Biology subjects

Shakeel, A.

Publications and source records attributed to Shakeel, A..

4 recordsLinked to original sources

bioRxiv2024

Genetically modifying the protein matrix of macroscopic living materials to control their structure and rheological properties

The field of engineering living materials (ELMs) seeks to engineer cells to form macroscopic materials with tailorable structures and properties. While centimeter-scale ELMs can be grown from Caulobacter crescentus engineered to secrete a protein matrix, how the sequence of the protein matrix affects structural and rheological properties remains poorly understood. Here, we explore how changing the elastin-like polypeptide (ELP) length impacts ELM microstructure and viscoelastic behavior. We demonstrate that shortening ELP produces fibers almost 2x thicker than other variants, resulting in a stiffer material at rest. Interestingly, the mid-length ELP forms a complex structure with globules and multidirectional fibers with increased yield stress under flow conditions. Lengthening ELP creates thinner strands between cells with similar storage and loss moduli to the mid-length ELP. This study indicates that sequence-structure-property relationships in these ELMs are complex with few parallels to other biocomposite models. Furthermore, it highlights that fine-tuning genetic sequences can create significant differences in rheological properties, uncovering new design principles of ELMs.

synthetic biology↗

bioRxiv2021

Analysis of vascular architecture and parenchymal damage generated by reduced blood perfusion in decellularized porcine kidneys using a gray level co-occurrence matrix

There is no cure for kidney failure, but a bioartificial kidney may help address this global problem. Decellularization provides a promising platform to generate transplantable organs. However, maintaining a viable vasculature is a significant challenge to this technology. Even though angiography offers a valuable way to assess scaffold structure/function, subtle changes are overlooked by specialists. In recent years, innovative image analysis methods in radiology have been suggested to detect and identify subtle changes in tissue architecture. The aim of our research was to apply one of these methods based on a gray level co-occurrence matrix (GLCM) computational algorithm in the analysis of vascular architecture and parenchymal damage generated by hypoperfusion in decellularized porcine. Perfusion decellularization of the whole porcine kidneys was performed using previously established protocols. We analyzed and compared angiograms of kidneys subjected to pathophysiological arterial perfusion of whole blood. For regions of interest (ROIs) covering kidney medulla and the main elements of the vascular network, five major GLCM features were calculated: angular second moment as an indicator of textural uniformity, inverse difference moment as an indicator of textural homogeneity, GLCM contrast, GLCM correlation, and sum variance of the co-occurrence matrix. In addition to GLCM, we also performed discrete wavelet transform analysis of angiogram ROIs by calculating the respective wavelet coefficient energies using high and low-pass filtering. We report statistically significant changes in GLCM and wavelet features, including the reduction of the angular second moment and inverse difference moment, indicating a substantial rise in angiogram textural heterogeneity. Our findings suggest that the GLCM method can be successfully used as an addition to conventional fluoroscopic angiography analyses of micro/macrovascular integrity following in vitro blood perfusion to investigate scaffold integrity. This approach is the first step toward developing an automated network that can detect changes in the decellularized vasculature.

bioengineering↗

bioRxiv2020

Genome Wide Characterization, Identification And Expression Analysis Of Erf Gene Family In Cotton

ERF is a subfamily of AP2/EREBP superfamily, contained single AP2 domain. The overexpression of ERF genes steered to abiotic stress tolerance and pathogen resistance in transgenic plants. Here, a genome-wide analysis of ERF gene family within two diploid species (G. arboreum & G. raimondii) and two tetraploid species (G. barbadense, G. hirsutum) was performed. A total of 118, 120, 213, 220 genes contained sequence single AP2 domain were identified in G. arboreum, G. raimondii, G. barbadense and G. hirsutum respectively. The identified genes were unevenly distributed across 13/26 chromosomes of A and D genomes of cotton. Genome comparison revealed that segmental duplication may have played crucial roles in the expansion of the cotton ERF gene family, and tandem duplication also played a minor role. Analysis of RNA-Seq data indicated that cotton ERF gene expression levels varied across different tissues and in response to different abiotic stress. Overall, our results could provide valuable information for better understanding the evolution of cotton ERF genes and lays a foundation for future investigation in cotton.

bioinformatics↗

bioRxiv2019

The effect of single-task training on learning transfer to a novel bimanual task

BackgroundThe contextual interference effect suggests that the random practice of multiple-tasks is more beneficial for the retention and transfer of the learning as compared to blocked practice. Therefore, the transfer of learning is usually attributed to the contextual interference effect and is studied in a multi-task setting. ObjectiveThe goals of this study were to evaluate whether the transfer of learning (i) can occur when a single bimanual task is practiced, (ii) is affected by the knowledge of results (feedback), and (iii) sustains over an extended number of trials. MethodsFifty-two healthy subjects were equally divided into four groups. Before the transfer test, two groups practiced a bimanual finger-tapping task with feedback (EF) and without feedback (ENF). The third group (IM) practiced the same task using the kinesthetic motor imagery, whereas the last group acted as a control (CTRL) and performed only a bimanual button-pressing task used for the transfer test. ResultsLinear mixed-model showed that in the transfer test, groups EF, ENF and IM had similar performance but significantly higher scores compared to the CTRL group. Compared to the CTRL, the EF and IM groups showed significantly improved performance in most of the sessions but group ENF had similar results. ConclusionThis study suggests that the single-task practice of a discrete bimanual task can facilitate the learning transfer to a novel task and knowledge of results (feedback) have no significant impact on the transfer of learning. Moreover, the transfer of learning effect does not disappear in extended trials. HighlightsO_LISingle-task practice of a discrete bimanual task can facilitate the learning of a novel bimanual task C_LIO_LIKnowledge of results (feedback) does not improve learning transfer in single-task setting C_LIO_LITransfer of learning effect does not disappear in extended trials C_LI

neuroscience↗