Existing methodologies for identifying data quality problems are typically user-centric, where data quality requirements are first determined in a top-down manner following well-established design guidelines, organizational structures and data governance frameworks. In the current data landscape, however, users are often confronted with new, unexplored datasets that they may not have any ownership of, but that are perceived to have relevance and potential to create value for them. Such repurposed datasets can be found in government open data portals, data markets and several publicly available data repositories. In such scenarios, applying top-down data quality checking approaches is not feasible, as the consumers of the data have no control over its creation and governance. Hence, data consumers-data scientists and analysts-need to be empowered with data exploration capabilities that allow them to investigate and understand the quality of such datasets to facilitate well-informed decisions on their use. This research aims to develop such an approach for discovering data quality problems using generic exploratory methods that can be effectively applied in settings where data creation and use is separated. The approach, named LANG, is developed through a Design Science approach on the basis of semiotics theory and data quality dimensions. LANG is empirically validated in terms of soundness of the approach, its repeatability and generalizability.

Understanding human population distribution on the earth at fine scales is an increasingly need to a broad range of geoscience fields, including resource allocation, transport and city planning, infectious disease assessment, disaster risk response, and climate change. Many approaches have been developed to spatially downscale census data to gridded population distribution datasets, which are preferable to integration with natural and socio-economic variables. We present a novel population downscaling approach that geographically weighted area-to-point regression kriging technique is used to downscale census data to gridded population distribution datasets with multisource geospatial and social sensing data. As a case study in Nanjing city, China we evaluated the effectiveness of the proposed population downscaling approach. The experimental results demonstrated that the proposed approach generated more accurate details of population distribution and higher accuracy than existing widely-used gridded population distribution products. Hence, the proposed population downscaling approach is a valuable option in producing gridded population distribution maps.INDEX TERMS Gridded population distribution, census data, geospatial data, social sensing data, geographically weighted area-to-point regression kriging, downscaling, geographical information science.

The pentapeptide repeat protein (PRP) superfamily, identified in 1998, has grown to nearly 39,000 sequences from over 3300 species. PRPs, recognized as having at least eight contiguous pentapeptide repeats (PRs) of a consensus pentapeptide sequence, adopt a remarkable structure, namely, a right-handed quadrilateral β-helix with four consecutive PRs forming a single β-helix coil. Adjacent coils join together to form a β-helix “tower” stabilized by β-ladders on the tower faces and type I, type II, or type IV β-turns facilitating an approximately −90° redirection of the polypeptide chain joining one coil face to the next. PRPs have been found in all branches of life, but they are predominantly found in cyanobacteria. Cyanobacteria have existed on earth for more than two billion years and are thought to be responsible for oxygenation of the earth’s atmosphere. Filamentous cyanobacteria such as Nostoc sp. strain PCC 7120 may also represent the oldest and simplest multicellular organisms known to undergo cell differentiation on earth. Knowledge of the biochemical function of these PRPs is essential to understanding how ancient cyanobacteria achieved functions critical to early development of life on earth. PRPs are predicted to exist in all cyanobacteria compartments including thylakoid and cell-wall membranes, cytoplasm, and thylakoid periplasmic space. Despite their intriguing structure and importance to understanding ancient cyanobacteria, the biochemical functions of PRPs in cyanobacteria remain almost completely unknown. The precise biochemical function of only a handful of PRPs is currently known from any organisms, and three-dimensional structures of only sixteen PRPs or PRP-containing multidomain proteins from any organism have been reported. In this review, the current knowledge of the structures and functions of PRPs is presented and discussed.

The present study aimed to explore the diagnostic values of neutrophil-lymphocyte ratio (NLR) and microRNA (miR)-141 in patients with osteoarthritis and their association with the severity of knee osteoarthritis. In total 142 patients with osteoarthritis (the study group) admitted to Shanghai TCM-Integrated Hospital, Shanghai University of TCM from January 2017 to January 2019 and 150 healthy controls (the control group) were enrolled in the present study. NLR and miR-141 in peripheral blood and their diagnostic values for osteoarthritis were compared between the two groups. The two indicators in the study group were significantly increased (P<0.001), and their combined detection had a better diagnostic value for the disease (P<0.001). Moreover, they were closely associated to the progression of the disease and were independent risk factors (P<0.001). To sum up, NLR and miR-141 were significantly increased in the peripheral blood of patients with osteoarthritis. Their combined detection exhibited a good diagnostic value for the disease and may become a potential therapeutic target osteoarthritis in the future.

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