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Item Augmenting Indiana's groundwater level monitoring network: optimal siting of additional wells to address spatial and categorical sampling gaps(2014-11-21) Sperl, Benjamin J.; Banerjee, Aniruddha; Lulla, Vijay O.; Bein, Frederick L. (Frederick Louis), 1943-Groundwater monitoring networks are subject to change by budgetary actions and stakeholder initiatives that result in wells being abandoned or added. A strategy for network design is presented that addresses the latter situation. It was developed in response to consensus in the state of Indiana that additional monitoring wells are needed to effectively characterize water availability in aquifer systems throughout the state. The strategic methodology has two primary objectives that guide decision making for new installations: (1) purposive sampling of a diversity of environmental variables having relevance to groundwater recharge, and (2) spatial optimization by means of maximizing geographic distances that separate monitoring wells. Design objectives are integrated in a discrete facility location model known as the p-median problem, and solved to optimality using a mathematical programming package.Item Identification of potential key genes associated with severe pneumonia using mRNA-seq(Spandidos, 2018-08) Feng, Cong; Huang, He; Huang, Sai; Zhai, Yong-Zhi; Dong, Jing; Chen, Li; Huang, Zhi; Zhou, Xuan; Li, Bei; Wang, Li-Li; Chen, Wei; Lv, Fa-Qin; Li, Tan-Shi; Electrical and Computer Engineering, School of Engineering and TechnologyThis study aimed to identify the potential key genes associated with severe pneumonia using mRNA-seq. Nine peripheral blood samples from patients with severe pneumonia alone (SP group, n=3) and severe pneumonia accompanied with chronic obstructive pulmonary disease (COPD; CSP group, n=3), as well as volunteers without pneumonia (control group, n=3) underwent mRNA-seq. Based on the sequencing data, differentially expressed genes (DEGs) were identified by Limma package. Following the pathway enrichment analysis of DEGs, the genes that were differentially expressed in the SP and CSP groups were selected for pathway enrichment analysis and coexpression analysis. In addition, potential genes related to pneumonia were identified based on the information in the Comparative Toxicogenomics Database. In total, 645 and 528 DEGs were identified in the SP and CSP groups, respectively, compared with the normal controls. Among these DEGs, 88 upregulated genes and 80 downregulated genes were common between the two groups. The functions of the common DEGs were similar to those of the DEGs in the SP group. In the coexpression network, the commonly downregulated genes (including ND1, ND3, ND4L, and ND6) and the commonly upregulated genes (including TSPY6P and CDY10P) exhibited a higher degree. In addition, 131 DEGs (including ND1, ND3, ND6, MIR449A and TAS2R43) were predicted to be potential pneumonia-related genes. In conclusion, the present study demonstrated that the common DEGs may be associated with the progression of severe pneumonia.Item miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer’s disease(Springer Nature, 2024-01-09) Han, Sang‑Won; Pyun, Jung‑Min; Bice, Paula J.; Bennett, David A.; Saykin, Andrew J.; Kim, Sang Yun; Park, Young Ho; Nho, Kwangsik; Radiology and Imaging Sciences, School of MedicineBackground: Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers. Methods: We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification. Results: Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs. Conclusions: Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.Item Public bike stations in Indianapolis: a location allocation study(2018-02) Cooper, Samuel D.; Banerjee, Aniruddha; Wilson, Jeffrey S.; Lulla, VijayLocation Allocation, rooted in Operations Research and Mathematical programming, allows real world problems to be solved using optimization (based on mathematics and science) and equity principles (based on ethics). Finding nearest facilities for everyone simultaneously is a task solved by numerical and algebraic solutions. Bikeshare as a public good requires equitable allocation of bikeshare resources. Distance, as an impediment, can be minimized using location allocation algorithms. Since location allocation of this kind involves large numbers, sophisticated algorithms are needed to solve them due to their combinatorically explosive nature (i.e. as ‘n’ rises, solution time rises at least exponentially – sometimes called ‘Non Polynomial Time-Hard’ problems). Every day, researchers are working to improve such algorithms, since faster and better solutions can improve such algorithms and in turn help improve our daily lives.Item The vulnerability of ecosystem structure in the semi-arid area revealed by the functional trait networks(Elsevier, 2022-06) Gao, Dexin; Wang, Shuai; Wei, Fangli; Wu, Xutong; Zhou, Sha; Wang, Lixin; Li, Zidong; Chen, Peng; Fu, Bojie; Earth and Environmental Sciences, School of ScienceThe ecosystems were characterized by complex, nonlinear interactions determined by different plant functional traits. The characteristics of the multiple relationships between ecosystem functional traits affected the vulnerability to drought. A three-level network analysis on instead of the network metrics, relationships among inter-components, and essential traits was conducted in dryland ecosystems of China. The new network of functional traits included leaf, root, and biomass components was constructed to simulate different aridity conditions. Results show that the multiple relationships of functional traits that co-regulated ecosystem biomass differ along an aridity gradient. The highest network modularity and degree centrality were observed in the semi-arid ecosystems indicating low integration and high sensitivity of semi-arid ecosystems (269% and 23.7% higher than in dry sub-humid site, and 142% and 51.1% higher than arid sites). The leaf quantity strongly affected the connection between functional traits at the semi-arid zone. The semi-arid areawas found to have relatively low resistance to environmental change because of low integration and high sensitivity of the ecosystem structure at that site. An increase of degree centrality of the root traits and trade-off relationships between roots and leaves indicated greater allocation of resources by vecgetation to underground components by the arid ecosystems to increase water absorption. The study reveals the complex relationships between leaf, root, and biomass components, and the essential traits of the ecosystem. It enhanced understanding of the vulnerability of semi-arid ecosystems to environmental change.