Protocol for Energy Efficient Cluster Head Election for Collaborative Cluster Head Elections.

In wireless sensor networks (WSNs) , energy is a major constrain.Energy efficient network protocols is required to maintain reliable sensing of the sensing field . WSNs that use LEACH protocol, have node in a cluster periodically take trials to become cluster - head,such that the nodes in the cluster becomes cluster - head evenly. Nodes with greater transmission distance to the base station in the cluster dies out faster because it performs more work in transmitting data when it is cluster-head. The distance-based algorithm presented in this project, ensures that work is allocated to the nodes in the cluster more evenly ,thus, all areas of the sensor field is sensed more reliably

Impact of agricultural policy regimes on the output of food crops in nigeria (1980 – 2015)

The study evaluated the impact of agricultural policy regimes on the output of food crops in Nigeria (1980-2015). The specific objective was to; determine the growth rate of selected crop output. Time series data were used for the study. Data used in the study were obtained from Food and Agricultural Organization (FAO) crop production database for  Nigeria, covering the period 1980-2015, and was analyzed using  both descriptive and inferential statistics. Growth model was used to examine the trend in selected crop output. The study showed that the compound growth rates for all the crops were positive; cassava (4.92%), cocoa (2.61%), maize (5.84%), palm oil (2.84%) and rice (4.15%). This implies that there was a moderate increase in the output of the selected crops over the years. The compound growth rate in the output of maize among the crops considered was highest (5.84 % per annum) followed by cassava and was slow in cocoa with a compound growth rate of 2.61 % per annum. This result suggests that among the crops considered, maize is witnessing appreciable increase in production. The result specifically leads to the conclusion that output of cassava and rice had a direct influence on GDP growth in Nigeria from 1980 to 2015. The study therefore recommends that, the slow process of growth (deceleration) in the output of cassava, cocoa, maize and rice could be enhanced by the use of improved extension services and provision of input supports to the farmers involved in the cultivation of these crops

Grammar-based distance in progressive multiple sequence alignment

Background: We propose a multiple sequence alignment (MSA) algorithm and compare the alignment-quality and execution-time of the proposed algorithm with that of existing algorithms. The proposed progressive alignment algorithm uses a grammar-based distance metric to determine the order in which biological sequences are to be pairwise aligned. The progressive alignment occurs via pairwise aligning new sequences with an ensemble of the sequences previously aligned. Results: The performance of the proposed algorithm is validated via comparison to popular progressive multiple alignment approaches, ClustalW and T-Coffee, and to the more recently developed algorithms MAFFT, MUSCLE, Kalign, and PSAlign using the BAliBASE 3.0 database of amino acid alignment files and a set of longer sequences generated by Rose software. The proposed algorithm has successfully built multiple alignments comparable to other programs with significant improvements in running time. The results are especially striking for large datasets. Conclusion: We introduce a computationally efficient progressive alignment algorithm using a grammar based sequence distance particularly useful in aligning large datasets

Higher C-reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study

Background—Delirium is a common, morbid, and costly postoperative complication.. We aimed to identify blood-based postoperative delirium markers in a nested case control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. Methods and Materials—The Successful Aging after Elective Surgery Study enrolled dementia-free adults age ≥70 undergoing major scheduled non-cardiac surgery (N=566; 24% delirium). Plasma was collected at 4 timepoints: preoperatively (PREOP), post-anesthesia care unit (PACU), postoperative day 2 (POD2) and 1 month follow-up (PO1MO). Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). iTRAQ-based relative quantitation mass spectrometry proteomics was performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using non-parametric signed-rank tests were performed in all cohorts examining the association between the identified protein and delirium. Results—C-reactive protein (CRP) emerged from the proteomics analysis as the strongest delirium-related protein. ELISA validation confirmed that compared to controls, cases had significantly higher CRP levels (*p\u3c.05, **p\u3c.01) in the discovery, replication, and pooled cohorts at PREOP (median paired difference [mg/L] 1.97*, 0.29, 1.56**, respectively), PACU (2.83, 2.22*, 2.53**, respectively) and POD2 (71.97**, 35.18*, 63.76**, respectively), but not PO1MO (2.72, −0.66, 1.10, respectively). Discussion—Elevated pre- and postoperative plasma levels of CRP were associated with delirium, suggesting that a pre-inflammatory state and heightened inflammatory response to surgery are potential pathophysiological mechanisms of delirium

Differential Expression of GADD45\u3ci\u3eβ\u3c/i\u3e in Normal and Osteoarthritic Cartilage: Potential Role in Homeostasis of Articular Chondrocytes

Objective—Our previous study suggested that growth arrest and DNA damage–inducible protein 45β (GADD45β) prolonged the survival of hypertrophic chondrocytes in the developing mouse embryo. This study was undertaken, therefore, to investigate whether GADD45β plays a role in adult articular cartilage. Methods—Gene expression profiles of cartilage from patients with late-stage osteoarthritis (OA) were compared with those from patients with early OA and normal controls in 2 separate microarray analyses. Histologic features of cartilage were graded using the Mankin scale, and GADD45β was localized by immunohistochemistry. Human chondrocytes were transduced with small interfering RNA (siRNA)–GADD45β or GADD45β-FLAG. GADD45β and COL2A1 messenger RNA (mRNA) levels were analyzed by real-time reverse transcriptase–polymerase chain reaction, and promoter activities were analyzed by transient transfection. Cell death was detected by Hoechst 33342 staining of condensed chromatin. Results—GADD45β was expressed at higher levels in cartilage from normal donors and patients with early OA than in cartilage from patients with late-stage OA. All chondrocyte nuclei in normal cartilage immunostained for GADD45β. In early OA cartilage, GADD45β was distributed variably in chondrocyte clusters, in middle and deep zone cells, and in osteophytes. In contrast, COL2A1, other collagen genes, and factors associated with skeletal development were up-regulated in late OA, compared with early OA or normal cartilage. In overexpression and knockdown experiments, GADD45β down-regulated COL2A1 mRNA and promoter activity. NF-κB overexpression increased GADD45β promoter activity, and siRNA-GADD45β decreased cell survival per se and enhanced tumor necrosis factor α–induced cell death in human articular chondrocytes. Conclusion—These observations suggest that GADD45β might play an important role in regulating chondrocyte homeostasis by modulating collagen gene expression and promoting cell survival in normal adult cartilage and in early OA

SHREC2020 track:Multi-domain protein shape retrieval challenge

Proteins are natural modular objects usually composed of several domains, each domain bearing a specific function that is mediated through its surface, which is accessible to vicinal molecules. This draws attention to an understudied characteristic of protein structures: surface, that is mostly unexploited by protein structure comparison methods. In the present work, we evaluated the performance of six shape comparison methods, among which three are based on machine learning, to distinguish between 588 multi-domain proteins and to recreate the evolutionary relationships at the proteinand species levels of the SCOPe database. The six groups that participated in the challenge submitted a total of 15 sets of results. We observed that the performance of all the methods significantly decreases at the species level, suggesting that shape-only protein comparison is challenging for closely related proteins. Even if the dataset is limited in size (only 588 proteins are considered whereas more than 160,000 protein structures are experimentally solved), we think that this work provides useful insights into the current shape comparison methods performance, and highlights possible limitations to large-scale applications due to the computational cost

A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences

Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. The proposed clustering algorithm uses a grammar-based distance metric to determine partitioning for a set of biological sequences. The algorithm performs clustering in which new sequences are compared with cluster-representative sequences to determine membership. If comparison fails to identify a suitable cluster, a new cluster is created. Results: The performance of the proposed algorithm is validated via comparison to the popular DNA/RNA sequence clustering approach, CD-HIT-EST, and to the recently developed algorithm, UCLUST, using two different sets of 16S rDNA sequences from 2,255 genera. The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. The validation results are especially striking for large datasets. Conclusions: We introduce a fast and accurate clustering algorithm that relies on a grammar-based sequence distance. Its statistical clustering quality is validated by clustering large datasets containing 16S rDNA sequences

Surface-based protein domains retrieval methods from a SHREC2021 challenge

publication dans une revue suite à la communication hal-03467479 (SHREC 2021: surface-based protein domains retrieval)International audienceProteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore of primary importance for their activity. In the present work, we assess the ability of different methods to detect such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone. Finally, the discussion permits to expose the results with respect to ones obtained in the previous contests for the extended method. The source codes of each presented method have been made available online

SHREC’20 Track:Retrieval of digital surfaces with similar geometric reliefs

International audienceThis paper presents the methods that have participated in the SHREC'20 contest on retrieval of surface patches with similar geometric reliefs and 1 the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local "geometric pattern" information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches