Substance use disorders continue to be major medical and social problems worldwide. The use of opiate has grown substantially over the past three decades reaching the dimensions of a global epidemic. Current drug treatments have many limitations: long treatment times, dependency on treatment medications, relapses after treatment, high costs of treatment, and non-adherence by affected persons. Most of the available drug treatments for opiate addiction belong to the opioid family. Some worry that the availability of the drugs may simply cause substituting one opioid medication for another.

The discovery of proper sensitizers for immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) treatment represents a significant breakthrough in the field of cancer therapy, but it is still in initial stage [1,2].

Machine learning (ML) is a branch of artificial intelligence that uses an algorithm to process the data, retrieve valuable information, learn from it, find a pattern, and make predictions. Manual data analyses suffer from several disadvantages including it is time-consuming and subject to error.

Lung cancer is the leading cause of cancer death among both men and women in the United States. Because lung cancer is genetically heterogeneous, tailored therapy alone or in combination with chemotherapy would increase patient overall survival as compared with the one-size-fits-all chemotherapy. TP53-mutant lung cancer accounts for more than half of all lung cancer cases and is oftentimes more aggressive and resistant to chemotherapy. Directly targeting mutant p53 has not yet been successful, so identification of novel therapy targets and biomarkers in the TP53-mutant lung cancer is urgently needed to increase the overall survival in this subgroup.

Arthritis remains a common and debilitating disease affecting millions of people worldwide. Osteoarthritis (OA) and rheumatoid arthritis (RA) are among the most common forms of this chronic, degenerative disease, which is moving toward precision medicine.