The research of interactions between the pathogens and their hosts is key for understanding the biology of infection. Commencing on the level of individual molecules, these interactions define the behavior of infectious agents and the outcomes they elicit. Discovery of host-pathogen interactions (HPIs) conventionally involves a stepwise laborious research process. Yet, amid the global pandemic the urge for rapid discovery acceleration through the novel computational methodologies has become ever so poignant. This review explores the challenges of HPI discovery and investigates the efforts currently undertaken to apply the latest machine learning (ML) and artificial intelligence (AI) methodologies to this field. This includes applications to molecular and genetic data, as well as image and language data. Furthermore, a number of breakthroughs, obstacles, along with prospects of AI for host-pathogen interactions (HPI), are discussed.

Human livelihood highly depends on applying different sources of energy whose utilization is associated with air pollution. On the other hand, air pollution may be associated with glioblastoma multiforme (GBM) development. Unlike other environmental causes of cancer (e.g., irradiation), air pollution cannot efficiently be controlled by geographical borders, regulations, and policies. The unavoidable exposure to air pollution can modify cancer incidence and mortality. GBM treatment with chemotherapy or even its surgical removal has proven insufficient (100% recurrence rate; patient\'s survival mean of 15 months; 90% fatality within five years) due to glioma infiltrative and migratory capacities. Given the barrage of attention and research investments currently plowed into next-generation cancer therapy, oncolytic viruses are perhaps the most vigorously pursued. Provision of an insight into the current state of the research and future direction is essential for stimulating new ideas with the potentials of filling research gaps. This review manuscript aims to overview types of brain cancer, their burden, and different causative agents. It also describes why air pollution is becoming a concerning factor. The different opinions on the association of air pollution with brain cancer are reviewed. It tries to address the significant controversy in this field by hypothesizing the air-pollution-brain-cancer association via inflammation and atopic conditions. The last section of this review deals with the oncolytic viruses, which have been used in, or are still under clinical trials for GBM treatment. Engineered adenoviruses (i.e., DNX-2401, DNX-2440, CRAd8-S-pk7 loaded Neural stem cells), herpes simplex virus type 1 (i.e., HSV-1 C134, HSV-1 rQNestin34.5v.2, HSV-1 G207, HSV-1 M032), measles virus (i.e., MV-CEA), parvovirus (i.e., ParvOryx), poliovirus (i.e., Poliovirus PVSRIPO), reovirus (i.e., pelareorep), moloney murine leukemia virus (i.e., Toca 511 vector), and vaccinia virus (i.e., vaccinia virus TG6002) as possible life-changing alleviations for GBM have been discussed. To the best of our knowledge, this review is the first review that comprehensively discusses both (i) the negative/positive association of air pollution with GBM; and (ii) the application of oncolytic viruses for GBM, including the most recent advances and clinical trials. It is also the first review that addresses the controversies over air pollution and brain cancer association. We believe that the article will significantly appeal to a broad readership of virologists, oncologists, neurologists, environmentalists, and those who work in the field of (bio)energy. Policymakers may also use it to establish better health policies and regulations about air pollution and (bio)fuels exploration, production, and consumption.