Plankton communities normally consist of few abundant and many rare species, yet little is known about the ecological role of rare planktonic eukaryotes. Here we used a 18S ribosomal DNA sequencing ...approach to investigate the dynamics of rare planktonic eukaryotes, and to explore the co-occurrence patterns of abundant and rare eukaryotic plankton in a subtropical reservoir following a cyanobacterial bloom event. Our results showed that the bloom event significantly altered the eukaryotic plankton community composition and rare plankton diversity without affecting the diversity of abundant plankton. The similarities of both abundant and rare eukaryotic plankton subcommunities significantly declined with the increase in time-lag, but stronger temporal turnover was observed in rare taxa. Further, species turnover of both subcommunities explained a higher percentage of the community variation than species richness. Both deterministic and stochastic processes significantly influenced eukaryotic plankton community assembly, and the stochastic pattern (e.g., ecological drift) was particularly pronounced for rare taxa. Co-occurrence network analysis revealed that keystone taxa mainly belonged to rare species, which may play fundamental roles in network persistence. Importantly, covariations between rare and non-rare taxa were predominantly positive, implying multispecies cooperation might contribute to the stability and resilience of the microbial community. Overall, these findings expand current understanding of the ecological mechanisms and microbial interactions underlying plankton dynamics in changing aquatic ecosystems.
The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One ...promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, "trained" networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale's principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied.
Abstract
This article explores how liberal feminism has been received and hybridized with local feminisms in post-socialist China. Based on interviews and documents from four Ford Foundation ...projects, the results show how local actors appropriated elements from three strands of feminism: liberal, socialist, and cultural. Conflicts among these strands were reconciled by de-emphasizing the structural origins of gender inequality and putting impetus for change on individual women. The human rights-based understandings of gender equality are thereby converted into women’s obligation to improve their “quality” and exercise their legal rights, which ignores intersectional disadvantages confronting rural women.
Neurologic Wilson disease is an inherited disease characterized by a copper metabolic disorder that causes damage to many organs, especially the brain. Few studies report the relationships between ...these neurologic symptoms and MR imaging of the brain. Therefore, we investigated the correlation of brain abnormalities in patients with neurologic Wilson disease with their clinical symptoms, age of onset, and lag time to diagnosis.
A cohort of 364 patients was recruited in China between January 2003 and December 2017. Age of onset, lag time until diagnosis, and neurologic symptoms were recorded, and cranial MR imaging was performed. Patients were divided into groups within each of these factors for correlation analysis with the MR imaging brain scans.
Abnormal signals in the MR imaging brain scans were seen in all 364 cases. Affected regions included the putamen, pons, midbrain, and thalamus, while the medulla and occipital lobe were unaffected. The putamen was the most frequently damaged brain region in this study. With the age of onset younger than 10 years, cranial MR imaging scans showed only impairment in the putamen. Patients with a longer lag time before diagnosis were more likely to have impairment in the pons, midbrain, and cortex. Among neurologic symptoms of Wilson disease, torsion spasm is associated with the midbrain and cortex, and choreoathetosis is related to the caudate nucleus.
Abnormalities in the putamen, pons, midbrain, and thalamus are part of the neuroimaging spectrum of Wilson disease. There is a significant correlation between the site of brain injury and diagnosis lag time.
Abstract
We present a solution for the ultraviolet – submillimetre (submm) interstellar radiation fields (ISRFs) of the Milky Way (MW), derived from modelling COBE, IRAS and Planck maps of the ...all-sky emission in the near-, mid-, far-infrared and submm. The analysis uses the axisymmetric radiative transfer model that we have previously implemented to model the panchromatic spectral energy distributions (SEDs) of star-forming galaxies in the nearby universe, but with a new methodology allowing for optimization of the radial and vertical geometry of stellar emissivity and dust opacity, as deduced from the highly resolved emission seen from the vantage point of the Sun. As such, this is the first self-consistent model of the broad-band continuum emission from the MW. In this paper, we present model predictions for the spatially integrated SED of the MW as seen from the Sun, showing good agreement with the data, and give a detailed description of the solutions for the distribution of ISRFs, as well as their physical origin, throughout the volume of the galaxy. We explore how the spatial and spectral distributions of our new predictions for the ISRF in the MW affects the amplitude and spectral distributions of the gamma rays produced via inverse Compton scattering for cosmic ray (CR) electrons situated at different positions in the galaxy, as well as the attenuation of the gamma rays due to interactions of the gamma-ray photons with photons of the ISRF. We also compare and contrast our solutions for the ISRF with those incorporated in the galprop package used for modelling the high-energy emission from CR in the MW.
Tungsten carbide is one of the most promising electrocatalysts for the hydrogen evolution reaction, although it exhibits sluggish kinetics due to a strong tungsten-hydrogen bond. In addition, ...tungsten carbide's catalytic activity toward the oxygen evolution reaction has yet to be reported. Here, we introduce a superaerophobic nitrogen-doped tungsten carbide nanoarray electrode exhibiting high stability and activity toward hydrogen evolution reaction as well as driving oxygen evolution efficiently in acid. Nitrogen-doping and nanoarray structure accelerate hydrogen gas release from the electrode, realizing a current density of -200 mA cm
at the potential of -190 mV vs. reversible hydrogen electrode, which manifest one of the best non-noble metal catalysts for hydrogen evolution reaction. Under acidic conditions (0.5 M sulfuric acid), water splitting catalyzed by nitrogen-doped tungsten carbide nanoarray starts from about 1.4 V, and outperforms most other water splitting catalysts.
Summary
Due to the huge gap in the care of patients with osteoporosis and fragility fractures, we aimed to explore the effectiveness of the osteoporosis liaison service (OLS) in osteoporosis care. We ...found that OLS can improve osteoporosis care, including increasing medication compliance, increasing calcium/vitamin D/protein intake, and reducing fall rate.
Introduction
A significant gap exists in the care of patients with osteoporosis and fragility fractures. This study aimed to evaluate 1-year outcomes of an osteoporosis liaison service (OLS) program that includes two independent components: medication management services (MMS) to improve medication adherence and fracture liaison services (FLS) for secondary prevention.
Methods
Patients with new hip fracture or untreated vertebral fractures enrolled in the FLS program (
n
= 600), and those with osteoporosis medication management issues but not necessarily fragility fractures enrolled in the MMS program (
n
= 499) were included. To evaluate outcomes, care coordinators assessed baseline items adapted from the 13 Best Practices Framework (BPF) standards of the International Osteoporosis Foundation, with telephone follow-up every 4 months for 1 year.
Results
Mean age of this cohort was 76.2 ± 10.3 years, 78.8% were female. After 1-year participation in the program, all patients had received bone mineral density tests, and medication adherence for the entire cohort at 12 months was 91.9 ± 19.6%, with significant improvement in fall rates (23.4% reduction), exercise rates (16.8% increase), calcium intake (26.5% increase), vitamin D intake (26.4% increase), and adequate protein intake (17.3% increase) (all
p
< 0.05). After 1-year OLS program, the overall rates of mortality, incident fracture, and falls were 6.6%, 4.0%, and 24.3%, respectively.
Conclusions
The OLS program is associated with improved osteoporosis care, including increased medication adherence, calcium/vitamin D and protein intake, and reduced fall rate.
Although it is widely recognized that cyanobacterial blooms have substantial influence on the plankton community in general, their correlations with the whole community of eukaryotic plankton at ...longer time scales remain largely unknown. Here, we investigated the temporal dynamics of eukaryotic plankton communities in two subtropical reservoirs over a 6-year period (2010-2015) following one cyanobacterial biomass cycle-the cyanobacterial bloom (middle 2010), cyanobacteria decrease (late 2010-early 2011), non-bloom (2011-2014), cyanobacteria increase, and second bloom (late 2014-2015). The eukaryotic community succession that strongly correlated with this cyanobacterial biomass cycle was divided into four periods, and each period had distinct characteristics in cyanobacterial biomass and environments in both reservoirs. Integrated co-occurrence networks of eukaryotic plankton based on the whole study period revealed that the cyanobacterial biomass had remarkably high network centralities, and the eukaryotic OTUs that had stronger correlations with the cyanobacterial biomass exhibited higher centralities. The integrated networks were also modularly responded to different eukaryotic succession periods, and therefore correlated with the cyanobacterial biomass cycle. Moreover, sub-networks based on the different eukaryotic succession periods indicated that the eukaryotic co-occurrence patterns were not constant but varied largely associating with the cyanobacterial biomass. Based on these long-term observations, our results reveal that the cyanobacterial biomass cycle created distinct niches between persistent bloom, non-bloom, decrease and increase of cyanobacteria, and therefore associated with distinct eukaryotic plankton patterns. Our results have important implications for understanding how complex aquatic plankton communities respond to cyanobacterial blooms under the changing environments.