605 research outputs found
Xynobius chrysops Wu, van Achterberg, Sheng & Chen 2018
No full text<i>Xynobius chrysops</i> Wu, van Achterberg, Sheng & Chen, 2018 (Fig. 3) <p> <b>Material examined.</b> Two females on card; India: Karnataka: Sakleshpura; sweep net; 30.xii.2022; coll. Hemanth Kumar H. M; code—NIM/ NBAIR /Hym/Brac/Opi/Xyn/30222-A & B (NIM).</p>Published as part of <i>Gupta, Ankita, Achterberg, Cornelis Van, Pattar, Rohit & Kumar, Hemanth, 2023, First report of two braconid genera Syntretus Foerster and Xynobius Foerster from India with description of one new species, pp. 582-588 in Zootaxa 5319 (4)</i> on page 586, DOI: 10.11646/zootaxa.5319.4.8, <a href="http://zenodo.org/record/8203380">http://zenodo.org/record/8203380</a>
Integration of Clinical and Genomic data: a Methodological Survey
No full textHuman diseases are inherently complex and governed by the complicated interplay of several underlying factors. Clinical research focuses on behavioral, demographic and pathology information, whereas molecular genomics focuses on finding underlying genetic and genomic factors in genomic data collected on mRNA expression, proteomics, biological networks, and other microbiological features. However, each of these clinical and genomic datasets contains information only about one particular aspect of a complex disease, rather than covering all of the several complicated underlying risk factors. This has led to a new area of research that integrates both clinical and genomic data and aims to extract more information about diseases by considering not only all the various factors, but also the interactions among those factors, which cannot be captured by clinical and genomic studies that are performed independently of each other. Although initial efforts have already been made to develop such integrative modeling of the clinical and genomic data to shed light on the biological mechanism of the diseases, the research field is still in a rudimentary stage. In this review article, we survey the general issues, challenges and current work of clinicogenomic studies. We also summarize the current state of the field and discuss some possibilities for future work.Dey, Sanjoy; Gupta, Rohit; Steinbach, Michael; Kumar, Vipin. (2013). Integration of Clinical and Genomic data: a Methodological Survey. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215908
Syntretus curvatus Gupta, van Achterberg & Pattar 2023, sp. nov.
No full text<i>Syntretus curvatus</i> Gupta, van Achterberg & Pattar, sp. nov. (Figs 1–2) <p> <b>Type material.</b> <b>Holotype.</b> Female on card; India: Karnataka: Bengaluru; sweep net; 18.vi.2021; coll. R. Prajwal; code—NIM/ NBAIR /Hym/Brac/Syn/180621-H (NIM). Paratype: one female on card; same data as holotype; code—NIM/ NBAIR /Hym/Brac/Syn/180621-P1.</p> <p>Holotype. Body length 3.7 mm; antenna 23 antennomeres; fore wing 2.6 mm long (1.0 mm wide).</p> <p>Colour: Body brownish yellow, except for black eyes and ovipositor sheath; ocelli, apex of mandibles, lateral sides of mesoscutum and metanotum reddish brown; antenna light brown, except with yellowish scape and pedicel, pterostigma light yellow with darker margins and yellowish brown veins.</p> <p>Head: Width of head in dorsal view 1.7 × its length; antennal segments 23, antenna 0.6 × length of body, length of first flagellomere 0.9–1.1 × second flagellomere, length of first, second, third and penultimate flagellomeres 1.6, 1.5, 1.4 and 2.1 × their width, respectively; OOL: OD: POL (relative) = 2.8: 1: 1.9; length of eye in dorsal view 1.5 × temple; temple roundly narrowed behind eyes; temple and vertex smooth, glabrous; face with a distinct medio-longitudinal groove; nearly smooth, sparsely setose, inter-tentorial line 1.3 × tentorio-ocular line; clypeus convex, medially straight, nearly smooth, its width 3.5 × its height; clypeus narrower than face; length of malar space 2.5 × basal width of mandible.</p> <p>Mesosoma: Length of mesosoma 1.4 × its height; pronotum dorsally crenulate; mesopleuron largely smooth except for few oblique rugae slightly below its centre; notauli shallowly impressed anteriorly; mesoscutum and scutellum smooth, glabrous; propodeum with medio-longitudinal groove and few median transverse carinae in basal one third, remaining part reticulate-rugose.</p> <p>Wings: Fore wing subhyaline and 2.6 × longer than wide; pterostigma 2.4 × as long as wide; length of vein 1- R 1 0.6 × length of pterostigma; vein 3-SR+SR1 6.0–6.4 × longer than r; r issued from middle of pterostigma, 0.4 × width of pterostigma; vein 3-SR+SR1 curved, ending before apex; r:2-SR:SR1+3-SR (relative) = 1:2.6:5.9; l-CU1:2-CU1= 1:4.8; 2-1A absent. Hind wing: vein 1-SC+ R of hind wing unsclerotised or absent (as most other veins; Fig. 2H).</p> <p>Legs: Hind coxa nearly smooth; length of hind femur, tibia and basitarsus 4.1, 9.6 and 9.4 × their width, respectively; length of hind tibial spurs 0.30 and 0.28 × hind basitarsus.</p> <p>Metasoma: Length of first tergite 3.6 × its apical width, first tergite slender and smooth, basally, medially and apically slightly widened, ratio of maximum width to minimum width is 2.7 and laterope absent; following tergites smooth; second tergite compressed and with dorsal fold (Fig. 2G); ovipositor sheath slightly protruding beyond apex of metasoma and 0.3 × as long as first tergite; apical half of ovipositor narrow and decurved.</p> <p>Etymology: Named after the decurved ovipositor, “curvus” is Latin for bent.</p> <p> Comments: This Indian species comes close to <i>S. amoenus</i> Belokobylskij in having reticulate sculpture of the propodeum, the second and third metasomal tergites compressed and in dorsal view their upper part hardly wider than the first tergite, no laterope of the first tergite and veins of the hind wing mainly absent and differs as follows in Table 1:</p>Published as part of <i>Gupta, Ankita, Achterberg, Cornelis Van, Pattar, Rohit & Kumar, Hemanth, 2023, First report of two braconid genera Syntretus Foerster and Xynobius Foerster from India with description of one new species, pp. 582-588 in Zootaxa 5319 (4)</i> on page 583, DOI: 10.11646/zootaxa.5319.4.8, <a href="http://zenodo.org/record/8203380">http://zenodo.org/record/8203380</a>
Synthesis and characterization of biocompatible bimetallic-semi-aromatic polyester hybrid nanocomposite
No full textFunding Information: Dr. Piyush Kumar Gupta is thankful to the Department of Life Sciences, Sharda University, Greater Noida, India for providing infrastructure and research facilities. Publisher Copyright: © 2021 Elsevier B.V.Nanocomposites have been broadly used in bioelectronic, biosensing, photocatalytic, and bioimaging. Moreover, its use in bioengineering field is emerging continuously. The present study reports first-time the synthesis of a novel bimetallic-semi-aromatic polyester hybrid nanocomposite. The obtained MnFe2O4-poly(tBGE-alt-PA) hybrid nanocomposite was physicochemically characterized. FTIR analysis confirmed the synthesis of hybrid nanocomposite. XRD data showed the crystal nature of hybrid nanocomposite due to MnFe2O4 nanoparticles (NPs). TGA study presented the thermostable nature of hybrid nanocomposite and DSC analysis exhibited the absence of chemical interactions between the copolymer and MnFe2O4 NPs in hybrid nanocomposite. Further, the net negative charge was measured on the surface of this almost spherical hybrid nanocomposite. Later, we observed the biocompatible and hemocompatible nature of nanocomposite and in future, it may open many novel avenues in various fields of biomedical science.Peer reviewe
A Novel Error-Tolerant Frequent Itemset Model for Binary and Real-Valued Data
No full textFrequent pattern mining has been successfully applied to a broad range of applications, however, it has two major drawbacks, which limits its applicability to several domains. First, as the traditional 'exact' model of frequent pattern mining uses a strict definition of support, it limits the recovery of frequent itemset patterns in real-life data sets where the patterns may be fragmented due to random noise/errors. Second, as traditional frequent pattern mining algorithms works with only binary or boolean attributes, it requires transformation of real-valued attributes to binary attributes, which often results in loss of information. As many of the real-life data sets are both noisy and real-valued in nature, past approaches have tried to independently address these issues and there is no systematic approach that addresses both of these issues together. In this paper, we propose a novel Error-Tolerant Frequent Itemset (ETFI) model for binary as well as real-valued data. We also propose a bottom-up pattern mining algorithm to sequentially discover all ETFIs from both types of data sets. To illustrate the efficacy of our proposed ETFI approach, we use two real-valued S.Cerevisiae microarray gene-expression data sets and evaluate the patterns obtained in terms of their functional coherence as evaluated using the GO-based functional enrichment analysis. Our results clearly demonstrate the importance of directly accounting for errors/noise in the data. Finally, the statistical significance of the discovered ETFIs as estimated by using two randomization tests, reveal that discovered ETFIs are indeed biologically meaningful and are neither obtained by random chance nor capture random structure in the data.Gupta, Rohit; Rao, Navneet; Kumar, Vipin. (2009). A Novel Error-Tolerant Frequent Itemset Model for Binary and Real-Valued Data. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215813
Prevention of endotoxin-induced uveitis in rabbits by Triphala, an Ayurvedic formulation
No full textPurpose: Triphala (TA) is an Ayurvedic formulation used to treat various disorders. The present study was designed to investigate the anti-inflammatory effect of TA aqueous extract on experimental uveitis in the rabbit. Methods: Anterior uveitis was induced in rabbits by intravitreal injection of lipopolysaccharide from Eschericha coli after pretreatment with TA aqueous extract. Subsequently the anti-inflammatory activity of TA was evaluated by grading the clinical signs and estimating the inflammatory cell count, protein, and TNF-α level in the aqueous humour. Results: The anterior segment inflammation in the control group was significantly higher than in TA and prednisolone treated groups, as observed by clinical grading. The inflammatory cell count in the control group was 31.23 ± 0.80 × 105cells/ml, whereas it was 3.29 ± 0.47 × 105cells/ml (P < 0.0001 vs. control) and 1.31 ± 0.31 × 105 (P < 0.0001 vs. control) cells/ml in the TA and prednisolone treated groups, respectively. The protein content of the aqueous humour was 15.43 ± 0.54, 3.13 ± 0.35 (P < 0.0001 vs. control), and 1.96 ± 0.39 (P < 0.0001 vs. control) mg/ml in the control, TA and prednisolone treated groups respectively. The aqueous TNF- α level in the control group was 942.20 ± 6.46 pg/ml and was 261.30 ± 13.60 (P < 0.001 vs. control) and 104.00 ± 4.50 (P < 0.0001 vs. control) pg/ml in the TA and prednisolone treated groups, respectively. \ud
Conclusions: Topical administration of aqueous extract of TA prevented uveitis in endotoxin-induced experimental rabbits.\u
Quantitative Evaluation of Approximate Frequent Pattern Mining Algorithms
No full textTraditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life datasets, this limits the recovery of frequent itemset patterns as they are fragmented due to random noise and other errors in the data. Hence, a number of methods have been proposed recently to discover approximate frequent itemsets in the presence of noise. These algorithms use a relaxed definition of support and additional parameters, such as row and column error thresholds to allow some degree of "error" in the discovered patterns. Though these algorithms have been shown to be successful in finding the approximate frequent itemsets, a systematic and quantitative approach to evaluate them has been lacking. In this paper, we propose a comprehensive evaluation framework to compare different approximate frequent pattern mining algorithms. The key idea is to select the optimal parameters for each algorithm on a given dataset and use the itemsets generated with these optimal parameters in order to compare different algorithms. We also propose simple variations of some of the existing algorithms by introducing an additional post-processing step. Subsequently, we have applied our proposed evaluation framework to a wide variety of synthetic datasets with varying amounts of noise and a real dataset to compare existing and our proposed variations of the approximate pattern mining algorithms. Source code and the datasets used in this study are made publicly available.Gupta, Rohit; Fang, Gang; Field, Blayne; Steinbach, Michael; Kumar, Vipin. (2009). Quantitative Evaluation of Approximate Frequent Pattern Mining Algorithms. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215792
- …
