A prefrontal-habenular circuitry regulates social fear behaviour.

The medial prefrontal cortex (mPFC) has been implicated in the pathophysiology of social impairments including social fear. However, the precise subcortical partners that mediate mPFC dysfunction on social fear behaviour have not been identified. Employing a social fear conditioning paradigm, we induced robust social fear in mice and found that the lateral habenula (LHb) neurons and LHb-projecting mPFC neurons are synchronously activated during social fear expression. Moreover, optogenetic inhibition of the mPFC-LHb projection significantly reduced social fear responses. Importantly, consistent with animal studies, we observed an elevated prefrontal-habenular functional connectivity in subclinical individuals with higher social anxiety characterized by heightened social fear. These results unravel a crucial role of the prefrontal-habenular circuitry in social fear regulation and suggest that this pathway could serve as a potential target for the treatment of social fear symptom often observed in many psychiatric disorders.

Forest carbon stocks increase with higher dominance of ectomycorrhizal trees in high latitude forests.

Understanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.

Milling Stability Prediction: A New Approach Based on a Composited Newton-Cotes Formula.

Based on a composited Newton-Cotes formula, this paper proposes a numerical method to predict milling stability considering regenerative chatter and focusing on rate and prediction accuracy. First, the dynamic model of milling motion is expressed as state-space equations considering regenerative chatter, with the tooth passing period divided into a set of time intervals. Second, a composited Newton-Cotes formula is introduced to calculate the transition function map for each time interval. Third, the state transition matrix is constructed based on the above-mentioned transition function, and the prediction stability boundary is determined by the Floquet theory. Finally, simulation analysis and experimental verification are conducted to verify the effectiveness of the proposed method. The simulation results demonstrate that, for the milling model with a single degree of freedom (DOF), the convergence rate and prediction accuracy of the proposed method are higher than those of the comparison method. The experimental results demonstrate that, for the milling model with two DOFs, the machining parameters below the prediction stability boundary can avoid the chatter as much as possible, ensuring the machined surface quality.

A limited overlap of interactions between the bacterial community of water and sediment in wetland ecosystem of the Yellow River floodplain.

Introduction: Aquatic ecosystems in floodplains provide homes for a variety of active bacterial populations. However, the coexistence pattern of bacterial communities of water and sediment in these ecosystems is unclear. Methods: In the present study, Illumina Mi-Seq sequencing were to assess bacteria's co-occurrence patterns in the water and sediment of different time dynamics and plant communities of the Yellow River floodplain ecosystem. Results and discussion: The results showed that compared to water, the α-diversity of the bacterial community was way greater in sediment. The bacterial community structure significantly differed between water and sediment, and there was a limited overlap of interactions between the bacterial community of water and sediment. In addition, bacteria in water and sediment coexisting show different temporal shifts and community assembly patterns. The water was selected for specific groups of microorganisms that assemble over time in a non-reproducible and non-random way, whereas the sediment environment was relatively stable, and the bacterial communities were gathered randomly. The depth and plant cover significantly influenced the structure of a bacterial community in the sediment. The bacterial community in sediment formed a more robust network than those in water to cope with external changes. These findings improved our comprehension of the ecological trends of water and sediment bacterium colonies coexisting enhanced the biological barrier function, and the capacity of floodplain ecosystems to provide services and offered support for doing so.

Effects of Variation in Tamarix chinensis Plantations on Soil Microbial Community Composition in the Middle Yellow River Floodplain.

Floodplains have important ecological and hydrological functions in terrestrial ecosystems, experience severe soil erosion, and are vulnerable to losing soil fertility. Tamarix chinensis Lour. plantation is the main vegetation restoration measure for maintaining soil quality in floodplains. Soil microorganisms are essential for driving biogeochemical cycling processes. However, the effects of sampling location and shrub patch size on soil microbial community composition remain unclear. In this study, we characterized changes in microbial structure, as well as the factors driving them, in inside- and outside-canopy soils of three patch sizes (small, medium, large) of T. chinensis plants in the middle Yellow River floodplain. Compared with the outside-canopy soils, inside-canopy had higher microbial phospholipid fatty acids (PLFAs), including fungi, bacteria, Gram-positive bacteria (GP), Gram-negative bacteria (GN), and arbuscular mycorrhizal fungi. The ratio of fungi to bacteria and GP to GN gradually decreased as shrub patch size increased. Differences between inside-canopy and outside-canopy soils in soil nutrients (organic matter, total nitrogen, and available phosphorus) and soil salt content increased by 59.73%, 40.75%, 34.41%, and 110.08% from small to large shrub patch size. Changes in microbial community composition were mainly driven by variation in soil organic matter, which accounted for 61.90% of the variation in inside-canopy soils. Resource islands could alter microbial community structure, and this effect was stronger when shrub patch size was large. The results indicated that T. chinensis plantations enhanced the soil nutrient contents (organic matter, total nitrogen, and available phosphorus) and elevated soil microbial biomass and changed microbial community composition; T. chinensis plantations might thus provide a suitable approach for restoring degraded floodplain ecosystems.

Distinct response patterns of plants and soil microorganisms to agronomic practices and seasonal variation in a floodplain ecosystem.

Introduction: Climate change and anthropogenic activities are the greatest threats to floodplain ecosystems. A growing body of literature shows that floodplain ecosystems have experienced increased chemical fertilizer and pesticide loads, which will disturb the above and belowground ecosystems. However, we lack knowledge regarding the effects of such human activities on the vegetation and soil microbiomes in these ecosystems. Methods: In the present study, plant functional traits and Illumina Mi-Seq sequencing were to assess the impact of nitrogen fertilizer and glyphosate addition on the structure and function of the vegetation and soil microbiomes (bacteria, fungi, and protists) in a floodplain ecosystem, and to assess the influence of seasonal variation. Results: We identified distinct response mechanisms of plant and microbial communities to the addition of nitrogen fertilizer and glyphosate, and seasonal variation. Nitrogen fertilizer and glyphosate significantly affected plant diversity, aboveground and underground biomass, and C and N content and significantly changed the leaf area and plant stature of dominant plants. However, the addition of nitrogen fertilizer and glyphosate did not significantly affect the diversity and structure of bacterial, fungal, and protist communities. The application of nitrogen fertilizer could improve the negative effects of glyphosate on the functional traits of plant communities. The seasonal variation of floodplain has significantly changed the soil's physical, chemical, and biological properties. Our results showed that compared with that in summer, the soil ecosystem multifunctionality of the floodplain ecosystem in autumn was significantly lower. Seasonal variation had a significant effect on plant diversity and functional traits. Moreover, seasonal variation significantly affected the community compositions, diversity, and structure of bacteria, fungi, and protists. Seasonal variation had a stronger impact on fungal community assembly than on that of bacteria and protists. In summer, the assembly of the fungal community was dominated by a deterministic process, while in autumn, it is dominated by a stochastic process. In addition, the negative association among bacteria, fungi, and protists has been strengthened in autumn and formed a more robust network to cope with external changes. Discussion: These results extended our understanding of the ecological patterns of soil microbiomes in floodplain ecosystems and provided support for enhancing the ecological barrier function and the service potential of floodplain ecosystems.

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance.

Robotic milling has broad application prospects in many processing fields. However, the milling performance of a robot in a certain posture, such as in face milling or grooving tasks, is extremely sensitive to process parameters due to the influence of the serial structure of the robot system. Improper process parameters are prone to produce machining defects such as low surface quality. These deficiencies substantially decrease the further application development of robotic milling. Therefore, this paper selected a certain posture and carried out the robotic flat-end milling experiments on a 7075-T651 high-strength aeronautical aluminum alloy under dry conditions. Milling load, surface quality and vibration were selected to assess the influence of process parameters like milling depth, spindle speed and feed rate on the milling performance. Most notably, the contribution ratio based on the analysis of variance (ANOVA) was introduced to statistically investigate the relation between parameters and milling performance. The obtained results show that milling depth is highly significant in milling load, which had a contribution ratio of 69.25%. Milling depth is also highly significant in vibration, which had a contribution ratio of 51.41% in the X direction, 41.42% in the Y direction and 75.97% in the Z direction. Moreover, the spindle speed is highly significant in surface roughness, which had a contribution ratio of 48.02%. This present study aims to quantitatively evaluate the influence of key process parameters on robotic milling performance, which helps to select reasonable milling parameters and improve the milling performance of the robot system. It is beneficial to give full play to the advantages of robots and present more possibilities of robot applications in machining and manufacturing.

Predicting Milling Stability Based on Composite Cotes-Based and Simpson's 3/8-Based Methods.

Avoiding chatter in milling processes is critical for obtaining machined parts with high surface quality. In this paper, we propose two methods for predicting the milling stability based on the composite Cotes and Simpson's 3/8 formulas. First, a time-delay differential equation is established, wherein the regenerative effects are considered. Subsequently, it is discretized into a series of integral equations. Based on these integral equations, a transition matrix is determined using the composite Cotes formula. Finally, the system stability is analyzed according to the Floquet theory to obtain the milling stability lobe diagrams. The simulation results demonstrate that for the single degree of freedom (single-DOF) model, the convergence speed of the composite Cotes-based method is higher than that of the semi-discrete method and the Simpson's equation method. In addition, the composite Cotes-based method demonstrates high computational efficiency. Moreover, to further improve the convergence speed, a second method based on the Simpson's 3/8 formula is proposed. The simulation results show that the Simpson's 3/8-based method has the fastest convergence speed when the radial immersion ratio is large; for the two degrees of freedom (two-DOF) model, it performs better in terms of calculation accuracy and efficiency.

Elevated CO2, warming, N addition, and increased precipitation affect different aspects of the arbuscular mycorrhizal fungal community.

The functional diversity of arbuscular mycorrhizal fungi (AMF) affects the resistance and resilience of plant communities to environmental stress. However, considerable uncertainty remains regarding how the complex interactions among elevated atmospheric CO2 (eCO2), nitrogen deposition (eN), precipitation (eP), and warming (eT) affect AMF communities. These global change factors (GCFs) do not occur in isolation, and their interactions likely affect AMF community structure and assembly processes. In this study, the interactive effects of these four GCFs on AMF communities were explored using an open-top chamber field experiment in a semiarid grassland. Elevated CO2, eN, eT, eP, and their interactions did not affect AMF biomass. The relative abundance of Paraglomus increased with N addition across treatment combinations, whereas that of Glomus decreased with N addition, especially combined with eT and eCO2. Precipitation, temperature (T), and N affected AMF phylogenetic α-diversity, and the three-way interaction among CO2, T, and N affected taxonomic and phylogenetic α-diversity. N addition significantly affected the composition of AMF communities. Both variable selection and dispersal limitation played major roles in shaping AMF communities, whereas homogeneous selection and homogenizing dispersal had little effect on AMF community assembly. The contribution of variable selection decreased under eCO2, eN and eT but not under eP. The contribution of dispersal limitation decreased under eCO2, eT, and eP but increased under eN. The assembly of AMF communities under the sixteen GCF combinations was strongly affected by dispersal limitation, variable selection and ecological drift. Elevated CO2, warming, N addition, and increased precipitation affected different aspects of AMF communities. The interactive effects of the four GCFs on AMF communities were limited. Overall, the results of this study suggest that AMF communities in semiarid grasslands can resist changes in global climate.

Cell type-differential modulation of prefrontal cortical GABAergic interneurons on low gamma rhythm and social interaction.

Prefrontal GABAergic interneurons (INs) are crucial for social behavior by maintaining excitation/inhibition balance. However, the underlying neuronal correlates and network computations are poorly understood. We identified distinct firing patterns of prefrontal parvalbumin (PV) INs and somatostatin (SST) INs upon social interaction. Moreover, social interaction closely correlated with elevated gamma rhythms particularly at low gamma band (20 to 50 Hz). Pharmacogenetic inhibition of PV INs, instead of SST INs, reduced low gamma power and impaired sociability. Optogenetic synchronization of either PV INs or SST INs at low gamma frequency improved sociability, whereas high gamma frequency or random frequency stimulation had no effect. These results reveal a functional differentiation among IN subtypes and suggest the importance of low gamma rhythms in social interaction behavior. Furthermore, our findings underscore previously unrecognized potential of SST INs as therapeutic targets for social impairments commonly observed in major neuropsychiatric disorders.

Identified plasma proteins related to vascular structure are associated with coarctation of the aorta in children.

BACKGROUND: Coarctation of the aorta (CoA), presenting with local stenosis of the aorta is involved in many cardiovascular processes. However, there has been little research on the mechanism of coarctation of the aorta. METHODS: Altered proteins were identified by isobaric tag for relative and absolute quantitation (iTRAQ) technology in 8 participants, and further analysed by heatmap, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and Search Tool for the Retrieval of Interacting Gene (STRING). Of these, two vascular structure-related proteins were further validated by using enzyme-linked immunosorbent assay (ELISA) in a new cohort of CoA patients. RESULTS: 39 differentially expressed plasma proteins were first identified in patients with coarctation of the aorta by iTRAQ. Of these, fibulin-1 (FBLN1) and insulin-like growth factor-binding protein complex acid labile subunit (ALS) were considered candidates and further validation also showed that the level of FBLN1 in the CoA group (8.92 ± 2.36 µg/ml) was significantly higher compared with control group (6.13 ± 1.94 µg/ml), and the level of ALS in CoA children (348.08 ± 216.74 ng/ml) was significantly lower than the level in normal children (619.46 ± 274.08 ng/ml). CONCLUSIONS: The differentially expressed proteins identified in the plasma from CoA patients indicated that they may play critical roles in CoA and that they could potentially be utilized as biomarkers for diagnosis. Altered vascular related proteins were associated with COA. These results provide a foundation for further understanding and studying the aetiology and pathogenesis of coarctation of the aorta.

Friction and Wear Mechanism Analysis of Polymer Flexible Cable Using a High Natural Frequency Piezoelectric Sensor.

The friction and wear of flexible cables are the main factors that cause electrical breakdown and insulation aging, and they greatly reduce the reliability and safety of robots. In order to enhance the reliability and safety of the robot, it is of great necessity to investigate the friction and wear mechanisms of the flexible cable. In this research, the friction and wear mechanisms have been discussed. The effects of relative speed, ambient temperature, and positive pressure on the flexible cables are considered by an orthogonal frictional movement. The cable friction force has been measured by a piezoelectric sensor with high natural frequency characteristics. The relations among friction and different factors affecting friction have also been discussed. The results show that the relative speed and the ambient temperature are the main factors affecting the friction and wear of the cable; the main form of flexible cable wear is mechanical-force chemical friction and wear. Those discoveries will greatly deepen the understanding of the friction and wear mechanisms of flexible cables, and will be beneficial to robot cable-reliability design.

A Disinhibitory Microcircuit Mediates Conditioned Social Fear in the Prefrontal Cortex.

Fear behavior is under tight control of the prefrontal cortex, but the underlying microcircuit mechanism remains elusive. In particular, it is unclear how distinct subtypes of inhibitory interneurons (INs) within prefrontal cortex interact and contribute to fear expression. We employed a social fear conditioning paradigm and induced robust social fear in mice. We found that social fear is characterized by activation of dorsal medial prefrontal cortex (dmPFC) and is largely diminished by dmPFC inactivation. With a combination of in vivo electrophysiological recordings and fiber photometry together with cell-type-specific pharmacogenetics, we further demonstrated that somatostatin (SST) INs suppressed parvalbumin (PV) INs and disinhibited pyramidal cells and consequently enhanced dmPFC output to mediate social fear responses. These results reveal a previously unknown disinhibitory microcircuit in prefrontal cortex through interactions between IN subtypes and suggest that SST INs-mediated disinhibition represents an important circuit mechanism in gating social fear behavior.