Grazing alters the soil nematode communities in grasslands: A meta-analysis.

Grazing causes great disturbances in grassland ecosystems and may change the abundance, diversity, and ecological function of soil biota. Because of their important role in nutrient cycling and as good environmental indicators, nematodes are very representative soil organisms. However, the mechanisms by which grazing intensity, livestock type, duration, and environmental factors (e.g., climate and edaphic factors) affect soil nematodes remain poorly understood. In this study, we collected 1964 paired observations all over the world from 53 studies to clarify the grazing response patterns of soil nematodes and their potential mechanisms. Overall, grazing significantly decreased the abundance of bacterial-feeding (BF) nematodes (-16.54%) and omnivorous-predatory (OP) nematodes (-36.81%), and decreased nematode community diversity indices (Shannon-Weiner index: -4.33%, evenness index: -9.22%, species richness: -5.35%), but had no effect on ecological indices under a global regional scale. The response of soil nematodes to grazing varied by grazing intensity, animals, and duration. Heavy grazing decreased OP nematode abundance, but had no effect on the abundance of other trophic groups, or on diversity or ecological indices. Grazing by small animals had stronger effects than that by large animals and mixed-size animals on BF, fungal-feeding (FF), plant-feeding (PF) and OP nematodes, the Shannon-Wiener index, and the species richness index. The abundance of FF and OP nematodes influenced significantly under short-term grazing. The evenness index decreased significantly under long-term grazing (>10 years). Climate and edaphic factors impacted the effects of grazing on nematode abundance, diversity, and ecological indices. When resources (i.e., rain, heat, and soil nutrients) were abundant, the negative effects of grazing on nematodes were reduced; under sufficiently abundant resources, grazing even had positive effects on soil nematode communities. Thus, the influence of grazing on soil nematode communities is resource-dependent. Our study provides decision makers with grazing strategies based on the resource abundance. Resource-poor areas should have less grazing, while resource-rich areas should have more grazing to conserve soil biodiversity and maintain soil health.

Variations and controlling factors of soil denitrification rate.

The denitrification process profoundly affects soil nitrogen (N) availability and generates its byproduct, nitrous oxide, as a potent greenhouse gas. There are large uncertainties in predicting global denitrification because its controlling factors remain elusive. In this study, we compiled 4301 observations of denitrification rates across a variety of terrestrial ecosystems from 214 papers published in the literature. The averaged denitrification rate was 3516.3 ± 91.1 µg N kg-1  soil day-1 . The highest denitrification rate was 4242.3 ± 152.3 µg N kg-1  soil day-1 under humid subtropical climates, and the lowest was 965.8 ± 150.4 µg N kg-1 under dry climates. The denitrification rate increased with temperature, precipitation, soil carbon and N contents, as well as microbial biomass carbon and N, but decreased with soil clay contents. The variables related to soil N contents (e.g., nitrate, ammonium, and total N) explained the variation of denitrification more than climatic and edaphic variables (e.g., mean annual temperature (MAT), soil moisture, soil pH, and clay content) according to structural equation models. Soil microbial biomass carbon, which was influenced by soil nitrate, ammonium, and total N, also strongly influenced denitrification at a global scale. Collectively, soil N contents, microbial biomass, pH, texture, moisture, and MAT accounted for 60% of the variation in global denitrification rates. The findings suggest that soil N contents and microbial biomass are strong predictors of denitrification at the global scale.

Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex.

Images of visual scenes comprise essential features important for visual cognition of the brain. The complexity of visual features lies at different levels, from simple artificial patterns to natural images with different scenes. It has been a focus of using stimulus images to predict neural responses. However, it remains unclear how to extract features from neuronal responses. Here we address this question by leveraging two-photon calcium neural data recorded from the visual cortex of awake macaque monkeys. With stimuli including various categories of artificial patterns and diverse scenes of natural images, we employed a deep neural network decoder inspired by image segmentation technique. Consistent with the notation of sparse coding for natural images, a few neurons with stronger responses dominated the decoding performance, whereas decoding of ar tificial patterns needs a large number of neurons. When natural images using the model pretrained on artificial patterns are decoded, salient features of natural scenes can be extracted, as well as the conventional category information. Altogether, our results give a new perspective on studying neural encoding principles using reverse-engineering decoding strategies.

Complexity and diversity in sparse code priors improve receptive field characterization of Macaque V1 neurons.

System identification techniques-projection pursuit regression models (PPRs) and convolutional neural networks (CNNs)-provide state-of-the-art performance in predicting visual cortical neurons' responses to arbitrary input stimuli. However, the constituent kernels recovered by these methods are often noisy and lack coherent structure, making it difficult to understand the underlying component features of a neuron's receptive field. In this paper, we show that using a dictionary of diverse kernels with complex shapes learned from natural scenes based on efficient coding theory, as the front-end for PPRs and CNNs can improve their performance in neuronal response prediction as well as algorithmic data efficiency and convergence speed. Extensive experimental results also indicate that these sparse-code kernels provide important information on the component features of a neuron's receptive field. In addition, we find that models with the complex-shaped sparse code front-end are significantly better than models with a standard orientation-selective Gabor filter front-end for modeling V1 neurons that have been found to exhibit complex pattern selectivity. We show that the relative performance difference due to these two front-ends can be used to produce a sensitive metric for detecting complex selectivity in V1 neurons.

Orientation Tuning and End-stopping in Macaque V1 Studied with Two-photon Calcium Imaging.

Orientation tuning is a fundamental response property of V1 neurons and has been extensively studied with single-/multiunit recording and intrinsic signal optical imaging. Long-term 2-photon calcium imaging allows simultaneous recording of hundreds of neurons at single neuron resolution over an extended time in awake macaques, which may help elucidate V1 orientation tuning properties in greater detail. We used this new technology to study the microstructures of orientation functional maps, as well as population tuning properties, in V1 superficial layers of 5 awake macaques. Cellular orientation maps displayed horizontal and vertical clustering of neurons according to orientation preferences, but not tuning bandwidths, as well as less frequent pinwheels than previous estimates. The orientation tuning bandwidths were narrower than previous layer-specific single-unit estimates, suggesting more precise orientation selectivity. Moreover, neurons tuned to cardinal and oblique orientations did not differ in quantities and bandwidths, likely indicating minimal V1 representation of the oblique effect. Our experimental design also permitted rough estimates of length tuning. The results revealed significantly more end-stopped cells at a more superficial 150 µm depth (vs. 300 µm), but unchanged orientation tuning bandwidth with different length tuning. These results will help construct more precise models of V1 orientation processing.

Long-term all-optical interrogation of cortical neurons in awake-behaving nonhuman primates.

Whereas optogenetic techniques have proven successful in their ability to manipulate neuronal populations-with high spatial and temporal fidelity-in species ranging from insects to rodents, significant obstacles remain in their application to nonhuman primates (NHPs). Robust optogenetics-activated behavior and long-term monitoring of target neurons have been challenging in NHPs. Here, we present a method for all-optical interrogation (AOI), integrating optical stimulation and simultaneous two-photon (2P) imaging of neuronal populations in the primary visual cortex (V1) of awake rhesus macaques. A red-shifted channel-rhodopsin transgene (ChR1/VChR1 [C1V1]) and genetically encoded calcium indicators (genetically encoded calmodulin protein [GCaMP]5 or GCaMP6s) were delivered by adeno-associated viruses (AAVs) and subsequently expressed in V1 neuronal populations for months. We achieved optogenetic stimulation using both single-photon (1P) activation of neuronal populations and 2P activation of single cells, while simultaneously recording 2P calcium imaging in awake NHPs. Optogenetic manipulations of V1 neuronal populations produced reliable artificial visual percepts. Together, our advances show the feasibility of precise and stable AOI of cortical neurons in awake NHPs, which may lead to broad applications in high-level cognition and preclinical testing studies.

Advanced Circuit and Cellular Imaging Methods in Nonhuman Primates.

Novel genetically encoded tools and advanced microscopy methods have revolutionized neural circuit analyses in insects and rodents over the last two decades. Whereas numerous technical hurdles originally barred these methodologies from success in nonhuman primates (NHPs), current research has started to overcome those barriers. In some cases, methodological advances developed with NHPs have even surpassed their precursors. One such advance includes new ultra-large imaging windows on NHP cortex, which are larger than the entire rodent brain and allow analysis unprecedented ultra-large-scale circuits. NHP imaging chambers now remain patent for periods longer than a mouse's lifespan, allowing for long-term all-optical interrogation of identified circuits and neurons over timeframes that are relevant to human cognitive development. Here we present some recent imaging advances brought forth by research teams using macaques and marmosets. These include technical developments in optogenetics; voltage-, calcium- and glutamate-sensitive dye imaging; two-photon and wide-field optical imaging; viral delivery; and genetic expression of indicators and light-activated proteins that result in the visualization of tens of thousands of identified cortical neurons in NHPs. We describe a subset of the many recent advances in circuit and cellular imaging tools in NHPs focusing here primarily on the research presented during the corresponding mini-symposium at the 2019 Society for Neuroscience annual meeting.

Convolutional neural network models of V1 responses to complex patterns.

In this study, we evaluated the convolutional neural network (CNN) method for modeling V1 neurons of awake macaque monkeys in response to a large set of complex pattern stimuli. CNN models outperformed all the other baseline models, such as Gabor-based standard models for V1 cells and various variants of generalized linear models. We then systematically dissected different components of the CNN and found two key factors that made CNNs outperform other models: thresholding nonlinearity and convolution. In addition, we fitted our data using a pre-trained deep CNN via transfer learning. The deep CNN's higher layers, which encode more complex patterns, outperformed lower ones, and this result was consistent with our earlier work on the complexity of V1 neural code. Our study systematically evaluates the relative merits of different CNN components in the context of V1 neuron modeling.

Toward ultrasensitive and fast colorimetric detection of indoor formaldehyde across the visible region using cetyltrimethylammonium chloride-capped bone-shaped gold nanorods as "chromophores".

Plasmonic nanostructures have been broadly used for chemical detections, but their applications are limited by slow detection rates, insufficient visual resolution and sensitivity due to the chemical and structural stability of conventional plasmonic nanomaterials. It is thus essential to develop strategies to enhance the detection kinetics while promoting their excellent plasmonic properties. In this work, a colorimetric assay for HCHO measurement is developed based on the fact that HCHO can react with Tollens' reagent to anisotropically deposit a layer of silver shells onto the bone-shaped gold nanorod (Au NR) cores. Compared to the routine rod-shaped Au NRs, the bone-shaped Au NRs facilitate the deposition of Ag onto the sunken section due to their unique concave structures, giving rise to fast reaction kinetics and detection rate. It is also important to point out that the surface ligand exchange from CTAB to CTAC is helpful to accelerate the deposition of silver onto Au NRs, which significantly shortens the reaction time. The preferential deposition of Ag on the concave Au NRs induces more dramatic morphology changes and therefore promotes the plasmonic shift of the bone-shaped Au NRs and improves the sensing efficiency. Correspondingly, the apparent color of the solution changes from light gray to dark blue, purple, red, orange and finally to yellow as the longitudinal localized surface plasmon resonance (LSPR) band shifts from 710 to 500 nm along with the emergence of a new LSPR band at 400 nm almost covering the full visible region. The colorimetric method developed enables sensitive detection of HCHO with a low detection limit (1 nM), wide linear range (0.1-50 µM), high visual resolution and good specificity against other common indoor gases. It was successfully applied to the detection of gaseous HCHO present in the air collected from a furniture plaza, showing its potential practicality for on-site HCHO analysis.

Stretchable Transparent Electrode Arrays for Simultaneous Electrical and Optical Interrogation of Neural Circuits in Vivo.

Recent developments of transparent electrode arrays provide a unique capability for simultaneous optical and electrical interrogation of neural circuits in the brain. However, none of these electrode arrays possess the stretchability highly desired for interfacing with mechanically active neural systems, such as the brain under injury, the spinal cord, and the peripheral nervous system (PNS). Here, we report a stretchable transparent electrode array from carbon nanotube (CNT) web-like thin films that retains excellent electrochemical performance and broad-band optical transparency under stretching and is highly durable under cyclic stretching deformation. We show that the CNT electrodes record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Simultaneous two-photon calcium imaging through the transparent CNT electrodes from cortical surfaces of GCaMP-expressing mice with epilepsy shows individual activated neurons in brain regions from which the concurrent electrical recording is taken, thus providing complementary cellular information in addition to the high-temporal-resolution electrical recording. Notably, the studies on rats show that the CNT electrodes remain operational during and after brain contusion that involves the rapid deformation of both the electrode array and brain tissue. This enables real-time, continuous electrophysiological monitoring of cortical activity under traumatic brain injury. These results highlight the potential application of the stretchable transparent CNT electrode arrays in combining electrical and optical modalities to study neural circuits, especially under mechanically active conditions, which could potentially provide important new insights into the local circuit dynamics of the spinal cord and PNS as well as the mechanism underlying traumatic injuries of the nervous system.

Effect of grazing on methane uptake from Eurasian steppe of China.

BACKGROUND: The effects of grazing on soil methane (CH4) uptake in steppe ecosystems are important for understanding carbon sequestration and cycling because the role of grassland soil for CH4 uptake can have major impacts at the global level. Here, a meta-analysis of 27 individual studies was carried out to assess the response patterns of soil CH4 uptake to grazing in steppe ecosystems of China. The weighted log response ratio was used to assess the effect size. RESULTS: We found that heavy grazing significantly depressed soil CH4 uptake by 36.47%, but light and moderate grazing had no significant effects in grassland ecosystem. The response of grassland soil CH4 uptake to grazing also was found to depend upon grazing intensity, grazing duration and climatic types. The increase in soil temperature and reduced aboveground biomass and soil moisture induced by heavy grazing may be the major regulators of the soil CH4 uptake. CONCLUSIONS: These findings imply that grazing effects on soil CH4 uptake are highly context-specific and that grazing in different grasslands might be managed differently to help mitigate greenhouse gas emissions.

Association between diabetes and risk of suicide death: A meta-analysis of 3 million participants.

BACKGROUND: Results of the relationships between diabetes and the risk of suicide death are inconclusive. This meta-analysis was conducted to assess this association. METHODS: We systematically searched PubMed, EMBASE, Web of Science and the Cochrane Library up to February 29, 2016 for relevant observational studies regarding the association between diabetes and risk of suicide. Random-effects models were used to calculate summary relative risk (RR) and 95% confidence interval (CI). RESULTS: 6 observational studies (8 independent reports) with a total of 3,075,214 participants and 3038 suicide deaths events were included in the meta-analysis. Overall, diabetes was not associated with risk of suicide deaths, with significant heterogeneity among studies observed (Summary RR=1.61, 95% CI: 0.91-2.83, Pheterogeneity<0.001, I2=97.2%). No publication bias was detected across studies, and both the subgroup analysis and sensitivity analysis suggested that the general result was robust. CONCLUSION: Our meta-analysis based on more than 3 million participants indicates that diabetes is not associated with increased risk of suicide death. Further well-designed prospective cohort studies are needed to confirm the findings of this meta-analysis.

Perceptual color map in macaque visual area V4.

Colors distinguishable with trichromatic vision can be defined by a 3D color space, such as red-green-blue or hue-saturation-lightness (HSL) space, but it remains unclear how the cortex represents colors along these dimensions. Using intrinsic optical imaging and electrophysiology, and systematically choosing color stimuli from HSL coordinates, we examined how perceptual colors are mapped in visual area V4 in behaving macaques. We show that any color activates 1-4 separate cortical patches within "globs," millimeter-sized color-preferring modules. Most patches belong to different hue or lightness clusters, in which sequential representations follow the color order in HSL space. Some patches overlap greatly with those of related colors, forming stacks, possibly representing invariable features, whereas few seem positioned irregularly. However, for any color, saturation increases the activity of all its patches. These results reveal how the color map in V4 is organized along the framework of the perceptual HSL space, whereupon different multipatch activity patterns represent different colors. We propose that such distributed and combinatorial representations may expand the encodable color space of small cortical maps and facilitate binding color information to other image features.

Development of a loop-mediated isothermal amplification (LAMP) assay for rapid and specific detection of common genetically modified organisms (GMOs).

Here, we developed a loop-mediated isothermal amplification (LAMP) assay for 11 common transgenic target DNA in GMOs. Six sets of LAMP primer candidates for each target were designed and their specificity, sensitivity, and reproductivity were evaluated. With the optimized LAMP primers, this LAMP assay was simply run within 45-60 min to detect all these targets in GMOs tested. The sensitivity, specificity, and reproductivity of the LAMP assay were further analyzed in comparison with those of Real-Time PCR. In consistent with real-time PCR, detection of 0.5% GMOs in equivalent background DNA was possible using this LAMP assay for all targets. In comparison with real-time PCR, the LAMP assay showed the same results with simple instruments. Hence, the LAMP assay developed can provide a rapid and simple approach for routine screening as well as specific events detection of many GMOs.

Soil nitrogen availability drives the response of soil microbial biomass to warming.

Although soil microbial biomass responses to experimental warming have been extensively studied, the mechanisms through which elevated temperatures influence soil microbial biomass remain unclear. In this study, we performed a global meta-analysis to quantify the global pattern of soil microbial biomass in response to warming. Our findings suggest that global warming effect is not apparent when all the data are pooled together, while warming does increase microbial biomass under specific conditions (Δ°C ≥ 2 °C). This constructive influence is particularly accentuated under certain circumstances, including high precipitation levels (>800 mm), short treatment durations (<1 year), and within agricultural ecosystems. More importantly, our findings suggest that the impact of global warming on soil microbial biomass is largely mediated by changes in soil nitrogen availability. These findings underscore the pivotal role of nitrogen availability in modulating the response of soil microbial biomass to warming, while also emphasizing the intricate influence between multiple factors such as temperature, duration, and precipitation in shaping the patterns of warming effects.

A novel laccase for alkaline medium temperature environments in the textile industry.

Laccases are extensively used in the textile industry due to their ability to decolorize dyes, modify fabric surfaces, and bleach textiles. Identifying a laccase with both high thermal stability and alkali tolerance suitable for textile applications presents a significant challenge. A novel alkaline laccase, LacCT, was discovered from Caldalkalibacillus thermarum and successfully expressed it in Escherichia coli. LacCT displayed optimal activity at 65°C and maintained high stability across a pH range of 6.0-10.0, with an optimal pH of 7.5. Through rational design, the thermal stability of the best variant, G190P/Q254Y/G336M/D510F (LacCT-11), was significantly enhanced, resulting in a half-life of 63.2 min at 60°C - 1.8 times longer than that of the wild type. This research introduces a promising new laccase with considerable potential for decolorizing textile wastewater and improving the ramie degumming process.

Population coding for figure-ground texture segregation in macaque V1 and V4.

Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

Ocular dominance-dependent binocular combination of monocular neuronal responses in macaque V1.

Primates rely on two eyes to perceive depth, while maintaining stable vision when either one eye or both eyes are open. Although psychophysical and modeling studies have investigated how monocular signals are combined to form binocular vision, the underlying neuronal mechanisms, particularly in V1 where most neurons exhibit binocularity with varying eye preferences, remain poorly understood. Here, we used two-photon calcium imaging to compare the monocular and binocular responses of thousands of simultaneously recorded V1 superficial-layer neurons in three awake macaques. During monocular stimulation, neurons preferring the stimulated eye exhibited significantly stronger responses compared to those preferring both eyes. However, during binocular stimulation, the responses of neurons preferring either eye were suppressed on the average, while those preferring both eyes were enhanced, resulting in similar neuronal responses irrespective of their eye preferences, and an overall response level similar to that with monocular viewing. A neuronally realistic model of binocular combination, which incorporates ocular dominance-dependent divisive interocular inhibition and binocular summation, is proposed to account for these findings.

Large-scale calcium imaging reveals a systematic V4 map for encoding natural scenes.

Biological visual systems have evolved to process natural scenes. A full understanding of visual cortical functions requires a comprehensive characterization of how neuronal populations in each visual area encode natural scenes. Here, we utilized widefield calcium imaging to record V4 cortical response to tens of thousands of natural images in male macaques. Using this large dataset, we developed a deep-learning digital twin of V4 that allowed us to map the natural image preferences of the neural population at 100-µm scale. This detailed map revealed a diverse set of functional domains in V4, each encoding distinct natural image features. We validated these model predictions using additional widefield imaging and single-cell resolution two-photon imaging. Feature attribution analysis revealed that these domains lie along a continuum from preferring spatially localized shape features to preferring spatially dispersed surface features. These results provide insights into the organizing principles that govern natural scene encoding in V4.