Pharmacokinetics of FK506 in liver transplant recipients after continuous intravenous infusion

The first-dose pharmacokinetics of FK506 was studied in nine orthotopic liver transplant patients receiving continuous intravenous infusion of 0.15 mg/kg/day. Multiple blood samples were obtained during the infusion and plasma FK506 concentrations were measured by enzyme-linked immunosorbent assay. The plasma clearance ranged from 0.47 to 5.8 L/minute, and the half- life ranged from 4.5 hours to 33.1 hours. These results indicate the pharmacokinetics of FK506 to be highly variable between patients. FK506 is extensively distributed outside the plasma compartment. FK506 is extensively metabolized in the body, with less than 1% of the administered dose being excreted in the urine as unchanged FK506. The large variability in FK506 kinetics during the immediate postoperative period is attributed to the variability in the functional status of the liver in the transplant patients. Because of the long half-life of FK506, it takes more than 45 hours to reach steady-state concentrations after continuous infusion. Based on the estimated kinetic parameters, it appears that a combination of a bolus or a rapid infusion of .02 mg/kg with a continuous infusion of 0.05 mg/kg/day will provide and maintain a concentration of more than 2 ng/mL from the beginning of the drug treatment

Cyclosporine Absorption Following Orthotopic Liver Transplantation

Blood concentrations of cyclosporine were determined in adult and pediatric patients following orthotopic liver transplantation to quantitate cyclosporine blood clearance and oral absorption. Seventeen bioavailability studies were performed following transplantation surgery in nine children and seven adults. The intravenous cyclosporine study was performed following an average dose of 2.1 mg/kg. The patients were again studied when they received the same intravenous dose plus an oral dose of cyclosporine of 8.6 mg/kg or an oral dose alone. Blood samples were collected and analyzed for cyclosporine using high-performance liquid chromatography. Cyclosporine blood clearance ranged from 29 to 203 mL/min (1.9–21.5 mL/min/kg) in children and from 253 to 680 mL/min (3.2–7.6 mL/min/kg) in adults. The mean cyclosporine clearance value was 9.3 mL/min/kg in the pediatric patients and 5.5 mL/min/kg in the adults. Cyclosporine bioavailability was less than 5% in six studies on five pediatric patients in the immediate postoperative period. The bioavailability varied from 8% to 60% in adult liver transplant patients (mean, 27%). We conclude that: (1) cyclosporine clearance is highly variable between patients, (2) pediatric patients clear the drug more rapidly than adults and therefore need a higher cyclosporine dose on a body weight basis, (3) cyclosporine is poorly and variably absorbed in liver transplant patients, and (4) cyclosporine blood concentration monitoring is essential following orthotopic liver transplantation

Sparse Regression Codes for Multi-terminal Source and Channel Coding

We study a new class of codes for Gaussian multi-terminal source and channel coding. These codes are designed using the statistical framework of high-dimensional linear regression and are called Sparse Superposition or Sparse Regression codes. Codewords are linear combinations of subsets of columns of a design matrix. These codes were recently introduced by Barron and Joseph and shown to achieve the channel capacity of AWGN channels with computationally feasible decoding. They have also recently been shown to achieve the optimal rate-distortion function for Gaussian sources. In this paper, we demonstrate how to implement random binning and superposition coding using sparse regression codes. In particular, with minimum-distance encoding/decoding it is shown that sparse regression codes attain the optimal information-theoretic limits for a variety of multi-terminal source and channel coding problems.Comment: 9 pages, appeared in the Proceedings of the 50th Annual Allerton Conference on Communication, Control, and Computing - 201

An Achievable Rate Region for the Broadcast Channel with Feedback

A single-letter achievable rate region is proposed for the two-receiver discrete memoryless broadcast channel with generalized feedback. The coding strategy involves block-Markov superposition coding, using Marton's coding scheme for the broadcast channel without feedback as the starting point. If the message rates in the Marton scheme are too high to be decoded at the end of a block, each receiver is left with a list of messages compatible with its output. Resolution information is sent in the following block to enable each receiver to resolve its list. The key observation is that the resolution information of the first receiver is correlated with that of the second. This correlated information is efficiently transmitted via joint source-channel coding, using ideas similar to the Han-Costa coding scheme. Using the result, we obtain an achievable rate region for the stochastically degraded AWGN broadcast channel with noisy feedback from only one receiver. It is shown that this region is strictly larger than the no-feedback capacity region.Comment: To appear in IEEE Transactions on Information Theory. Contains example of AWGN Broadcast Channel with noisy feedbac

Lossy Compression via Sparse Linear Regression: Performance under Minimum-distance Encoding

We study a new class of codes for lossy compression with the squared-error distortion criterion, designed using the statistical framework of high-dimensional linear regression. Codewords are linear combinations of subsets of columns of a design matrix. Called a Sparse Superposition or Sparse Regression codebook, this structure is motivated by an analogous construction proposed recently by Barron and Joseph for communication over an AWGN channel. For i.i.d Gaussian sources and minimum-distance encoding, we show that such a code can attain the Shannon rate-distortion function with the optimal error exponent, for all distortions below a specified value. It is also shown that sparse regression codes are robust in the following sense: a codebook designed to compress an i.i.d Gaussian source of variance $\sigma^2$ with (squared-error) distortion $D$ can compress any ergodic source of variance less than $\sigma^2$ to within distortion $D$. Thus the sparse regression ensemble retains many of the good covering properties of the i.i.d random Gaussian ensemble, while having having a compact representation in terms of a matrix whose size is a low-order polynomial in the block-length.Comment: This version corrects a typo in the statement of Theorem 2 of the published pape

Lossy Compression via Sparse Linear Regression: Computationally Efficient Encoding and Decoding

We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are structured linear combinations of columns of this matrix. The proposed encoding algorithm sequentially chooses columns of the design matrix to successively approximate the source sequence. It is shown to achieve the optimal distortion-rate function for i.i.d Gaussian sources under the squared-error distortion criterion. For a given rate, the parameters of the design matrix can be varied to trade off distortion performance with encoding complexity. An example of such a trade-off as a function of the block length n is the following. With computational resource (space or time) per source sample of O((n/\log n)^2), for a fixed distortion-level above the Gaussian distortion-rate function, the probability of excess distortion decays exponentially in n. The Sparse Regression Code is robust in the following sense: for any ergodic source, the proposed encoder achieves the optimal distortion-rate function of an i.i.d Gaussian source with the same variance. Simulations show that the encoder has good empirical performance, especially at low and moderate rates.Comment: 14 pages, to appear in IEEE Transactions on Information Theor

Communicating over Filter-and-Forward Relay Networks with Channel Output Feedback

Relay networks aid in increasing the rate of communication from source to destination. However, the capacity of even a three-terminal relay channel is an open problem. In this work, we propose a new lower bound for the capacity of the three-terminal relay channel with destination-to-source feedback in the presence of correlated noise. Our lower bound improves on the existing bounds in the literature. We then extend our lower bound to general relay network configurations using an arbitrary number of filter-and-forward relay nodes. Such network configurations are common in many multi-hop communication systems where the intermediate nodes can only perform minimal processing due to limited computational power. Simulation results show that significant improvements in the achievable rate can be obtained through our approach. We next derive a coding strategy (optimized using post processed signal-to-noise ratio as a criterion) for the three-terminal relay channel with noisy channel output feedback for two transmissions. This coding scheme can be used in conjunction with open-loop codes for applications like automatic repeat request (ARQ) or hybrid-ARQ.Comment: 15 pages, 8 figures, to appear in IEEE Transactions on Signal Processin