A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer.

To better understand the relationship between tumor-host interactions and the efficacy of chemotherapy, we have developed an analytical approach to quantify several biological processes observed in gene expression data sets. We tested the approach on tumor biopsies from individuals with estrogen receptor-negative breast cancer treated with chemotherapy. We report that increased stromal gene expression predicts resistance to preoperative chemotherapy with 5-fluorouracil, epirubicin and cyclophosphamide (FEC) in subjects in the EORTC 10994/BIG 00-01 trial. The predictive value of the stromal signature was successfully validated in two independent cohorts of subjects who received chemotherapy but not in an untreated control group, indicating that the signature is predictive rather than prognostic. The genes in the signature are expressed in reactive stroma, according to reanalysis of data from microdissected breast tumor samples. These findings identify a previously undescribed resistance mechanism to FEC treatment and suggest that antistromal agents may offer new ways to overcome resistance to chemotherapy.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Europa als ulls dels Annales (1093-1933)

During this first third of this century, the continent of Europe witnessed far-reaching territorial transformations in the nineteenth century model. To some extent, the setting wich had inspired the epistemological structure of the French regional school was being replaced by one in which -at least to externa1 appearances- the relationship between the physical environment and human activities was much less evident. The adaptation of the theoretical and methodological context to the new Europe seems to take the form of a non-lineal evolution, for in the latter years of the period examined, evolutionary tendencies indicate a return to the more classical model. In this way, the growing interest which the publication had shown in Atlantic Europe and topics of a more economic nature, was truncated. The traditional settings --especially the Mediterranean- came to the fore again and interest in rural societies was renewed. Likewise, the monographic studies which had demonstrated distinct functional objectives in the midtwenties, recovered elements of ecological explanation, and the search for the relationship between environment and society

La vie des oiseaux : scènes d'après nature / par le Bon d'Hamonville,...

Collection : Bibliothèque scientifique contemporaine

The Effect of Adding CO2 to Hypoxic Inspired Gas on Cerebral Blood Flow Velocity and Breathing during Incremental Exercise

Hypoxia increases the ventilatory response to exercise, which leads to hyperventilation-induced hypocapnia and subsequent reduction in cerebral blood flow (CBF). We studied the effects of adding CO2 to a hypoxic inspired gas on CBF during heavy exercise in an altitude naïve population. We hypothesized that augmented inspired CO2 and hypoxia would exert synergistic effects on increasing CBF during exercise, which would improve exercise capacity compared to hypocapnic hypoxia. We also examined the responsiveness of CO2 and O2 chemoreception on the regulation ventilation (E) during incremental exercise. We measured middle cerebral artery velocity (MCAv; index of CBF), E, end-tidal PCO2, respiratory compensation threshold (RC) and ventilatory response to exercise (E slope) in ten healthy men during incremental cycling to exhaustion in normoxia and hypoxia (FIO2 = 0.10) with and without augmenting the fraction of inspired CO2 (FICO2). During exercise in normoxia, augmenting FICO2 elevated MCAv throughout exercise and lowered both RC onset andE slope below RC (P<0.05). In hypoxia, MCAv and E slope below RC during exercise were elevated, while the onset of RC occurred at lower exercise intensity (P<0.05). Augmenting FICO2 in hypoxia increased E at RC (P<0.05) but no difference was observed in RC onset, MCAv, or E slope below RC (P>0.05). The E slope above RC was unchanged with either hypoxia or augmented FICO2 (P>0.05). We found augmenting FICO2 increased CBF during sub-maximal exercise in normoxia, but not in hypoxia, indicating that the 'normal' cerebrovascular response to hypercapnia is blunted during exercise in hypoxia, possibly due to an exhaustion of cerebral vasodilatory reserve. This finding may explain the lack of improvement of exercise capacity in hypoxia with augmented CO2. Our data further indicate that, during exercise below RC, chemoreception is responsive, while above RC the ventilatory response to CO2 is blunted.

Data-parallel computation in parallel and distributed environments

The past few decades have seen a considerable increase in the number of parallel and distributed systems. With the development of more complex applications, the need for more powerful systems has emerged and various parallel and distributed environments have been designed and implemented. Each of the environments, including hardware and software, has unique strengths and weaknesses. There is no single parallel environment that can be identified as the best environment for all applications with respect to hardware and software properties. The main goal of this thesis is to provide a novel way of performing data-parallel computation in parallel and distributed environments by utilizing the best characteristics of difference aspects of parallel computing. For the purpose of this thesis, three aspects of parallel computing were identified and studied. First, three parallel environments (shared memory, distributed memory, and a network of workstations) are evaluated to quantify theirsuitability for different parallel applications. Due to the parallel and distributed nature of the environments, networks connecting the processors in these environments were investigated with respect to their performance characteristics. Second, scheduling algorithms are studied in order to make them more efficient and effective. A concept of application-specific information scheduling is introduced. The application- specific information is data about the workload extractedfrom an application, which is provided to a scheduling algorithm. Three scheduling algorithms are enhanced to utilize the application-specific information to further refine their scheduling properties. A more accurate description of the workload is especially important in cases where the workunits are heterogeneous and the parallel environment is heterogeneous and/or non-dedicated. The results obtained show that the additional information regarding the workload has a positive impact on the performance of applications. Third, a programming paradigm for networks of symmetric multiprocessor (SMP) workstations is introduced. The MPIT programming paradigm incorporates the Message Passing Interface (MPI) with threads to provide a methodology to write parallel applications that efficiently utilize the available resources and minimize the overhead. The MPIT allows for communication and computation to overlap by deploying a dedicated thread for communication. Furthermore, the programming paradigm implements an application-specific scheduling algorithm. The scheduling algorithm is executed by the communication thread. Thus, the scheduling does not affect the execution of the parallel application. Performance results achieved from the MPIT show that considerable improvements over conventional MPI applications are achieved.