Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the TNFα-Induced Apoptosis Pathway in Hepatocytes

The proinflammatory cytokine TNFα fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Recently, we showed that TNFα is able to sensitize primary murine hepatocytes cultured on collagen to Fas ligand-induced apoptosis and presented a mathematical model of the sensitizing effect. Here, we analyze how TNFα induces apoptosis in combination with the transcriptional inhibitor actinomycin D (ActD). Accumulation of reactive oxygen species (ROS) in response to TNFR activation turns out to be critical for sustained activation of JNK which then triggers mitochondrial pathway-dependent apoptosis. In addition, the amount of JNK is strongly upregulated in a ROS-dependent way. In contrast to TNFα plus cycloheximide no cFLIP degradation is observed suggesting a different apoptosis pathway in which the Itch-mediated cFLIP degradation and predominantly caspase-8 activation is not involved. Time-resolved data of the respective pro- and antiapoptotic factors are obtained and subjected to mathematical modeling. On the basis of these data we developed a mathematical model which reproduces the complex interplay regulating the phosphorylation status of JNK and generation of ROS. This model was fully integrated with our model of TNFα/Fas ligand sensitizing as well as with a published NF-κB-model. The resulting comprehensive model delivers insight in the dynamical interplay between the TNFα and FasL pathways, NF-κB and ROS and gives an example for successful model integration.
Rubella Seromarkers and Determinants of Infection among Tanzanian Children and Adolescents in Prevaccination Era: Are We in the Right Track?

Background: The World health organization advocates assessment of the burden of rubella and congenital rubella syndrome (CRS) by seroepidemiological surveys and surveillance programs in all countries without vaccination programs. Due to scarcity of data in developing countries, this study was conducted to assess the seromakers for natural rubella infection in Tanzania during prevaccination era so as to ascertain the gaps for future research and prevention strategies. Methods: A cross-sectional study was conducted between September and October 2014. Indirect enzyme-linked immunosorbent assay was used to detect rubella IgG and IgM antibodies. STATA version 11 was used to perform data analysis. Results: Of 723 enrolled participants, 368 (50.8%) and 94 (13%) were positive for specific IgG and IgM rubella antibodies, respectively. On multivariable logistic regression analysis, significant determinants of rubella IgG seropositivity were increase in age (odds ratios [OR]: 1.24, 95% confidence interval [CI]: 1.18–1.29, P < 0.001), low socioeconomic status (SES) (OR: 2.38, 95% CI: 1.1.23–4.50, P = 0.010), and absence of rash (OR: 4.34, 95% CI: 1.1.17–15.3, P = 0.027), while only the presence of rashes was significant determinant of rubella IgM seropositivity (OR: 2.5, 95%; 1.07–5.98, P = 0.034). Significantly higher mean IgG titers were observed in population ≥10 years (P < 0.001), those residing in urban and peri-urban areas (P < 0.001), those from employed mothers (P = 0.018), and those with no current history of fever (P = 0.018). Conclusions: The prevalence of specific rubella IgG antibodies in Tanzania is high and is associated with increase in age, absence of rash, and low SES. Results suggest a need to reconsider upper age limit for vaccination campaigns in developing countries. Screening and vaccinating women may be cost-effective campaign to prevent CRS in developing countries.
IRB Problems and Solutions in Health Communication Research

ABSTRACT In this article, we contribute to the current literature on the difficulties that social scientists encounter with IRBs, but with a focus on the distinct challenges that health communication scholars face in dealing with IRBs at their own institutions and elsewhere. Although health communication researchers, like other communication researchers, can expect to face many of the same challenges that their social science colleagues face during the IRB process, the researcher narratives we present in this article suggest that health communication research presents some distinct challenges because the communication interactions that we investigate occur in highly protected, private spaces, including the medical exam room, online patient forums, and electronic health records. To that end, we present a series of examples in which health communication researchers were able to find solutions or workarounds to the challenges they faced in gaining IRB approval for their research. In every case that we present, the researcher had to revise her initial study design to get around the constraints imposed by IRB requirements, and in every case, the researcher reports having experienced points of incommensurability similar to those reported by many other social scientists. In some situations, investigators even express frustration that the IRB’s needs and demands superseded those of healthcare professionals and the patients whom they serve. Additionally, in some situations, investigators’ understandings of human subjects’ protection actually go further to protect patients’ privacy and confidentiality than the IRB required. But, in all four cases that we present, the health communication research was ultimately successful.
Sparse NMF – half-baked or well done?

Non-negative matrix factorization (NMF) has been a popular method for modeling audio signals, in particular for single-channel source separation. An important factor in the success of NMF-based algorithms is the ”quality” of the basis functions that are obtained from training data. In order to model rich signals such as speech or wide ranges of non-stationary noises, NMF typically requires using a large number of basis functions. However, without additional constraints, using a large number of bases leads to trivial solutions where the bases can indis-criminately model any signal. Two main approaches have been considered to cope with this issue: introducing sparsity on the activation coeﬃcients, or skipping training altogether and randomly selecting basis functions as a subset of the training data (”exemplarbased NMF”). Surprisingly, the sparsity route is widely regarded as leading to similar or worse results than the simple and extremely eﬃcient (no training! ) exemplar-based approach. Only a small fraction of researchers have realized that sparse NMF works well if implemented correctly. However, to our knowledge, no thorough comparison has been presented in the literature, and many researchers in the ﬁeld may remain unaware of this fact. We review exemplar-based NMF as well as two versions of sparse NMF, a simplistic ad hoc one and a principled one, giving a detailed derivation of the update equations for the latter in the general case of beta divergences, and we perform a thorough comparison of the three methods on a speech separation task using the 2nd CHiME Speech Separation and Recognition Challenge dataset. Results show that, contrary to a popular belief in the community, learning basis functions us-ing NMF with sparsity, if done the right way, leads to signiﬁcant gains in source-to-distortion ratio with respect to both exemplar-based NMF and the ad hoc implementation of sparse NMF.
Molecular and Physiological Diversity of Cortical Nonpyramidal Cells

The physiological and molecular features of nonpyramidal cells were investigated in acute slices of sensory-motor cortex using whole-cell recordings combined with single-cell RT-PCR to detect simultaneously the mRNAs of three calcium binding proteins (calbindin D28k, parvalbumin, and calretinin) and four neuropeptides (neuropeptide Y, vasoactive intestinal polypeptide, somatostatin, and cholecystokinin). In the 97 neurons analyzed, all expressed mRNAs of at least one calcium binding protein, and the majority (n = 73) contained mRNAs of at least one neuropeptide. Three groups of nonpyramidal cells were defined according to their firing pattern. (1) Fast spiking cells (n = 34) displayed tonic discharges of fast action potentials with no accommodation. They expressed parvalbumin (n = 30) and/or calbindin (n = 19) mRNAs, and half of them also contained transcripts of at least one of the four neuropeptides. (2) Regular spiking nonpyramidal cells (n = 48) displayed a firing behavior characterized by a marked accommodation and presented a large diversity of expression patterns of the seven biochemical markers. (3) Finally, a small population of vertically oriented bipolar cells, termed irregular spiking cells (n = 15), fired bursts of action potentials at an irregular frequency. They consistently co-expressed calretinin and vasoactive intestinal polypeptide. Additional investigations of these cells showed that they also co-expressed glutamic acid decarboxylase and choline acetyl transferase. Our results indicate that neocortical nonpyramidal neurons display a large diversity in their firing properties and biochemical patterns of co-expression and that both characteristics could be correlated to define discrete subpopulations.
Reduced Bacterial Colony Count of Anaerobic Bacteria Is Associated with a Worsening in Lung Clearance Index and Inflammation in Cystic Fibrosis

Anaerobic bacteria have been identified in abundance in the airways of cystic fibrosis (CF) subjects. The impact their presence and abundance has on lung function and inflammation is unclear. The aim of this study was to investigate the relationship between the colony count of aerobic and anaerobic bacteria, lung clearance index (LCI), spirometry and C-Reactive Protein (CRP) in patients with CF. Sputum and blood were collected from CF patients at a single cross-sectional visit when clinically stable. Community composition and bacterial colony counts were analysed using extended aerobic and anaerobic culture. Patients completed spirometry and a multiple breath washout (MBW) test to obtain LCI. An inverse correlation between colony count of aerobic bacteria (n = 41, r = -0.35; p = 0.02), anaerobic bacteria (n = 41, r = -0.44, p = 0.004) and LCI was observed. There was an inverse correlation between colony count of anaerobic bacteria and CRP (n = 25, r = -0.44, p = 0.03) only. The results of this study demonstrate that a lower colony count of aerobic and anaerobic bacteria correlated with a worse LCI. A lower colony count of anaerobic bacteria also correlated with higher CRP levels. These results indicate that lower abundance of aerobic and anaerobic bacteria may reflect microbiota disruption and disease progression in the CF lung.
Mediterranean diet impact on changes in abdominal fat and 10-year incidence of abdominal obesity in a Spanish population

Abdominal obesity is a strong predictor of metabolic disorders. Prospective data on the association between the Mediterranean diet and surrogate markers of abdominal adiposity are scarce. The present study evaluated the relationship between adherence to the Mediterranean diet and (1) changes in waist circumference (WC) and (2) 10-year incidence of abdominal obesity. We conducted a prospective, population-based study in 3058 male and female Spaniards aged 25–74 years, followed from 2000 to 2009. Dietary intake and leisure-time physical activity levels were recorded using validated questionnaires. Weight, height and WC were measured. Adherence to the Mediterranean diet, determined using the previously validated REGICOR-Mediterranean diet score (R-MDS), based on the distribution of population food intake and on the dietary recommendations (MDS-rec), was negatively associated with WC gain (P= 0·007 and 0·024, respectively) in fully adjusted models. In the multivariate logistic analysis, the odds of abdominal obesity incidence decreased across the tertiles of the R-MDS, but the association was not significant. In conclusion, adherence to the Mediterranean diet was associated with lower abdominal fat gain, but not with 10-year incidence of abdominal obesity.
Perturbation centrality: a novel centrality measure obtained by the general network dynamics tool, Turbine

Analysis of network dynamics became increasingly important to understand the mechanisms and consequences of changes in biological systems from macromolecules to cells and organisms. Currently available network dynamics tools are mostly tailored for specific tasks such as calculation of molecular or neural dynamics. Our Turbine software offers a generic framework enabling the simulation of any algorithmically definable dynamics of any network. Turbine is also optimized for handling very large networks in the range of millions of nodes and edges. Using a perturbation transmission model inspired by communicating vessels, here we introduce a novel centrality measure termed as perturbation centrality. Perturbation centrality is the reciprocal of the time needed to dissipate a starting perturbation in the network. Hubs and inter-modular nodes proved to be highly efficient in perturbation propagation. High perturbation centrality nodes of the Met-tRNA synthetase protein structure network were identified as amino acids involved in substrate binding and allosteric communication by earlier studies. Changes in perturbation centralities of yeast protein-protein interaction network nodes upon various stresses well recapitulated the functional changes of stressed yeast cells. The Turbine software and the perturbation centrality measure provide a large variety of novel options for future studies on network robustness, signaling mechanisms and drug design.
Community composition of bacterial biofilms on two submerged macrophytes and an artificial substrate in a pre-alpine lake

We compared the heterotrophic community composition of bacterial biofilms on the sub- merged macrophytes Myriophyllum spicatum and Potamogeton perfoliatus and on an artificial sur- face in Lower Lake Constance (Germany) on spatial (plant age) and temporal scales using denatur- ing gradient gel electrophoresis (DGGE) and fluorescence in situ hybridization (FISH). M. spicatum contains polyphenolic allelochemicals that inhibit algae, cyanobacteria, and heterotrophic bacteria, and possibly influence the community composition, whereas P. perfoliatus does not. In 2005, the com- munity composition of bacterial biofilms on apices and leaves of M. spicatum differed significantly. In 2006, the biofilm communities on the apices or leaves of M. spicatum and P. perfoliatus and the arti- ficial surface did not differ significantly, although all except one apex sample of M. spicatum formed a distinct cluster based on DGGE banding patterns. On all surfaces, members of the Cytophaga- Flavobacter-Bacteroidetes (CFB) group (16 to 22%), Alphaproteobacteria (19%), and Betaproteo- bacteria (7 to 31%) were abundant; Actinobacteria and Planctomycetes occurred less frequently. Sequences of DNA fragments excised from DGGE gels were mainly affiliated with yet uncultured clones originating from various freshwater habitats. Several sequences were from bacteria capable of degrading phenolic and aromatic compounds. The chemical composition of the 2 plant species and of the different parts of M. spicatum differed up to an order of magnitude. Differences in the biofilm community composition mainly depended on environmental factors (water level, conductivity, tem- perature, pH) and the plant chemical composition, especially the carbon and total phenolic content. Our results suggest that the biofilm community on M. spicatum apices is related to specific bacterial functions in this microenvironment.
Predicting Object Dynamics in Scenes

Given a static scene, a human can trivially enumerate the myriad of things that can happen next and characterize the relative likelihood of each. In the process, we make use of enormous amounts of commonsense knowledge about how the world works. In this paper, we investigate learning this commonsense knowledge from data. To overcome a lack of densely annotated spatiotemporal data, we learn from sequences of abstract images gathered using crowd-sourcing. The abstract scenes provide both object location and attribute information. We demonstrate qualitatively and quantitatively that our models produce plausible scene predictions on both the abstract images, as well as natural images taken from the Internet.
Cycle transversals in bounded degree graphs

In this work we investigate the algorithmic complexity of computing a minimum C(k)-transversal, i.e., a subset of vertices that intersects all the chordless cycles with k vertices of the input graph, for a fixed k \textgreater= 3. For graphs of maximum degree at most three, we prove that this problem is polynomial-time solvable when k \textless= 4, and NP-hard otherwise. For graphs of maximum degree at most four, we prove that this problem is NP-hard for any fixed k \textgreater= 3. We also discuss polynomial-time approximation algorithms for computing C(3)-transversals in graphs of maximum degree at most four, based on a new decomposition theorem for such graphs that leads to useful reduction rules.
Identification of Climatic Factors Affecting the Epidemiology of Human West Nile Virus Infections in Northern Greece

Climate can affect the geographic and seasonal patterns of vector-borne disease incidence such as West Nile Virus (WNV) infections. We explore the association between climatic factors and the occurrence of West Nile fever (WNF) or West Nile neuro-invasive disease (WNND) in humans in Northern Greece over the years 2010–2014. Time series over a period of 30 years (1979–2008) of climatic data of air temperature, relative humidity, soil temperature, volumetric soil water content, wind speed, and precipitation representing average climate were obtained utilising the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-Interim) system allowing for a homogeneous set of data in time and space. We analysed data of reported human cases of WNF/WNND and Culex mosquitoes in Northern Greece. Quantitative assessment resulted in identifying associations between the above climatic variables and reported human cases of WNF/WNND. A substantial fraction of the cases was linked to the upper percentiles of the distribution of air and soil temperature for the period 1979–2008 and the lower percentiles of relative humidity and soil water content. A statistically relevant relationship between the mean weekly value climatic anomalies of wind speed (negative association), relative humidity (negative association) and air temperature (positive association) over 30 years, and reported human cases of WNF/WNND during the period 2010–2014 could be shown. A negative association between the presence of WNV infected Culex mosquitoes and wind speed could be identified. The statistically significant associations could also be confirmed for the week the WNF/WNND human cases appear and when a time lag of up to three weeks was considered. Similar statistically significant associations were identified with the weekly anomalies of the maximum and minimum values of the above climatic factors. Utilising the ERA-Interim re-analysis methodology it could be shown that besides air temperature, climatic factors such as soil temperature, relative humidity, soil water content and wind speed may affect the epidemiology of WNV.
Limited capacity to lie: Cognitive load interferes with being dishonest

The current study tested the boundary conditions of ethical decision-making by increasing cognitive load. This manipulation is believed to hinder deliberation, and, as we argue, reduces the cognitive capacity needed for a self-serving bias to occur. As telling a lie is believed to be more cognitively taxing than telling the truth, we hypothesized that participants would be more honest under high cognitive load than low cognitive load. 173 participants anonymously rolled a die three times and reported their outcomes — of which one of the rolls would be paid out — while either under high or low cognitive load. For the roll that determined pay, participants under low cognitive load, but not under high cognitive load, reported die rolls that were significantly different from a uniform (honest) distribution. The reported outcome of this roll was also significantly higher in the low load condition than in the high load condition, suggesting that participants in the low load condition lied to get higher pay. This pattern was not observed for the second and third roll where participants knew the rolls were not going to be paid out and where therefore lying would not serve self-interest. Results thus indicate that having limited cognitive capacity will unveil a tendency to be honest in a situation where having more cognitive capacity would have enabled one to serve self-interest by lying.
"Selfish spermatogonial selection": a novel mechanism for the association between advanced paternal age and neurodevelopmental disorders.

There is robust evidence from epidemiological studies that the offspring of older fathers have an increased risk of neurodevelopmental disorders, such as schizophrenia and autism. The authors present a novel mechanism that may contribute to this association. Because the male germ cell undergoes many more cell divisions across the reproductive age range, copy errors taking place in the paternal germline are associated with de novo mutations in the offspring of older men. Recently it has been recognized that somatic mutations in male germ cells that modify proliferation through dysregulation of the RAS protein pathway can lead to within-testis expansion of mutant clonal lines. First identified in association with rare disorders related to paternal age (e.g., Apert syndrome, achondroplasia), this process is known as "selfish spermatogonial selection. " This mechanism favors propagation of germ cells carrying pathogenic mutations, increasingly skews the mutational profile of sperm as men age, and enriches de novo mutations in the offspring of older fathers that preferentially affect specific cellular signaling pathways. This mechanism not only offers a parsimonious explanation for the association between advanced paternal age and various neurodevelopmental disorders but also provides insights into the genetic architecture (role of de novo mutations), neurobiological correlates (altered cell cycle), and some epidemiological features of these disorders. The authors outline hypotheses to test this model. Given the secular changes for delayed parenthood in most societies, this hypothesis has important public health implications.