Management options influence seasonal CO2 soil emissions in Mediterranean olive ecosystems

Field trials were conducted at traditional Mediterranean olive agro-ecosystems grown at two locations (Italy –IT, Greece –GR). Groves were managed for many years using sustainable (S, cover crops, compost application, mulching of pruning biomass) or conventional (C) practices (e.g., soil tillage, burning of pruning residuals). The IT grove was rainfed (RAIN) while the GR was irrigated (IRR). This study examined the seasonal variation of soil CO2 emission (Rs) to explore the effect of the management options (C, S) on Rs at both sites. The second aim was to test the hypothesis that the seasonal Rs is differentially modulated by soil temperature and moisture, namely that (i) soil moisture limits Rs when it is below the lower limit of the readily available water (RAWLLim) and (ii) soil temperature above a threshold (max_T) reduces Rs even if soil moisture is non limiting. On the whole-season basis, the mean Rs rate at the rainfed site was 2.17 ± 0.06 (SE) at CRAIN and 2.32 ± 0.06 μmol CO2 m−2 s–1 at SRAIN plot, while at the irrigated site Rs was about 3.64 ± 0.11 (CIRR) and 4.05 ± 0.15 μmol CO2 m−2 s–1 (SIRR). The seasonal oscillation of Rs was consistent across locations and partitionable in three periods according to DOY (Day of Year) interval: Phase I (DOY 20–103 –GR; 20–118 -IT), Phase II (DOY 141÷257, GR; 142–257, IT) and Phase III (DOY 291–357, GR; 286–350, -IT). Pooling all the Rs data across sites and managements, max_T was ∼ 20 °C discriminating a differential response of Rs when soil moisture was < or > RAWLLim. These differential modulations exerted by temperature and moisture were integrated into a conditional model developed with a repeated random subsampling cross-validation procedure to effectively (R2 = 0.84) predict Rs. This paper mechanistically describes the interaction of the environment (soil moisture and temperature) and the management options (S, C) under various moisture conditions on Rs and would support carbon flux accounting procedures (e.g., regulating ecosystem services) tailored to the estimation of sink/source capability of traditional olive agro-ecosystem within environmental-friendly agricultural domains

Quantitative identification of functional connectivity disturbances in neuropsychiatric lupus based on resting-state fMRI: a robust machine learning approach

Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These connections were subsequently filtered through rigorous surrogate analysis, a technique borrowed from physics, novel to neuroimaging. Next, global as well as nodal network metrics were estimated for each individual functional brain network and were input to a robust machine learning algorithm consisting of a random forest feature selection and nested cross-validation strategy. The proposed pipeline is data-driven in its entirety, and several tests were performed in order to ensure model robustness. The best-fitting model utilizing nodal graph metrics for 11 brain regions was associated with 73.5% accuracy (74.5% sensitivity and 73% specificity) in discriminating NPSLE from healthy individuals with adequate statistical power. Closer inspection of graph metric values suggested an increased role within the functional brain network in NSPLE (indicated by higher nodal degree, local efficiency, betweenness centrality, or eigenvalue efficiency) as compared to healthy controls for seven brain regions and a reduced role for four areas. These findings corroborate earlier work regarding hemodynamic disturbances in these brain regions in NPSLE. The validity of the results is further supported by significant associations of certain selected graph metrics with accumulated organ damage incurred by lupus, with visuomotor performance and mental flexibility scores obtained independently from NPSLE patients. View Full-Text Keywords: neuropsychiatric systemic lupus erythematosus; rs-fMRI; graph theory; functional connectivity; surrogate data; machine learning; visuomotor ability; mental flexibilit

The effect of self‐generated versus externally generated actions on timing, duration, and amplitude of blood oxygen level dependent response for visual feedback processing

It has been widely assumed that internal forward models use efference copies to create predictions about the sensory consequences of our own actions. While these predictions have frequently been associated with a reduced blood oxygen level dependent (BOLD) response in sensory cortices, the timing and duration of the hemodynamic response for the processing of video feedback of self-generated (active) versus externally generated (passive) movements is poorly understood. In the present study, we tested the hypothesis that predictive mechanisms for self-generated actions lead to early and shorter neural processing compared with externally generated movements. We investigated active and passive movements using a custom-made fMRI-compatible movement device. Visual video feedback of the active and passive movements was presented in real time or with variable delays. Participants had to judge whether the feedback was delayed. Timing and duration of BOLD impulse response was calculated using a first (temporal derivative [TD]) and second-order (dispersion derivative [DD]) Taylor approximation. Our reanalysis confirmed our previous finding of reduced BOLD response for active compared to passive movements. Moreover, we found positive effects of the TD and DD in the supplementary motor area, cerebellum, visual cortices, and subcortical structures, indicating earlier and shorter hemodynamic responses for active compared to passive movements. Furthermore, earlier activation in the putamen for active compared to passive conditions was associated with reduced delay detection performance. These findings indicate that efference copy-based predictive mechanisms enable earlier processing of action feedback, which might have reduced the ability to detect short delays between action and feedback

Lotus japonicus contains two distinct ENOD40 genes that are expressed in symbiotic, nonsymbiotic, and embryonic tissues

ENOD40, an early nodulin gene, has been postulated to play a significant role in legume root nodule ontogenesis, We have isolated two distinct ENOD40 genes from Lotus japonicus, The transcribed regions of the two ENOD40 genes share 65% homology, while the two promoters showed no significant homology, Both transcripts encode a putative dodecapeptide similar to that identified in other legumes forming determinate nodules, Both ENOD40 genes are coordinately expressed following inoculation of roots with Mesorhizobium loti or treatment with purified Nod factors. In the former case, mRNA accumulation could be detected up to 10 days following inoculation while in the latter case the accumulation was transient. High levels of both ENOD40 gene transcripts were found in nonsymbiotic tissues such as stems, fully developed flowers, green seed pods, and hypocotyls, A relatively lower level of both transcripts was observed in leaves, roots, and cotyledons. In situ hybridization studies revealed that, in mature nodules, transcripts of both ENOD40 genes accumulate in the nodule vascular system; additionally, in young seed pods strong signal is observed in the ovule, particularly In the phloem and epithelium, as well as in globular stage embryos.Animal science

Anxiety and depression severity in neuropsychiatric SLE are associated with perfusion and functional connectivity changes of the frontolimbic neural circuit: a resting-state f(unctional) MRI study.

peer reviewed[en] OBJECTIVE: To examine the hypothesis that perfusion and functional connectivity disturbances in brain areas implicated in emotional processing are linked to emotion-related symptoms in neuropsychiatric SLE (NPSLE). METHODS: Resting-state fMRI (rs-fMRI) was performed and anxiety and/or depression symptoms were assessed in 32 patients with NPSLE and 18 healthy controls (HC). Whole-brain time-shift analysis (TSA) maps, voxel-wise global connectivity (assessed through intrinsic connectivity contrast (ICC)) and within-network connectivity were estimated and submitted to one-sample t-tests. Subgroup differences (high vs low anxiety and high vs low depression symptoms) were assessed using independent-samples t-tests. In the total group, associations between anxiety (controlling for depression) or depression symptoms (controlling for anxiety) and regional TSA or ICC metrics were also assessed. RESULTS: Elevated anxiety symptoms in patients with NPSLE were distinctly associated with relatively faster haemodynamic response (haemodynamic lead) in the right amygdala, relatively lower intrinsic connectivity of orbital dlPFC, and relatively lower bidirectional connectivity between dlPFC and vmPFC combined with relatively higher bidirectional connectivity between ACC and amygdala. Elevated depression symptoms in patients with NPSLE were distinctly associated with haemodynamic lead in vmPFC regions in both hemispheres (lateral and medial orbitofrontal cortex) combined with relatively lower intrinsic connectivity in the right medial orbitofrontal cortex. These measures failed to account for self-rated, milder depression symptoms in the HC group. CONCLUSION: By using rs-fMRI, altered perfusion dynamics and functional connectivity was found in limbic and prefrontal brain regions in patients with NPSLE with severe anxiety and depression symptoms. Although these changes could not be directly attributed to NPSLE pathology, results offer new insights on the pathophysiological substrate of psychoemotional symptomatology in patients with lupus, which may assist its clinical diagnosis and treatment

Converging evidence of impaired brain function in systemic lupus erythematosus: changes in perfusion dynamics and intrinsic functional connectivity.

peer reviewed[en] PURPOSE: Τhe study examined changes in hemodynamics and functional connectivity in patients with systemic lupus erythematosus (SLE) with or without neuropsychiatric manifestations. METHODS: Participants were 44 patients with neuropsychiatric SLE (NPSLE), 20 SLE patients without such manifestations (non-NPSLE), and 35 healthy controls. Resting-state functional MRI (rs-fMRI) was used to obtain whole-brain maps of (a) perfusion dynamics derived through time shift analysis (TSA), (b) regional functional connectivity (intrinsic connectivity contrast (ICC) coefficients), and (c) hemodynamic-connectivity coupling. Group differences were assessed through independent samples t-tests, and correlations of rs-fMRI indices with clinical variables and neuropsychological test scores were, also, computed. RESULTS: Compared to HC, NPSLE patients demonstrated intrinsic hypoconnectivity of anterior Default Mode Network (DMN) and hyperconnectivity of posterior DMN components. These changes were paralleled by elevated hemodynamic lag. In NPSLE, cognitive performance was positively related to higher intrinsic connectivity in these regions, and to higher connectivity-hemodynamic coupling in posterior DMN components. Uncoupling between hemodynamics and connectivity in the posterior DMN was associated with worse task performance. Non-NPSLE patients displayed hyperconnectivity in posterior DMN and sensorimotor regions paralleled by relatively increased hemodynamic lag. CONCLUSION: Adaptation of regional brain function to hemodynamic changes in NPSLE may involve locally decreased or locally increased intrinsic connectivity (which can be beneficial for cognitive function). This process may also involve elevated coupling of hemodynamics with functional connectivity (beneficial for cognitive performance) or uncoupling, which may be detrimental for the cognitive skills of NPSLE patients

Chronic Mild Traumatic Brain Injury: Aberrant Static and Dynamic Connectomic Features Identified Through Machine Learning Model Fusion.

peer reviewedTraumatic Brain Injury (TBI) is a frequently occurring condition and approximately 90% of TBI cases are classified as mild (mTBI). However, conventional MRI has limited diagnostic and prognostic value, thus warranting the utilization of additional imaging modalities and analysis procedures. The functional connectomic approach using resting-state functional MRI (rs-fMRI) has shown great potential and promising diagnostic capabilities across multiple clinical scenarios, including mTBI. Additionally, there is increasing recognition of a fundamental role of brain dynamics in healthy and pathological cognition. Here, we undertake an in-depth investigation of mTBI-related connectomic disturbances and their emotional and cognitive correlates. We leveraged machine learning and graph theory to combine static and dynamic functional connectivity (FC) with regional entropy values, achieving classification accuracy up to 75% (77, 74 and 76% precision, sensitivity and specificity, respectively). As compared to healthy controls, the mTBI group displayed hypoconnectivity in the temporal poles, which correlated positively with semantic (r = 0.43, p < 0.008) and phonemic verbal fluency (r = 0.46, p < 0.004), while hypoconnectivity in the right dorsal posterior cingulate correlated positively with depression symptom severity (r = 0.54, p < 0.0006). These results highlight the importance of residual FC in these regions for preserved cognitive and emotional function in mTBI. Conversely, hyperconnectivity was observed in the right precentral and supramarginal gyri, which correlated negatively with semantic verbal fluency (r=-0.47, p < 0.003), indicating a potential ineffective compensatory mechanism. These novel results are promising toward understanding the pathophysiology of mTBI and explaining some of its most lingering emotional and cognitive symptoms

Tomato TILLING Technology: Development of a Reverse Genetics Tool for the Efficient Isolation of Mutants from Micro-Tom Mutant Libraries

To accelerate functional genomic research in tomato, we developed a Micro-Tom TILLING (Targeting Induced Local Lesions In Genomes) platform. DNA pools were constructed from 3,052 ethyl methanesulfonate (EMS) mutant lines treated with 0.5 or 1.0% EMS. The mutation frequency was calculated by screening 10 genes. The 0.5% EMS population had a mild mutation frequency of one mutation per 1,710 kb, whereas the 1.0% EMS population had a frequency of one mutation per 737 kb, a frequency suitable for producing an allelic series of mutations in the target genes. The overall mutation frequency was one mutation per 1,237 kb, which affected an average of three alleles per kilobase screened. To assess whether a Micro-Tom TILLING platform could be used for efficient mutant isolation, six ethylene receptor genes in tomato (SlETR1–SlETR6) were screened. Two allelic mutants of SlETR1 (Sletr1-1 and Sletr1-2) that resulted in reduced ethylene responses were identified, indicating that our Micro-Tom TILLING platform provides a powerful tool for the rapid detection of mutations in an EMS mutant library. This work provides a practical and publicly accessible tool for the study of fruit biology and for obtaining novel genetic material that can be used to improve important agronomic traits in tomato

Multitrophic Interaction in the Rhizosphere of Maize: Root Feeding of Western Corn Rootworm Larvae Alters the Microbial Community Composition

BACKGROUND: Larvae of the Western Corn Rootworm (WCR) feeding on maize roots cause heavy economical losses in the US and in Europe. New or adapted pest management strategies urgently require a better understanding of the multitrophic interaction in the rhizosphere. This study aimed to investigate the effect of WCR root feeding on the microbial communities colonizing the maize rhizosphere. METHODOLOGY/PRINCIPAL FINDINGS: In a greenhouse experiment, maize lines KWS13, KWS14, KWS15 and MON88017 were grown in three different soil types in presence and in absence of WCR larvae. Bacterial and fungal community structures were analyzed by denaturing gradient gel electrophoresis (DGGE) of the 16S rRNA gene and ITS fragments, PCR amplified from the total rhizosphere community DNA. DGGE bands with increased intensity were excised from the gel, cloned and sequenced in order to identify specific bacteria responding to WCR larval feeding. DGGE fingerprints showed that the soil type and the maize line influenced the fungal and bacterial communities inhabiting the maize rhizosphere. WCR larval feeding affected the rhiyosphere microbial populations in a soil type and maize line dependent manner. DGGE band sequencing revealed an increased abundance of Acinetobacter calcoaceticus in the rhizosphere of several maize lines in all soil types upon WCR larval feeding. CONCLUSION/SIGNIFICANCE: The effects of both rhizosphere and WCR larval feeding seemed to be stronger on bacterial communities than on fungi. Bacterial and fungal community shifts in response to larval feeding were most likely due to changes of root exudation patterns. The increased abundance of A. calcoaceticus suggested that phenolic compounds were released upon WCR wounding