Inhibition of FLT3: A Prototype for Molecular Targeted Therapy in Acute Myeloid Leukemia

Modern therapy of acute myeloid leukemia (AML) began in 1973 with the first report of the successful combination of daunorubicin and cytarabine, which led to complete remission in approximately 45% of patients. Accurate AML diagnosis was dependent on morphology, aided initially only by cytochemistry. Unlike acute lymphoblastic leukemia (ALL), immunophenotyping offered little in the diagnosis of AML, at least during the 1970s and 1980s. The advent of reliable cytogenetics changed the entire prognostic outlook of AML. With karyotypic analysis, different groups of AML could be classified and stratified for various therapies. Unique mutational profiling was a major advance in further categorizing AML patients, aided by the immunophenotypic identification of antigenic markers on the cells. All these advances were occurring as the understanding of the importance of the tumor burden—known as minimal residual disease (MRD)—became crucial for the management of AML patients. The efficacy of MRD has rapidly progressed in the past decade, from a specificity of 10⁻³ with immunophenotyping to 10⁻⁴ with polymerase chain reaction (PCR), which is only appropriate for some patients with AML, and finally to 10⁻⁵ or even 10⁻⁶ cells with the extraordinary sensitivity of next-generation sequencing (NGS). All of these advances have promoted the concept of personalized medicine, which has led to the advent of targeted agents that can accurately be used for specific diagnostic subtypes. Responses can be predicted and measured accurately. Such targeted agents have now become a cornerstone in the management of AML, increasing efficacy and dramatically reducing toxicity. The focus of this review is on one of the most well-studied targeted agents in AML: the FMS-like tyrosine kinase 3 (FLT3) inhibitors, which have impacted the prognostication and therapeutics of AML. This review selectively discusses the FLT3 inhibitors in detail, as a model for the other burgeoning targeted agents that have already been approved, as well as those that are currently in development.     

The influence of different zeolitic supports on hydrogen production and waste degradation

The photocatalyst composition affects the chemical–physical properties and directly impacts photocatalytic activity, both in the hydrogen production and degradation of organic contaminants. In this work, the influence of zeolitic structures NaA, NaY, and ZSM-5 combined with a 10% active phase, TiO₂ catalyst doped with 1% copper, and cobalt cocatalysts was tested to mineralize the reactive blue dye (CI250) and to produce hydrogen by photocatalysis under ultraviolet radiation. The band gap energy was affected mainly by the cocatalyst, while the Brunauer-Emmett-Teller method (BET) area was affected by the zeolite structure as well as the X-ray diffraction (XRD). The most active catalyst was the Cu@TiO₂/NaY, which promoted a hydrogen production rate of 240 μmolH₂gcat⁻¹ using 10% ethanol (v/v) aqueous solution as a sacrificial agent and mineralization of 53% of the organic dye, followed by the catalysts impregnated on ZSM-5 zeolites, which had discolouration up to 50% and hydrogen evolution of 92.6 and 109.7 μmolH₂gcat⁻¹ for the catalyst doped with Cu and Co, respectively.     

Identification of an insulin-responsive, slow endocytic recycling mechanism in Chinese hamster ovary cells

In adipocytes, the insulin-regulated aminopeptidase (IRAP) is trafficked through the same insulin-regulated recycling pathway as the GLUT4 glucose transporter. We find that a chimera, containing the cytoplasmic domain of IRAP fused to transmembrane and extracellular domains of the transferrin receptor, is slowly recycled and rapidly internalized in Chinese hamster ovary cells. Morphological studies indicate that the chimera is slowly trafficked through the general endosomal recycling compartment rather than being sorted to a specialized recycling pathway. A chimera in which a di-leucine sequence within the cytoplasmic domain of IRAP has been mutated to alanines is rapidly internalized and rapidly recycled, indicating that this di-leucine is required for the slow recycling but not for the rapid internalization. Insulin stimulates a 2-3-fold increase in the recycling of the chimera and only a 1.2-fold increase in the recycling of the transferrin receptor. The effect of insulin on the recycling of the chimera is blocked by wortmannin, a phosphatidylinositol 3'-kinase inhibitor. GTPgammaS (guanosine 5'-3-O-(thio)triphosphate) increases the recycling of the chimera by 50% but has no effect on the recycling of the transferrin receptor. In these studies, we have identified in Chinese hamster ovary cells a novel, slow endocytic recycling mechanism that is regulated by insulin.     

An automatically tuning intrusion detection system.

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.     

Fuzzy operator logic and fuzzy resolution

There have been only few attempts to extend fuzzy logic to automated theorem proving. In particular, the applicability of the resolution principle to fuzzy logic has been little examined. The approaches that have been suggested in the literature, however, have made some semantic assumptions which resulted in limitations and inflexibilities of the inference mechanism. In this paper we present a new approach to fuzzy logic and reasoning under uncertainty using the resolution principle based on a new operator, the fuzzy operator. We present the fuzzy resolution principle for this logic and show its completeness as an inference rule.