The predominance of M2-polarized macrophages in the stroma of low-hypoxic bladder tumors is associated with BCG immunotherapy failure

OBJECTIVE: Bacillus Calmette-Guérin (BCG) immunotherapy is the gold standard treatment for superficial bladder tumors with intermediate/high risk of recurrence or progression. However, approximately 30% of patients fail to respond to the treatment. Effective BCG therapy needs precise activation of the type 1 helper cells immune pathway. Tumor-associated macrophages (TAMs) often assume an immunoregulatory M2 phenotype and may directly interfere with the BCG-induced antitumor immune response. Thus, we aim to clarify the influence of TAMs, in particular of the M2 phenotype in stroma and tumor areas, in BCG treatment outcome. PATIENTS AND METHODS: The study included 99 patients with bladder cancer treated with BCG. Tumors resected before treatment were evaluated using immunohistochemistry for CD68 and CD163 antigens, which identify a lineage macrophage marker and a M2-polarized specific cell surface receptor, respectively. CD68+ and CD163+ macrophages were evaluated within the stroma and tumor areas, and high density of infiltrating cells spots were selected for counting. Hypoxia, an event known to modulate macrophage phenotype, was also assessed through hypoxia induced factor (HIF)-1α expression. RESULTS: Patients in whom BCG failed had high stroma-predominant CD163+ macrophage counts (high stroma but low tumor CD163+ macrophages counts) when compared with the ones with a successful treatment (71% vs. 47%, P = 0.017). Furthermore, patients presenting this phenotype showed decreased recurrence-free survival (log rank, P = 0.008) and a clear 2-fold increased risk of BCG treatment failure was observed in univariate analysis (hazard ratio = 2.343; 95% CI: 1.197-4.587; P = 0.013). Even when adjusted for potential confounders, such as age and therapeutic scheme, multivariate analysis revealed 2.6-fold increased risk of recurrence (hazard ratio = 2.627; 95% CI: 1.340-5.150; P = 0.005). High stroma-predominant CD163+ macrophage counts were also associated with low expression of HIF-1α in tumor areas, whereas high counts of CD163+ in the tumor presented high expression of HIF-1α in tumor nests. CONCLUSIONS: TAMs evaluation using CD163 is a good indicator of BCG treatment failure. Moreover, elevated infiltration of CD163+ macrophages, predominantly in stroma areas but not in the tumor, may be a useful indicator of BCG treatment outcome, possibly owing to its immunosuppressive phenotype.

Provably good scheduling of sporadic tasks with resource sharing on a two-type heterogeneous multiprocessor platform

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of |R| shared resources. There are m1 processors of type-1 and m2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3Cvpr also meets deadlines if given processors 4+6*ceil(|R|/min(m1,m2)) times as fast. As far as we know, it is the first result for resource sharing on heterogeneous platforms with provable performance.

A conjecture about provably good task assignment on heterogeneous multiprocessor platforms but with a stronger adversary

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a heterogeneous multiprocessor platform. We use an algorithm proposed in [1] (we refer to it as LP-EE) from state-of-the-art for assigning tasks to heterogeneous multiprocessor platform and (re-)prove its performance guarantee but for a stronger adversary.We conjecture that if a task set can be scheduled to meet deadlines on a heterogeneous multiprocessor platform by an optimal task assignment scheme that allows task migrations then LP-EE meets deadlines as well with no migrations if given processors twice as fast. We illustrate this with an example.

Provably good task assignment on heterogeneous multiprocessor platforms for a restricted case but with a stronger adversary

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a heterogeneous multiprocessor platform. We consider a restricted case where the maximum utilization of any task on any processor in the system is no greater than one. We use an algorithm proposed in [1] (we refer to it as LP-EE) from state-of-the-art for assigning tasks to heterogeneous multiprocessor platform and (re-)prove its performance guarantee for this restricted case but for a stronger adversary. We show that if a task set can be scheduled to meet deadlines on a heterogeneous multiprocessor platform by an optimal task assignment scheme that allows task migrations then LP-EE meets deadlines as well with no migrations if given processors twice as fast.

Provably good multiprocessor scheduling with resource sharing

We present a 12(1 + 3R/(4m)) competitive algorithm for scheduling implicit-deadline sporadic tasks on a platform comprising m processors, where a task may request one of R shared resources.

Penalty fuzzy function for derivative-free optimization

Penalty and Barrier methods are normally used to solve Nonlinear Optimization Problems constrained problems. The problems appear in areas such as engineering and are often characterised by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. This means that optimization methods based on derivatives cannot net used. A Java based API was implemented, including only derivative-free optimizationmethods, to solve both constrained and unconstrained problems, which includes Penalty and Barriers methods. In this work a new penalty function, based on Fuzzy Logic, is presented. This function imposes a progressive penalization to solutions that violate the constraints. This means that the function imposes a low penalization when the violation of the constraints is low and a heavy penalisation when the violation is high. The value of the penalization is not known in beforehand, it is the outcome of a fuzzy inference engine. Numerical results comparing the proposed function with two of the classic penalty/barrier functions are presented. Regarding the presented results one can conclude that the prosed penalty function besides being very robust also exhibits a very good performance.

Development of procedures for the simulation of atmospheric flows over complex terrain, using OpenFOAM

The main purpose of this work was the development of procedures for the simulation of atmospheric ows over complex terrain, using OpenFOAM. For this aim, tools and procedures were developed apart from this code for the preprocessing and data extraction, which were thereafter applied in the simulation of a real case. For the generation of the computational domain, a systematic method able to translate the terrain elevation model to a native OpenFOAM format (blockMeshDict) was developed. The outcome was a structured mesh, in which the user has the ability to de ne the number of control volumes and its dimensions. With this procedure, the di culties of case set up and the high computation computational e ort reported in literature associated to the use of snappyHexMesh, the OpenFOAM resource explored until then for the accomplishment of this task, were considered to be overwhelmed. Developed procedures for the generation of boundary conditions allowed for the automatic creation of idealized inlet vertical pro les, de nition of wall functions boundary conditions and the calculation of internal eld rst guesses for the iterative solution process, having as input experimental data supplied by the user. The applicability of the generated boundary conditions was limited to the simulation of turbulent, steady-state, incompressible and neutrally strati ed atmospheric ows, always recurring to RaNS (Reynolds-averaged Navier-Stokes) models. For the modelling of terrain roughness, the developed procedure allowed to the user the de nition of idealized conditions, like an uniform aerodynamic roughness length or making its value variable as a function of topography characteristic values, or the using of real site data, and it was complemented by the development of techniques for the visual inspection of generated roughness maps. The absence and the non inclusion of a forest canopy model limited the applicability of this procedure to low aerodynamic roughness lengths. The developed tools and procedures were then applied in the simulation of a neutrally strati ed atmospheric ow over the Askervein hill. In the performed simulations was evaluated the solution sensibility to di erent convection schemes, mesh dimensions, ground roughness and formulations of the k - ε and k - ω models. When compared to experimental data, calculated values showed a good agreement of speed-up in hill top and lee side, with a relative error of less than 10% at a height of 10 m above ground level. Turbulent kinetic energy was considered to be well simulated in the hill windward and hill top, and grossly predicted in the lee side, where a zone of ow separation was also identi ed. Despite the need of more work to evaluate the importance of the downstream recirculation zone in the quality of gathered results, the agreement between the calculated and experimental values and the OpenFOAM sensibility to the tested parameters were considered to be generally in line with the simulations presented in the reviewed bibliographic sources.

Immunohistochemical molecular phenotypes of gastric cancer based on SOX2 and CDX2 predict patient outcome

Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.

TERT Promoter Mutations Are a Major Indicator of Poor Outcome in Differentiated Thyroid Carcinomas

Context: Telomerase promoter mutations (TERT) were recently described in follicular cell-derived thyroid carcinomas (FCDTC) and seem to be more prevalent in aggressive cancers. Objectives: We aimed to evaluate the frequency of TERT promoter mutations in thyroid lesions and to investigate the prognostic significance of such mutations in a large cohort of patients with differentiated thyroid carcinomas (DTCs). Design: This was a retrospective observational study. Setting and Patients: We studied 647 tumors and tumor-like lesions. A total of 469 patients with FCDTC treated and followed in five university hospitals were included. Mean follow-up (±SD) was 7.8 ± 5.8 years. Main Outcome Measures: Predictive value of TERT promoter mutations for distant metastasization, disease persistence at the end of follow-up, and disease-specific mortality. Results: TERT promoter mutations were found in 7.5% of papillary carcinomas (PTCs), 17.1% of follicular carcinomas, 29.0% of poorly differentiated carcinomas, and 33.3% of anaplastic thyroid carcinomas. Patients with TERT-mutated tumors were older (P < .001) and had larger tumors (P = .002). In DTCs, TERT promoter mutations were significantly associated with distant metastases (P < .001) and higher stage (P < .001). Patients with DTC harboring TERT promoter mutations were submitted to more radioiodine treatments (P = .009) with higher cumulative dose (P = .004) and to more treatment modalities (P = .001). At the end of follow-up, patients with TERT-mutated DTCs were more prone to have persistent disease (P = .001). TERT promoter mutations were significantly associated with disease-specific mortality [in the whole FCDTC (P < .001)] in DTCs (P < .001), PTCs (P = .001), and follicular carcinomas (P < .001). After adjusting for age at diagnosis and gender, the hazard ratio was 10.35 (95% confidence interval 2.01–53.24; P = .005) in DTC and 23.81 (95% confidence interval 1.36–415.76; P = .03) in PTCs. Conclusions: TERT promoter mutations are an indicator of clinically aggressive tumors, being correlated with worse outcome and disease-specific mortality in DTC. TERT promoter mutations have an independent prognostic value in DTC and, notably, in PTC.

Unified overhead-aware schedulability analysis for slot-based task-splitting

Hard real- time multiprocessor scheduling has seen, in recent years, the flourishing of semi-partitioned scheduling algorithms. This category of scheduling schemes combines elements of partitioned and global scheduling for the purposes of achieving efficient utilization of the system’s processing resources with strong schedulability guarantees and with low dispatching overheads. The sub-class of slot-based “task-splitting” scheduling algorithms, in particular, offers very good trade-offs between schedulability guarantees (in the form of high utilization bounds) and the number of preemptions/migrations involved. However, so far there did not exist unified scheduling theory for such algorithms; each one was formulated in its own accompanying analysis. This article changes this fragmented landscape by formulating a more unified schedulability theory covering the two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F (both fixed job-priority based). This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analysis. In turn, since schedulability testing guides the task assignment under the schemes in consideration, we also formulate an improved task assignment procedure. As the other main contribution of this article, and as a response to the fact that many unrealistic assumptions, present in the original theory, tend to undermine the theoretical potential of such scheduling schemes, we identified and modelled into the new analysis all overheads incurred by the algorithms in consideration. The outcome is a new overhead-aware schedulability analysis that permits increased efficiency and reliability. The merits of this new theory are evaluated by an extensive set of experiments.

Provably Good Task Assignment for Two-Type Heterogeneous Multiprocessors Using Cutting Planes

Consider scheduling of real-time tasks on a multiprocessor where migration is forbidden. Specifically, consider the problem of determining a task-to-processor assignment for a given collection of implicit-deadline sporadic tasks upon a multiprocessor platform in which there are two distinct types of processors. For this problem, we propose a new algorithm, LPC (task assignment based on solving a Linear Program with Cutting planes). The algorithm offers the following guarantee: for a given task set and a platform, if there exists a feasible task-to-processor assignment, then LPC succeeds in finding such a feasible task-to-processor assignment as well but on a platform in which each processor is 1.5 × faster and has three additional processors. For systems with a large number of processors, LPC has a better approximation ratio than state-of-the-art algorithms. To the best of our knowledge, this is the first work that develops a provably good real-time task assignment algorithm using cutting planes.

The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.