Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational modelling of biological systems: tools and visions

We are currently witnessing the advent of a revolutionary new tool for biomedical research. Complex biochemically, biophysically and pharmacologically detailed mathematical models of ‘living cells’ are being arranged in morphologically representative tissue assemblies, and, using large–scale supercomputers, utilized to produce anatomically structured models of integrated tissue and organ function. This provides biomedical sciences with a radical new tool: ‘in silico’ organs, organ systems and, ultimately, organisms. In silico models will be a crucial tool for biomedical research and development in the new millennium, extracting knowledge from the vast amount of increasingly detailed data, and integrating this into a comprehensive analytical description of biological function with predictive power: the Physiome. Our review will illustrate this approach using the example of the cardiovascular system, which, along with neurophysiology, has been at the forefront of analytical bio–mathematical modelling for many years, and which is about to deliver the first anatomico–physiological model of a whole organ. Already, electrophysiologically detailed cardiac cell models have been incorporated into mathematical descriptions of representative ventricular tissue architecture and anatomy, including the coronary vasculature, and assimilated to realistic representation of ventricular active and passive mechanical properties. This is being extended by matching atrial models and linked to an artificial torso to compute the body surface electrocardiogram as a function of sub–cellular activity during various (patho–)physiological conditions. We will illustrate the utility of in silico biological research in the context of refinement and partial replacement of in vivo and in vitro experimental work, show the potential of this approach for devising patient–specific treatment strategies, and try to forecast the impact of this new technology on biomedical research, health–care, and related industries.
Using Forest Cover Maps and Local People’s Perceptions to Evaluate the Effectiveness of Community-based Ecotourism for Forest Conservation in Chambok (Cambodia)

Summary Increasing attention has been given to evaluating the effectiveness of forest conservation projects, but it is not well known whether different methods yield similar results when evaluating changes in forest resources. The present study compares forest cover maps and local people’s perceptions for evaluating the effectiveness of the Chambok community-based ecotourism (CBET) programme in Cambodia. We assessed forest cover changes from 2000 to 2012 using published global maps and used a covariate matching method to compare forest sites in CBET and non-CBET areas. We also analysed local people’s perceptions of forest resource changes by interviewing 174 households. The forest cover maps showed that the Chambok CBET was effective at reducing deforestation, although the outcome was not completely robust to unobserved heterogeneity. Local people’s perceptions concurred with the effectiveness observed in the forest cover maps, in that 64% of the people perceived that forest resources increased and 75% thought that the local community could protect its own forest resources. We conclude that the Chambok CBET performed effectively for forest conservation and suggest that mixed-method approaches are essential for evaluating the effectiveness of conservation programmes.
On the Necessity of Recurrent Processing during Object Recognition: It Depends on the Need for Scene Segmentation

Although feedforward activity may suffice for recognizing objects in isolation, additional visual operations that aid object recognition might be needed for real-world scenes. One such additional operation is figure-ground segmentation, extracting the relevant features and locations of the target object while ignoring irrelevant features. In this study of 60 human participants (female and male), we show objects on backgrounds of increasing complexity to investigate whether recurrent computations are increasingly important for segmenting objects from more complex backgrounds. Three lines of evidence show that recurrent processing is critical for recognition of objects embedded in complex scenes. First, behavioral results indicated a greater reduction in performance after masking objects presented on more complex backgrounds, with the degree of impairment increasing with increasing background complexity. Second, electroencephalography (EEG) measurements showed clear differences in the evoked response potentials between conditions around time points beyond feedforward activity, and exploratory object decoding analyses based on the EEG signal indicated later decoding onsets for objects embedded in more complex backgrounds. Third, deep convolutional neural network performance confirmed this interpretation. Feedforward and less deep networks showed a higher degree of impairment in recognition for objects in complex backgrounds compared with recurrent and deeper networks. Together, these results support the notion that recurrent computations drive figure-ground segmentation of objects in complex scenes. SIGNIFICANCE STATEMENT The incredible speed of object recognition suggests that it relies purely on a fast feedforward buildup of perceptual activity. However, this view is contradicted by studies showing that disruption of recurrent processing leads to decreased object recognition performance. Here, we resolve this issue by showing that how object recognition is resolved and whether recurrent processing is crucial depends on the context in which it is presented. For objects presented in isolation or in simple environments, feedforward activity could be sufficient for successful object recognition. However, when the environment is more complex, additional processing seems necessary to select the elements that belong to the object and by that segregate them from the background.
Working Memory Capacities Neurally Dissociate: Evidence from Acute Stroke

Substantial behavioral evidence implies the existence of separable working memory (WM) components for maintaining phonological and semantic information. In contrast, only a few studies have addressed the neural basis of phonological vs. semantic WM using functional neuroimaging and none has used a lesion-symptom mapping (LSM) approach. Here we address this gap, reporting a multivariate LSM study of phonological and semantic WM for 94 individuals at the acute stage of left hemisphere stroke. Testing at the acute stage avoids issues of brain reorganization and the adoption of patient strategies for task performance. The LSM analyses for each WM component controlled for the other WM component and semantic and phonological knowledge at the single word level. For phonological WM, the regions uncovered included the supramarginal gyrus, argued to be the site of phonological storage, and several cortical and subcortical regions plausibly related to inner rehearsal. For semantic WM, inferior frontal regions and the angular gyrus were uncovered. The findings thus provide converging evidence for separable systems for phonological and semantic WM that are distinguished from the systems supporting long-term knowledge representations in those domains.
Decomposing the role of alpha oscillations during brain maturation

Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body of literature investigated neurophysiological changes during brain maturation by focusing on the most dominant feature of the human EEG signal: the alpha oscillation. Ambiguous results were reported for the developmental trajectory of the power of the alpha oscillation. Simulations in this study show that conventional measures of alpha power are confounded by various factors and need to be decomposed into periodic and aperiodic components, which represent distinct underlying brain mechanisms. It is therefore unclear how each part of the signal relates to changes during brain maturation. Using multivariate Bayesian generalized linear mixed models, we examined aperiodic and periodic parameters of alpha activity in the largest openly available pediatric dataset (N=2529, age range 5-21 years) and replicated these findings in a preregistered analysis of an independent validation sample (N=369, age range 6–21yrs). First, the well documented age-related decrease in total alpha power was replicated. However, when controlling for the aperiodic signal component, our findings provide strong evidence for a reversed developmental trajectory of the periodic alpha power, whereas the aperiodic signal components, slope and offset, decreased. Consequently, earlier interpretations on age related changes of alpha power need to be fundamentally reconsidered, incorporating changes in the aperiodic signal. The interpretation of decreased total alpha power as elimination of active synapses rather links to decreases in the aperiodic intercept. Instead, additional analyses of diffusion tensor imaging data indicate that the maturational increase in periodic alpha power is related to increased thalamocortical connectivity. Functionally, our results suggest that increased thalamic control of cortical alpha power is linked to improved attentional performance during brain maturation.
A combined flow injection/reversed phase chromatography – high resolution mass spectrometry workflow for accurate absolute lipid quantification with 13C- internal standards

We propose a fully automated novel workflow for lipidomics based on flow injection-followed by liquid chromatography high resolution mass spectrometry (FI/LC-HRMS). The workflow combined in-depth characterization of the lipidome achieved via reversed phase LC-HRMS with absolute quantification as obtained by a high number of lipid species-specific- and/or retention time (RT) matched/class-specific calibrants. The lipidome of 13C labelled yeast (LILY) provided a cost efficient, large panel of internal standards covering triacylglycerols (TG), steryl esters (SE), free fatty acids (FA), diacylglycerols (DG), sterols (ST), ceramides (Cer), hexosyl ceramides (HexCer), phosphatidylglycerols (PG), phosphatidylethanolamines (PE), phosphatidic acids (PA), cardiolipins (CL), phosphatidylinositols (PI), phosphatidylserines (PS), phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). In order to exploit the full potential of isotopically enriched biomass, LILY was absolutely quantified on demand via reversed isotope dilution analysis using FI-HRMS. Subsequent LC-HRMS analysis integrated different calibration strategies including lipid species-specific standards for >90 lipids. Extensive measures on quality control allowed to rank the calibration strategies and to automatically selected the calibration strategy of highest metrological order for the respective lipid species. Overall, the workflow enabled a streamlined analysis pipeline (identification and quantification in separate analytical runs) and provided validation tools together with absolute concentration values for >350 lipids in human plasma on a species level with an analytical run-time of less than 25 min per sample. TOC
Swimming, fast and slow: strategy and survival of bacterial predators in response to chemical cues

Bdellovibrio bacteriovorus is a predatory bacterium that preys upon gram-negative bacteria. As such, B. bacteriovorus has the potential to control antibiotic-resistant pathogens and biofilm populations. To survive and reproduce, B. bacteriovorus must locate and infect a host cell. However, in the temporary absence of prey, it is largely unknown how B. bacteriovorus modulate their motility patterns in response to physical or chemical environmental cues to optimize their energy expenditure. To investigate B. bacteriovorus’ predation strategy, we track and quantify their motion by measuring speed distributions and velocity autocorrelations as a function of starvation time. An initial unimodal speed distribution, relaxing to that expected for pure diffusion at long times, may be expected. Instead, we observe a complex, non-Brownian, search strategy as evidenced by distinctly bimodal speed distributions. That is, for an increasing amount of time over which B. bacteriovorus is starved, we observe a progressive re-weighting from a fast mode to a slow mode in the speed distribution obtained over consecutive frames. By contrast to its predator, B. bacteriovorus’ prey, Escherichia coli exhibits almost immediate decrease to a speed expected from passive diffusion following resuspension from rich to poor media. Distributions of trajectory-averaged speeds for B. bacteriovorus are largely unimodal, indicating nontrivial switching between fast and slow swimming modes within individual observed trajectories rather than there being distinct fast and slow populations. We also find that B. bacteriovorus’ slow speed mode is not merely caused by the diffusion of inviable bacteria as subsequent spiking experiments show that bacteria can be resuscitated and bimodality restored. Indeed, starved B. bacteriovorus may modulate the frequency and duration of active swimming as a means of balancing energy consumption and procurement. Our results are evidence of a nontrivial predation strategy, which contrasts with the comparatively simple search pattern of its prey, in response to environmental cues. SIGNIFICANCE Bdellovibrio bacteriovorus is a predatory bacterium that is poised to help control gram-negative bacterial populations in environmental and clinical settings. In order to locate its prey in solution, B. bacteriovorus must expend energy in order to fight hydrodynamic drag. This raises the question as to how B. bacteriovorus should expend its energy reserves in the absence of chemical cues from its prey. Here, we show that B. bacteriovorus adapts its motility to minimize energy expenditure (due to fighting drag in swimming) upon prolonged starvation by exploiting two modes of motility. This is in sharp contrast to its prey, E. coli, which shows little active motility under starvation conditions.
Varying richness need not imply non-random species co-occurrence: implications for specifying null models

Background Non-random species co-occurrence is of fundamental interest to ecologists. One approach to analysing non-random patterns is null modelling. This involves calculation of a metric for the observed dataset, and comparison to a distribution obtained by repeatedly randomising the data. Choice of randomisation algorithm, specifically whether null model species richness is fixed at that of the observed dataset, is likely to affect model results. This is particularly important in cases when there is high variation in species richness between sampling units in the observed data. Methods Here I demonstrate the effects of accounting for variation in species richness. I use the C-score, a metric measuring species segregation as “checkerboard units”, applied to 289 datasets. First, I run null models in which sites are equally likely to be occupied (fixed-equiprobable algorithm). I do this both for the original datasets, and for the same datasets where occurrences are randomised with the species richness distribution fixed (pre-randomised datasets). Second, I run null models that fix site species richness to that observed (fixed-fixed algorithm). Results For real datasets, using the fixed-equiprobable algorithm (sites are equally likely to be colonised), C-score standardised effect size (SES) was positively related to variability in species richness between sites within a dataset. This effect was also found for pre-randomised datasets, indicating that variability in species richness can be exclusively responsible for detection of non-random species co-occurrence. When using the fixed-fixed algorithm (richness is constrained to that of real sites), there was no relationship between SES and variability in species richness. There was also a reverse in the effect direction, with 94% of significant tests indicating a lower C-score than expected for the fixed-equiprobable algorithm, but 98% of significant tests indicating a higher C-score than expected for the fixed-fixed algorithm. Discussion I speculate that when variation in species richness is high, fewer checkerboard units are possible, regardless of segregation between species. Therefore, use of fixed-equiprobable algorithms in situations where real species richness is highly variable between sites within a dataset will yield significant results, even if species co-occur randomly within the constraints of the species richness distribution. Consequently, use of such tests makes the a priori assumption that high within-dataset variation in species richness indicates non-random species co-occurrence. I recommend using algorithms that explicitly take into account species richness distributions when one wants to eliminate the effect of richness variation in terms of producing significant but spurious positive co-occurrence results. Alternatively, non-null mechanistic models can be created, in which hypothesised species assembly processes must be explicitly stated and tested.
Temperature affects the repeatability of evolution in the microbial eukaryote Tetrahymena thermophila

Evolutionary biologists have long sought to understand what factors affect the repeatability of adaptive outcomes. To better understand the role of temperature in determining the repeatability of adaptive trajectories, we evolved populations of different genotypes of the ciliate Tetrahymena thermophila at low and high temperatures and followed changes in growth rate over 4,000 generations. As expected, growth rate increased with a decelerating rate for all populations; however, there were differences in the patterns of evolution at the two temperatures. The growth rates of the different genotypes converged as evolution proceeded at both temperatures, but this convergence was quicker at the higher temperature. Likewise, we found greater repeatability of evolution, in terms of change in growth rate, among replicates of the same genotype at the higher temperature. Finally, we found no evidence of trade-offs in fitness between temperatures, but did observe asymmetry in the correlated responses, whereby evolution in a high temperature increases growth rate at the lower temperature significantly more than the reverse. These results demonstrate the importance of temperature in determining the repeatability of evolutionary trajectories.
Dose Super-Resolution in Prostate Volumetric Modulated Arc Therapy Using Cascaded Deep Learning Networks

Purpose This study proposes a cascaded network model for generating high-resolution doses (i.e., a 1 mm grid) from low-resolution doses (i.e., ≥3 mm grids) with reduced computation time. Methods Using the anisotropic analytical algorithm with three grid sizes (1, 3, and 5 mm) and the Acuros XB algorithm with two grid sizes (1 and 3 mm), dose distributions were calculated for volumetric modulated arc therapy plans for 73 prostate cancer patients. Our cascaded network model consisted of a hierarchically densely connected U-net (HD U-net) and a residual dense network (RDN), which were trained separately following a two-dimensional slice-by-slice procedure. The first network (HD U-net) predicted the downsampled high-resolution dose (generated through bicubic downsampling of the baseline high-resolution dose) using the low-resolution dose; subsequently, the second network (RDN) predicted the high-resolution dose from the output of the first network. Further, the predicted high-resolution dose was converted to its absolute value. We quantified the network performance using the spatial/dosimetric parameters (dice similarity coefficient, mean dose, maximum dose, minimum dose, homogeneity index, conformity index, and V95%, V70%, V50%, and V30%) for the low-resolution and predicted high-resolution doses relative to the baseline high-resolution dose. Gamma analysis (between the baseline dose and the low-resolution dose/predicted high-resolution dose) was performed with a 2%/2 mm criterion and 10% threshold. Results The average computation time to predict a high-resolution axial dose plane was <0.02 s. The dice similarity coefficient values for the predicted doses were closer to 1 when compared to those for the low-resolution doses. Most of the dosimetric parameters for the predicted doses agreed more closely with those for the baseline than for the low-resolution doses. In most of the parameters, no significant differences (p-value of >0.05) between the baseline and predicted doses were observed. The gamma passing rates for the predicted high-resolution does were higher than those for the low-resolution doses. Conclusion The proposed model accurately predicted high-resolution doses for the same dose calculation algorithm. Our model uses only dose data as the input without additional data, which provides advantages of convenience to user over other dose super-resolution methods.
Familial Risk Factors and Emotional Problems in Early Childhood: The Promotive and Protective Role of Children’s Self-Efficacy and Self-Concept

The present study aimed to examine the promotive and protective role of general self-efficacy and positive self-concept in the context of the effects of early familial risk factors on children’s development of emotional problems from early to middle childhood. A total of 293 (T1; Mage = 2.81), 239 (T2; Mage = 3.76), and 189 (T3; Mage = 9.69) children from 25 childcare centers took part in the present study. Fourteen familial risk factors were assessed at T1 using an interview and a questionnaire that were administered to children’s primary caregivers. These 14 familial risk factors were used to compute a familial risk factors score. Primary caregivers also reported on their children’s emotional problems at T2 and T3 and on their children’s general self-efficacy at T2. Children reported on their positive self-concept at T2. Results showed that early familial risk factors were positively associated with emotional problems in the short and long term, although the long-term effect was small and non-significant. Further, the pattern of effect sizes of both promotive and protective effects of general self-efficacy as well as positive self-concept was found to be consistent in the short term. However, in the long term, no consistent support for either the promotive or the protective role of general self-efficacy or positive self-concept was found. These results suggest that general self-efficacy and positive self-concept might contribute to promote mental health and to protect from undesired effects of familial risk factors in the short term. Possible reasons for a lack of long-term effects are discussed along with practical implications.