Studies on the Properties of Chitosan-Starch Beads and their Application as Drug Release Materials

In this work, chitosan and blends of chitosan-starch beads were prepared and crosslinked with glutaraldehyde (pentane-1,5-dial). The blends were prepared with 1:1, 2:1 and 3:1 chitosan-starch ratios. Metformin hydrochloride (N,N-dimethylimidodicarbonimidic diamide hydrochloride), a type 2 diabetis drug, was incorporated into them. The materials were subjected to swellability tests and the effects of time and pH were established. Fourier Transformed Infrared Spectrophotometeric (FTIR) analysis was also carried out on the materials and their potentials as drug release systems studied. The results obtained from the FTIR studies showed that the uncrosslinked chitosan-starch bead showed O-H stretching band at 3424cm-1 and N-H band at 1640cm-1. The chitosan-starch bead also showed a band at 597cm-1 corresponding to C-Cl band, due to the presence of metformin hydrochloride in the bead and its O-H stretching band was very strong and broad due to the numerous –OH groups in starch and chitosan. The results of swelling studies showed that the percent swellability of the polymer matrices increased in both the crosslinked and uncrosslinked beads as the amount of starch in them increased. The uncrosslinked chitosan beads had maximum swelling of 83.74%, while its crosslinked analogue had 47.93% in acidic medium (pH 2.06) within the range of test period of 60 minutes. The amount of drug released by the 1:1, 2:1 and 3:1 crosslinked chitosan-starch beads (13.90, 13.60, and 12.30mg/L, respectively) was much lower than that of their uncrosslinked analogues (22.50, 20.90, and 16.60mg/L, respectively) after 120 minutes, suggesting that the release of drug is delayed by crosslinking. This suggests that the crosslinked chitosan-starch beads can be used for regulating release of drugs in solid dosages such as beads or tablets.Keywords: chitosan, chitosan-starch beads, drug release, metformin hydrochloride, swellin

Spheres and Prolate and Oblate Ellipsoids from an Analytical Solution of Spontaneous Curvature Fluid Membrane Model

An analytic solution for Helfrich spontaneous curvature membrane model (H. Naito, M.Okuda and Ou-Yang Zhong-Can, Phys. Rev. E {\bf 48}, 2304 (1993); {\bf 54}, 2816 (1996)), which has a conspicuous feature of representing the circular biconcave shape, is studied. Results show that the solution in fact describes a family of shapes, which can be classified as: i) the flat plane (trivial case), ii) the sphere, iii) the prolate ellipsoid, iv) the capped cylinder, v) the oblate ellipsoid, vi) the circular biconcave shape, vii) the self-intersecting inverted circular biconcave shape, and viii) the self-intersecting nodoidlike cylinder. Among the closed shapes (ii)-(vii), a circular biconcave shape is the one with the minimum of local curvature energy.Comment: 11 pages, 11 figures. Phys. Rev. E (to appear in Sept. 1999

Capture on High Curvature Region: Aggregation of Colloidal Particle Bound to Giant Phospholipid Vesicles

A very recent observation on the membrane mediated attraction and ordered aggregation of colloidal particles bound to giant phospholipid vesicles (I. Koltover, J. O. R\"{a}dler, C. R. Safinya, Phys. Rev. Lett. {\bf 82}, 1991(1999)) is investigated theoretically within the frame of Helfrich curvature elasticity theory of lipid bilayer fluid membrane. Since the concave or waist regions of the vesicle possess the highest local bending energy density, the aggregation of colloidal beads on these places can reduce the elastic energy in maximum. Our calculation shows that a bead in the concave region lowers its energy $\sim 20 k_B T$. For an axisymmetrical dumbbell vesicle, the local curvature energy density along the waist is equally of maximum, the beads can thus be distributed freely with varying separation distance.Comment: 12 pages, 2 figures. REVte

Learning neural trans-dimensional random field language models with noise-contrastive estimation

Trans-dimensional random field language models (TRF LMs) where sentences are modeled as a collection of random fields, have shown close performance with LSTM LMs in speech recognition and are computationally more efficient in inference. However, the training efficiency of neural TRF LMs is not satisfactory, which limits the scalability of TRF LMs on large training corpus. In this paper, several techniques on both model formulation and parameter estimation are proposed to improve the training efficiency and the performance of neural TRF LMs. First, TRFs are reformulated in the form of exponential tilting of a reference distribution. Second, noise-contrastive estimation (NCE) is introduced to jointly estimate the model parameters and normalization constants. Third, we extend the neural TRF LMs by marrying the deep convolutional neural network (CNN) and the bidirectional LSTM into the potential function to extract the deep hierarchical features and bidirectionally sequential features. Utilizing all the above techniques enables the successful and efficient training of neural TRF LMs on a 40x larger training set with only 1/3 training time and further reduces the WER with relative reduction of 4.7% on top of a strong LSTM LM baseline.Comment: 5 pages and 2 figure

H&H Committee Coming Out Speech

Notes for a speech on Coming Ou

Direct Observation of Field-Induced Incommensurate Fluctuations in a One-Dimensional S=1/2 Antiferromagnet

Neutron scattering from copper benzoate, Cu(C6D5COO)2 3D2O, provides the first direct experimental evidence for field-dependent incommensurate low energy modes in a one-dimensional spin S = 1/2 antiferromagnet. Soft modes occur for wavevectors q=\pi +- dq(H) where dq(H) ~ 2 \pi M(H)/g\mu_B as predicted by Bethe ansatz and spinon descriptions of the S = 1/2 chain. Unexpected was a field-induced energy gap $\Delta(H) \propto H^\alpha$, where $\alpha = 0.65(3)$ as determined from specific heat measurements. At H = 7 T (g\mu_B H/J = 0.52), the magnitude of the gap varies from 0.06 - 0.3 J depending on the orientation of the applied field.Comment: 11 pages, 5 postscript figures, LaTeX, Submitted to PRL 3/31/97, e-mail comments to [email protected]