Understanding Fairness and its Impact on Quality of Service in IEEE 802.11

The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this paper we provide an accurate model for the fairness of the DCF. Given M greedy stations we assume fairness if a tagged station contributes a share of 1/M to the overall number of packets transmitted. We derive the probability distribution of fairness deviations and support our analytical results by an extensive set of measurements. We find a closed-form expression for the improvement of long-term over short-term fairness. Regarding the random countdown values we quantify the significance of their distribution whereas we discover that fairness is largely insensitive to the distribution parameters. Based on our findings we view the DCF as emulating an ideal fair queuing system to quantify the deviations from a fair rate allocation. We deduce a stochastic service curve model for the DCF to predict packet delays in IEEE 802.11. We show how a station can estimate its fair bandwidth share from passive measurements of its traffic arrivals and departures

Kinomic exploration of temozolomide and radiation resistance in Glioblastoma multiforme xenolines

Glioblastoma multiforme (GBM) represents the most common and deadly primary brain malignancy, particularly due to temozolomide (TMZ) and radiation (RT) resistance. To better understand resistance mechanisms, we examined global kinase activity (kinomic profiling) in both treatment sensitive and resistant human GBM patient-derived xenografts (PDX or “xenolines”)

Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study.

BACKGROUND: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas. METHODS AND FINDINGS: We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p \u3c 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p \u3c 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials. CONCLUSIONS: The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life

BMP signaling mediates glioma stem cell quiescence and confers treatment resistance in glioblastoma.

Despite advances in therapy, glioblastoma remains an incurable disease with a dismal prognosis. Recent studies have implicated cancer stem cells within glioblastoma (glioma stem cells, GSCs) as mediators of therapeutic resistance and tumor progression. In this study, we investigated the role of the transforming growth factor-β (TGF-β) superfamily, which has been found to play an integral role in the maintenance of stem cell homeostasis within multiple stem cell systems, as a mediator of stem-like cells in glioblastoma. We find that BMP and TGF-β signaling define divergent molecular and functional identities in glioblastoma, and mark relatively quiescent and proliferative GSCs, respectively. Treatment of GSCs with BMP inhibits cell proliferation, but does not abrogate their stem-ness, as measured by self-renewal and tumorigencity. Further, BMP pathway activation confers relative resistance to radiation and temozolomide chemotherapy. Our findings define a quiescent cancer stem cell population in glioblastoma that may be a cellular reservoir for tumor recurrence following cytotoxic therapy

MicroRNA-31 is required for astrocyte specification

Previously, we determined microRNA-31 (miR-31) is a noncoding tumor suppressive gene frequently deleted in glioblastoma (GBM); miR-31 suppresses tumor growth, in part, by limiting the activity of NF-κB. Herein, we expand our previous studies by characterizing the role of miR-31 during neural precursor cell (NPC) to astrocyte differentiation. We demonstrate that miR-31 expression and activity is suppressed in NPCs by stem cell factors such as Lin28, c-Myc, SOX2 and Oct4. However, during astrocytogenesis, miR-31 is induced by STAT3 and SMAD1/5/8, which mediate astrocyte differentiation. We determined miR-31 is required for terminal astrocyte differentiation, and that the loss of miR-31 impairs this process and/or prevents astrocyte maturation. We demonstrate that miR-31 promotes astrocyte development, in part, by reducing the levels of Lin28, a stem cell factor implicated in NPC renewal. These data suggest that miR-31 deletions may disrupt astrocyte development and/or homeostasis

Early termination of ISRCTN45828668, a phase 1/2 prospective, randomized study of Sulfasalazine for the treatment of progressing malignant gliomas in adults

BACKGROUND: Sulfasalazine, a NF-kappaB and x(c)-cystine/glutamate antiport inhibitor, has demonstrated a strong antitumoral potential in preclinical models of malignant gliomas. As it presents an excellent safety profile, we initiated a phase 1/2 clinical study of this anti-inflammatory drug for the treatment of recurrent WHO grade 3 and 4 astrocytic gliomas in adults. METHODS: 10 patients with advanced recurrent anaplastic astrocytoma (n = 2) or glioblastoma (n = 8) aged 32-62 years were recruited prior to the planned interim analysis of the study. Subjects were randomly assigned to daily doses of 1.5, 3, 4.5, or 6 grams of oral sulfasalazine, and treated until clinical or radiological evidence of disease progression or the development of serious or unbearable side effects. Primary endpoints were the evaluation of toxicities according to the CTCAE v.3.0, and the observation of radiological tumor responses based on MacDonald criteria. RESULTS: No clinical response was observed. One tumor remained stable for 2 months with sulfasalazine treatment, at the lowest daily dose of the drug. The median progression-free survival was 32 days. Side effects were common, as all patients developed grade 1-3 adverse events (mean: 7.2/patient), four patients developed grade 4 toxicity. Two patients died while on treatment or shortly after its discontinuation. CONCLUSION: Although the proper influence of sulfasalazine treatment on patient outcome was difficult to ascertain in these debilitated patients with a large tumor burden (median KPS = 50), ISRCTN45828668 was terminated after its interim analysis. This study urges to exert cautiousness in future trials of Sulfasalazine for the treatment of malignant gliomas. TRIAL REGISTRATION: Current Controlled Trials ISRCTN45828668