The research of cellulose derivatives as chiral stationary phases and high performance liquid chromatography with polarimeter as on-line detector

Three cellulose derivatives were synthesized and used as chiral stationary phases based on silica gel. The effects of adsorbances on the column numbers and stabilities have been investigated. These stationary phases exhibited high chiral recognition for various racemates. At the same time, the on-line curves of polarimeter were obtained by high performance liquid chromatography with polarimeter as on-line detector.

On-line concentration of proteins in pressurized capillary electrochromatography coupled with electrospray ionization-mass spectrometry

Pressurized capillary electrochromatography (pCEC) and electrospray ionization-mass spectrometry (ESI-MS) have been hyphenated for protein analysis. Taken cytochrome c, lysozyme, and insulin as samples, the limits of detection (LODs) for absolute concentrations are 10(-11) mol (signal-to-noise ratio S/N = 3) with relative standard deviations (RSDs) of retention time and peak area, respectively, of less than 1.7% and 4.8%. In order to improve the detection sensitivity, on-line concentration by field-enhanced sample-stacking effect and chromatographic zone-sharpening effect has been developed, and parameters affecting separation and detection, such as pH and electrolyte concentration in the mobile phase, separation voltage, as well as enrichment voltage and time, have been studied systematically. Under the optimized conditions, the LODs of the three proteins could be decreased up to 100-fold. In addition, the feasibility of such techniques has been further demonstrated by the analysis of modified insulins at a concentration of 20 mu g/mL.

On-line concentration of peptides and proteins with the hyphenation of polymer monolithic immobilized metal affinity chromatography and capillary electrophoresis

An iminodiacetic acid (IDA)-type adsorbent is prepared at the one end of a capillary by covalently bonding IDA to the monolithic rods of macroporous poly(glycidyl methacrylate-co-ethylene dimethacrylate). Cu(II) is later introduced to the support via the interaction with IDA. By this means, polymer monolithic immobilized metal affinity chromatography (IMAC) materials are prepared. With such a column, IMAC for on-line concentration and capillary electrophoresis (CE) for the subsequent analysis are hyphenated for the analysis of peptides and proteins. The reproducibility of such a column has been proved good with relative standard deviations (RSDs) of dead time of less than 5% for injection-to-injection and 12% for column-to-column (n = 3). Through application on the analysis of standard peptides and real protein samples, such a technique has shown promising in proteome study.

ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

Vector Associative Maps: Unsupervised Real-time Error-based Learning and Control of Movement Trajectories

This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

Paclitaxel versus doxorubicin as first-line single-agent chemotherapy for metastatic breast cancer: a European Organization for Research and Treatment of Cancer Randomized Study with cross-over.

PURPOSE: To compare the efficacy of paclitaxel versus doxorubicin given as single agents in first-line therapy of advanced breast cancer (primary end point, progression-free survival ¿PFS) and to explore the degree of cross-resistance between the two agents. PATIENTS AND METHODS: Three hundred thirty-one patients were randomized to receive either paclitaxel 200 mg/m(2), 3-hour infusion every 3 weeks, or doxorubicin 75 mg/m(2), intravenous bolus every 3 weeks. Seven courses were planned unless progression or unacceptable toxicity occurred before the seven courses were finished. Patients who progressed within the seven courses underwent early cross-over to the alternative drug, while a delayed cross-over was optional for the remainder of patients at the time of disease progression. RESULTS: Objective response in first-line therapy was significantly better (P =.003) for doxorubicin (response rate ¿RR, 41%) than for paclitaxel (RR, 25%), with doxorubicin achieving a longer median PFS (7.5 months for doxorubicin v 3.9 months for paclitaxel, P <.001). In second-line therapy, cross-over to doxorubicin (91 patients) and to paclitaxel (77 patients) gave response rates of 30% and 16%, respectively. The median survival durations of 18.3 months for doxorubicin and 15.6 months for paclitaxel were not significantly different (P =.38). The doxorubicin arm had greater toxicity, but this was counterbalanced by better symptom control. CONCLUSION: At the dosages and schedules used in the present study, doxorubicin achieves better disease and symptom control than paclitaxel in first-line treatment. Doxorubicin and paclitaxel are not totally cross-resistant, which supports further investigation of these drugs in combination or in sequence, both in advanced disease and in the adjuvant setting.

Randomized, controlled trial investigating short-term health-related quality of life with doxorubicin and paclitaxel versus doxorubicin and cyclophosphamide as first-line chemotherapy in patients with metastatic breast cancer: European Organization for Research and Treatment of Cancer Breast Cancer Group, Investigational Drug Branch for Breast Cancer and the New Drug Development Group Study.

PURPOSE: To compare health-related quality of life (HRQOL) in patients with metastatic breast cancer receiving the combination of doxorubicin and paclitaxel (AT) or doxorubicin and cyclophosphamide (AC) as first-line chemotherapy treatment. PATIENTS AND METHODS: Eligible patients (n = 275) with anthracycline-naive measurable metastatic breast cancer were randomly assigned to AT (doxorubicin 60 mg/m(2) as an intravenous bolus plus paclitaxel 175 mg/m(2) as a 3-hour infusion) or AC (doxorubicin 60 mg/m(2) plus cyclophosphamide 600 mg/m(2)) every 3 weeks for a maximum of six cycles. Dose escalation of paclitaxel (200 mg/m(2)) and cyclophosphamide (750 mg/m(2)) was planned at cycle 2 to reach equivalent myelosuppression in the two groups. HRQOL was assessed with the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire C30 and the EORTC Breast Module at baseline and the start of cycles 2, 4, and 6, and 3 months after the last cycle. RESULTS: Seventy-nine percent of the patients (n = 219) completed a baseline measure. However, there were no statistically significant differences in HRQOL between the two treatment groups. In both groups, selected aspects of HRQOL were impaired over time, with increased fatigue, although some clinically significant improvements in emotional functioning were seen, as well as a reduction in pain over time. Overall, global quality of life was maintained in both treatment groups. CONCLUSION: This information is important when advising women patients of the expected HRQOL consequences of treatment regimens and should help clinicians and their patients make informed treatment decisions.

Mature results of a randomized phase II multicenter study of exemestane versus tamoxifen as first-line hormone therapy for postmenopausal women with metastatic breast cancer.

BACKGROUND: Women with hormone-responsive metastatic breast cancer (MBC) may respond to or have stable disease with a number of hormone therapies. We explored the efficacy and safety of the steroidal aromatase inactivator exemestane as first-line hormonal therapy in MBC in postmenopausal women. PATIENTS AND METHODS: Patients with measurable disease were eligible if they had received no prior hormone therapy for metastatic disease and had hormone receptor positive disease or hormone receptor unknown disease with a long disease-free interval from adjuvant therapy. They were randomized to tamoxifen 20 mg/day or exemestane 25 mg/day in this open-label study. RESULTS: Blinded independently reviewed response rates for exemestane and tamoxifen were 41% and 17%, respectively. Fifty-seven per cent of exemestane- and 42% of tamoxifen-treated patients experienced clinical benefit, defined as complete or partial response, or disease stabilization lasting at least 6 months. There was a low incidence of severe flushing, sweating, nausea and edema in women who received exemestane. One exemestane-treated patient had a pulmonary embolism with grade 4 dyspnea. CONCLUSIONS: Exemestane is well tolerated and active in the first-line treatment of hormone-responsive MBC. An ongoing EORTC phase III trial is comparing the efficacy, measuring time-to-disease progression, of exemestane and tamoxifen.

Promising results with exemestane in the first-line treatment of metastatic breast cancer: a randomized phase II EORTC trial with a tamoxifen control.

Because tamoxifen (TAM), a nonsteroidal antiestrogen, is routinely used in the adjuvant setting, other hormone therapies are needed as alternatives for first-line treatment of metastatic breast cancer (MBC). Currently, exemestane (EXE) and other antiaromatase agents are indicated for use in patients who experience failure of TAM. In this multicenter, randomized, open-label, TAM-controlled (20 mg/day), phase II trial, we examined the activity and tolerability of EXE 25 mg/day for the first-line treatment of MBC in postmenopausal women. Exemestane was well tolerated and demonstrated substantial first-line antitumor activity based on intent-to-treat analysis of peer-reviewed responses. In the EXE arm, values for complete, partial, and objective response, clinical benefit, and time to tumor progression (TTP) exceeded those reported for TAM although no statistical comparison was made. Based on these encouraging results, a phase III trial will compare EXE and TAM.

The effect of exemestane on serum lipid profile in postmenopausal women with metastatic breast cancer: a companion study to EORTC Trial 10951, 'Randomized phase II study in first line hormonal treatment for metastatic breast cancer with exemestane or tamoxifen in postmenopausal patients'.

BACKGROUND: The impact of aromatase inhibitors (AIs) on non-cancer-related outcomes, which are known to be affected by oestrogens, has become increasingly important in postmenopausal women with hormone-dependent breast cancer. So far, data related to the effect of AIs on lipid profile in postmenopausal women is scarce. This study, as a companion substudy of an EORTC phase II trial (10951), evaluated the impact of exemestane, a steroidal aromatase inactivator, on the lipid profile of postmenopausal metastatic breast cancer (MBC) patients. PATIENTS AND METHODS: The EORTC trial 10951 randomised 122 postmenopausal breast cancer patients to exemestane (E) 25 mg (n = 62) or tamoxifen (T) 20 mg (n = 60) once daily as a first-line treatment in the metastatic setting. Exemestane showed promising results in all the primary efficacy end points of the trial (response rate, clinical benefit rate and response duration), and it was well tolerated with low incidence of serious toxicity. As a secondary end point of this phase II trial, serum triglycerides (TRG), high-density lipoprotein cholesterol (HDL), total cholesterol (TC), lipoprotein a (Lip a), and apolipoproteins (Apo) B and A1 were measured at baseline and while on therapy (at 8, 24 and 48 weeks) to assess the impact of exemestane and tamoxifen on serum lipid profiles. Of the 122 randomised patients, those who had baseline and at least one other lipid assessment are included in the present analysis. The patients who received concomitant drugs that could affect lipid profile are included only if these drugs were administered throughout the study treatment. Increase or decrease in lipid parameters within 20% of baseline were considered as non-significant and thus unchanged. RESULTS: Seventy-two patients (36 in both arms) were included in the statistical analysis. The majority of patients had abnormal TC and normal TRG, HDL, Apo A1, Apo B and Lip a levels at baseline. Neither exemestane nor tamoxifen had adverse effects on TC, HDL, Apo A1, Apo B or Lip a levels at 8, 24 and 48 weeks of treatment. Exemestane and tamoxifen had opposite effects on TRG levels: exemestane lowered while tamoxifen increased TRG levels over time. There were too few patients with normal baseline TC and abnormal TRG, HDL, Apo A1, Apo B and Lip a levels to allow for assessment of E's impact on these subsets. The atherogenic risk determined by Apo A1:Apo B and TC:HDL ratios remained unchanged throughout the treatment period in both the E and T arms. CONCLUSIONS: Overall, exemestane has no detrimental effect on cholesterol levels and the atherogenic indices, which are well-known risk factors for coronary artery disease. In addition, it has a beneficial effect on TRG levels. These data, coupled with E's excellent efficacy and tolerability, support further exploration of its potential in the metastatic, adjuvant and chemopreventive setting.

Evaluation of tumor response, disease control, progression-free survival, and time to progression as potential surrogate end points in metastatic breast cancer.

PURPOSE: Overall survival (OS) can be observed only after prolonged follow-up, and any potential effect of first-line therapies on OS may be confounded by the effects of subsequent therapy. We investigated whether tumor response, disease control, progression-free survival (PFS), or time to progression (TTP) could be considered a valid surrogate for OS to assess the benefits of first-line therapies for patients with metastatic breast cancer. PATIENTS AND METHODS: Individual patient data were collected on 3,953 patients in 11 randomized trials that compared an anthracycline (alone or in combination) with a taxane (alone or in combination with an anthracycline). Surrogacy was assessed through the correlation between the end points as well as through the correlation between the treatment effects on the end points. RESULTS: Tumor response (survival odds ratio [OR], 6.2; 95% CI, 5.3 to 7.0) and disease control (survival OR, 5.5; 95% CI, 4.8 to 6.3) were strongly associated with OS. PFS (rank correlation coefficient, 0.688; 95% CI, 0.686 to 0.690) and TTP (rank correlation coefficient, 0.682; 95% CI, 0.680 to 0.684) were moderately associated with OS. Response log ORs were strongly correlated with PFS log hazard ratios (linear coefficient [rho], 0.96; 95% CI, 0.73 to 1.19). Response and disease control log ORs and PFS and TTP log hazard ratios were poorly correlated with log hazard ratios for OS, but the confidence limits of rho were too wide to be informative. CONCLUSION: No end point could be demonstrated as a good surrogate for OS in these trials. Tumor response may be an acceptable surrogate for PFS.

On-line algorithms for single machine scheduling with family setup times

The paper considers an on-line single machine scheduling problem where the goal is to minimize the makespan. The jobs are partitioned into families and a setup is performed every time the machine starts processing a batch of jobs of the same family. The scheduler is aware of the number of families and knows the setup time of each family, although information about a job only becomes available when that job is released. We give a lower bound on the competitive ratio of any on-line algorithm. Moreover, for the case of two families, we provide an algorithm with a competitive ratio that achieves this lower bound. As the number of families increases, the lower bound approaches 2, and we give a simple algorithm with a competitive ratio of 2.

On the Front Line: frontal zones as priority at-sea conservation areas for mobile marine vertebrates

1.Identifying priority areas for marine vertebrate conservation is complex because species of conservation concern are highly mobile, inhabit dynamic habitats and are difficult to monitor. 2.Many marine vertebrates are known to associate with oceanographic fronts – physical interfaces at the transition between water masses – for foraging and migration, making them important candidate sites for conservation. Here, we review associations between marine vertebrates and fronts and how they vary with scale, regional oceanography and foraging ecology. 3.Accessibility, spatiotemporal predictability and relative productivity of front-associated foraging habitats are key aspects of their ecological importance. Predictable mesoscale (10s–100s km) regions of persistent frontal activity (‘frontal zones’) are particularly significant. 4.Frontal zones are hotspots of overlap between critical habitat and spatially explicit anthropogenic threats, such as the concentration of fisheries activity. As such, they represent tractable conservation units, in which to target measures for threat mitigation. 5.Front mapping via Earth observation (EO) remote sensing facilitates identification and monitoring of these hotspots of vulnerability. Seasonal or climatological products can locate biophysical hotspots, while near-real-time front mapping augments the suite of tools supporting spatially dynamic ocean management. 6.Synthesis and applications. Frontal zones are ecologically important for mobile marine vertebrates. We surmise that relative accessibility, predictability and productivity are key biophysical characteristics of ecologically significant frontal zones in contrasting oceanographic regions. Persistent frontal zones are potential priority conservation areas for multiple marine vertebrate taxa and are easily identifiable through front mapping via EO remote sensing. These insights are useful for marine spatial planning and marine biodiversity conservation, both within Exclusive Economic Zones and in the open oceans.

Discrete-time modelling of woodwind instrument bores using wave variables

A method for simulation of acoustical bores, useful in the context of sound synthesis by physical modeling of woodwind instruments, is presented. As with previously developed methods, such as digital waveguide modeling (DWM) [Smith, Comput. Music J. 16, pp 74-91 (1992)] and the multi convolution algorithm (MCA) [Martinez et al., J. Acoust. Soc. Am. 84, pp 1620-1627 (1988)], the approach is based on a one-dimensional model of wave propagation in the bore. Both the DWM method and the MCA explicitly compute the transmission and reflection of wave variables that represent actual traveling pressure waves. The method presented in this report, the wave digital modeling (WDM) method, avoids the typical limitations associated with these methods by using a more general definition of the wave variables. An efficient and spatially modular discrete-time model is constructed from the digital representations of elemental bore units such as cylindrical sections, conical sections, and toneholes. Frequency-dependent phenomena, such as boundary losses, are approximated with digital filters. The stability of a simulation of a complete acoustic bore is investigated empirically. Results of the simulation of a full clarinet show that a very good concordance with classic transmission-line theory is obtained.