203 research outputs found
A Framework for Automatic Behavior Generation in Multi-Function Swarms
17 USC 105 interim-entered record; under review.Multi-function swarms are swarms that solve multiple tasks at once. For example, a quadcopter swarm could be tasked with exploring an area of interest while simultaneously functioning as ad-hoc relays. With this type of multi-function comes the challenge of handling potentially conflicting requirements simultaneously. Using the Quality-Diversity algorithm MAP-elites in combination with a suitable controller structure, a framework for automatic behavior generation in multi-function swarms is proposed. The framework is tested on a scenario with three simultaneous tasks: exploration, communication network creation and geolocation of Radio Frequency (RF) emitters. A repertoire is evolved, consisting of a wide range of controllers, or behavior primitives, with different characteristics and trade-offs in the different tasks. This repertoire enables the swarm to online transition between behaviors featuring different trade-offs of applications depending on the situational requirements. Furthermore, the effect of noise on the behavior characteristics in MAP-elites is investigated. A moderate number of re-evaluations is found to increase the robustness while keeping the computational requirements relatively low. A few selected controllers are examined, and the dynamics of transitioning between these controllers are explored. Finally, the study investigates the importance of individual sensor or controller inputs. This is done through ablation, where individual inputs are disabled and their impact on the performance of the swarm controllers is assessed and analyzed
A Framework for Automatic Behavior Generation in Multi-Function Swarms
Multi-function swarms are swarms that solve multiple tasks at once. For
example, a quadcopter swarm could be tasked with exploring an area of interest
while simultaneously functioning as ad-hoc relays. With this type of
multi-function comes the challenge of handling potentially conflicting
requirements simultaneously. Using the Quality-Diversity algorithm MAP-elites
in combination with a suitable controller structure, a framework for automatic
behavior generation in multi-function swarms is proposed. The framework is
tested on a scenario with three simultaneous tasks: exploration, communication
network creation and geolocation of RF emitters. A repertoire is evolved,
consisting of a wide range of controllers, or behavior primitives, with
different characteristics and trade-offs in the different tasks. This
repertoire would enable the swarm to transition between behavior trade-offs
online, according to the situational requirements. Furthermore, the effect of
noise on the behavior characteristics in MAP-elites is investigated. A moderate
number of re-evaluations is found to increase the robustness while keeping the
computational requirements relatively low. A few selected controllers are
examined, and the dynamics of transitioning between these controllers are
explored. Finally, the study develops a methodology for analyzing the makeup of
the resulting controllers. This is done through a parameter variation study
where the importance of individual inputs to the swarm controllers is assessed
and analyzed
Gefitinib in Combination with Weekly Docetaxel in Patients with Metastatic Breast Cancer Caused Unexpected Toxicity: Results from a Randomized Phase II Clinical Trial
In patients with metastatic breast cancer, taxane treatment demonstrates activity but is not curative. Targeted treatment modalities are therefore necessary in order to improve outcomes in this group. A randomized placebo-controlled phase II trial was initiated to evaluate effect and toxicity of gefitinib (250 mg QD) and docetaxel 35 mg/m2 (six of seven weeks) (NCT 00319618). The inclusion of 66 patients was planned. The study was closed due to treatment-related toxicity. Of the 18 included patients, seven (of which three received gefitinib) were withdrawn from the study due to toxicity. Of the nine patients receiving gefitinib and chemotherapy, one achieved a partial response and four stable disease. In the chemotherapy of nine patients, four had a partial response and four stable disease. The breast cancer patients in this study were genotyped using a panel of 14 single-nucleotide polymorphisms (SNPs), previously found associated with docetaxel clearance in a cohort of lung cancer patients. We were unable to identify genes related to toxicity in this study. Nevertheless, toxicity was aggravated by the addition of the tyrosine kinase inhibitor. In conclusion, despite adequately tolerated as monotherapy, combination regimens should be carefully considered for overlapping adverse events in order to avoid increased treatment-related toxicity
High-throughput screen in vitro identifies dasatinib as a candidate for combinatorial treatment with HER2-targeting drugs in breast cancer
Peer reviewe
Detection of phenotype-specific therapeutic vulnerabilities in breast cells using a CRISPR loss-of-function screen
publishedVersio
Therapeutic Effects of Holmium-166 Chitosan Complex in Rat Brain Tumor Model
This study examined the effectiveness of Holmium-166 (Ho-166) chitosan complex therapy for a malignant glioma. Cultured C6 glioma cells (100,000 in 5 µl) were injected into the caudate/putamen of 200 - 250 gram Wistar rats. Five days later, a Ho-166 chitosan complex was injected into the same site of the glioma injection. Four injection doses were administered: the control group received PBS 10 µl, group 1 received an injection of 100 µCi (10 µl), group 2 received an injection of 50 µCi (5 µl), and group 3 received an injection of 10 µCi (1 µl). The average tumor volume for each group was 1.385 mm3 for the control group, 0.036 mm3 for group 1, 0.104 mm3 for group 2, and 0.111 mm3 for group 3. Compared with the control group, the size of the tumors in groups 1, 2 and 3 was reduced by an average of 97.4%, 92.5% and 91.9%, respectively. The Kaplan-Meier survival curve of group 2 was the longest, followed by groups 3, group 1 and the control. The mean survival was 22.8, 59, 60, and 44.6 days for the control group and groups 3, 2 and 1, respectively. H-E staining revealed that group 2 yielded the best results in the destruction of the malignant glioma. TUNEL staining and immunohistochemical studies indicated apoptotic features. The Ho-166 chitosan complex proved to be effective in destroying the malignant glioma
Expression of CD44 3′-untranslated region regulates endogenous microRNA functions in tumorigenesis and angiogenesis
The non-coding 3′-untranslated region (UTR) plays an important role in the regulation of microRNA (miRNA) functions, since it can bind and inactivate multiple miRNAs. Here, we show the 3′-UTR of CD44 is able to antagonize cytoplasmic miRNAs, and result in the increased translation of CD44 and downstream target mRNA, CDC42. A series of cell function assays in the human breast cancer cell line, MT-1, have shown that the CD44 3′-UTR inhibits proliferation, colony formation and tumor growth. Furthermore, it modulated endothelial cell activities, favored angiogenesis, induced tumor cell apoptosis and increased sensitivity to Docetaxel. These results are due to the interaction of the CD44 3′-UTR with multiple miRNAs. Computational algorithms have predicted three miRNAs, miR-216a, miR-330 and miR-608, can bind to both the CD44 and CDC42 3′-UTRs. This was confirmed with luciferase assays, western blotting and immunohistochemical staining and correlated with a series of siRNA assays. Thus, the non-coding CD44 3′-UTR serves as a competitor for miRNA binding and subsequently inactivates miRNA functions, by freeing the target mRNAs from being repressed
Neoadjuvant chemotherapy in breast cancer-response evaluation and prediction of response to treatment using dynamic contrast-enhanced and diffusion-weighted MR imaging
Objective To explore the predictive value of MRI parameters and tumour characteristics before neoadjuvant chemotherapy (NAC) and to compare changes in tumour size and tumour apparent diffusion coefficient (ADC) during treatment, between patients who achieved pathological complete response (pCR) and those who did not. Methods Approval by the Regional Ethics Committee and written informed consent were obtained. Thirty-one patients with invasive breast carcinoma scheduled for NAC were enrolled (mean age, 50.7; range, 37–72). Study design included MRI before treatment (Tp0), after four cycles of NAC (Tp1) and before surgery (Tp2). Data in pCR versus non-pCR groups were compared and cut-off values for pCR prediction were evaluated. Results Before NAC, HER2 overexpression was the single significant predictor of pCR (p=0.006). At Tp1 ADC, tumour size and changes in tumour size were all significantly different in the pCR and non-pCR groups. Using 1.42×10−3 mm2/s as the cut-off value for ADC, pCR was predicted with sensitivity and specificity of 88% and 80%, respectively. Using a cut-off value of 83% for tumour volume reduction, sensitivity and specificity for pCR were 91% and 80%. Conclusion ADC, tumour size and tumour size reduction at Tp1 were strong independent predictors of pCR
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