Combination therapy involving adenovirus-mediated transfer of the genes for herpes thymidine kinase (tk) and murine interleukin 2 (mIL-2) was used to treat head and neck cancer in C3H/HeJ mice. Tumors were generated by transcutaneous injection of 5 X 10(5) murine squamous carcinoma cells into the floor of the mouth of these syngeneic mice. After 1 week, recombinant adenoviral vectors containing...

A crystal-like ordered microporous inorganic hybrid solid was prepared using silane functionalized Cr-MIL-101 (Si-MIL-101) as the precursor, via a surface coating reinforced framework strategy.

A detailed hydrographic survey of the water column of the Amazon shelf was performed using stable oxygen and hydrogen isotopes to determine the source and fate of waters on the shelf. δO-H2O and δD measurements were made on water column samples from approximately 60 stations (three depths per station) which were each collected during four Amasseds (A Multidisciplinary Amazon Shelf SEDiment Stud...

BACKGROUND Metal organic frameworks (MOFs) have attracted more attention in the last decade because of a suitable pore size, large surface area, and high pore volume. Developing biocompatible MOFs such as the MIL family as a drug delivery system is possible. PURPOSE Flurbiprofen (FBP), a nonsteroidal anti-inflammatory agent, is practically insoluble in aqueous solution, and, therefore, needs ...

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Leishmania donovani is an intracellular protozoan parasite that causes visceral leishmaniasis (VL). Antimonials (SSG) have long been the first-line treatment against VL, but have now been replaced by miltefosine (MIL) in the Indian subcontinent due to the emergence of SSG-resistance. Our previous study hypothesised that SSG-resistant L. donovani might have increased in vivo survival skills whic...

Multiple Instance Learning (MIL) is concerned with learning from sets (bags) of feature vectors (instances), where the individual instance labels are ambiguous. In MIL it is often assumed that positive bags contain at least one instance from a so-called concept in instance space, whereas negative bags only contain negative instances. The classes in a MIL problem are therefore not treated in the...

Multiple-instance learning (MIL) deals with learning under ambiguity, in which patterns to be classified are described by bags of instances. There has been a growing interest in the design and use of MIL algorithms as it provides a natural framework to solve a wide variety of pattern recognition problems. In this paper, we address MIL from a view that transforms the problem into a standard supe...