SYNAPTIC PLASTICITY IN THE INJURED BRAIN DEPENDS ON THE TEMPORAL PATTERN OF STIMULATION.

Neurostimulation protocols are increasingly used as therapeutic interventions, including for brain injury. In addition to the direct activation of neurons, these stimulation protocols are also likely to have downstream effects on those neurons' synaptic outputs. It is well known that alterations in the strength of synaptic connections (long-term potentiation, LTP; long-term depression, LTD) are sensitive to the frequency of stimulation used for induction, however little is known about the contribution of the temporal pattern of stimulation to the downstream synaptic plasticity that may be induced by neurostimulation in the injured brain. We explored interactions of the temporal pattern and frequency of neurostimulation in the normal cerebral cortex and after mild traumatic brain injury (mTBI), to inform therapies to strengthen or weaken neural circuits in injured brains, as well as to better understand the role of these factors in normal brain plasticity. Whole-cell (WC) patch-clamp recordings of evoked postsynaptic potentials (PSPs) in individual neurons, as well as field potential (FP) recordings, were made from layer 2/3 of visual cortex in response to stimulation of layer 4, in acute slices from control (naïve), sham operated, and mTBI rats. We compared synaptic plasticity induced by different stimulation protocols, each consisting of a specific frequency (1 Hz, 10 Hz, or 100 Hz), continuity (continuous or discontinuous), and temporal pattern (perfectly regular, slightly irregular, or highly irregular). At the individual neuron level, dramatic differences in plasticity outcome occurred when the highly irregular stimulation protocol was used at 1 Hz or 10 Hz, producing an overall LTD in controls and shams, but a robust overall LTP after mTBI. Consistent with the individual neuron results, the plasticity outcomes for simultaneous FP recordings were similar, indicative of our results generalizing to a larger scale synaptic network than can be sampled by individual WC recordings alone. In addition to the differences in plasticity outcome between control (naïve or sham) and injured brains, the dynamics of the changes in synaptic responses that developed during stimulation were predictive of the final plasticity outcome. Our results demonstrate that the temporal pattern of stimulation plays a role in the polarity and magnitude of synaptic plasticity induced in the cerebral cortex while highlighting differences between normal and injured brain responses. Moreover, these results may be useful for optimization of neurostimulation therapies to treat mTBI and other brain disorders, in addition to providing new insights into downstream plasticity signaling mechanisms in the normal brain.

MCU-enriched dendritic mitochondria regulate plasticity in distinct hippocampal circuits.

Mitochondria are dynamic organelles that are morphologically and functionally diverse across cell types and subcellular compartments in order to meet unique energy demands. Mitochondrial dysfunction has been implicated in a wide variety of neurological disorders, including psychiatric disorders like schizophrenia and bipolar disorder. Despite it being well known that mitochondria are essential for synaptic transmission and synaptic plasticity, the mechanisms regulating mitochondria in support of normal synapse function are incompletely understood. The mitochondrial calcium uniporter (MCU) regulates calcium entry into the mitochondria, which in turn regulates the bioenergetics and distribution of mitochondria to active synapses. Evidence suggests that calcium influx via MCU couples neuronal activity to mitochondrial metabolism and ATP production, which would allow neurons to rapidly adapt to changing energy demands. Intriguingly, MCU is uniquely enriched in hippocampal CA2 distal dendrites relative to neighboring hippocampal CA1 or CA3 distal dendrites, however, the functional significance of this enrichment is not clear. Synapses from the entorhinal cortex layer II (ECII) onto CA2 distal dendrites readily express long term potentiation (LTP), unlike the LTP- resistant synapses from CA3 onto CA2 proximal dendrites, but the mechanisms underlying these different plasticity profiles are unknown. We hypothesized that enrichment of MCU near ECII-CA2 synapses promotes LTP in an otherwise plasticity-restricted cell type. Using a CA2-specific MCU knockout (cKO) mouse, we found that MCU is required for LTP at distal dendrite synapses but does not affect the lack of LTP at proximal dendrite synapses. Loss of LTP at ECII-CA2 synapses correlated with a trend for decreased spine density in CA2 distal dendrites of cKO mice compared to control (CTL) mice, which was predominantly seen in immature spines. Moreover, mitochondria were significantly smaller and more numerous across all dendritic layers of CA2 in cKO mice compared to CTL mice, suggesting an overall increase in mitochondrial fragmentation. Fragmented mitochondria might have functional changes, such as altered ATP production, that might explain a deficit in synaptic plasticity. Collectively, our data reveal that MCU regulates layer-specific forms of plasticity in CA2 dendrites, potentially by maintaining proper mitochondria morphology and distribution within dendrites. Differences in MCU expression across different cell types and circuits might be a general mechanism to tune the sensitivity of mitochondria to cytoplasmic calcium levels to power synaptic plasticity. MAIN TAKE HOME POINTS: The mitochondrial calcium uniporter (MCU) regulates plasticity selectively at synapses in CA2 distal dendrites.The MCU-cKO induced LTP deficit correlates with a trending reduction in spine density in CA2 distal dendrites.Loss of MCU in CA2 results in ultrastructural changes in dendritic mitochondria that suggest an increase in mitochondrial fragmentation. These ultrastructural changes could result in functional consequences, such as decreased ATP production, that could underlie the plasticity deficit.Dendritic mitochondrial fragmentation in MCU cKO occurred throughout the dendritic laminae, suggesting that MCU is dispensable for establishing layer-specific mitochondrial structural diversity.

A ratiometric, fluorometric approach for surface charge mapping of biosilica features.

We describe a surface charge imaging method for heterogeneous biosilicas based on relationships between zeta (ζ) potential, feature size of nanoparticles, and PDMPO fluorescence and apply it to silicified structures from plants and diatoms. The methodology provides the first opportunity to map the surface charge of large heterogeneous biosilica materials and indicates that local surface charge is related to morphology below the diffraction limit (ca. 20-130 nm) with sharper features showing less negative zeta potential equivalent surface charge suggesting that the zeta potential of silica structures can be adjusted by engineering surface morphology. We show that the approach can be used to study living silicified biological tissues without recourse to sectioning and fixation. Further, the approach could be used for the study of other metal oxides possessing hydroxylated moieties. The method has potential to open up opportunities for the engineering of materials with defined charge characteristics for the solution of biomedical engineering problems including materials for tissue replacement.

Machine learning partners in criminal networks.

Recent research has shown that criminal networks have complex organizational structures, but whether this can be used to predict static and dynamic properties of criminal networks remains little explored. Here, by combining graph representation learning and machine learning methods, we show that structural properties of political corruption, police intelligence, and money laundering networks can be used to recover missing criminal partnerships, distinguish among different types of criminal and legal associations, as well as predict the total amount of money exchanged among criminal agents, all with outstanding accuracy. We also show that our approach can anticipate future criminal associations during the dynamic growth of corruption networks with significant accuracy. Thus, similar to evidence found at crime scenes, we conclude that structural patterns of criminal networks carry crucial information about illegal activities, which allows machine learning methods to predict missing information and even anticipate future criminal behavior.

Universality of political corruption networks.

Corruption crimes demand highly coordinated actions among criminal agents to succeed. But research dedicated to corruption networks is still in its infancy and indeed little is known about the properties of these networks. Here we present a comprehensive investigation of corruption networks related to political scandals in Spain and Brazil over nearly three decades. We show that corruption networks of both countries share universal structural and dynamical properties, including similar degree distributions, clustering and assortativity coefficients, modular structure, and a growth process that is marked by the coalescence of network components due to a few recidivist criminals. We propose a simple model that not only reproduces these empirical properties but reveals also that corruption networks operate near a critical recidivism rate below which the network is entirely fragmented and above which it is overly connected. Our research thus indicates that actions focused on decreasing corruption recidivism may substantially mitigate this type of organized crime.

Masking by health care and public safety workers in non-patient care areas to mitigate SARS-CoV-2 infection: A systematic review.

Objectives: Wearing a mask is an important method for reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in health care and public safety settings. We assess the evidence regarding masking in the workplace during the initial months of the COVID-19 pandemic (PROSPERO CRD4202432097). Methods: We performed a systematic review of published literature from 4 databases and evaluated the quality of evidence with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. We searched for observational and experimental research involving public safety and health care workers. We included articles evaluating the use of masks, versus no mask, on the outcome of SARS-CoV-2 infection. Results: Our search yielded 15,013 records, of which 9 studies were included. Most studies (n = 8; 88.9%) involved infections or outbreaks among health care workers. The majority (88.9%) used in-depth interviews of cases and non-cases to obtain self-reported use of masks during periods of exposure. One of 9 studies quantitatively assessed differences in SARS-CoV-2 infection based on use of masks in non-patient care settings. Use of observational study designs, small sample sizes, inadequate control for confounding, and inadequate measurement of exposure and non-exposure periods with infected coworkers contributed to the quality of evidence being judged as very low. Conclusions: The available evidence from the initial months of the pandemic suggests that the use of masks in congregate, non-patient care settings, such as breakrooms, helps to reduce risk of SARS-CoV-2 virus transmission. However, this evidence is limited and is of very low quality. Prospective studies incorporating active observation measures are warranted.

Population density and spreading of COVID-19 in England and Wales.

We investigated daily COVID-19 cases and deaths in the 337 lower tier local authority regions in England and Wales to better understand how the disease propagated over a 15-month period. Population density scaling models revealed residual variance and skewness to be sensitive indicators of the dynamics of propagation. Lockdowns and schools reopening coincided with increased variance indicative of conditions with local impact and country scale heterogeneity. University reopening and December holidays reduced variance indicative of country scale homogenisation which reached a minimum in mid-January 2021. Homogeneous propagation was associated with better correspondence with normally distributed residuals while heterogeneous propagation was more consistent with skewed models. Skewness varied from strongly negative to strongly positive revealing an unappreciated feature of community propagation. Hot spots and super-spreading events are well understood descriptors of regional disease dynamics that would be expected to be associated with positively skewed distributions. Positively skewed behaviour was observed; however, negative skewness indicative of "cold-spots" and "super-isolation" dominated for approximately 8 months during the period of study. In contrast, death metrics showed near constant behaviour in scaling, variance, and skewness metrics over the full period with rural regions preferentially affected, an observation consistent with regional age demographics in England and Wales. Regional positions relative to density scaling laws were remarkably persistent after the first 5-9 days of the available data set. The determinants of this persistent behaviour probably precede the pandemic and remain unchanged.

Does the evidence support brief (≤30-mins), moderate (31-60-mins), or long duration naps (61+ mins) on the night shift? A systematic review.

We performed a systematic review of four databases to determine if the evidence supports a short or long duration nap during night shifts to mitigate fatigue, and/or improve health, safety, or performance for emergency services and public safety personnel (PROSPERO CRD42020156780). We focused on experimental research and evaluated the quality of evidence with the grading of recommendations, assessment, development, and evaluation (GRADE) framework. We used the Cochrane Collaboration's risk of bias tool to assess bias and reported findings using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. Our search yielded n = 10,345 records and n = 44 were reviewed in full-text. Inter-rater agreement during screening was substantial (Kappa = 0.66). We retained n = 11 publications, reporting on n = 7 experimental studies with a cumulative sample size of n = 140. We identified wide variation in study design, napping interventions (i.e., timing, placement, and duration), and outcomes. We identified mixed findings comparing brief, moderate, and long duration naps on outcomes of interest. All seven studies presented serious risk of bias and the quality of evidence was rated as low. Based on the best available evidence, decisions regarding nap duration during night shift work should be based on time (post-nap) and outcome.

Rural-urban scaling of age, mortality, crime and property reveals a loss of expected self-similar behaviour.

The urban scaling hypothesis has improved our understanding of cities; however, rural areas have been neglected. We investigated rural-urban population density scaling in England and Wales using 67 indicators of crime, mortality, property, and age. Most indicators exhibited segmented scaling about a median critical density of 27 people per hectare. Above the critical density, urban regions preferentially attract young adults (25-40 years) and lose older people (> 45 years). Density scale adjusted metrics (DSAMs) were analysed using hierarchical clustering, networks, and self-organizing maps (SOMs) revealing regional differences and an inverse relationship between excess value of property transactions and a range of preventable mortality (e.g. diabetes, suicide, lung cancer). The most striking finding is that age demographics break the expected self-similarity underlying the urban scaling hypothesis. Urban dynamism is fuelled by preferential attraction of young adults and not a fundamental property of total urban population.

Statistical models for identifying frequent hitters in high throughput screening.

High throughput screening (HTS) interrogates compound libraries to find those that are "active" in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor function (BSF) model of "frequent hitters" using 872 publicly available HTS data sets. We found large numbers of "infrequent hitters" using this model leading us to reject the BSF for identifying "frequent hitters." As alternatives, we investigated generalized logistic, gamma, and negative binomial distributions as models for compound behavior. The gamma model reduced the proportion of both frequent and infrequent hitters relative to the BSF. Within this data set, conclusions about individual compound behavior were limited by the number of times individual compounds were tested (1-1613 times) and disproportionate testing of some compounds. Specifically, most tests (78%) were on a 309,847-compound subset (17.6% of compounds) each tested ≥ 300 times. We concluded that the disproportionate retesting of some compounds represents compound repurposing at scale rather than drug discovery. The approach to drug discovery represented by these 872 data sets characterizes the assays well by challenging them with many compounds while each compound is characterized poorly with a single assay. Aggregating the testing information from each compound across the multiple screens yielded a continuum with no clear boundary between normal and frequent hitting compounds.

City size and the spreading of COVID-19 in Brazil.

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate small towns are proportionally more affected by COVID-19 during the initial spread of the disease, such that the cumulative numbers of cases and deaths per capita initially decrease with population size. However, during the long-term course of the pandemic, this urban advantage vanishes and large cities start to exhibit higher incidence of cases and deaths, such that every 1% rise in population is associated with a 0.14% increase in the number of fatalities per capita after about four months since the first two daily deaths. We argue that these patterns may be related to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones over time.

Endpoint PCR Detection of Sars-CoV-2 RNA

Quantitative real-time PCR methods have been used to perform approximately 278 million tests for COVID-19 up to mid-July 2020. Real-time PCR involves a rate limiting step where the samples are measured in situ during each PCR amplification cycle. This creates a bottleneck limiting scalability and as a consequence reducing access to inexpensive reliable testing at national and international scales. We investigated endpoint PCR for the qualitative detection of SARS-CoV-2 sequences on synthetic RNA standards and hospital patient samples. The endpoint PCR detection limit is constrained only by the stochastics of low copy numbers and reliably detected single copies of synthetic RNA standards. On a set of 30 patient samples, endpoint PCR found one additional positive sample and was able to confirm an indeterminate sample as negative. These results were found using 4 l reagent and 1 l of sample representing an 80% reduction in required RNA extract input and PCR reagent volumes relative to the NHS protocol (20 l reagent and 5 l sample). These results indicate that endpoint PCR should be the method of choice for large scale testing programmes. Based on the experience from ultra-high throughput genotyping efforts a single workflow using 384-well plates has similar PCR capacity (250 Million) to that required for all testing done worldwide during the first 7 month of the pandemic.

Platform for Screening Abiotic/Biotic Interactions Using Indicator Displacement Assays.

This paper describes novel adaptations of optically sectioned planar format assays to screen compounds for their affinities to materials surfaces. The novel platform, which we name optically sectioned indicator displacement assays (O-IDA), makes use of displaceable dyes in a format adaptable to high-throughput multiwell plate technologies. We describe two approaches: the first being where the dye exhibits fluorescence in both the surface bound and unbound state and the second, where fluorescence is lost upon displacement of the dye from the surface. Half maximal inhibitory concentration (IC50), binding affinity (Ki), and binding free energy (ΔGads) values can be extracted from the raw data. Representative biomolecules were tested for interactions with silica in an aqueous environment and ZnO(0001)-Zn and (10-10) facets in a nonaqueous environment. We provide the first experimental values for both the binding of small molecules to silica and the facet-dependent ZnO binding affinity of key amino acids associated with ZnO-specific oligopeptides. The specific data will be invaluable to those studying interactions at interfaces both experimentally and computationally. O-IDA provides a general framework for the high-throughput screening of molecule binding to materials surfaces, which has important applications in drug delivery, (bio-) catalysis, biosensing, and biomaterial engineering.

The Distribution of Standard Deviations Applied to High Throughput Screening.

High throughput screening (HTS) assesses compound libraries for "activity" using target assays. A subset of HTS data contains a large number of sample measurements replicated a small number of times providing an opportunity to introduce the distribution of standard deviations (DSD). Applying the DSD to some HTS data sets revealed signs of bias in some of the data and discovered a sub-population of compounds exhibiting high variability which may be difficult to screen. In the data examined, 21% of 1189 such compounds were pan-assay interference compounds. This proportion reached 57% for the most closely related compounds within the sub-population. Using the DSD, large HTS data sets can be modelled in many cases as two distributions: a large group of nearly normally distributed "inactive" compounds and a residual distribution of "active" compounds. The latter were not normally distributed, overlapped inactive distributions - on both sides -, and were larger than typically assumed. As such, a large number of compounds are being misclassified as "inactive" or are invisible to current methods which could become the next generation of drugs. Although applied here to HTS, it is applicable to data sets with a large number of samples measured a small number of times.

Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools.

Scale-adjusted metrics (SAMs) are a significant achievement of the urban scaling hypothesis. SAMs remove the inherent biases of per capita measures computed in the absence of isometric allometries. However, this approach is limited to urban areas, while a large portion of the world's population still lives outside cities and rural areas dominate land use worldwide. Here, we extend the concept of SAMs to population density scale-adjusted metrics (DSAMs) to reveal relationships among different types of crime and property metrics. Our approach allows all human environments to be considered, avoids problems in the definition of urban areas, and accounts for the heterogeneity of population distributions within urban regions. By combining DSAMs, cross-correlation, and complex network analysis, we find that crime and property types have intricate and hierarchically organized relationships leading to some striking conclusions. Drugs and burglary had uncorrelated DSAMs and, to the extent property transaction values are indicators of affluence, twelve out of fourteen crime metrics showed no evidence of specifically targeting affluence. Burglary and robbery were the most connected in our network analysis and the modular structures suggest an alternative to "zero-tolerance" policies by unveiling the crime and/or property types most likely to affect each other.

Fluctuation Scaling, Calibration of Dispersion, and Detection of Differences.

Fluctuation scaling describes the relationship between the mean and standard deviation of a set of measurements. An example is Horwitz scaling, which has been reported from interlaboratory studies. Horwitz and similar studies have reported simple exponential and segmented scaling laws with exponents (α) typically between 0.85 (Horwitz) and 1 when not operating near a detection limit. When approaching a detection limit, the exponents change and approach an apparently Gaussian (α = 0) model. This behavior is often presented as a property of interlaboratory studies, which makes controlled replication to understand the behavior costly to perform. To assess the contribution of instrumentation to larger scale fluctuation scaling, we measured the behavior of two inductively coupled plasma atomic emission spectrometry (ICP-AES) systems, in two laboratories measuring thulium using two emission lines. The standard deviation universally increased with the uncalibrated signal, indicating the system was heteroscedastic. The response from all lines and both instruments was consistent with a single exponential dispersion model having parameters α = 1.09 and ß = 0.0035. No evidence of Horwitz scaling was found, and there was no evidence of Poisson noise limiting behavior. The "Gaussian" component was a consequence of background subtraction for all lines and both instruments. The observation of a simple exponential dispersion model in the data allows for the definition of a difference detection limit (DDL) with universal applicability to systems following known dispersion. The DDL is the minimum separation between two points along a dispersion model required to claim they are different according to a particular statistical test. The DDL scales transparently with the mean and works at any location in a response function.

GABAB receptor-dependent bidirectional regulation of critical period ocular dominance plasticity in cats.

Gama amino butyric acid (GABA) inhibition plays an important role in the onset and offset of the critical period for ocular dominance (OD) plasticity in the primary visual cortex. Previous studies have focused on the involvement of GABAA receptors, while the potential contribution of GABAB receptors to OD plasticity has been neglected. In this study, the GABAB receptor antagonist SCH50911 or agonist baclofen was infused into the primary visual cortex of cats concurrently with a period of monocular deprivation (MD). Using single-unit recordings we found that the OD shift induced by four days of MD during the critical period was impaired by infusion of the antagonist SCH50911, but enhanced by infusion of the agonist baclofen. In contrast, seven days of MD in adult cats did not induce any significant OD shift, even when combined with the infusion of SCH50911 or baclofen. Together, these findings indicate that an endogenous GABAB receptor-mediated inhibition contributes to juvenile, but not adult, OD plasticity.

Copy-number analysis identified new prognostic marker in acute myeloid leukemia.

Recent advances in genomic technologies have revolutionized acute myeloid leukemia (AML) understanding by identifying potential novel actionable genomic alterations. Consequently, current risk stratification at diagnosis not only relies on cytogenetics, but also on the inclusion of several of these abnormalities. Despite this progress, AML remains a heterogeneous and complex malignancy with variable response to current therapy. Although copy-number alterations (CNAs) are accepted prognostic markers in cancers, large-scale genomic studies aiming at identifying specific prognostic CNA-based markers in AML are still lacking. Using 367 AML, we identified four recurrent CNA on chromosomes 11 and 21 that predicted outcome even after adjusting for standard prognostic risk factors and potentially delineated two new subclasses of AML with poor prognosis. ERG amplification, the most frequent CNA, was related to cytarabine resistance, a cornerstone drug of AML therapy. These findings were further validated in The Cancer Genome Atlas data. Our results demonstrate that specific CNA are of independent prognostic relevance, and provide new molecular information into the genomic basis of AML and cytarabine response. Finally, these CNA identified two potential novel risk groups of AML, which when confirmed prospectively, may improve the clinical risk stratification and potentially the AML outcome.

Correction: Rural to Urban Population Density Scaling of Crime and Property Transactions in English and Welsh Parliamentary Constituencies.

[This corrects the article DOI: 10.1371/journal.pone.0149546.].

IMA Genome-F 6: Draft genome sequences of Armillaria fuscipes, Ceratocystiopsis minuta, Ceratocystis adiposa, Endoconidiophora laricicola, E. polonica and Penicillium freii DAOMC 242723.

The genomes of Armillaria fuscipes, Ceratocystiopsis minuta, Ceratocystis adiposa, Endoconidiophora laricicola, E. polonica, and Penicillium freii DAOMC 242723 are presented in this genome announcement. These six genomes are from plant pathogens and otherwise economically important fungal species. The genome sizes range from 21 Mb in the case of Ceratocystiopsis minuta to 58 Mb for the basidiomycete Armillaria fuscipes. These genomes include the first reports of genomes for the genus Endoconidiophora. The availability of these genome data will provide opportunities to resolve longstanding questions regarding the taxonomy of species in these genera. In addition these genome sequences through comparative studies with closely related organisms will increase our understanding of how these pathogens cause disease.