Transgenerational Seed Exposure to Elevated CO2 Involves Stress Memory Regulation at Metabolic Levels to Confer Drought Resistance in Wheat.

Drought is the worst environmental stress constraint that inflicts heavy losses to global food production, such as wheat. The metabolic responses of seeds produced overtransgenerational exposure to e[CO2] to recover drought's effects on wheat are still unexplored. Seeds were produced constantly for four generations (F1 to F4) under ambient CO2 (a[CO2], 400 µmol L-1) and elevated CO2 (e[CO2], 800 µmol L-1) concentrations, and then further regrown under natural CO2 conditions to investigate their effects on the stress memory metabolic processes liable for increasing drought resistance in the next generation (F5). At the anthesis stage, plants were subjected to normal (100% FC, field capacity) and drought stress (60% FC) conditions. Under drought stress, plants of transgenerational e[CO2] exposed seeds showed markedly increased superoxide dismutase (16%), catalase (24%), peroxidase (9%), total antioxidants (14%), and proline (35%) levels that helped the plants to sustain normal growth through scavenging of hydrogen peroxide (11%) and malondialdehyde (26%). The carbohydrate metabolic enzymes such as aldolase (36%), phosphoglucomutase (12%), UDP-glucose pyrophosphorylase (25%), vacuolar invertase (33%), glucose-6-phosphate-dehydrogenase (68%), and cell wall invertase (17%) were decreased significantly; however, transgenerational seeds produced under e[CO2] showed a considerable increase in their activities in drought-stressed wheat plants. Moreover, transgenerational e[CO2] exposed seeds under drought stress caused a marked increase in leaf Ψw (15%), chlorophyll a (19%), chlorophyll b (8%), carotenoids (12%), grain spike (16%), hundred grain weight (19%), and grain yield (10%). Hence, transgenerational seeds exposed to e[CO2] upregulate the drought recovery metabolic processes to improve the grain yield of wheat under drought stress conditions.

Phytonutritional and Sensorial Assessment of a Novel Functional Beverage Formulated from an Underutilized Fruit of Carissa spinarum L.

Carissa spinarum L. belongs to the family Apocynaceae. It is a native shrub of Asia, locally known as Karonda or Karanda, and is an underutilized crop throughout the Asian region. The Karonda fruit is a rich source of vitamin C, minerals, phenolics, antioxidants, flavonoids, and other biofunctional compounds. The lack of awareness and knowledge among the community results in the wastage of fruits. Therefore, the present research was designed to formulate an easy-to-prepare beverage drink using C. spinarum fruit to evaluate the nutritional potential of the undervalued Karonda fruit. A beverage drink was formulated with three pulp concentrations: 20, 30, and 40%, each having 12, 14, and 16 °Brix, respectively. A total of nine treatments were prepared and stored for up to 10 weeks in refrigerated storage. The physicochemical parameters, such as pH, titratable acidity, vitamin C, total sugars, anthocyanin, total phenolics, flavonoids, and antioxidants, were measured at two-week intervals from 0 to 10 weeks. Additionally, a sensory assessment of the beverage was conducted. A decreasing trend in titratable acidity was exhibited among all the treatments (from treatment 1 to treatment 9), with the values decreasing from 0.815 to 0.556 as the fruit concentration increased. On the other hand, an increasing trend was observed for pH (from 3.04 to 3.37), vitamin C (from 22.2 to 31.48), reducing and non-reducing sugars, anthocyanin (from 31.95 to 110), total phenolics (from 19.86 to 32.16), flavonoids (from 0.64 to 0.77), and antioxidants (from 48.8 to 67.6) from treatment 1 to treatment 9, respectively. The sensory studies of the beverage formulations revealed that treatment 9, which consisted of a 40% fruit base and 16 °Brix, was the most acceptable for further development of the beverage at a commercial scale. This study represents a novel scientific contribution toward the utilization of the undervalued fruit of C. spinarum L. for the development of a beverage product. Ultimately, it has the potential to address food insecurity issues worldwide while offering its associated health benefits.

On implementation of DCTCP on three-tier and fat-tree data center network topologies.

A data center is a facility for housing computational and storage systems interconnected through a communication network called data center network (DCN). Due to a tremendous growth in the computational power, storage capacity and the number of inter-connected servers, the DCN faces challenges concerning efficiency, reliability and scalability. Although transmission control protocol (TCP) is a time-tested transport protocol in the Internet, DCN challenges such as inadequate buffer space in switches and bandwidth limitations have prompted the researchers to propose techniques to improve TCP performance or design new transport protocols for DCN. Data center TCP (DCTCP) emerge as one of the most promising solutions in this domain which employs the explicit congestion notification feature of TCP to enhance the TCP congestion control algorithm. While DCTCP has been analyzed for two-tier tree-based DCN topology for traffic between servers in the same rack which is common in cloud applications, it remains oblivious to the traffic patterns common in university and private enterprise networks which traverse the complete network interconnect spanning upper tier layers. We also recognize that DCTCP performance cannot remain unaffected by the underlying DCN architecture hence there is a need to test and compare DCTCP performance when implemented over diverse DCN architectures. Some of the most notable DCN architectures are the legacy three-tier, fat-tree, BCube, DCell, VL2, and CamCube. In this research, we simulate the two switch-centric DCN architectures; the widely deployed legacy three-tier architecture and the promising fat-tree architecture using network simulator and analyze the performance of DCTCP in terms of throughput and delay for realistic traffic patterns. We also examine how DCTCP prevents incast and outcast congestion when realistic DCN traffic patterns are employed in above mentioned topologies. Our results show that the underlying DCN architecture significantly impacts DCTCP performance. We find that DCTCP gives optimal performance in fat-tree topology and is most suitable for large networks.

Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

Crystal structure of catena-poly[silver(I)-µ-l-tyrosinato-κ(2) O:N].

The title compound, [Ag(C9H10NO3)] n , is a polymeric silver(I) complex of l-tyrosine. The Ag(I) atom is connected to N and O atoms of two different l-tyrosine ligands in an almost linear arrangement, with an N(i)-Ag-O1 bond angle of 173.4 (2)° [symmetry code: (i) x + 1, y, z]. The Ag-N(i) and Ag-O bond lengths are 2.156 (5) and 2.162 (4) Å, respectively. The polymeric chains extend along the crystallographic a axis. Strong hydrogen bonds of the N-H⋯O and O-H⋯O types and additional C-H⋯O inter-actions connect these chains into a double-layer polymeric network in the ab plane.

cyclo-Tetrakis(µ(2)-3-sulfidopropyl-κC,S:S)tetrakis[chloridocobalt(III)].

In the centrosymmetric title compound, [Co(4)Cl(4)(C(3)H(6)S)](4)], the two independent Co(III) ions are each coordinated in a distorted tetra-hedral geometry by one C, one Cl and two S atoms. The mol-ecules are stabilized by C-H⋯Cl hydrogen bonds. In the crystal, inter-molecular C-H⋯Cl and C-H⋯S hydrogen bonds with R(2) (2)(8), R(4) (2)(8) and R(2) (2)(6) ring motifs generate a polymeric network.