Repurposing Metabolic Inhibitors in the Treatment of Colon Adenocarcinoma Patient-Derived Models.

The effect of agonists on AMP-activated protein kinase (AMPK), mainly metformin and phenformin, has been appreciated in the treatment of multiple types of tumors. Specifically, the antitumor activity of phenformin has been demonstrated in melanomas containing the v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) activating mutation. In this report, we elucidated the synergistic antitumor effects of biguanides with metabolism inhibitors on colon tumors. Phenformin with 2-deoxy-D-glucose (2DG) inhibited tumor cell growth in cancer cell lines, including HT29 cells harboring BRAF- and p53-mutations. Biochemical analyses showed that two chemotherapeutics exerted cooperative effects to reduce tumor growth through cell cycle arrest, apoptosis, and autophagy. The drugs demonstrated activity against phosphorylated ERK and the gain-of-function p53 mutant protein. To demonstrate tumor regressive effects in vivo, we established patient-derived models, including xenograft (PDX) and organoids (PDO). Co-treatment of biguanides with chemotherapeutics efficiently reduced the growth of patient-derived colon models in comparison to treatment with a single agent. These results strongly suggest that significant therapeutic advantages would be achieved by combining AMPK activators such as phenformin and cancer metabolic inhibitors such as 2DG.

A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.