Resolution of serum and cerebrospinal fluid abnormalities after treatment of neurosyphilis. Influence of concomitant human immunodeficiency virus infection

BACKGROUND AND OBJECTIVES: Little is known about resolution of serum and cerebrospinal fluid abnormalities after neurosyphilis treatment, especially in patients infected with human immunodeficiency virus (HIV). GOAL: To examine the time course of resolution of these abnormalities. STUDY DESIGN: Case series of 22 patients with neurosyphilis (13 infected with HIV) with reactive cerebrospinal fluid Venereal Disease Research Laboratory test who underwent at least one lumbar puncture after treatment. RESULTS: Resolution of all serum and cerebrospinal fluid measures was slower in patients infected with HIV. Serum and cerebrospinal fluid abnormalities resolved in most patients not infected with HIV by 30 weeks, and all met Centers for Disease Control and Prevention criteria for cure. One patient infected with HIV failed therapy by Centers for Disease Control and Prevention criteria, and three others had persistent pleocytosis. CONCLUSIONS: HIV-infected patients with neurosyphilis have slower resolution of serum and cerebrospinal fluid abnormalities after therapy. This observation may suggest impaired clearance of Treponema pallidum from the central nervous system.     

The interaction of coumarin antibiotics with fragments of DNA gyrase B protein

DNA gyrase is the target of the coumarin group of antibacterial agents. The drugs are known to inhibit the ATPase activity of gyrase and bind to the 24-kDa N-terminal subdomain of gyrase B protein. Supercoiling assays with intact DNA gyrase and ATPase assays with a 43-kDa N-terminal fragment of the B protein suggest that the drugs bind tightly, with Kd values <10(-7) M. In addition, the ATPase data suggest that 1 coumermycin molecule interacts with 2 molecules of the 43-kDa protein while the other coumarins form a 1:1 complex. This result is confirmed by cross-linking experiments. Rapid gel-filtration experiments show that the binding of ADPNP(5'-adneylyl beta,gamm-imidodiphosphate) and coumarins to the 43-kDa protein is mutally exclusive, consistent with a competitive mode of action for the drugs. Rapid gel-filtration binding experiments using both the 24-and 43-kDa proteins also show that the drugs bind with association rate constants of >10(5) M-1.s-1, and dissociation rate constants of approximately 3x10(-3)s-1 and approximately 4x10(-3)s-1 for the 43-and 24-kDa proteins, respectively. Titration calorimetry shows that the Kd values for coumarins binding to both proteins are approximately 10-8M and that binding is enthalpy driven.     

IV World Congress on Water Resources,September 3–11, 1982, Argentina,on “Water for Human Consumption,Man and his Environment”

ABSTRACT

The major hydroclimatic cause of the 1993 Upper Mississippi River Basin flood was the persistence of heavy rains over a period of several months. As a result, precipitation totals for April-September 1993 were unprecedented, exceeding by a large margin any previous six-month precipitation total since 1895. Using standard hydrometeorological methods, the frequency of occurrence of these precipitation totals is expected to be less than once every 200 years. The core of the heavy rain area was located in Iowa and Missouri near the main stems of the Mississippi and Missouri Rivers. Thus, runof from many of the heavy rain events was deposited directly into these main stems. The persistence of the heavy rains maintained high soil moisture levels throughout the summer period. Thus, the heavy rains during the summer were accompanied by very high runoff rates. Also, the frequent rains were accompanied by many cloudy days. Primarily for this reason (and to a lesser extent because of lower temperatures), potential evapotranspiration was considerably below the long-term average. This was a contributing factor to maintaining the high soil moisture levels and high runoff.     

Application of NIR chemometric methods for quantification of the crystalline fraction of warfarin sodium in drug product

Abstract

Monitoring of the physical state of warfarin sodium (WS) in products is essential for minimizing product quality variability in order to ensure consistent clinical performance. This study reports the development of chemometric models for quantifying the crystalline and amorphous fractions of WS in commercial drug products using NIR spectroscopy. Formulations based on commercially available products with different API to excipient ratio were used for the study. For each content, two formulations containing either lactose monohydrate or lactose anhydrous as the predominant formulation excipient were prepared. Two formulations containing either 100% amorphous WS (AWS) or crystalline WS (CWS) were prepared and mixed in various ratios to obtain sample matrices containing AWS/CWS 0–100%. The uniformity of the samples was confirmed by near infrared chemical imaging. Data were mathematically pretreated by multiplicative signal correction and Savitzky–Golay second derivative. Principal component regression and partial least square regression models were developed from mathematically treated data. All the models showed linear trend for amorphous and crystalline fractions of the WS as indicated by correlation and R²?>?0.99 and >0.98, respectively. The models demonstrated good performance parameters with a low-root mean squared error, standard error and bias. The model predicted CWS and AWS contents were in very close agreement with the actual values. The study indicated the utility of NIR chemometric methods in quantification of the crystalline and/or amorphous fraction of WS in its products.     

Implementation of machine-learning classification in remote sensing: an applied review

Machine learning offers the potential for effective and efficient classification of remotely sensed imagery. The strengths of machine learning include the capacity to handle data of high dimensionality and to map classes with very complex characteristics. Nevertheless, implementing a machine-learning classification is not straightforward, and the literature provides conflicting advice regarding many key issues. This article therefore provides an overview of machine learning from an applied perspective. We focus on the relatively mature methods of support vector machines, single decision trees (DTs), Random Forests, boosted DTs, artificial neural networks, and k-nearest neighbours (k-NN). Issues considered include the choice of algorithm, training data requirements, user-defined parameter selection and optimization, feature space impacts and reduction, and computational costs. We illustrate these issues through applying machine-learning classification to two publically available remotely sensed data sets.     

The deformation of hybrid-particulate composites

The deformation behaviour of a hybrid-particulate epoxy composite has been examined. The Young's modulusE and yield stress have been determined as a function of temperature and volume fraction of rigid glass spheres, for both a simple epoxy matrix and a two-phase epoxy toughened by the presence of rubber particles. In addition, the effect of improving the particle-matrix interface with a silane bonding agent has been studied. It is found that there is a steady increase in Young's modulus with the volume fraction of spheres for all systems. In contrast, the yield stress is only found to increase with the volume fraction of rigid particles when the epoxy matrix is not toughened with rubber. It is found that the yield stress is virtually independent of particle volume fraction when a rubber-modified epoxy matrix is employed. Finally, it is found that for all compositions tested the Young's modulus and yield stress increase with increasing temperature. The overall behaviour has been discussed in terms of existing theories concerning the deformation behaviour of amorphous polymers.     

New and improved catalytic processes for clean fuels

New and more stringent environmental legislation is expected to have a major impact on the refining industry. Reformulated gasoline which is currently being introduced into parts of the United States is an example of the shift towards cleaner burning fuels. To achieve future government specifications for such fuels significant changes will likely be required in refinery operations to produce products with good combustion characteristics and reduced emissions.Catalysis is expected to play a dominant role in both modifying existing processes and developing new routes to these more environmentally acceptable fuels. Both new and improved catalysts systems which will be required for the production of so-called reformulated gasoline are discussed. For example, oxygenated components in gasoline such as methyl tertiary butyl ether (MTBE) will continue to be required on a large scale necessitating new process and catalyst technology to achieve improved economics.Natural gas can be considered as a clean feedstock from which to produce liquid fuels of high quality. A number of new process routes to convert remote natural gas into readily transportable liquid fuels are also discussed. This area of technology offers considerable scope for further major improvements based on innovation in the field of syngas catalysis.     

Dynamic mechanical properties of polymer melts: The dependence of viscoelastic properties on molecular weight distribution

An investigation of the dynamic mechanical properties of several molten polymers was performed using the Maxwell Orthogonal Rheometer. Relaxation spectra derived from experimental data for the terminal region of viscoelastic response indicate that as molecular weight distribution broadens, terminal relaxation phenomena associated with molecular disentanglement and translation extend over a corresponding wider frequency range. The same data indicate that a true maximum relaxation time beyond which no elastic response is observed exists for the materials studied. Moreover, the maximum relaxation time corresponds to the reciprocal of the frequency where the dynamic viscosity deviates from its zero-shear value. Thus an estimate of the time necessary for complete elastic recovery in polymer melts is readily obtained experimentally.     

Sleeping on the Job: Energy-Efficient and Robust Broadcast for Radio Networks

We address the problem of minimizing power consumption when broadcasting a message from one node to all the other nodes in a radio network. To enable power savings for such a problem, we introduce a compelling new data streaming problem which we call the Bad Santa problem. Our results on this problem apply for any situation where: (1) a node can listen to a set of n nodes, out of which at least half are non-faulty and know the correct message; and (2) each of these n nodes sends according to some predetermined schedule which assigns each of them its own unique time slot. In this situation, we show that in order to receive the correct message with probability 1, it is necessary and sufficient for the listening node to listen to a \(\Theta(\sqrt{n})\) expected number of time slots. Moreover, if we allow for repetitions of transmissions so that each sending node sends the message O(log?^? n) times (i.e. in O(log?^? n) rounds each consisting of the n time slots), then listening to O(log?^? n) expected number of time slots suffices. We show that this is near optimal.We describe an application of our result to the popular grid model for a radio network. Each node in the network is located on a point in a two dimensional grid, and whenever a node sends a message m, all awake nodes within L _∞ distance r receive m. In this model, up to \(t<\frac{r}{2}(2r+1)\) nodes within any 2r+1 by 2r+1 square in the grid can suffer Byzantine faults. Moreover, we assume that the nodes that suffer Byzantine faults are chosen and controlled by an adversary that knows everything except for the random bits of each non-faulty node. This type of adversary models worst-case behavior due to malicious attacks on the network; mobile nodes moving around in the network; or static nodes losing power or ceasing to function. Let n=r(2r+1). We show how to solve the broadcast problem in this model with each node sending and receiving an expected \(O(n\log^{2}{|m|}+\sqrt{n}|m|)\) bits where |m| is the number of bits in m, and, after broadcasting a fingerprint of m, each node is awake only an expected \(O(\sqrt{n})\) time slots. Moreover, for t≤(1?ε)(r/2)(2r+1), for any constant ε>0, we can achieve an even better energy savings. In particular, if we allow each node to send O(log?^? n) times, we achieve reliable broadcast with each node sending O(nlog?²|m|+(log?^? n)|m|) bits and receiving an expected O(nlog?²|m|+(log?^? n)|m|) bits and, after broadcasting a fingerprint of m, each node is awake for only an expected O(log?^? n) time slots. Our results compare favorably with previous protocols that required each node to send Θ(|m|) bits, receive Θ(n|m|) bits and be awake for Θ(n) time slots.     

Demonstration of a real-time interferometer as a bunch-length monitor in a high-current electron beam accelerator

A real-time interferometer (RTI) has been developed to monitor the bunch length of an electron beam in an accelerator. The RTI employs spatial autocorrelation, reflective optics, and a fast response pyro-detector array to obtain a real-time autocorrelation trace of the coherent radiation from an electron beam thus providing the possibility of online bunch-length diagnostics. A complete RTI system has been commissioned at the A0 photoinjector facility to measure sub-mm bunches at 13 MeV. Bunch length variation (FWHM) between 0.8 ps (~0.24 mm) and 1.5 ps (~0.45 mm) has been measured and compared with a Martin-Puplett interferometer and a streak camera. The comparisons show that RTI is a viable, complementary bunch length diagnostic for sub-mm electron bunches.