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Breaking down barriers
(2024)
Many researchers hesitate to provide full access to their datasets due to a lack of knowledge about research data management (RDM) tools and perceived fears, such as losing the value of one's own data. Existing tools and approaches often do not take into account these fears and missing knowledge. In this study, we examined how conversational agents (CAs) can provide a natural way of guidance through RDM processes and nudge researchers towards more data sharing. This work offers an online experiment in which researchers interacted with a CA on a self-developed RDM platform and a survey on participants’ data sharing behavior. Our findings indicate that the presence of a guiding and enlightening CA on an RDM platform has a constructive influence on both the intention to share data and the actual behavior of data sharing. Notably, individual factors do not appear to impede or hinder this effect.
Social media constitute an important arena for public debates and steady interchange of issues relevant to society. To boost their reputation, commercial organizations also engage in political, social, or environmental debates on social media. To engage in this type of digital activism, organizations increasingly utilize the social media profiles of executive employees and other brand ambassadors. However, the relationship between brand ambassadors’ digital activism and corporate reputation is only vaguely understood. The results of a qualitative inquiry suggest that digital activism via brand ambassadors can be risky (e.g., creating additional surface for firestorms, financial loss) and rewarding (e.g., emitting authenticity, employing ‘megaphones’ for industry change) at the same time. The paper informs both scholarship and practitioners about strategic trade-offs that need to be considered when employing brand ambassadors for digital activism.
Mastery is a psychological resource that is defined as the extent to which individuals perceive having control over important circumstances of their lives. Although mastery has been associated with various physical and psychological health outcomes, studies assessing its relationship with weight status and dietary behavior are lacking. The aim of this cross-sectional study was to assess the relationship between mastery and weight status, food intake, snacking, and eating disorder (ED) symptoms in the NutriNet-Sante cohort study. Mastery was measured with the Pearlin Mastery Scale (PMS) in 32,588 adults (77.45% female), the mean age was 50.04 (14.53) years. Height and weight were self-reported. Overall diet quality and food group consumption were evaluated with >= 3 self-reported 24-h dietary records (range: 3-27). Snacking was assessed with an ad-hoc question. ED symptoms were assessed with the Sick-Control-One-Fat-Food Questionnaire (SCOFF). Linear and logistic regression analyses were conducted to assess the relationship between mastery and weight status, food intake, snacking, and ED symptoms, controlling for sociodemographic and lifestyle characteristics. Females with a higher level of mastery were less likely to be underweight (OR: 0.88; 95%CI: 0.84, 0.93), overweight [OR: 0.94 (0.91, 0.97)], or obese [class I: OR: 0.86 (0.82, 0.90); class II: OR: 0.76 (0.71, 0.82); class III: OR: 0.77 (0.69, 0.86)]. Males with a higher level of mastery were less likely to be obese [class III: OR: 0.75 (0.57, 0.99)]. Mastery was associated with better diet quality overall, a higher consumption of fruit and vegetables, seafood, wholegrain foods, legumes, non-salted oleaginous fruits, and alcoholic beverages and with a lower consumption of meat and poultry, dairy products, sugary and fatty products, milk-based desserts, and sweetened beverages. Mastery was also associated with lower snacking frequency [OR: 0.89 (0.86, 0.91)] and less ED symptoms [OR: 0.73 (0.71, 0.75)]. As mastery was associated with favorable dietary behavior and weight status, targeting mastery might be a promising approach in promoting healthy behaviors.
Tula orthohantavirus (TULV) is a rodent-borne hantavirus with broad geographical distribution in Europe. Its major reservoir is the common vole (Microtus arvalis), but TULV has also been detected in closely related vole species. Given the large distributional range and high amplitude population dynamics of common voles, this host-pathogen complex presents an ideal system to study the complex mechanisms of pathogen transmission in a wild rodent reservoir. We investigated the dynamics of TULV prevalence and the subsequent potential effects on the molecular evolution of TULV in common voles of the Central evolutionary lineage. Rodents were trapped for three years in four regions of Germany and samples were analyzed for the presence of TULV-reactive antibodies and TULV RNA with subsequent sequence determination. The results show that individual (sex) and population-level factors (abundance) of hosts were significant predictors of local TULV dynamics. At the large geographic scale, different phylogenetic TULV clades and an overall isolation-by-distance pattern in virus sequences were detected, while at the small scale (<4 km) this depended on the study area. In combination with an overall delayed density dependence, our results highlight that frequent, localized bottleneck events for the common vole and TULV do occur and can be offset by local recolonization dynamics.
Simple Summary Gliomas are heterogenous types of cancer, therefore the therapy should be personalized and targeted toward specific pathways. We developed a methodology that corrected strong batch effects from The Cancer Genome Atlas datasets and estimated glioma grade-specific co-enrichment mechanisms using machine learning. Our findings created hypotheses for annotations, e.g., pathways, that should be considered as therapeutic targets. Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for gliomas is The Cancer Genome Atlas (TCGA). However, such big cohorts should be processed with caution and evaluated thoroughly as they can contain batch and other effects. Furthermore, biological mechanisms of cancer contain interactions among biomarkers. Thus, we applied an interpretable machine learning approach to discover such relationships. This type of transparent learning provides not only good predictability, but also reveals co-predictive mechanisms among features. In this study, we corrected the strong and confounded batch effect in the TCGA glioma data. We further used the corrected datasets to perform comprehensive machine learning analysis applied on single-sample gene set enrichment scores using collections from the Molecular Signature Database. Furthermore, using rule-based classifiers, we displayed networks of co-enrichment related to glioma grades. Moreover, we validated our results using the external glioma cohorts. We believe that utilizing corrected glioma cohorts from TCGA may improve the application and validation of any future studies. Finally, the co-enrichment and survival analysis provided detailed explanations for glioma progression and consequently, it should support the targeted treatment.
We present the discovery of a new double-detonation progenitor system consisting of a hot subdwarf B (sdB) binary with a white dwarf companion with a P (orb) = 76.34179(2) minutes orbital period. Spectroscopic observations are consistent with an sdB star during helium core burning residing on the extreme horizontal branch. Chimera light curves are dominated by ellipsoidal deformation of the sdB star and a weak eclipse of the companion white dwarf. Combining spectroscopic and light curve fits, we find a low-mass sdB star, M (sdB) = 0.383 +/- 0.028 M (circle dot) with a massive white dwarf companion, M (WD) = 0.725 +/- 0.026 M (circle dot). From the eclipses we find a blackbody temperature for the white dwarf of 26,800 K resulting in a cooling age of approximate to 25 Myr whereas our MESA model predicts an sdB age of approximate to 170 Myr. We conclude that the sdB formed first through stable mass transfer followed by a common envelope which led to the formation of the white dwarf companion approximate to 25 Myr ago. Using the MESA stellar evolutionary code we find that the sdB star will start mass transfer in approximate to 6 Myr and in approximate to 60 Myr the white dwarf will reach a total mass of 0.92 M (circle dot) with a thick helium layer of 0.17 M (circle dot). This will lead to a detonation that will likely destroy the white dwarf in a peculiar thermonuclear supernova. PTF1 J2238+7430 is only the second confirmed candidate for a double-detonation thermonuclear supernova. Using both systems we estimate that at least approximate to 1% of white dwarf thermonuclear supernovae originate from sdB+WD binaries with thick helium layers, consistent with the small number of observed peculiar thermonuclear explosions.
The aim of this study was to investigate the effects of listening to preferred music during a warm up or exercise, on performance during a 6-min all-out exercise test (6-MT) in young adult males. Twenty-five healthy males volunteered to participate in this study. Following a within subject design, participants performed three test conditions (MDT: music during the test; MDW: music during the warm-up; WM: without music) in random order. Outcomes included mean running speed over the 6-min test (MRS6), total distance covered (TDC), heart rate responses (HRpeak, HRmean), blood lactate (3-min after the test), and the rating of perceived exertion (RPE); additionally, feeling scale scores were recorded. Listening to preferred music during running resulted in significant TDC (Delta up arrow 10%, p=0.006, ES=0.80) and MRS6 (Delta up arrow 14%, p=0.012, ES=1.02) improvement during the 6-MT, improvement was also noted for the warm-up with music condition (TDC:Delta up arrow 8%, p=0.028, ES=0.63; MRS6:Delta up arrow 8%, p=0.032, ES=0.61). A similar reverse "J-shaped" pacing profile was detected during the three conditions. Blood lactate was lower in the MDT condition by 8% (p=0.01, ES=1.10), but not the MDW condition, compared to MW. In addition, no statistically significant differences were found between the test sessions for the HR, RPE, and feeling scale scores. In conclusion, listening to music during exercise testing would be more beneficial for optimal TDC and MRS6 performances compared to MDW and WM.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
The study addresses the question, if observed changes in terms of Arctic-midlatitude linkages during winter are driven by Arctic Sea ice decline alone or if the increase of global sea surface temperatures plays an additional role. We compare atmosphere-only model experiments with ECHAM6 to ERA-Interim Reanalysis data. The model sensitivity experiment is implemented as a set of four combinations of sea ice and sea surface temperature boundary conditions. Atmospheric circulation regimes are determined and evaluated in terms of their cyclone and blocking characteristics and changes in frequency during winter. As a prerequisite, ECHAM6 reproduces general features of circulation regimes very well. Tropospheric changes induced by the change of boundary conditions are revealed and further impacts on the large-scale circulation up into the stratosphere are investigated. In early winter, the observed increase of atmospheric blocking in the region between Scandinavia and the Urals are primarily related to the changes in sea surface temperatures. During late winter, we f nd a weakened polar stratospheric vortex in the reanalysis that further impacts the troposphere. In the model sensitivity study a climatologically weakened polar vortex occurs only if sea ice is reduced and sea surface temperatures are increased together. This response is delayed compared to the reanalysis. The tropospheric response during late winter is inconclusive in the model, which is potentially related to the weak and delayed response in the stratosphere. The model experiments do not reproduce the connection between early and late winter as interpreted from the reanalysis. Potentially explaining this mismatch, we identify a discrepancy of ECHAM6 to reproduce the weakening of the stratospheric polar vortex through blocking induced upward propagation of planetary waves.
The capillary-venous pathology cerebral cavernous malformation (CCM) is caused by loss of CCM1/Krev interaction trapped protein 1 (KRIT1), CCM2/MGC4607, or CCM3/PDCD10 in some endothelial cells. Mutations of CCM genes within the brain vasculature can lead to recurrent cerebral hemorrhages. Pharmacological treatment options are urgently needed when lesions are located in deeply-seated and in-operable regions of the central nervous system. Previous pharmacological suppression screens in disease models of CCM led to the discovery that treatment with retinoic acid improved CCM phenotypes. This finding raised a need to investigate the involvement of retinoic acid in CCM and test whether it has a curative effect in preclinical mouse models. Here, we show that components of the retinoic acid synthesis and degradation pathway are transcriptionally misregulated across disease models of CCM. We complemented this analysis by pharmacologically modifying retinoic acid levels in zebrafish and human endothelial cell models of CCM, and in acute and chronic mouse models of CCM. Our pharmacological intervention studies in CCM2-depleted human umbilical vein endothelial cells (HUVECs) and krit1 mutant zebrafish showed positive effects when retinoic acid levels were increased. However, therapeutic approaches to prevent the development of vascular lesions in adult chronic murine models of CCM were drug regiment-sensitive, possibly due to adverse developmental effects of this hormone. A treatment with high doses of retinoic acid even worsened CCM lesions in an adult chronic murine model of CCM. This study provides evidence that retinoic acid signaling is impaired in the CCM pathophysiology and suggests that modification of retinoic acid levels can alleviate CCM phenotypes.