Genome-Wide Identification and Characterization of PIN-FORMED (PIN) Gene Family Reveals Role in Developmental and Various Stress Conditions in Triticum aestivum L.

PIN-FORMED (PIN) genes play a crucial role in regulating polar auxin distribution in diverse developmental processes, including tropic responses, embryogenesis, tissue differentiation, and organogenesis. However, the role of PIN-mediated auxin transport in various plant species is poorly understood. Currently, no information is available about this gene family in wheat (Triticum aestivum L.). In the present investigation, we identified the PIN gene family in wheat to understand the evolution of PIN-mediated auxin transport and its role in various developmental processes and under different biotic and abiotic stress conditions. In this study, we performed genome-wide analysis of the PIN gene family in common wheat and identified 44 TaPIN genes through a homology search, further characterizing them to understand their structure, function, and distribution across various tissues. Phylogenetic analyses led to the classification of TaPIN genes into seven different groups, providing evidence of an evolutionary relationship with Arabidopsis thaliana and Oryza sativa. A gene exon/intron structure analysis showed a distinct evolutionary path and predicted the possible gene duplication events. Further, the physical and biochemical properties, conserved motifs, chromosomal, subcellular localization, transmembrane domains, and three-dimensional (3D) structure were also examined using various computational approaches. Cis-elements analysis of TaPIN genes showed that TaPIN promoters consist of phytohormone, plant growth and development, and stress-related cis-elements. In addition, expression profile analysis also revealed that the expression patterns of the TaPIN genes were different in different tissues and developmental stages. Several members of the TaPIN family were induced during biotic and abiotic stress. Moreover, the expression patterns of TaPIN genes were verified by qRT-PCR. The qRT-PCR results also show a similar expression with slight variation. Therefore, the outcome of this study provides basic genomic information on the expression of the TaPIN gene family and will pave the way for dissecting the precise role of TaPINs in plant developmental processes and different stress conditions.     

Structure-property relations for a phase-pure,nanograined tetragonal zirconia ceramic stabilized with minimum CaO doping

Dense (~97%) CaO-stabilized ZrO₂ ceramic was stabilized with minimum (3 mol%) doping (reported to date) and processed via conventional sintering at a low temperature (~1200°C); compositional analysis via X-ray florescence confirmed the CaO doping accuracy. Phase-pure tetragonal structure (characterized via both X-ray diffraction and Raman spectroscopy) along with uniform nanograins (90 nm) of the ceramic ensured the evolution of no monoclinic phase even after vigorous low-temperature degradation experiments (both thermal and hydrothermal aging for 80-100 h). The sintered ceramic recorded a high hardness (~15 GPa); the indentation toughness value was also comparable to a 3 mol% yttria-stabilized zirconia system. The remarkable structure–property correlations in the 3 mol% CaO-stabilized ZrO₂ ceramic suggests that the same may be worth examining for suitable future applications (e.g., in dental ceramics).     

Optimal Sizing of a DBD Ozone Generator Using Response Surface Modeling

Dielectric barrier discharge (DBD) reactors used as ozone generators are well known today and widely used for water treatment and air disinfection. The purpose of this article is to propose an experimental procedure based on the response surface modeling in order to optimize the geometrical dimensions of the cylindrical shape ozone generator, i.e., the discharge gap and the electrodes length. Because an effective ozone generator is expected to give high ozone concentration with a minimum of power requirements, the applied high voltage was associated with the geometrical parameters to carry out a composite centered faces design. Obtained results indicate that for an efficient ozone generator, length of the electrodes needs to be optimized while the discharge gap should be minimized.     

Analysis of Fatty Acid and Lignan Composition of Indian Germplasm of Sesame to Evaluate Their Nutritional Merits

An attempt was made to individually analyze a germplasm collection of 54 indigenous Indian sesame cultivars for fatty acid and lignan composition of their seed oil by gas chromatography and high performance liquid chromatography, respectively. The entries varied in their fatty acid and lignan composition. The mean percentage contents of palmitic, stearic, oleic, linoleic and α‐linolenic acids ranged between 10–22, 5–10, 38–50, 18–43 and less than 1 whereas sesamol, sesamin and sesamolin scored between 3–37, 27–67, 20–59 of the total percentage of lignan, respectively. The highest percentage of α‐linolenic acid (ALA) was obtained in Var‐9 (1.3 % of the total fatty acids). Among the lignans, high sesamin content is considered to be significant, particularly in terms of long shelf life and nutraceutical value of sesame seed oil. The study has broadened our understanding related to differential biochemical composition of the rich sesame germplasms, thereby providing us with a useful groundwork for identifying potential targets and suitable cultivars for genetic engineering approaches to be undertaken in order to improve the nutritional quality of sesame oil, which in turn would be beneficial towards human health.     

Self-Assembly and Neurotoxicity of β-Amyloid (21–40) Peptide Fragment: The Regulatory Role of GxxxG Motifs

The three GxxxG repeating motifs from the C-terminal region of β-amyloid (Aβ) peptide play a significant role in regulating the aggregation kinetics of the peptide. Mutation of these glycine residues to leucine greatly accelerates the fibrillation process but generates a varied toxicity profile. Using an array of biophysical techniques, we demonstrated the uniqueness of the composite glycine residues in these structural repeats. We used solvent relaxation NMR spectroscopy to investigate the role played by the surrounding water molecules in determining the corresponding aggregation pathway. Notably, the conformational changes induced by Gly³³ and Gly³⁷ mutations result in significantly decreased toxicity in a neuronal cell line. Our results indicate that G³³xxxG³⁷ is the primary motif responsible for Aβ neurotoxicity, hence providing a direct structure–function correlation. Targeting this motif, therefore, can be a promising strategy to prevent neuronal cell death associated with Alzheimer's and other related diseases, such as type II diabetes and Parkinson's.     

Loading Rate Effect on Nanohardness of Soda-Lime-Silica Glass

To understand how hardness, the key design parameter for applications of brittle solids such as glass concerning contact deformation, is affected by loading rate variation, nanoindentation with a Berkovich tip was used to measure the nanohardness of a 330-μm-thick soda-lime-silica glass as a function of loading rate (1 to 1000 mN·s⁻¹). The results showed for the very first time that, with variations in the loading rate, there was a 6 to 9 pct increase in the nanohardness of glass up to a threshold loading rate (TLR), whereafter it did not appreciably increase with further increase in loading rate. Further, the nanohardness data showed an indentation size effect (ISE) that obeyed the Meyer’s law. These observations were explained in terms of a strong shear stress component developed just beneath the nanoindenter and the related shear-induced deformation processes at local microstructural scale weak links. The significant or insignificant presence of shear-induced serrations in load depth plots and corresponding scanning electron microscopic evidence of a strong or mild presence of shear deformation bands in and around the nanoindentation cavity supported such a rationalization. Finally, a qualitative picture was developed for different deformation processes induced at various loading rates in glass.     

Localized Delaunay Refinement for Sampling and Meshing

The technique of Delaunay refinement has been recognized as a versatile tool to generate Delaunay meshes of a variety of geometries. Despite its usefulness, it suffers from one lacuna that limits its application. It does not scale well with the mesh size. As the sample point set grows, the Delaunay triangulation starts stressing the available memory space which ultimately stalls any effective progress. A natural solution to the problem is to maintain the point set in clusters and run the refinement on each individual cluster. However, this needs a careful point insertion strategy and a balanced coordination among the neighboring clusters to ensure consistency across individual meshes. We design an octtree based localized Delaunay refinement method for meshing surfaces in three dimensions which meets these goals. We prove that the algorithm terminates and provide guarantees about structural properties of the output mesh. Experimental results show that the method can avoid memory thrashing while computing large meshes and thus scales much better than the standard Delaunay refinement method.     

Reversible,repeatable and low phase transition behaviour of spin coated nanostructured vanadium oxide thin films with superior mechanical properties

Smooth, uniform and crystalline vanadium oxide thin films were deposited on quartz by spin coating technique with four different rpm i.e., 1000, 2000, 3000 and 4000 and subsequently post annealed at 350, 450 and 550?°C in vacuum. Transmission electron microscopy (TEM), Field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD) techniques were utilized for microstructural characterizations and phase analysis, respectively, for vanadium oxide powder and deposited film. Nanorods were observed to be grown after vacuum annealing. X-ray photoelectron spectroscopy (XPS) technique was utilized to study the elemental oxidation state of deposited vanadium oxide films. Thermo-optical and electrical properties such as solar transmittance (τ_s), reflectance (ρ_s), absorptance (α_s), infrared (IR) emittance (ε_ir) and sheet resistance (R_s) of different thin films were evaluated. Based on the optical characteristics the optimized condition of the film processing was identified to be spin coated at 3000?rpm. Subsequently, the nanoindentation technique was utilized to measure hardness and Young's modulus of the optimized film. The measured nanomechanical properties were found to be superior to those reported for sputtered vanadium oxide films. Finally, temperature dependent phase transition characteristics of optimized vanadium oxide films were studied by differential scanning calorimetry (DSC) technique. Reversible and repeatable phase transition was found to occur in the range of 44–48?°C which was significantly lower than the phase transition temperature (i.e., 68?°C) of bulk VO₂.     

Knowledge-based systems using neural networks for electron beam welding process of reactive material (Zircaloy-4)

Bead-on-plate welding of zircaloy-4 (a reactive material) plates was conducted using electron beam according to central composite design of experiments. Its predictive models were developed in the form of knowledge-based systems in both forward and reverse directions using neural networks. Input parameters considered for this welding of reactive metals were accelerating voltage, beam current and weld speed. The responses of the welding process were measured in terms of bead width, depth of penetration and micro-hardness. Forward mapping of the welding process was conducted using regression analysis, back-propagation neural network (BPNN), genetic algorithm-tuned neural network (GANN) and particle swarm optimization algorithm-tuned neural network (PSONN). Reverse mapping of this process was also carried out using the BPNN, GANN and PSONN-based approaches. Neural network-based approaches could model this welding process of reactive material in both forward and reverse directions efficiently, which is required for the automation of the same. The performance of the neural network models was found to be data-dependent. The BPNN could outperform the other two approaches for most of the cases but not all in both the forward and reverse mappings.