PER1, PER2, PER3, CRY1, CRY2, CKIε, TIM, and BMAL1 are deregulated in HNSCC tissues. This review paper comprehensively presents data on deregulation of circadian genes in HNSCC and critically evaluates their potential diagnostics and prognostics role in this type of pathology.

Data suggest association between TGFB1 29 T → C transition (rs1800470) and IL6 -572G → C transversion (rs1800796) with DDH, and also a possibility of TGF-beta1 and IL-6 interaction in DDH pathogenesis.

Circadian timing system includes an input pathway transmitting environmental signals to a core oscillator that generates circadian signals responsible for the peripheral physiological or behavioural events. Circadian 24-h rhythms regulate diverse physiologic processes. Deregulation of these rhythms is associated with a number of pathogenic conditions including depression, diabetes, metabolic syndrome and cancer. Melanoma is a less common type of skin cancer yet more aggressive often with a lethal ending. However, little is known about circadian control in melanoma and exact functional associations between core clock genes and development of melanoma skin cancer. This paper, therefore, comprehensively analyses current literature data on the involvement of circadian clock components in melanoma development. In particular, the role of circadian rhythm deregulation is discussed in the context of DNA repair mechanisms and influence of UV radiation and artificial light exposure on cancer development. The role of arylalkylamine N-acetyltransferase (AANAT) enzyme and impact of melatonin, as a major output factor of circadian rhythm, and its protective role in melanoma are discussed in details. We hypothesise that further understanding of clock genes' involvement and circadian regulation might foster discoveries in the field of melanoma diagnostics and treatment.