Flamingo Jelly Fish search optimization-based routing with deep-learning enabled energy prediction in WSN data communication.

Nowadays, wireless sensor networks (WSN) have gained huge attention worldwide due to their wide applications in different domains. The limited amount of energy resources is considered as the main limitations of WSN, which generally affect the network life time. Hence, a dynamic clustering and routing model is designed to resolve this issue. In this research work, a deep-learning model is employed for the prediction of energy and an optimization algorithmic technique is designed for the determination of optimal routes. Initially, the dynamic cluster WSN is simulated using energy, mobility, trust, and Link Life Time (LLT) models. The deep neuro-fuzzy network (DNFN) is utilized for the prediction of residual energy of nodes and the cluster workloads are dynamically balanced by the dynamic clustering of data using a fuzzy system. The designed Flamingo Jellyfish Search Optimization (FJSO) model is used for tuning the weights of the fuzzy system by considering different fitness parameters. Moreover, routing is performed using FJSO model which is used for the identification of optimal path to transmit data. In addition, the experimentation is done using MATLAB tool and the results proved that the designed FJSO model attained maximum of 0.657J energy, a minimum of 0.739 m distance, 0.649 s delay, 0.849 trust, and 0.885 Mbps throughput.

Effect of Low-Level Laser Therapy and Platelet-Rich Fibrin on the Treatment of Intra-bony Defects.

Introduction: Attempts to regenerate the periodontal osseous defect, which is lost as a result of periodontal disease, require the tapping of the innate healing potential of periodontium through appropriately designed therapeutic strategies. A multitude of grafted and non-grafted approaches have been used in the management of Intra-bony defects. However, they do not provide predictable periodontal regeneration. The aim of this study was to evaluate the combined effect of low-level laser therapy (LLLT) and platelet-rich fibrin (PRF), in site modulated intra-bony defects (decortication), which were accessed using a simplified papilla preservation flap (SPPF), on the clinical and radiographic outcomes of periodontal disease. Methods: A total of 30 patients with intra-bony defects were recruited for the study and randomly distributed in two groups (n=15). Test group sites were accessed with SPPF and the defects received intra-marrow Penetration (IMP) following debridement and were irradiated with a low-level laser followed by PRF grafting and suturing done. The control group defects were accessed with SPPF and grafted with PRF before being secured by sutures. The plaque and bleeding score, PPD, CAL, and the position of the gingival margin with radiographic defect depth were recorded and analyzed at baseline and six months post-intervention using the student's t test and Wilcoxon signed rank test. Results: The test group showed a clinically relevant increase in mean PPD reduction, CAL gain, and radiographic bone fill (3.6 ± 1.35 mm, 3.26 ± 1.16 mm and 2.44 ± 1.24 mm) compared to the control group (2.93 ±1.1 mm, 2.267 ± 1.33 mm and 1.26 ± 0.99 mm) six months post-intervention. However, intergroup comparison between the test and control groups did not show any statistically significant difference. Conclusion: These results highlights that test protocol had greater amelioration of the effects of periodontal disease and all the investigated clinical and radiographic parameters showed considerable improvement from baseline to 6 months within test and control group, but intergroup comparison between the test and control groups did not show any statistically significant difference, indicating statistical equivalence between the test and control protocol.

Association of Receptor for advanced glycation end products G82S polymorphism with chronic periodontitis in type II diabetic and non-diabetic South Indians.

AIM The current study investigated the association of RAGE G82S polymorphism with chronic periodontitis in South Indians with and without type II Diabetes mellitus. MATERIALS AND METHODS: 405 individuals were enrolled into 3 groups-systemically and periodontally healthy with no attachment loss (n = 135), generalized chronic periodontitis (n = 135)and generalized chronic periodontitis with type II diabetes mellitus(n = 135). Periodontal clinical parameters were recorded. RFLP-PCR was utilized for genotyping. RESULTS: Frequencies of genotype GG, GA and AA were 133, 2, 0 in group I respectively, 131, 4, 0 in group II respectively and 118, 13, 4 in group III respectively. Pearson's Chi squared test demonstrated a significant difference in the genotype distribution between the three groups (χ2 = 19.88,P < 0.001). Fischer exact-test showed that the variant GA/AA genotype was associated with a significantly increased risk for generalized chronic periodontitis in type II diabetics when compared with the GG genotype of systemically and periodontally healthy subjects (OR-9.58, 95% CI 2.168-42.339, P < 0.001) and non-diabetic chronic periodontitis subjects (OR- 4.71, 95% CI: 1.54-14.42, P < 0.05). No association and increased susceptibility to chronic periodontitis was observed in subjects with GA/AA genotype when compared with systemically and periodontally healthy subjects (OR- 2.031, 95% CI: 0.366-11.277 P > 0.05). Furthermore, comparison of clinical parameters based on genotype distribution revealed statistically significant higher mean plaque (P < 0.05) and sulcus bleeding score (P < 0.001) in group-III subjects. CONCLUSION: RAGE G82S gene polymorphism confers susceptibility to generalized chronic periodontitis in type II diabetic subjects of South Indian Tamilian ethnicity.

Alumina/activated carbon nano-composites: Synthesis and application in sulphide ion removal from water.

An investigation of adsorption of sulphide ion (S2-) in water onto carbon/alumina nano-composites synthesized from aluminium carboxylate precursors, in presence of HCl, NaOH, NaCl and surfactant is reported in this paper. A controlled oxygen free pyrolytic technique has been adopted for the synthesis of nano-composites, using acetate, acetyl acetonate, lactate and distearate of aluminium and activated carbon. XRD, SEM and TEM studies of the composites show that they contain clusters made of nano carbon particles of size 50-130nm into which nano alumina particles of size around 10nm are dispersed. While applying the adsorption data in Langmuir, Freundlich, Temkin and Dubinin-Raduskevich isotherm models, the data fit well with Langmuir model. All composites have increased porosity and decreased surface area compared to bare carbon. The adsorption capacity of composites obtained from acetate and lactate are higher and are found to be in the range of 71-200mg/g.

In silico characterization and molecular dynamics simulation of Pfcyc-1, a cyclin homolog of Plasmodium falciparum.

Malaria is still one of the deadly diseases resulting in deaths of millions of people worldwide and situation has become worse due to alarming rise in anti-malarial drug resistance. Genome sequence availability of Plasmodium falciparum, the main causal organism of severe malaria in humans, has enabled identification of various parasite cell cycle regulators like several cyclins and cyclin dependent kinases or CDKs which are promising novel drug targets for Malaria. Here, we present in silico characterization of tertiary structure of Pfcyc-1, a P. falciparum cyclin homolog, which enables identification of key structural elements that contribute to its tertiary structure and function. We have investigated the structure and dynamics of Pfcyc-1 structural model by performing 10 ns molecular dynamics (MD) simulation. Our study indicates that despite poor sequence similarities with cyclin H and A, the characteristic structural cyclin domains are conserved in Pfcyc-1 too. The Pfcyc-1 model reveals a cyclin box, consisting of two tandemly repeating five-helix bundles separated by a linker hinge peptide. Furthermore, the amino acid residues in other known cyclins mediating cyclin-CDK interactions are conserved in Pfcyc-1. The model and its MD simulation offer a first ever structural annotation of any plasmodium cyclin, which along with sequence comparisons, helps in identification of important functional residues mediating the Pfcyc-1-CDK like interactions.

Lung cancer biomarkers: State of the art.

Lung cancer is one of the deadliest cancers worldwide, with the highest incidence and mortality amongst all cancers. While the prognosis of lung cancer is generally grim, with 5-year survival rates of only 15%, there is hope, and evidence, that early detection of lung cancer can reduce mortality. Today, only computed tomography screening has shown to lead to early detection and reduction in mortality, but is limited by being anatomic in nature, unable to differentiate between inflammatory and neoplastic pathways, and therefore, susceptible to false positives. There is increasing interest in biomarkers for lung cancer, especially those that predict metastatic risk. Some biomarkers like DNA mutations and epigenetic changes potentially require tissue from the at-risk site; some like serum proteins and miRNAs are minimally invasive, but may not be specific to the lung. In comparison, emerging biomarkers from exhaled breath, like volatile organic compounds (VOC), and exhaled breath condensate, e.g., small molecules and nucleic acids, have the potential to combine the best of both. This mini review is intended to provide an overview of the field, briefly discussing the potential of what is known and highlighting the exciting recent developments, particularly with miRNAs and VOCs.

Support vector machine based prediction of P. falciparum proteasome inhibitors and development of focused library by molecular docking.

The emergence and spread of Plasmodium falciparum resistance to existing antimalarials emphasize the impelling search for novel drug targets and chemotherapeutic compounds. The ubiquitin-proteasome system plays a major role in overall protein turnover, in eukaryotic cells including plasmodia. 20S ß subunit is the catalytic core of this proteolytic machinery, and hence most of the inhibitors developed are being targeted towards this component. Inhibition of the proteasome is established as a promising strategy to develop novel antimalarial drugs. The present study reports identification of novel drug-like 20S proteasome inhibitors with potential activity against the 20S ß subunit of P. falciparum using a combination of ligand based (Support Vector Machines) and receptor based (molecular docking) techniques. The robust learning and generalizing capability of Support Vector Machines (SVM) has been exploited to classify proteasome inhibitors and non-inhibitors, targeted towards P. falciparum 20S proteasome. SVM model has been trained using 170 molecular descriptors of 64 inhibitors and 208 putative non-inhibitors of 20S proteasome. The non-linear classifier based on Radial Basis Function (RBF) kernel yielded highest classification accuracy in comparison to the linear classifier. The best classifier had 5-fold Cross-Validation (CV) accuracy of 97% and Area Under Curve (AUC) of 0.99 reflecting good accuracy of the model. The SVM model rapidly classified compounds with potential proteasomal activity. Subsequently, molecular docking studies aided the generation of focused collection of compounds with good binding affinity towards the substrate-binding site of 20S ß subunit. The novel drug-like 20S proteasome inhibitors identified in this study can be a good starting point to develop novel antimalarial drugs.

Molecular modeling studies of the interaction between Plasmodium falciparum HslU and HslV subunits.

The PfHslUV, a Plasmodium falciparum homolog of prokaryotic HslUV systems, is a newly identified drug target. The HslUV complex is an assembly of Heat Shock Locus gene products U and V. The formation of complete complex is essential for the proteasome to carry out its biochemical and physiological role in the parasite, namely to degrade specific target proteins in an ATP-dependent chaperone assisted manner. PfHslV subunit, a protease, exhibits increased proteolytic activity in the presence of PfHslU, the subunit believed to be responsible for allosteric activation of PfHslV. In the present work, we have employed computational methods to simulate the interaction of PfHslU and PfHslV subunits. We have used three methods--namely homology modeling, molecular docking and computational alanine scanning to model the complex, to predict the binding mode of PfHslU-V interaction and to predict the binding-energy hot-spots in protein-protein interface, respectively. The three dimensional models of PfHslV and PfHslU have been generated using MODELLER, based on the crystal structures of prokaryotic HslUV complex as templates. The modeled structures were docked using PatchDock, a geometry-based molecular docking algorithm. Finally, a three-dimensional PfHslUV complex model was generated that helped in comparing protein-protein interface characteristics with that of crystal structures of prokaryotic HslUV. Further, computational alanine scanning analysis of the generated complex was performed to calculate the binding free energy changes (DeltaDeltaGbind), which helped in identifying residues crucial for PfHslU and PfHslV interactions.

Virtual high throughput screening (vHTS)--a perspective.

With the exponential rise in the number of viable novel drug targets, computational methods are being increasingly applied to accelerate the drug discovery process. Virtual High Throughput Screening (vHTS) is one such established methodology to identify drug candidates from large collection of compound libraries. Although it complements the expensive and time consuming High Throughput Screening (HTS) of compound libraries, vHTS possess inherent challenges. The successful vHTS requires the careful implementation of each phase of computational screening experiment right from target preparation to hit identification and lead optimization. This article discusses some of the important considerations that are imperative for designing a successful vHTS experiment.