Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying Selection with Pool-Seq Time Series Data

Abstract Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies.
The neurobiology of uncertainty: implications for statistical learning

The capacity for assessing the degree of uncertainty in the environment relies on estimating statistics of temporally unfolding inputs. This, in turn, allows calibration of predictive and bottom-up processing, and signalling changes in temporally unfolding environmental features. In the last decade, several studies have examined how the brain codes for and responds to input uncertainty. Initial neurobiological experiments implicated frontoparietal and hippocampal systems, based largely on paradigms that manipulated distributional features of visual stimuli. However, later work in the auditory domain pointed to different systems, whose activation profiles have interesting implications for computational and neurobiological models of statistical learning (SL). This review begins by briefly recapping the historical development of ideas pertaining to the sensitivity to uncertainty in temporally unfolding inputs. It then discusses several issues at the interface of studies of uncertainty and SL. Following, it presents several current treatments of the neurobiology of uncertainty and reviews recent findings that point to principles that serve as important constraints on future neurobiological theories of uncertainty, and relatedly, SL. This review suggests it may be useful to establish closer links between neurobiological research on uncertainty and SL, considering particularly mechanisms sensitive to local and global structure in inputs, the degree of input uncertainty, the complexity of the system generating the input, learning mechanisms that operate on different temporal scales and the use of learnt information for online prediction. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.
Protective Ventilation of Preterm Lambs Exposed to Acute Chorioamnionitis Does Not Reduce Ventilation-Induced Lung or Brain Injury

Background The onset of mechanical ventilation is a critical time for the initiation of cerebral white matter (WM) injury in preterm neonates, particularly if they are inadvertently exposed to high tidal volumes (VT) in the delivery room. Protective ventilation strategies at birth reduce ventilation-induced lung and brain inflammation and injury, however its efficacy in a compromised newborn is not known. Chorioamnionitis is a common antecedent of preterm birth, and increases the risk and severity of WM injury. We investigated the effects of high VT ventilation, after chorioamnionitis, on preterm lung and WM inflammation and injury, and whether a protective ventilation strategy could mitigate the response. Methods Pregnant ewes (n = 18) received intra-amniotic lipopolysaccharide (LPS) 2 days before delivery, instrumentation and ventilation at 127±1 days gestation. Lambs were either immediately euthanased and used as unventilated controls (LPSUVC; n = 6), or were ventilated using an injurious high VT strategy (LPSINJ; n = 5) or a protective ventilation strategy (LPSPROT; n = 7) for a total of 90 min. Mean arterial pressure, heart rate and cerebral haemodynamics and oxygenation were measured continuously. Lungs and brains underwent molecular and histological assessment of inflammation and injury. Results LPSINJ lambs had poorer oxygenation than LPSPROT lambs. Ventilation requirements and cardiopulmonary and systemic haemodynamics were not different between ventilation strategies. Compared to unventilated lambs, LPSINJ and LPSPROT lambs had increases in pro-inflammatory cytokine expression within the lungs and brain, and increased astrogliosis (p<0.02) and cell death (p<0.05) in the WM, which were equivalent in magnitude between groups. Conclusions Ventilation after acute chorioamnionitis, irrespective of strategy used, increases haemodynamic instability and lung and cerebral inflammation and injury. Mechanical ventilation is a potential contributor to WM injury in infants exposed to chorioamnionitis.
Development of novel biopolymer blends based on poly(l‐lactic acid), poly((R)‐3‐hydroxybutyrate), and plasticizer

Poly(l-lactic acid) (PLLA), a biopolymer that can be derived from renewable resources, is known for its brittleness as a result of slow crystallization rates under supercooling conditions, which is associated with the formation of large spherulites. In addition, the glass transition temperature (Tg) of PLLA is 60°C, such that the polymer chain is immobile at room temperature. These disadvantages make PLLA unsuitable for use in the food packaging sector. In this research, biopolymer blends based on PLLA and poly((R)-3-hydroxybutyrate) (PHB), together with tributyl citrate (TBC) as a plasticizer, were developed. TBC was added to increase polymer chain mobility, and to decrease PLLA Tg from 60 to 10°C in blends. Furthermore, the addition of PHB as a nucleating agent to PLLA resulted in an increased proportion of smaller spherulites. Fourier-transform infrared (FT-IR) spectroscopy indicated that the carbonyl group and several other characteristic peaks in blends are shifted to lower wavenumber. In addition, polarized optical microscopy experiments confirmed the results of differential scanning calorimetry, FT-IR, and wide-angle X-ray diffraction, showing that PHB enhances the crystallization behavior by acting as a bionucleation. POLYM. ENG. SCI., 54:1394–1402, 2014. © 2013 Society of Plastics Engineers
The cohesin module is a major determinant of cellulosome mechanical stability

Cellulosomes are bacterial protein complexes that bind and efficiently degrade lignocellulosic substrates. These are formed by multimodular scaffolding proteins known as scaffoldins, which comprise cohesin modules capable of binding dockerin-bearing enzymes and usually a carbohydrate-binding module that anchors the system to a substrate. It has been suggested that cellulosomes bound to the bacterial cell surface might be exposed to significant mechanical forces. Accordingly, the mechanical properties of these anchored cellulosomes may be important to understand and improve cellulosome function. Here we used single-molecule force spectroscopy to study the mechanical properties of selected cohesin modules from scaffoldins of different cellulosomes. We found that cohesins located in the region connecting the cell and the substrate are more robust than those located outside these two anchoring points. This observation applies to cohesins from primary scaffoldins (i.e. those that directly bind dockerin-bearing enzymes) from different cellulosomes despite their sequence differences. Furthermore, we also found that cohesin nanomechanics (specifically, mechanostability and the position of the mechanical clamp of cohesin) are not significantly affected by other cellulosomal components, including linkers between cohesins, multiple cohesin repeats, and dockerin binding. Finally, we also found that cohesins (from both the connecting and external regions) have poor refolding efficiency but similar refolding rates, suggesting that the high mechanostability of connecting cohesins may be an evolutionarily conserved trait selected to minimize the occurrence of cohesin unfolding, which could irreversibly damage the cellulosome. We conclude that cohesin mechanostability is a major determinant of the overall mechanical stability of the cellulosome.
Limitations in Detecting a Single Dopant Atom Inside a Bulk Specimen

3-D positions of single dopant atoms in a bulk specimen have been identified using scanning transmission electron microscopy (STEM) [1] and identity of dopant has been confirmed using electron energy loss spectroscopy (EELS) [2]. Many of these results have been reported on samples that were especially prepared for microscopy purposes. The techniques have yet to be standardized for routine work on unknown samples, but the successes so far and development of aberration corrected microscopes, reaching up to 0.5 Å probe size, and monochromators, limiting energy dispersion to 0.13 eV at 300 kV [3], promise a 3-D atom by atom reconstruction of hard materials in the near future. In crystalline materials, electron channeling significantly changes the number of incident beam electrons along an atomic column parallel to the optic axis. As a result, depending on the position of a dopant atom, it may scatter many or few of the primary electrons. This, in turn, determines the visibility of a dopant atom. There are also many other factors that play a role in visibility of individual atoms. Here, we have studied theoretically the limits of dopant atom visibility as a function of probe size, beam voltage, depth of dopant atom, specimen thickness, and the Z-difference between dopant element and bulk host. Visibility is defined as percent change in intensity between a doped and non-doped atomic column in an ADF-STEM image. We are interested in gauging the visibility of a single atom and what parameters must be adjusted to increase the visibility of an otherwise invisible substitutional point defect. Studies are based on multislice simulations [4]. In the figures shown here, parameters used to form aberration corrected STEM probe are: 100 keV incident beam, 25 mrad objective aperture, C3 =-0.015 mm and C5=10 mm spherical aberration coefficients, and -30 Å defocus, resulting in a probe size of 0.8 Å at FWHM. ADF detector angles used to collect scattered electrons range from 54o to 340o [5]. Results show that beam intensity profile along an atomic column does not correlate directly with changes in visibility of dopant atom due to its position along the column, implying that there are more factors affecting visibility than simply the number of electrons interacting with the dopant atom that come from the beam placed directly above it. For instance, type of the dopant atom plays a critical part, since changing the dopant element changes the trend in visibility (Figure 1). We observed that oscillations in visibility with depth of the dopant atom are not a function of specimen thickness (Figure 2). Visibility decays with increasing specimen thickness with a power law (Figure 3). We also observed that similar sized probes give similar visibility, regardless of voltage [6].
Monte Carlo Analysis of Thermal Effects in Monolayer Graphene

ABSTRACT Thermal effects in monolayer graphene under an electron flow are investigated with a Monte Carlo (MC) analysis. The crystal heating is described by simulating the phonon dynamics. In particular, the balance equations for the energy of acoustic, Γ optical, and K phonons are deduced. They contain a heating source which is evaluated by counting the emission and absorption processes during the MC simulation of electron flow. The rate of temperature rise is obtained for several Fermi energies and applied electric voltages.
Study of replicated technology of micro-riblets on shark skin

It has been proved that micro-riblets on shark skin can help to reduce drag.Therefore,the replicated technology of micro-riblets on shark skin becomes one issue in drag-reduction field.Shark skin with micro-placoid scale was taken as the replicated template,and hot embossing method and vacuum casting method were applied to studying the replicated technology on plexiglass and unsaturated resin.The replication samples made by different materials and methods were observed and measured by the stereomicroscope and the stylus profiler.The experimental results show that compared with the hot embossing,the vacuum casting is a relatively perfect method for micro-riblets replication,which uses the unsaturated resin as mold material and casts the liquid silicone rubber under vacuum,micro-riblets on shark skin surface are replicated clearly and perfectly.It is found that the vacuum casting is an effective replication technology which is suitable to form large-area and highly accurate micro-riblets.
Corrigendum: High frequency performance of individual and arrays of single-walled carbon nanotubes (2012 Nanotechnology 23 245202)

We have studied the high frequency performance limits of single-walled carbon nanotube (SWNT) transistors in the diffusive transport regime limited by the acoustic phonon scattering. The relativistic band structure of single-walled carbon nanotubes combined with the acoustic phonon scattering provides an analytical model for the charge transport of the radio frequency transistors. We were able to obtain the intrinsic high frequency performance such as the cut-off frequency and the linearity of the SWNT transistors. We have extended our model to include transistors based on arrays of SWNTs. The effect of electrostatic screening in a dense array of SWNTs on the cut-off frequency is studied. (Some ﬁgures may appear in colour only in the online journal)
The Effect of Micron-Size Silicon Additions on Microstructure, Microhardness and Thermal Properties of Sn-Cu-Ni Solder Alloy

The effect of Si particulate addition on the commercial Sn-Cu-Ni solder system (SN100C) solder alloy has been investigated. The SN100C/Si composite solder was fabricated via powder metallurgy (PM) technique. In this study five different Si composition chosen were (0 wt. %, 0.25 wt. %, 0.5 wt. %, 0.75 wt. %, and 1.0 wt. %). The results indicated that adding a small amount of Si particulate can slightly improve the physical properties of the composite solder compared to monolithic solder alloy. Microstructural analysis revealed the reinforcement seen well distributed between the grains boundaries with additions of 1.0 wt. % resulted with highest hardness value.
Economic Costs of Diabetes in the U.S. in 2017

OBJECTIVE This study updates previous estimates of the economic burden of diagnosed diabetes and quantifies the increased health resource use and lost productivity associated with diabetes in 2017. RESEARCH DESIGN AND METHODS We use a prevalence-based approach that combines the demographics of the U.S. population in 2017 with diabetes prevalence, epidemiological data, health care cost, and economic data into a Cost of Diabetes Model. Health resource use and associated medical costs are analyzed by age, sex, race/ethnicity, insurance coverage, medical condition, and health service category. Data sources include national surveys, Medicare standard analytical files, and one of the largest claims databases for the commercially insured population in the U.S. RESULTS The total estimated cost of diagnosed diabetes in 2017 is $327 billion, including $237 billion in direct medical costs and $90 billion in reduced productivity. For the cost categories analyzed, care for people with diagnosed diabetes accounts for 1 in 4 health care dollars in the U.S., and more than half of that expenditure is directly attributable to diabetes. People with diagnosed diabetes incur average medical expenditures of ∼$16,750 per year, of which ∼$9,600 is attributed to diabetes. People with diagnosed diabetes, on average, have medical expenditures ∼2.3 times higher than what expenditures would be in the absence of diabetes. Indirect costs include increased absenteeism ($3.3 billion) and reduced productivity while at work ($26.9 billion) for the employed population, reduced productivity for those not in the labor force ($2.3 billion), inability to work because of disease-related disability ($37.5 billion), and lost productivity due to 277,000 premature deaths attributed to diabetes ($19.9 billion). CONCLUSIONS After adjusting for inflation, economic costs of diabetes increased by 26% from 2012 to 2017 due to the increased prevalence of diabetes and the increased cost per person with diabetes. The growth in diabetes prevalence and medical costs is primarily among the population aged 65 years and older, contributing to a growing economic cost to the Medicare program. The estimates in this article highlight the substantial financial burden that diabetes imposes on society, in addition to intangible costs from pain and suffering, resources from care provided by nonpaid caregivers, and costs associated with undiagnosed diabetes.
Microfluidic self-assembly of quantum dot compound micelles

This thesis is devoted to the development of microfluidic processes for the controlled self-assembly of quantum dot compound micelles (QDCMs). Microfluidic processes are developed to combine the constituents (cadmium sulfide quantum dots, and block copolymer stabilizing chains) with water to facilitate self-assembly of the composite particles, QDCMs, through initial phase separation, subsequent growth, and eventual quenching. Two genres of microfluidic reactors are developed. The on-chip evolution of QDCM formation and growth is resolved through fluorescence microscopy; QDCM size distributions and associated statistics are determined through off-chip analysis by transmission electron microscopy (TEM). In a flow-focusing reactor, control over the mean size of QDCMs is demonstrated through both the water concentration and the growth time (or reactor channel length). Controlled QDCM self-assembly is also demonstrated in a multiphase gas-liquid reactor. In contrast to the flow-focusing reactor, increasing the multiphase reactor channel length results in a decrease in QDCM size and polydispersity.
Toxicity assessment of nanoparticles in various systems and organs

Abstract In the past decades, much attention has been paid to toxicity assessment of nanoparticles prior to clinical and biological applications. While in vitro studies have been increasing constantly, in vivo studies of nanoparticles have not established a unified system until now. Predictive models and validated standard methods are imperative. This review summarizes the current progress in approaches assessing nanotoxicity in main systems, including the hepatic and renal, gastrointestinal, pulmonary, cardiovascular, nervous, and immune systems. Histopathological studies and specific functional examinations in each system are elucidated. Related injury mechanisms are also discussed.
Early Life Stress-Related Elevations in Reaction Time Variability Are Associated with Brain Volume Reductions in HIV+ Adults

There is burgeoning evidence that, among HIV+ adults, exposure to high levels of early life stress (ELS) is associated with increased cognitive impairment as well as brain volume abnormalities and elevated neuropsychiatric symptoms. Currently, we have a limited understanding of the degree to which cognitive difficulties observed in HIV+ High-ELS samples reflect underlying neural abnormalities rather than increases in neuropsychiatric symptoms. Here, we utilized a behavioral marker of cognitive function, reaction time intra-individual variability (RT-IIV), which is sensitive to both brain volume reductions and neuropsychiatric symptoms, to elucidate the unique contributions of brain volume abnormalities and neuropsychiatric symptoms to cognitive difficulties in HIV+ High-ELS adults. We assessed the relation of RT-IIV to neuropsychiatric symptom levels and total gray and white matter volumes in 44 HIV+ adults (26 with high ELS). RT-IIV was examined during a working memory task. Self-report measures assessed current neuropsychiatric symptoms (depression, stress, post-traumatic stress disorder). Magnetic resonance imaging was used to quantify total gray and white matter volumes. Compared to Low-ELS participants, High-ELS participants exhibited elevated RT-IIV, elevated neuropsychiatric symptoms, and reduced gray and white matter volumes. Across the entire sample, RT-IIV was significantly associated with gray and white matter volumes, whereas significant associations with neuropsychiatric symptoms were not observed. In the High-ELS group, despite the presence of elevated neuropsychiatric symptom levels, brain volume reductions explained more than 13% of the variance in RT-IIV, whereas neuropsychiatric symptoms explained less than 1%. Collectively, these data provide evidence that, in HIV+ High-ELS adults, ELS-related cognitive difficulties (as indexed by RT-IIV) exhibit strong associations with global brain volumes, whereas ELS-related elevations in neuropsychiatric symptoms appear to contribute minimally to these cognitive difficulties. Such findings support a growing body of evidence indicating that high ELS exposure is a significant risk factor for neurocognitive dysfunction in HIV+ adults. Further, these data highlight the need to better understand how ELS-related pathophysiological mechanisms contribute to volumetric and other neural abnormalities in HIV+ individuals.
The role of microRNAs in prethrombotic status associated with coronary artery disease

Summary The acute cardiovascular events following thrombus formation is a primary cause of morbidity and mortality of patients with coronary artery disease (CAD). Numerous studies have shown that a prethrombotic status, which can be defined as an imbalance between the procoagulant and anticoagulant conditions, would exist for a period of time before thrombogenesis. Therefore, early diagnosis and intervention of prethrombotic status are important for reducing acute cardiovascular events. However, none of prethrombotic indicators have been identified as golden standard for diagnosis of prethrombotic status to date. MicroRNAs (miRNAs), a class of short non-coding RNAs, have been shown to be involved in pathophysiologic processes related to prethrombotic status, such as endothelial dysfunction, platelet activation, impaired fibrinolysis and elevated procoagulant factors, etc. Owing to their multiple and fine-tuning impacts on gene expression, miRNAs raise a novel understanding in the underlying mechanism of prethrombotic status. This review aims to discuss the role of miRNAs in prethrombotic status, especially the differently expressed miRNAs in CAD, which may be meaningful for developing promising diagnostic biomarkers and therapeutic strategies for CAD patients in future.