Results from tests on the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) reference chemicals 31–50 in 67 different in vitro toxicity assays are presented in this paper as a prerequisite to in vitro/in vivo comparisons for all MEIC in vitro toxicity data in forthcoming papers, i.e. the final MEIC evaluation of the relevance of the tests. With the aim of increasing knowledge about the relative significance of some in vitro methodological factors, the strategies and methods of the preceding parts in the MEIC series (Parts II and III) were again employed to enable comparative cytotoxicity analysis of the new in vitro results presented in this paper. A principal components analysis (PCA) of the results from tests of the 20 chemicals in 67 assays demonstrated a dominating first component describing as much as 74% of the variance in the toxicity data, indicating a similar ranking of the cytotoxicities of the chemicals in most of the tests. The influence on the general variability of the results of a few, key methodological factors was also evaluated by using linear regression comparisons of the results of all pairs of methods available in the study, i.e. methods which were similar in all respects except for the factor being analysed. Results from this “random probe” analysis were: a) the cytotoxicities of 11 of the 20 chemicals increased considerably with exposure time (> 10 times over 4–168 hours); b) in general, human cell line toxicity was well predicted by cytotoxicity in animal cells; c) prediction of human cell line toxicity by most ecotoxicological tests was only fairly good; d) 14 comparisons of similar assays with different cell lines showed similar toxicities (mean R2 = 0.83); e) nine comparisons of similar assays employing different primary cultures and cell lines shared similar toxicities (mean R2 = 0.71); and f) 16 comparisons of similar assays with different growth/viability endpoints showed similar toxicities (mean R2 = 0.71). Results b, d, e and f must contribute to the PCA-documented high general similarity of the in vitro toxicity data. Results a and c, together with factors which were not analysed, such as different protocols and inter-laboratory variability of tests, could explain the 26% dissimilarity. To provide background information to the planned final MEIC evaluation of the relevance of the 61 methods in which all 50 chemicals have been tested, an additional PCA was made of the 50 chemical-61 assay in vitro database (from Parts II and III and the present paper). This supplementary PCA demonstrated an 80% similarity of results. Compared with the previous analysis of the tests of the first 30 MEIC reference chemicals (MEIC Part III), the present analysis of the tests of the last 20 MEIC chemicals indicates a somewhat higher variation in the results. Correspondingly, some deviating endpoint measurements and cell line responses were demonstrated by the pairwise comparisons in the present study. As a result, the analysis revealed a high correlation (R2 = 0.73) between the average human cell line toxicity and the results from a new protein denaturation test. These preliminary results suggest that intracellular protein denaturation may be a frequently occurring mechanism in basal cytotoxicity.

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Background Clinical guidelines recommend orthogeriatric care to improve older hip fracture patients' outcomes, but few studies have been conducted in China. This study evaluated the effects of an orthogeriatric co-management care model in six Chinese hospitals.Methods This non-randomised controlled study was designed as an exploratory trial and was conducted in 3 urban and 3 suburban hospitals. Eligible patients were aged ≥ 65 years with X-ray confirmed hip fracture and admitted to hospital within 21 days of injury. All patients received three times follow-ups within one year (1-month, 4-month and 12-month post admission). Co-management care was implemented in 1 urban hospital, while usual care continued in 5 urban and suburban hospitals. Patient demographics, pre-, peri-and post-operative information, complications and mortality were collected at baseline and follow-ups. The primary outcome was proportion of patients receiving surgery within 48 hours from ward arrival. Secondary outcomes included osteoporosis assessment, in-hospital rehabilitation, length of hospital stay, in-hospital mortality and one-year cumulative mortality.

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Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with traditional measurements. Simultaneously, artificial intelligence (AI), as an emerging interdiscipline, has a rapid development in these years. Traditional indices can't reflect the influence of the AI research outputs quickly, thus more timely altmetrics indices are needed. In this paper, we conduct four studies about altmetrics indices and AI research outputs based on the datasets collected from Altmetric.com and Scopus database. First, we provide a review of the research status in the AI field. Second, we show the AI researches that attracted the most attention. Third, we demonstrate the general effectiveness of altmetrics indices in the AI field. Last, we examine the effectiveness of altmetrics indices for different levels of AI journal papers and AI conference papers. Our results indicate that there is a rapid increase of AI publications and the public has paid more attention to AI research outputs since 2011. It is found that altmetrics indices are effective to discriminate highly cited publications and publications whose citation counts increase quickly. Among all Altmetric sub-indicators, Number of Mendeley readers is the most effective. Moreover, the results indicate that altmetrics indices are more effective in high levels of AI journal papers and AI conference papers. The main contribution of this paper is investigating the effectiveness of altmetrics indices from the perspective of different levels of publications. This study lays the foundation for further investigations about effectiveness of altmetrics indices from new perspectives, and it has important implication for the studies about the impact of social media on the scientific community.

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Wideband signals from a radio telescope have to be channelized for spectral observations or for dedispersion for pulsar observations. A polyphase filter bank is designed based on the improved weighted overlapadd (IWOLA) algorithm to achieve channelization. The IWOLA algorithm involves applying an equivalent Hilbert transform to the normal WOLA filter bank by shifting the center frequency of every sub-band by a half of the frequency bin, so that the IWOLA filter bank provides K independently output complex subbands instead of the usual K þ 1 sub-bands, reducing the subsequent processing units by one set. Performance of the proposed IWOLA filter bank is analyzed by means of MATLAB simulations. We show how the IWOLA filter bank can be used for a two-stage, high-resolution spectrometer, with a much reduced consumption of FPGA on-chip block RAM.