Soluble ACE2-mediated cell entry of SARS-CoV-2 via interaction with proteins related to the renin-angiotensin system.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can cause acute respiratory disease and multiorgan failure. Finding human host factors that are essential for SARS-CoV-2 infection could facilitate the formulation of treatment strategies. Using a human kidney cell line-HK-2-that is highly susceptible to SARS-CoV-2, we performed a genome-wide RNAi screen and identified virus dependency factors (VDFs), which play regulatory roles in biological pathways linked to clinical manifestations of SARS-CoV-2 infection. We found a role for a secretory form of SARS-CoV-2 receptor, soluble angiotensin converting enzyme 2 (sACE2), in SARS-CoV-2 infection. Further investigation revealed that SARS-CoV-2 exploits receptor-mediated endocytosis through interaction between its spike with sACE2 or sACE2-vasopressin via AT1 or AVPR1B, respectively. Our identification of VDFs and the regulatory effect of sACE2 on SARS-CoV-2 infection shed insight into pathogenesis and cell entry mechanisms of SARS-CoV-2 as well as potential treatment strategies for COVID-19.

Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening.

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma.

A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames (ORFs). To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a stepwise approach using multiple CRISPR-Cas9 screens to elucidate non-canonical ORFs and putative microproteins implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream ORFs (uORFs) exhibited selective functionality independent of main coding sequences. A microprotein encoded by one of these ORFs, ASNSD1-uORF or ASDURF, was upregulated, associated with MYC-family oncogenes, and promoted medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future studies seeking to define new cancer targets.

Needs for a conceptual bridge between biological domestication and early food globalization.

The past 15 y has seen much development in documentation of domestication of plants and animals as gradual traditions spanning millennia. There has also been considerable momentum in understanding the dispersals of major domesticated taxa across continents spanning thousands of miles. The two processes are often considered within different theoretical strains. What is missing from our repertoire of explanations is a conceptual bridge between the protracted process over millennia and the multiregional, globally dispersed nature of domestication. The evidence reviewed in this paper bears upon how we conceptualize domestication as an episode or a process. By bringing together the topics of crop domestication and crop movement, those complex, protracted, and continuous outcomes come more clearly into view.

A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data.

Spatially resolved transcriptomics data are being used in a revolutionary way to decipher the spatial pattern of gene expression and the spatial architecture of cell types. Much work has been done to exploit the genomic spatial architectures of cells. Such work is based on the common assumption that gene expression profiles of spatially adjacent spots are more similar than those of more distant spots. However, related work might not consider the nonlocal spatial co-expression dependency, which can better characterize the tissue architectures. Therefore, we propose MuCoST, a Multi-view graph Contrastive learning framework for deciphering complex Spatially resolved Transcriptomic architectures with dual scale structural dependency. To achieve this, we employ spot dependency augmentation by fusing gene expression correlation and spatial location proximity, thereby enabling MuCoST to model both nonlocal spatial co-expression dependency and spatially adjacent dependency. We benchmark MuCoST on four datasets, and we compare it with other state-of-the-art spatial domain identification methods. We demonstrate that MuCoST achieves the highest accuracy on spatial domain identification from various datasets. In particular, MuCoST accurately deciphers subtle biological textures and elaborates the variation of spatially functional patterns.

Age-dependent seasonal growth cessation in Populus.

In temperate and boreal regions, perennial plants adapt their annual growth cycle to the change of seasons. In natural forests, juvenile seedlings usually display longer growth seasons compared to adult trees to ensure their establishment and survival under canopy shade. However, how trees adjust their annual growth according to their age is not known. In this study, we show that age-dependent seasonal growth cessation is genetically controlled and found that the miR156-SPL3/5 module, a key regulon of vegetative phase change (VPC), also triggers age-dependent growth cessation in Populus trees. We show that miR156 promotes shoot elongation during vegetative growth, and its targets SPL3/5s function in the same pathway but as repressors. We find that the miR156-SPL3/5s regulon controls growth cessation in both leaves and shoot apices and through multiple pathways, but with a different mechanism compared to how the miR156-SPL regulon controls VPC in annual plants. Taken together, our results reveal an age-dependent genetic network in mediating seasonal growth cessation, a key phenological process in the climate adaptation of perennial trees.

Early Initiation of Biologics and Disease Outcomes in Adults and Children With Inflammatory Bowel Diseases: Results From the Epidemiology Group of the Nationwide Israeli Inflammatory Bowel Disease Research Nucleus Cohort.

BACKGROUND & AIMS: In this nationwide study, we explored whether early initiation of biologics is associated with improved outcomes in children and adults with Crohn's disease (CD) and ulcerative colitis (UC). METHODS: All patients diagnosed with CD or UC in Israel (2005-2020) were included in the Epidemiology Group of the Israeli Inflammatory Bowel Disease Research Nucleus cohort, encompassing 98% of the population. We compared disease duration at biologics initiation (ie, 0-3 months, >3-12 months, >1-2 years, and >2-3 years) using the cloning, censoring, and weighting by inverse probabilities method to emulate a target trial, adjusting for time-varying confounders and selection bias. RESULTS: Of the 34,375 included patients (of whom 5240 [15%] were children), 7452 of 19,264 (39%) with CD and 2235 of 15,111 (15%) with UC received biologics. In CD, by 10 years postdiagnosis, the probability of CD-related surgery decreased gradually but modestly with earlier initiation of biologics; a significant difference was noted between >2-3 years (31%) and 0-3 months (18%; P = .02; number needed to treat, 7.7), whereas there was no difference between the 0-3-month and >3-12-month periods. The 10-year probability of steroid dependency for the 0-3-month period (19%) differed both from the >2-3-year (31%; P < .001) and 1-2-year periods (37%; P < .001). In UC, no significant differences in colectomy or steroid dependency rates were observed between the treatment initiation periods. Similar trends were noted in the pediatric population. CONCLUSIONS: Very early initiation of biologics was not associated with some outcomes except for a modest risk reduction of surgery and steroid dependency for CD, which requires confirmation in future studies. In UC, early introduction of biologics was not associated with reduced risk of colectomy or steroid dependency.

The interferon-regulated host factor hnRNPA0 modulates HIV-1 production by interference with LTR activity, mRNA trafficking, and programmed ribosomal frameshifting.

The interplay between host factors and viral components impacts viral replication efficiency profoundly. Members of the cellular heterogeneous nuclear ribonucleoprotein family (hnRNPs) have been extensively studied as HIV-1 host dependency factors, but whether they play a role in innate immunity is currently unknown. This study aimed to identify hnRNPA0 as a type I interferon (IFN)-repressed host factor in HIV-1-infected cells. Knockdown of hnRNPA0, a situation that mirrors conditions under IFN stimulation, increased LTR activity, export of unspliced HIV-1 mRNA, viral particle production, and thus, increased infectivity. Conversely, hnRNPA0 overexpression primarily reduced plasmid-driven and integrated HIV-1 long terminal repeat (LTR) activity, significantly decreasing total viral mRNA and protein levels. In addition, high levels of hnRNPA0 significantly reduced the HIV-1 programmed ribosomal frameshifting efficiency, resulting in a shift in the HIV-1 p55/p15 ratio. The HIV-1 alternative splice site usage remained largely unaffected by altered hnRNPA0 levels suggesting that the synergistic inhibition of the LTR activity and viral mRNA transcription, as well as impaired ribosomal frameshifting efficiency, are critical factors for efficient HIV-1 replication regulated by hnRNPA0. The pleiotropic dose-dependent effects under high or low hnRNPA0 levels were further confirmed in HIV-1-infected Jurkat cells. Finally, our study revealed that hnRNPA0 levels in PBMCs were lower in therapy-naive HIV-1-infected individuals compared to healthy controls. Our findings highlight a significant role for hnRNPA0 in HIV-1 replication and suggest that its IFN-I-regulated expression levels are critical for viral fitness allowing replication in an antiviral environment.IMPORTANCERNA-binding proteins, in particular, heterogeneous nuclear ribonucleoproteins (hnRNPs), have been extensively studied. Some act as host dependency factors for HIV-1 since they are involved in multiple cellular gene expression processes. Our study revealed hnRNPA0 as an IFN-regulated host factor, that is differently expressed after IFN-I treatment in HIV-1 target cells and lower expressed in therapy-naïve HIV-1-infected individuals. Our findings demonstrate the significant pleiotropic role of hnRNPA0 in viral replication: In high concentrations, hnRNPA0 limits viral replication by negatively regulating Tat-LTR transcription, retaining unspliced mRNA in the nucleus, and significantly impairing programmed ribosomal frameshifting. Low hnRNPA0 levels as observed in IFN-treated THP-1 cells, particularly facilitate HIV LTR activity and unspliced mRNA export, suggesting a role in innate immunity in favor of HIV replication. Understanding the mode of action between hnRNPA0 and HIV-1 gene expression might help to identify novel therapeutically strategies against HIV-1 and other viruses.

Sequence-based prediction of pH-dependent protein solubility using CamSol.

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Land-use trajectories for sustainable land system transformations: Identifying leverage points in a global biodiversity hotspot.

Sustainable land-system transformations are necessary to avert biodiversity and climate collapse. However, it remains unclear where entry points for transformations exist in complex land systems. Here, we conceptualize land systems along land-use trajectories, which allows us to identify and evaluate leverage points, i.e., entry points on the trajectory where targeted interventions have particular leverage to influence land-use decisions. We apply this framework in the biodiversity hotspot Madagascar. In the northeast, smallholder agriculture results in a land-use trajectory originating in old-growth forests and spanning from forest fragments to shifting hill rice cultivation and vanilla agroforests. Integrating interdisciplinary empirical data on seven taxa, five ecosystem services, and three measures of agricultural productivity, we assess trade-offs and cobenefits of land-use decisions at three leverage points along the trajectory. These trade-offs and cobenefits differ between leverage points: Two leverage points are situated at the conversion of old-growth forests and forest fragments to shifting cultivation and agroforestry, resulting in considerable trade-offs, especially between endemic biodiversity and agricultural productivity. Here, interventions enabling smallholders to conserve forests are necessary. This is urgent since ongoing forest loss threatens to eliminate these leverage points due to path dependency. The third leverage point allows for the restoration of land under shifting cultivation through vanilla agroforests and offers cobenefits between restoration goals and agricultural productivity. The co-occurring leverage points highlight that conservation and restoration are simultaneously necessary to avert collapse of multifunctional mosaic landscapes. Methodologically, the framework highlights the importance of considering path dependency along trajectories to achieve sustainable land-system transformations.

Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations.

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. α oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while ß oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and ß oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language comprehension. Twenty-two (18 female) Dutch native speakers listened to stories in Dutch and French while MEG was recorded. We used dependency parsing to identify three dependency states at each word: the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed forward models to predict α and ß power from the dependency features. Results showed that dependency features predict α and ß power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in α, while frontal and parietal, higher-order language regions, and motor regions are involved in ß. Critically, α- and ß-band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Because of the temporal similarity of the α-ß responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and ß oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.SIGNIFICANCE STATEMENT It remains unclear whether the proposed functional role of α and ß oscillations in perceptual and motor function is generalizable to higher-level cognitive processes, such as spoken language comprehension. We found that syntactic features predict α and ß power in language-related regions beyond low-level linguistic features when listening to naturalistic speech in a known language. We offer experimental findings that integrate a neuroscientific framework on the role of brain oscillations as "building blocks" with spoken language comprehension. This supports the view of a domain-general role of oscillations across the hierarchy of cognitive functions, from low-level sensory operations to abstract linguistic processes.

Development of autonomic heart rate modulations during childhood and adolescence.

Autonomic control of heart rate is well known in adult subjects, but limited data are available on the development of the heart rate control during childhood and adolescence. Continuous 12-lead electrocardiograms were recorded in 1045 healthy children and adolescents (550 females) aged 4 to 19 years during postural manoeuvres involving repeated 10-min supine, unsupported sitting, and unsupported standing positions. In each position, heart rate was measured, and heart rate variability indices were evaluated (SDNN, RMSSD, and high (HF) and low (LF) frequency components were obtained). Quasi-normalized HF frequency components were defined as qnHF = HF/(HF + LF). These measurements were, among others, related to age using linear regressions. In supine position, heart rate decreases per year of age were significant in both sexes but lower in females than in males. In standing position, these decreases per year of age were substantially lowered. RMSSD and qnHF indices were independent of age in supine position but significantly decreased with age in sitting and standing positions. Correspondingly, LF/HF proportions showed steep increases with age in sitting and standing positions but not in the supine position. The study suggests that baseline supine parasympathetic influence shows little developmental changes during childhood and adolescence but that in young children, sympathetic branch is less responsive to vagal influence. While vagal influences modulate cardiac periods in young and older children equally, they are less able to suppress the sympathetic influence in younger children.

Discovery of a proliferation essential gene signature and actin-like 6A as potential biomarkers for predicting prognosis and neoadjuvant chemotherapy response in triple-positive breast cancer.

BACKGROUND: Patients with triple-positive breast cancer (TPBC) have a higher risk of recurrence and lower survival rates than patients with other luminal breast cancers. However, there are few studies on the predictive biomarkers of prognosis and treatment responses in TPBC. METHODS: Proliferation essential genes (PEGs) were acquired from clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR-Cas9) technology, and cohorts of patients with TPBC were obtained from public databases and our cohort. To develop a TPBC-PEG signature, Cox regression and least absolute shrinkage and selection operator regression analyses were applied. Functional analyses were performed with gene set enrichment analysis. The relationship between candidate genes and neoadjuvant chemotherapy (NACT) sensitivity was explored via real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) on the basis of clinical samples. RESULTS: Among 900 TPBC-PEGs, 437 showed significant differential expression between TPBC and normal tissues. Three prognostic PEGs (actin-like 6A [ACTL6A], chaperonin containing TCP1 subunit 2 [CCT2], and threonyl-TRNA synthetase [TARS]) were identified and used to construct the PEG signature. Patients with high PEG signature scores exhibited a worse overall survival and lower sensitivity to NACT than patients with low PEG signature scores. RT-qPCR results indicated that ACTL6A and CCT2 expression were significantly upregulated in patients who lacked sensitivity to NACT. IHC results showed that the ACTL6A protein was highly expressed in patients with NACT resistance and nonpathological complete responses. CONCLUSIONS: This efficient PEG signature prognostic model can predict the outcomes of TPBC. Furthermore, ACTL6A expression level was associated with the response to NACT, and could serve as an important factor in predicting prognosis and drug sensitivity of patients with TPBC.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω $$ \omega $$ , in addition to the diffusion tensor, D $$ \mathbf{D} $$ , and relaxation, R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , correlations. A D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Computer-assisted semi-rational design enhanced the enzymatic activity and protein stability of Proteinase K in calcium-free conditions.

Wild-type Proteinase K binds to two Ca2+ ions, which play an important role in regulating enzymaticactivity and maintaining protein stability. Therefore, a predetermined concentration of Ca2+ must be added during the use of Proteinase K, which increases its commercial cost. Herein, we addressed this challenge using a computational strategy to engineer a Proteinase K mutant that does not require Ca2+ and exhibits high enzymatic activity and protein stability. In the absence of Ca2+, the best mutant, MT24 (S17W-S176N-D260F), displayed an activity approximately 9.2-fold higher than that of wild-type Proteinase K. It also exhibited excellent protein stability, retaining 56.2 % of its enzymatic activity after storage at 4 °C for 5 days. The residual enzymatic activity was 65-fold higher than that of the wild-type Proteinase K under the same storage conditions. Structural analysis and molecular dynamics simulations suggest that the introduction of new hydrogen bond and π-π stacking at the Ca2+ binding sites due to the mutation may be the reasons for the increased enzymatic activity and stability of MT24.

Magnetic Removal of Micro- and Nanoplastics from Water-from 100 nm to 100 µm Debris Size.

Clean water is one of the most important resources of the planet but human-made contamination with diverse pollutants increases continuously. Microplastics (<5 mm diameter) which can have severe impacts on the environment, are present worldwide. Degradation processes lead to nanoplastics (<1 µm), which are potentially even more dangerous due to their increased bioavailability. State-of-the-art wastewater treatment plants show a deficit in effectively eliminating micro- and nanoplastics (MNP) from water, particularly in the case of nanoplastics. In this work, the magnetic removal of three different MNP types across three orders of magnitude in size (100 nm-100 µm) is investigated systematically. Superparamagnetic iron oxide nanoparticles (SPIONs) tend to attract oppositely charged MNPs and form aggregates that can be easily collected by a magnet. It shows that especially the smallest fractions (100-300 nm) can be separated in ordinary high numbers (1013  mg-1 SPION) while the highest mass is removed for MNP between 2.5 and 5 µm. The universal trend for all three types of MNP can be fitted with a derived model, which can make predictions for optimizing SPIONs for specific size ranges in the future.

Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs.

MOTIVATION: Long noncoding RNAs (lncRNAs) play an important role in the occurrence and development of diseases. Predicting disease-related lncRNAs can help to understand the pathogenesis of diseases deeply. The existing methods mainly rely on multi-source data related to lncRNAs and diseases when predicting the associations between lncRNAs and diseases. There are interdependencies among node attributes in a heterogeneous graph composed of all lncRNAs, diseases and micro RNAs. The meta-paths composed of various connections between them also contain rich semantic information. However, the existing methods neglect to integrate attribute information of intermediate nodes in meta-paths. RESULTS: We propose a novel association prediction model, GSMV, to learn and deeply integrate the global dependencies, semantic information of meta-paths and node-pair multi-view features related to lncRNAs and diseases. We firstly formulate the global representations of the lncRNA and disease nodes by establishing a self-attention mechanism to capture and learn the global dependencies among node attributes. Second, starting from the lncRNA and disease nodes, respectively, multiple meta-pathways are established to reveal different semantic information. Considering that each meta-path contains specific semantics and has multiple meta-path instances which have different contributions to revealing meta-path semantics, we design a graph neural network based module which consists of a meta-path instance encoding strategy and two novel attention mechanisms. The proposed meta-path instance encoding strategy is used to learn the contextual connections between nodes within a meta-path instance. One of the two new attention mechanisms is at the meta-path instance level, which learns rich and informative meta-path instances. The other attention mechanism integrates various semantic information from multiple meta-paths to learn the semantic representation of lncRNA and disease nodes. Finally, a dilated convolution-based learning module with adjustable receptive fields is proposed to learn multi-view features of lncRNA-disease node pairs. The experimental results prove that our method outperforms seven state-of-the-art comparing methods for lncRNA-disease association prediction. Ablation experiments demonstrate the contributions of the proposed global representation learning, semantic information learning, pairwise multi-view feature learning and the meta-path instance encoding strategy. Case studies on three cancers further demonstrate our method's ability to discover potential disease-related lncRNA candidates. CONTACT: zhang@hlju.edu.cn or peiliangwu@ysu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

Aridity-dependent shifts in biodiversity-stability relationships but not in underlying mechanisms.

Climate change will affect the way biodiversity influences the stability of plant communities. Although biodiversity, associated species asynchrony, and species stability could enhance community stability, the understanding of potential nonlinear shifts in the biodiversity-stability relationship across a wide range of aridity (measured as the aridity index, the precipitation/potential evapotranspiration ratio) gradients and the underlying mechanisms remain limited. Using an 8-year dataset from 687 sites in Mongolia, which included 5496 records of vegetation and productivity, we found that the temporal stability of plant communities decreased more rapidly in more arid areas than in less arid areas. The result suggests that future aridification across terrestrial ecosystems may adversely affect community stability. Additionally, we identified nonlinear shifts in the effects of species richness and species synchrony on temporal community stability along the aridity gradient. Species synchrony was a primary driver of community stability, which was consistently negatively affected by species richness while being positively affected by the synchrony between C3 and C4 species across the aridity gradient. These results highlight the crucial role of C4 species in stabilizing communities through differential responses to interannual climate variations between C3 and C4 species. Notably, species richness and the synchrony between C3 and C4 species independently regulated species synchrony, ultimately affecting community stability. We propose that maintaining plant communities with a high diversity of C3 and C4 species will be key to enhancing community stability across Mongolian grasslands. Moreover, species synchrony, species stability, species richness and the synchrony between C3 and C4 species across the aridity gradient consistently mediated the impacts of aridity on community stability. Hence, strategies aimed at promoting the maintenance of biological diversity and composition will help ecosystems adapt to climate change or mitigate its adverse effects on ecosystem stability.

Resting-State fMRI: Emerging Concepts for Future Clinical Application.

Resting-state functional magnetic resonance imaging (rsfMRI) has been developed as a method of investigating spontaneous neural activity. Based on its low-frequency signal synchronization, rsfMRI has made it possible to identify multiple macroscopic structures termed resting-state networks (RSNs) on a single scan of less than 10 minutes. It is easy to implement even in clinical practice, in which assigning tasks to patients can be challenging. These advantages have accelerated the adoption and growth of rsfMRI. Recently, studies on the global rsfMRI signal have attracted increasing attention. Because it primarily arises from physiological events, less attention has hitherto been paid to the global signal than to the local network (i.e., RSN) component. However, the global signal is not a mere nuisance or a subsidiary component. On the contrary, it is quantitatively the dominant component that accounts for most of the variance in the rsfMRI signal throughout the brain and provides rich information on local hemodynamics that can serve as an individual-level diagnostic biomarker. Moreover, spatiotemporal analyses of the global signal have revealed that it is closely and fundamentally associated with the organization of RSNs, thus challenging the basic assumptions made in conventional rsfMRI analyses and views on RSNs. This review introduces new concepts emerging from rsfMRI spatiotemporal analyses focusing on the global signal and discusses how they may contribute to future clinical medicine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Cerebellar Asymmetry of Motivational Direction: Anger-Dependent Effects of Cerebellar Transcranial Direct Current Stimulation on Aggression in Healthy Volunteers.

It has recently been theorized that the frontal asymmetry of approach- and avoidance-related motivation is mirrored in the posterolateral cerebellum. Accordingly, left-to-right dominant cerebellar activity is associated with avoidance-related motivation, whereas right-to-left dominant cerebellar activity is associated with approach-related motivation. The aim of this study was to examine the cerebellar asymmetry of motivational direction in approach-related behavior in the context of aggression. In this randomized double-blind sham-controlled crossover study, thirty healthy right-handed adult volunteers received 2 mA active or sham left cathodal-right anodal transcranial direct current stimulation (tDCS) to the cerebellum on two separate occasions while engaging in the Point Subtraction Aggression Paradigm (PSAP) task to measure aggressive behavior. Self-reported state anger was assessed before, halfway and immediately after the task, and heart rate and heart rate variability (HRV) were measured during the task. No main effects of tDCS on aggressive behavior, heart rate and HRV were found. Higher state anger before and during the PSAP task was associated with increased aggressive behavior in the active compared to sham tDCS condition. Aggressive behavior was positively correlated with heart rate during active tDCS, while an inverse association was observed during sham tDCS. Results provide support for the cerebellar asymmetry of motivational direction in approach-related behavior and illustrate the importance of affective state-dependency in tDCS-related effects.