Ritonavir (Kempf, D. J.; Marsh, K. C., Denissen, J. F.; McDonald, E.; Vasavanonda, S.; Flentge, C. A.; Green, B. E.; Fino, L.; Park, C. H.; Kong, X. P.; Wideburg, N. E.; Saldivar, A.; Ruitz, L.; Kati, W. M.; Sham, H. L.; Robins, T.; Stewart, K. D.; Hsu, A.; Plattner, J. J.; Leonard, J. M.; Norbeck, D. W. Proc. Natl. Acad. Sci. U.S.A. 1995, 92, 2484) is Abbott's novel protease inhibitor, for human immunodeficiency virus (HIV), the causative organism of acquired immunodeficiency syndrome (AIDS). It is marketed as Norvir. From the discovery of ritonavir until the new drug application (NDA) filing, only one crystalline form was known to exist. Attempts to identify other possible crystal forms were unsuccessful. Two years after the launch of Norvir to the market, some lots of Norvir capsules failed a dissolution specification. Investigation of this phenomena revealed the existence of a crystal form of ritonavir other than the one already known (Form I). This new crystal form was designated as Form II. The two crystal forms are polymorphs and differ substantially in their physical properties such as solubility. In this article, we will discuss the challenges these polymorphs created for the bulk drug substance as well as for the formulation, and how we dealt with these challenges.

Soil penetration resistance scone index) varies with water content. The field variation of water content could mask treatment differences. The correction of cone index data to a sin g le water content would help prevent this. We used equations from . TableCurve software and from the literature to correct cone indices for differences in soil water contents. Data were taken from two field experiments where cotton (Gossvpzum hirsutum L.) was grown usin g conventional and conservation tillage without irri g ation. and beans ( Phaseolus uuiearis L.) were grown using conventional tillage with microirri gation. Boundary conditions based on hard, dry and soft. wet ;oils were imposed on the equations. Equations tit the data with coefficients of determination ranging from 0.55 to 0.92 and error mean squares from 1.37 to 6.35. After correction, cone index dependence on water content was reduced. A sin g le-equation correction did not always fit the data across all treatments. Separate corrections, based on treatment. mi ght be required. When corrections required multiple equations. differences may be real or may be a manifestation of the correction differences. in this case, the correction may not be feasible (unless some future work can coordinate different equations and assure a uniform correction).1997 Elsevier Science B.V.

BackgroundCotton (Gossypium spp.) is produced in over 30 countries and represents the most important natural fiber in the world. One of the primary factors affecting both the quantity and quality of cotton production is water. A major facilitator of water movement through cell membranes of cotton and other plants are the aquaporin proteins. Aquaporin proteins are present as diverse forms in plants, where they function as transport systems for water and other small molecules. The plant aquaporins belong to the large major intrinsic protein (MIP) family. In higher plants, they consist of five subfamilies including plasma membrane intrinsic proteins (PIP), tonoplast intrinsic proteins (TIP), NOD26-like intrinsic proteins (NIP), small basic intrinsic proteins (SIP), and the recently discovered X intrinsic proteins (XIP). Although a great deal is known about aquaporins in plants, very little is known in cotton.ResultsFrom a molecular cloning effort, together with a bioinformatic homology search, 71 upland cotton (G. hirsutum) aquaporin genes were identified. The cotton aquaporins consist of 28 PIP and 23 TIP members with high sequence similarity. We also identified 12 NIP and 7 SIP members that showed more divergence. In addition, one XIP member was identified that formed a distinct 5th subfamily. To explore the physiological roles of these aquaporin genes in cotton, expression analyses were performed for a select set of aquaporin genes from each subfamily using semi-quantitative reverse transcription (RT)-PCR. Our results suggest that many cotton aquaporin genes have high sequence similarity and diverse roles as evidenced by analysis of sequences and their expression.ConclusionThis study presents a comprehensive identification of 71 cotton aquaporin genes. Phylogenetic analysis of amino acid sequences divided the large and highly similar multi-gene family into the known 5 aquaporin subfamilies. Together with expression and bioinformatic analyses, our results support the idea that the genes identified in this study represent an important genetic resource providing potential targets to modify the water use properties of cotton.

The flowering stage is the key yield determinant period of soybean. Short-duration water stress occurring during this stage significantly reduced soybean development and final productivity. Seed treatment with uniconazole powder application plays an important role in alleviating the adverse effects of dry soil on plant development. In order to explore effects of uniconazole on soybean morphological characteristics and yield under drought stress, different rate of uniconazole powder were examined under developing gradually drought stress during flowering stage. The yield of soybean decreased under drought, uniconazole application increased yield. All results suggest that 4 mg/kg is the optimal uniconazole application rate under drought for soybean at the flowering stage.

Despite considerable efforts in developing curve-fitting protocols to evaluate the crystallinity index (CI) from X-ray diffraction (XRD) measurements, in its present state XRD can only provide a qualitative or semi-quantitative assessment of the amounts of crystalline or amorphous fraction in a sample. The greatest barrier to establishing quantitative XRD is the lack of appropriate cellulose standards, which are needed to calibrate the XRD measurements. In practice, samples with known CI are very difficult to prepare or determine. In a previous study, we reported the development of a simple algorithm for determining fiber crystallinity information from Fourier transform infrared (FT-IR) spectroscopy. Hence, in this study we not only compared the fiber crystallinity information between FT-IR and XRD measurements, by developing a simple XRD algorithm in place of a time-consuming and subjective curve-fitting process, but we also suggested a direct way of determining cotton cellulose CI by calibrating XRD with the use of CI(IR) as references.