Temporal Trend in SARS-CoV-2 Symptoms in Pregnant Women

Objective The objective of this study was to examine temporal trends in the clinical presentation of patients diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in pregnancy. Study Design This is a retrospective cohort study of pregnant women who were universally screened for SARS-CoV-2 and tested positive. This multi-center study of admissions to labor and delivery units in New York City and Long Island included all SARS-CoV-2-infected pregnant women admitted to labor and delivery units between April 10th and June 4th 2020. Six Northwell Health hospitals and Maimonides Medical Center were included in the study. The main measures of the study included patient reports of COVID-19 symptoms: fever, cough, chest pain, shortness of breath, nausea, vomiting, and intensive care unit (ICU) admissions. The main outcome measure was the percentage of all infected women who reported any of the above symptoms. Results In total, 427 infected pregnant women were included in the study. There was a statistically significant decline in the percentage of patients presenting with any symptoms over the course of the study. In addition, disease severity, symptoms of fever, cough, and chest pain/shortness of breath also significantly declined over time, and no ICU admissions were noted after the third week of April. Conclusions There was a temporal shift away from symptomatic presentation in pregnant women diagnosed with SARS-CoV-2 over the course of the first months of the epidemic in New York. Further studies are necessary to elucidate the cause of this change in presentation among pregnant women, to determine whether this trend is also observed in other patient populations. Key Points

Temporal Development and Regeneration Dynamics of Restored Urban Forests

<p>Urban forest restoration programmes are a key tool used to initiate, re-create or accelerate the succession of forest species; improving ecosystem services, function, resilience and biodiversity. Succession is a temporal shift in species dominance driven by abiotic and biotic influences, but over decadal timescales the trajectory and success of restoration plantings in degraded urban environments can be hindered. To facilitate the successful reconstruction of forest ecosystems from scratch, an understanding of the temporal patterns in planted forest development, dynamics of seedling regeneration and dominant drivers of seedling diversity is required. Using a chronosequence approach, permanent plots were established at 44 restored urban forests aged 5 to 59 years since initial plantings took place, across five New Zealand cities between Wellington and Invercargill. Vegetation surveys were undertaken and data on micro-climate were collected. This study examined the 1) temporal dynamics of restored urban forest development and seedling regeneration and 2) dominant drivers of seedling regeneration. Data were analysed using linear regression models, breakpoint analysis and mixed-effects modelling. Early forest development (<20 years) exhibited the most changes in canopy composition and structure, forest floor dynamics, seedling community and microclimate. This period saw significant increases in canopy stem abundance, height, basal area and leaf litter cover. Significant declines occurred for light transmittance, herbaceous cover and daily soil and air temperature range within the same timeframe. Dominant traits amongst the seedling community included early successional species, tree species, shade and drought tolerant species, insect-pollinated species and frugivory dispersed species. Seedlings with these traits had higher species richness levels across the whole chronosequence. Collectively, five biotic drivers representing forest composition, structure and landscape factors strongly influenced seedling diversity. Seedling diversity increased with the proportion of surrounding natural landcover, sapling diversity, basal area, canopy diversity and herbaceous cover. The influence of these predictors of seedling diversity, was more significant when modelled as a set, than when viewed independently. Geographic location (city) was indicated as a stronger predictor for similarities in canopy and seedling community composition than the age of the restoration planting. This was shown by stronger clustering of sites according to their city, more so than forest planting age, in a non-metric multidimensional scaling analysis. Our results provide valuable insight to restoration practitioners on the outcomes of urban restoration programmes implemented across much of New Zealand and helps close the gap between the science of restoration ecology and the practice of ecological restoration.</p>

Temporal Development and Regeneration Dynamics of Restored Urban Forests

<p>Urban forest restoration programmes are a key tool used to initiate, re-create or accelerate the succession of forest species; improving ecosystem services, function, resilience and biodiversity. Succession is a temporal shift in species dominance driven by abiotic and biotic influences, but over decadal timescales the trajectory and success of restoration plantings in degraded urban environments can be hindered. To facilitate the successful reconstruction of forest ecosystems from scratch, an understanding of the temporal patterns in planted forest development, dynamics of seedling regeneration and dominant drivers of seedling diversity is required. Using a chronosequence approach, permanent plots were established at 44 restored urban forests aged 5 to 59 years since initial plantings took place, across five New Zealand cities between Wellington and Invercargill. Vegetation surveys were undertaken and data on micro-climate were collected. This study examined the 1) temporal dynamics of restored urban forest development and seedling regeneration and 2) dominant drivers of seedling regeneration. Data were analysed using linear regression models, breakpoint analysis and mixed-effects modelling. Early forest development (<20 years) exhibited the most changes in canopy composition and structure, forest floor dynamics, seedling community and microclimate. This period saw significant increases in canopy stem abundance, height, basal area and leaf litter cover. Significant declines occurred for light transmittance, herbaceous cover and daily soil and air temperature range within the same timeframe. Dominant traits amongst the seedling community included early successional species, tree species, shade and drought tolerant species, insect-pollinated species and frugivory dispersed species. Seedlings with these traits had higher species richness levels across the whole chronosequence. Collectively, five biotic drivers representing forest composition, structure and landscape factors strongly influenced seedling diversity. Seedling diversity increased with the proportion of surrounding natural landcover, sapling diversity, basal area, canopy diversity and herbaceous cover. The influence of these predictors of seedling diversity, was more significant when modelled as a set, than when viewed independently. Geographic location (city) was indicated as a stronger predictor for similarities in canopy and seedling community composition than the age of the restoration planting. This was shown by stronger clustering of sites according to their city, more so than forest planting age, in a non-metric multidimensional scaling analysis. Our results provide valuable insight to restoration practitioners on the outcomes of urban restoration programmes implemented across much of New Zealand and helps close the gap between the science of restoration ecology and the practice of ecological restoration.</p>

Neuronal population activity dynamics reveal a low-dimensional signature of operant learning

Learning engages a high-dimensional neuronal population space spanning multiple brain regions. We identified a low-dimensional signature associated with operant conditioning, a ubiquitous form of learning in which animals learn from the consequences of behavior. Using single-neuron resolution voltage imaging, we identified two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Our findings point to a temporal shift in module recruitment as the primary signature of operant learning.

Altered temporal sequence of transcriptional regulators in the generation of human cerebellar granule cells

Brain development is regulated by conserved transcriptional programs across species, but little is known about divergent mechanisms that create species-specific characteristics. Among brain regions, human cerebellar histogenesis differs in complexity compared with non-human primates and rodents, making it important to develop methods to generate human cerebellar neurons that closely resemble those in the developing human cerebellum. We report a rapid protocol for the derivation of the human ATOH1 lineage, the precursor of excitatory cerebellar neurons, from human pluripotent stem cells (hPSC). Upon transplantation into juvenile mice, hPSC-derived cerebellar granule cells migrated along glial fibers and integrated into the cerebellar cortex. By Translational Ribosome Affinity Purification-seq, we identified an unexpected temporal shift in the expression of RBFOX3 (NeuN) and NEUROD1, which are classically associated with differentiated neurons, in the human outer external granule layer. This molecular divergence may enable the protracted development of the human cerebellum compared to mice.

There Is No ‘Rule of Thumb’: Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates

The application of high-density polymorphic single-nucleotide polymorphisms (SNP) markers derived from high-throughput sequencing methods has heralded plenty of biological questions about the linkages of processes operating at micro- and macroevolutionary scales. However, the effects of SNP filtering practices on population genetic inference have received much less attention. By performing sensitivity analyses, we empirically investigated how decisions about the percentage of missing data (MD) and the minor allele frequency (MAF) set in bioinformatic processing of genomic data affect direct (i.e., parentage analysis) and indirect (i.e., fine-scale spatial genetic structure – SGS) gene flow estimates. We focus specifically on these manifestations in small plant populations, and particularly, in the rare tropical plant species Dinizia jueirana-facao, where assumptions implicit to analytical procedures for accurate estimates of gene flow may not hold. Avoiding biases in dispersal estimates are essential given this species is facing extinction risks due to habitat loss, and so we also investigate the effects of forest fragmentation on the accuracy of dispersal estimates under different filtering criteria by testing for recent decrease in the scale of gene flow. Our sensitivity analyses demonstrate that gene flow estimates are robust to different setting of MAF (0.05–0.35) and MD (0–20%). Comparing the direct and indirect estimates of dispersal, we find that contemporary estimates of gene dispersal distance (σrt = 41.8 m) was ∼ fourfold smaller than the historical estimates, supporting the hypothesis of a temporal shift in the scale of gene flow in D. jueirana-facao, which is consistent with predictions based on recent, dramatic forest fragmentation process. While we identified settings for filtering genomic data to avoid biases in gene flow estimates, we stress that there is no ‘rule of thumb’ for bioinformatic filtering and that relying on default program settings is not advisable. Instead, we suggest that the approach implemented here be applied independently in each separate empirical study to confirm appropriate settings to obtain unbiased population genetics estimates.

Evolution of antigen-specific follicular helper T cell transcriptional programs across effector function and through to memory

Understanding how follicular helper T cells (TFH) regulate the specialization, maturation, and differentiation of adaptive B cell immunity is crucial for developing durable high-affinity immune protection. Using indexed-single cell molecular strategies, we reveal a skewed intra-clonal assortment of higher affinity TCR and the distinct molecular programming of the localized TFH compartment compared to emigrant conventional effector TH (ETH) cells. We find a temporal shift in BCR class switch which permits identification of inflammatory and anti-inflammatory modules of transcriptional programming that subspecialize TFH function before and during the germinal center (GC) reaction. Late collapse of this local primary GC reaction reveals a persistent post-GC TFH population which discloses a putative memory TFH program. These studies define specialized antigen-specific TFH transcriptional programs that progressively direct class-specific evolution of high-affinity B cell immunity and uncover the transcriptional program of a memory TFH population as the regulators of antigen recall.Graphical AbstractSummaryDistinct inflammatory and anti-inflammatory antigen-specific TFH transcriptional programs regulate class-specific B cell maturation.Highlights- Skewed intra-clonal assortment of high affinity TCR into the TFH compartment- Significant temporal delay in anti-inflammatory IgG1 production- Inflammatory and anti-inflammatory transcriptional modules subspecialize TFH- Late GC collapse reveals a persisting post-GC putative memory TFH compartment

Optimizing the Amplifier Bandwidth for Pulse Reception

<p>Detecting and recognizing pulses is a critical task, in fields as widely separated as telecommunications, lidar, and target illumination. In all cases, the signal-to-noise ratio (SNR) is a key parameter that can be used to determine both the potential rate of errors and the probability of correct detection. In this paper the relationship among pulse width, amplifier bandwidth, and SNR is determined through modeling four approximations to pulse shapes and four amplifier lowpass filter configurations. The analysis determined that, given a specific filter and pulse shape, the bandwidth that maximizes SNR is a constant divided by the pulse width. For example, if the pulse has a Gaussian shape and the amplifier incorporates a second-order Chebyshev lowpass filter, this constant is 0.3389. Applying this, if the pulse width is 20 ns the maximum SNR comes for a filter bandwidth of 16.95 MHz, while if the pulse width is 50 µs the SNR is maximized at a 6.778-kHz bandwidth. Passing the signal through a filter also distorts the signal shape; the temporal shift and pulse lengthening are also determined. The calculated values are offered as inputs to a potential trade space that includes SNR, pulse distortion by the filter, and cost.</p>

Optimizing the Amplifier Bandwidth for Pulse Reception

<p>Detecting and recognizing pulses is a critical task, in fields as widely separated as telecommunications, lidar, and target illumination. In all cases, the signal-to-noise ratio (SNR) is a key parameter that can be used to determine both the potential rate of errors and the probability of correct detection. In this paper the relationship among pulse width, amplifier bandwidth, and SNR is determined through modeling four approximations to pulse shapes and four amplifier lowpass filter configurations. The analysis determined that, given a specific filter and pulse shape, the bandwidth that maximizes SNR is a constant divided by the pulse width. For example, if the pulse has a Gaussian shape and the amplifier incorporates a second-order Chebyshev lowpass filter, this constant is 0.3389. Applying this, if the pulse width is 20 ns the maximum SNR comes for a filter bandwidth of 16.95 MHz, while if the pulse width is 50 µs the SNR is maximized at a 6.778-kHz bandwidth. Passing the signal through a filter also distorts the signal shape; the temporal shift and pulse lengthening are also determined. The calculated values are offered as inputs to a potential trade space that includes SNR, pulse distortion by the filter, and cost.</p>