Research Notes : United States : Evaluation of soybean germplasm for stress tolerance biological efficiency : To evaluate soybean germplasm and cultivars for stress tolerance toward : Diseases

Screening of improved soybean lines from Alabama A&M University for multiple resistance against bacterial blight, stem canker, and soybean cyst nematode in the greenhouse and in the field continued at Alabama A&M University. Lines obtained from Virginia State University in MG IV (PI 339984, PI 408039, PI 80837); MG V (PI 96089, PI 123440, PI L-76-0132, PI L-77-0049, \u27Hill\u27, \u27Essex\u27); MG VI (FC 31665, PI 407868C, PI 159322, PI 416937, PI 379621, PI 221713, PI 230978, \u27Lee\u27); MG VII (PI 423911, PI 229358); and MG VIII (PI 417134, PI 417063, PI 417061, PI 416893) were screened. Initial results indicated PI L76-0049 is resistant to bacterial blight, PI 159322 and PI 230978 are resistant to soybean cyst nematode (race 3 and 5), and PI 417061 has multiple resistance to bacterial blight and stem canker

Research Notes : United States : Evaluation of soybean germplasm for stress tolerance and biological efficiency towards : Diseases

A field study was conducted for screening and selection of improved soybean germplasm for disease resistance in 1986. The soybean crossing block consisted of 207 germplasm entries screened at flowering and at maturity. One hundred and one were resistant and moderately resistant to bacterial blight (BB)

Realistic Tight Binding Model for the Electronic Structure of II-VI Semiconductors

We analyze the electronic structure of group II-VI semiconductors obtained within LMTO approach in order to arrive at a realistic and minimal tight binding model, parameterized to provide an accurate description of both valence and conduction bands. It is shown that a nearest-neighbor $sp^3d^5$ model is fairly sufficient to describe to a large extent the electronic structure of these systems over a wide energy range, obviating the use of any fictitious $s^*$ orbital. The obtained hopping parameters obey the universal scaling law proposed by Harrison, ensuring transferability to other systems. Furthermore, we show that certain subtle features in the bonding of these compounds require the inclusion of anion-anion interactions in addition to the nearest-neighbor cation-anion interactions.Comment: 9 pages, 9 figure

Evolution of the electronic structure with size in II-VI semiconductor nanocrystals

In order to provide a quantitatively accurate description of the band gap variation with sizes in various II-VI semiconductor nanocrystals, we make use of the recently reported tight-binding parametrization of the corresponding bulk systems. Using the same tight-binding scheme and parameters, we calculate the electronic structure of II-VI nanocrystals in real space with sizes ranging between 5 and 80 {\AA} in diameter. A comparison with available experimental results from the literature shows an excellent agreement over the entire range of sizes.Comment: 17 pages, 4 figures, accepted in Phys. Rev.

An accurate description of quantum size effects in InP nanocrystallites over a wide range of sizes

We obtain an effective parametrization of the bulk electronic structure of InP within the Tight Binding scheme. Using these parameters, we calculate the electronic structure of InP clusters with the size ranging upto 7.5 nm. The calculated variations in the electronic structure as a function of the cluster size is found to be in excellent agreement with experimental results over the entire range of sizes, establishing the effectiveness and transferability of the obtained parameter strengths.Comment: 9 pages, 3 figures, pdf file available at http://sscu.iisc.ernet.in/~sampan/publications.htm

DIETARY PHYTOCHEMICALS IN CELL CYCLE ARREST AND APOPTOSIS- AN INSIGHT

Recently chemoprevention by the use of naturally occurring dietary substances is considered as a practical approach to reduce the ever-increasing incidence of cancer. While a number of natural foods, fruit and vegetables are recommended for prevention of cancer and other diseases, their active ingredients and their mechanism of action are not well understood. A number of dietary phytochemicals are under phase III clinical trial due to their potent therapeutic effect against cancer. Moreover most of the drugs being used in chemotherapy have been derived from plant products. With an advanced knowledge of molecular science and refinement in isolation and structure elucidation techniques, world is in a much better position to identify various anticancer herbs and develop therapeutic agents for cancer. However lack of success with targeted mono-therapy and multi-drug resistance to existing chemotherapeutic agents has forced scientists to practice either combination therapy or use a number of agents working at different sites to get some synergistic effect. Since most of the cells do not show resistance to natural plant products; hence the use of natural plant products can be an alternative modality of treatment for multidrug resistant tumors. In this review article an attempt has been made to put some known phytochemicals of dietary origin that act at various stages of cell cycle and/or apoptotic pathway at a single platform, so that by understanding the synergistic, additive or antagonistic interactions of various constituents of anticancer herbs, the herbal regimens can be designed to fight cancer

Development and characterization of CD22-targeted pegylated-liposomal doxorubicin (IL-PLD)

Non-Hodgkin’s lymphoma (NHL) is the sixth most common cause of cancer deaths in the U.S. Most NHLs initially respond well to chemotherapy, but relapse is common and treatment is often limited due to the toxicity of chemotherapeutic agents. Pegylated-liposomal doxorubicin (PLD, Ben Venue Laboratories, Inc), a produces less myelotoxicity than non-liposomal (NL) doxorubicin. To further enhance efficacy and NHL targeting and to decrease toxicity, we conjugated an anti-CD22 monoclonal antibody (HB22.7) to the surface of PLD, thereby creating CD22-targeted immunoliposomal PLD (IL-PLD). HB22.7 was successfully conjugated to PLD and the resulting IL-PLD exhibits specific binding to CD22-expressing cells as assessed by immunofluorescence staining. IL-PLD exhibits more cytotoxicity than PLD in CD22 positive cell lines but does not increase killing of CD22 negative cells. The IC50 of IL-PLD is 3.1 to 5.4 times lower than that of PLD in CD22+ cell lines while the IC50 of IL-PLD is equal to that of PLD in CD22- cells. Furthermore, IL-PLD remained bound to the CD22+ cells after washing and continued to exert cytotoxic effects, while PLD and NL- doxorubicin could easily be washed from these cells

Optimization and deployment of CNNs at the Edge: The ALOHA experience

Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform inference tasks at the edge. This requires deployment of DL algorithms on low-energy and resource-constrained computing nodes, often heterogenous and parallel, that are usually more complex to program and to manage without adequate support and experience. In this paper, we present ALOHA, an integrated tool flow that tries to facilitate the design of DL applications and their porting on embedded heterogenous architectures. The proposed tool flow aims at automating different design steps and reducing development costs. ALOHA considers hardware-related variables and security, power efficiency, and adaptivity aspects during the whole development process, from pre-training hyperparameter optimization and algorithm configuration to deployment

Efficient unfolding pattern recognition in single molecule force spectroscopy data

BackgroundSingle-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.ResultsIn the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise unfolding of the transmembrane helices. In contrast, a side peak is an unfolding event in the alpha-helix or other secondary structural element. The algorithm is capable of detecting side peaks along with main peaks.Therefore, we can detect the individual unfolding pathway as the sequence of events labeled with their occurrences and co-occurrences special to bR\u27s unfolding pathway. We find that side peaks do not co-occur with one another in curves as frequently as main peaks do, which may imply a synergistic effect occurring between helices. While main peaks co-occur as pairs in at least 50% of curves, the side peaks co-occur with one another in less than 10% of curves. Moreover, the algorithm runtime scales well as the dataset size increases.ConclusionsOur algorithm satisfies the requirements of an automated methodology that combines high accuracy with efficiency in analyzing SMFS datasets. The algorithm tackles the force spectroscopy analysis bottleneck leading to more consistent and reproducible results