Sensory Electrical Stimulation Improves Foot Placement during Targeted Stepping Post-Stroke

Proper foot placement is vital for maintaining balance during walking, requiring the integration of multiple sensory signals with motor commands. Disruption of brain structures post-stroke likely alters the processing of sensory information by motor centers, interfering with precision control of foot placement and walking function for stroke survivors. In this study, we examined whether somatosensory stimulation, which improves functional movements of the paretic hand, could be used to improve foot placement of the paretic limb. Foot placement was evaluated before, during, and after application of somatosensory electrical stimulation to the paretic foot during a targeted stepping task. Starting from standing, twelve chronic stroke participants initiated movement with the non-paretic limb and stepped to one of five target locations projected onto the floor with distances normalized to the paretic stride length. Targeting error and lower extremity kinematics were used to assess changes in foot placement and limb control due to somatosensory stimulation. Significant reductions in placement error in the medial–lateral direction (p = 0.008) were observed during the stimulation and post-stimulation blocks. Seven participants, presenting with a hip circumduction walking pattern, had reductions (p = 0.008) in the magnitude and duration of hip abduction during swing with somatosensory stimulation. Reductions in circumduction correlated with both functional and clinical measures, with larger improvements observed in participants with greater impairment. The results of this study suggest that somatosensory stimulation of the paretic foot applied during movement can improve the precision control of foot placement

A new human chromogranin A (CgA) immunoradiometric assay involving monoclonal antibodies raised against the unprocessed central domain (145-245)

Chromogranin A (CgA), a major protein of chromaffin granules, has been described as a potential marker for neuroendocrine tumours. Because of an extensive proteolysis which leads to a large heterogeneity of circulating fragments, its presence in blood has been assessed in most cases either by competitive immunoassays or with polyclonal antibodies. In the present study, 24 monoclonal antibodies were raised against native or recombinant human CgA. Their mapping with proteolytic peptides showed that they defined eight distinct epitopic groups which spanned two-thirds of the C-terminal part of human CgA. All monoclonal antibodies were tested by pair and compared with a reference radioimmunoassay (RIA) involving CGS06, one of the monoclonal antibodies against the 198–245 sequence. It appears that CgA C-terminal end seems to be highly affected by proteolysis and the association of C-terminal and median-part monoclonal antibodies is inadequate for total CgA assessment. Our new immunoradiometric assay involves two monoclonal antibodies, whose contiguous epitopes lie within the median 145–245 sequence. This assay allows a sensitive detection of total human CgA and correlates well with RIA because dibasic cleavage sites present in the central domain do not seem to be affected by degradation. It has been proved to be efficient in measuring CgA levels in patients with neuroendocrine tumours. © 1999 Cancer Research Campaig

Trump vs. Hillary: What went Viral during the 2016 US Presidential Election

In this paper, we present quantitative and qualitative analysis of the top retweeted tweets (viral tweets) pertaining to the US presidential elections from September 1, 2016 to Election Day on November 8, 2016. For everyday, we tagged the top 50 most retweeted tweets as supporting or attacking either candidate or as neutral/irrelevant. Then we analyzed the tweets in each class for: general trends and statistics; the most frequently used hashtags, terms, and locations; the most retweeted accounts and tweets; and the most shared news and links. In all we analyzed the 3,450 most viral tweets that grabbed the most attention during the US election and were retweeted in total 26.3 million times accounting over 40% of the total tweet volume pertaining to the US election in the aforementioned period. Our analysis of the tweets highlights some of the differences between the social media strategies of both candidates, the penetration of their messages, and the potential effect of attacks on bothComment: Paper to appear in Springer SocInfo 201

Chromogranin A, a significant prognostic factor in small cell lung cancer

Chromogranin A (CgA) is a protein present in neuroendocrine vesicles. Small cell lung cancer (SCLC) is considered a neuroendocrine tumour. It is possible to demonstrate CgA expression in SCLC by immunohistochemical methods. Since CgA is released to the circulation it might also work as a clinical tumour marker. We used a newly developed two-site enzyme-linked immunosorbent assay for CgA in plasma from 150 newly diagnosed patients with SCLC. Follow-up was for a minimum of 5 years. Thirty-seven per cent of the patients had elevated pretreatment values and the values were significantly related to stage of disease. Multivariable analysis by Cox's proportional hazard model including nine known prognostic factors disclosed performance status as the most influential prognostic factor followed by stage of disease, CgA and LDH. A simple prognostic index (PI) could be established based on these four pretreatment features. In this way the patients could be separated into three groups with significant different prognosis. The median survival and 95% confidence intervals for the three groups were as follows: 424 days (311–537), 360 days (261–459) and 174 days (105–243). © 1999 Cancer Research Campaig

Social representations and the politics of participation

Recent work has called for the integration of different perspectives into the field of political psychology (Haste, 2012). This chapter suggests that one possible direction that such efforts can take is studying the role that social representations theory (SRT) can play in understanding political participation and social change. Social representations are systems of common-sense knowledge and social practice; they provide the lens through which to view and create social and political realities, mediate people's relations with these sociopolitical worlds and defend cultural and political identities. Social representations are therefore key for conceptualising participation as the activity that locates individuals and social groups in their sociopolitical world. Political participation is generally seen as conditional to membership of sociopolitical groups and therefore is often linked to citizenship. To be a citizen of a society or a member of any social group one has to participate as such. Often political participation is defined as the ability to communicate one's views to the political elite or to the political establishment (Uhlaner, 2001), or simply explicit involvement in politics and electoral processes (Milbrath, 1965). However, following scholars on ideology (Eagleton, 1991; Thompson, 1990) and social knowledge (Jovchelovitch, 2007), we extend our understanding of political participation to all social relations and also develop a more agentic model where individuals and groups construct, develop and resist their own views, ideas and beliefs. We thus adopt a broader approach to participation in comparison to other political-psychological approaches, such as personality approaches (e.g. Mondak and Halperin, 2008) and cognitive approaches or, more recently, neuropsychological approaches (Hatemi and McDermott, 2012). We move away from a focus on the individual's political behaviour and its antecedents and outline an approach that focuses on the interaction between psychological and political phenomena (Deutsch and Kinnvall, 2002) through examining the politics of social knowledge

Two-dimensional NMR lineshape analysis

NMR titration experiments are a rich source of structural, mechanistic, thermodynamic and kinetic information on biomolecular interactions, which can be extracted through the quantitative analysis of resonance lineshapes. However, applications of such analyses are frequently limited by peak overlap inherent to complex biomolecular systems. Moreover, systematic errors may arise due to the analysis of two-dimensional data using theoretical frameworks developed for one-dimensional experiments. Here we introduce a more accurate and convenient method for the analysis of such data, based on the direct quantum mechanical simulation and fitting of entire two-dimensional experiments, which we implement in a new software tool, TITAN (TITration ANalysis). We expect the approach, which we demonstrate for a variety of protein-protein and protein-ligand interactions, to be particularly useful in providing information on multi-step or multi-component interactions

Anthromes dispaying evidence of weekly cycles in active fire data cover 70% of the global land surface

Across the globe, human activities have been gaining importance relatively to climate and ecology as the main controls on fire regimes and consequently human activity became an important driver of the frequency, extent and intensity of vegetation burning worldwide. Our objective in the present study is to look for weekly cycles in vegetation fire activity at global scale as evidence of human agency, relying on the original MODIS active fire detections at 1 km spatial resolution (MCD14ML) and using novel statistical methodologies to detect significant periodicities in time series data. We tested the hypotheses that global fire activity displays weekly cycles and that the weekday with the fewest fires is Sunday. We also assessed the effect of land use and land cover on weekly fire cycle significance by testing those hypotheses separately for the Villages, Settlements, Croplands, Rangelands, Seminatural, and Wildlands anthromes. Based on a preliminary data analysis of the daily global active fire counts periodogram, we developed an harmonic regression model for the mean function of daily fire activity and assumed a linear model for the de-seasonalized time series. For inference purposes, we used a Bayesian methodology and constructed a simultaneous 95% credible band for the mean function. The hypothesis of a Sunday weekly minimum was directly investigated by computing the probabilities that the mean functions of every weekday (Monday to Saturday) are inside the credible band corresponding to mean Sunday fire activity. Since these probabilities are small, there is statistical evidence of significantly fewer fires on Sunday than on the other days of the week. Cropland, rangeland, and seminatural anthromes, which cover 70% of the global land area and account for 94% of the active fires analysed, display weekly cycles in fire activity. Due to lower land management intensity and less strict control over fire size and duration, weekly cycles in Rangelands and Seminatural anthromes, which jointly account for 53.46% of all fires, although statistically significant are weaker than those detected in Croplandsinfo:eu-repo/semantics/publishedVersio