Both long-term grasslands and crop diversity are needed to limit pest and weed infestations in agricultural landscapes.

Increasing landscape heterogeneity has been suggested to be an important strategy to strengthen natural pest control in crops, especially through enhancing the amount of seminatural habitats. Increasing crop diversity is also a promising strategy to complement or replace seminatural habitat when seminatural habitat is scarce. However, their relative or possibly interactive effects on pest and weed infestation remain poorly investigated, and the role of different types of seminatural habitats has been understudied. Using an extensive sampling effort in 974 arable fields across 7 y, we evaluated the separate and interactive effects of crop diversity (seven arable crop types) and the amount of four types of seminatural habitats (meadows, hay, forests, and hedgerows) in the landscape on pest and weed control. Meadows and crop diversity, respectively, supported insect pest and weed control services in agricultural landscapes through a complementarity effect. Crop diversity increased weed seed predation rate (by 16%) and reduced weed infestation (by 6%), whereas long-term grasslands (to a much higher degree than hay or woody habitats) increased insect pest predation rates (by 23%) and reduced pest infestation (by 19%) in most arable crops. Our results demonstrate that diversification of the agricultural landscape requires long-term grasslands as well as improved crop diversity to ensure the delivery of efficient pest and weed control services.

Structural insights into the interactions of glutathione transferases with a nitric oxide carrier and sodium nitroprusside.

Glutathione transferases are detoxification enzymes with multifaceted roles, including a role in the metabolism and scavenging of nitric oxide (NO) compounds in cells. Here, we explored the ability of Trametes versicolor glutathione transferases (GSTs) from the Omega class (TvGSTOs) to bind metal-nitrosyl compounds. TvGSTOs have been studied previously for their ligandin role and are interesting models to study protein‒ligand interactions. First, we determined the X-ray structure of the TvGSTO3S isoform bound to the dinitrosyl glutathionyl iron complex (DNGIC), a physiological compound involved in the storage of nitric oxide. Our results suggested a different binding mode compared to the one previously described in human GST Pi 1 (GSTP1). Then, we investigated the manner in which TvGSTO3S binds three nonphysiological metal-nitrosyl compounds with different metal cores (iron, ruthenium and osmium). We assayed sodium nitroprusside, a well-studied vasodilator used in cases of hypertensive crises or heart failure. Our results showed that the tested GST can bind metal-nitrosyls at two distinct binding sites. Thermal shift analysis with six isoforms of TvGSTOs identified TvGSTO6S as the best interactant. Using the Griess method, TvGSTO6S was found to improve the release of nitric oxide from sodium nitroprusside in vitro, whereas the effects of human GST alpha 1 (GSTA1) and GSTP1 were moderate. Our results open new structural perspectives for understanding the interactions of glutathione transferases with metal-nitrosyl compounds associated with the biochemical mechanisms of NO uptake/release in biological systems.

Diversity of Omega Glutathione Transferases in mushroom-forming fungi revealed by phylogenetic, transcriptomic, biochemical and structural approaches.

The Omega class of glutathione transferases (GSTs) forms a distinct class within the cytosolic GST superfamily because most of them possess a catalytic cysteine residue. The human GST Omega 1 isoform was first characterized twenty years ago, but it took years of work to clarify the roles of the human isoforms. Concerning the kingdom of fungi, little is known about the cellular functions of Omega glutathione transferases (GSTOs), although they are widely represented in some of these organisms. In this study, we re-assess the phylogeny and the classification of GSTOs based on 240 genomes of mushroom-forming fungi (Agaricomycetes). We observe that the number of GSTOs is not only extended in the order of Polyporales but also in other orders such as Boletales. Our analysis leads to a new classification in which the fungal GSTOs are divided into two Types A and B. The catalytic residue of Type-A is either cysteine or serine, while that of Type-B is cysteine. The present study focuses on Trametes versicolor GSTO isoforms that possess a catalytic cysteine residue. Transcriptomic data show that Type-A GSTOs are constitutive enzymes while Type-B are inducible ones. The crystallographic analysis reveals substantial structural differences between the two types while they have similar biochemical profiles in the tested conditions. Additionally, these enzymes have the ability to bind antioxidant molecules such as wood polyphenols in two possible binding sites as observed from X-ray structures. The multiplication of GSTOs could allow fungal organisms to adapt more easily to new environments.

Validation of the corticomedullary difference in magnetic resonance imaging-derived apparent diffusion coefficient for kidney fibrosis detection: a cross-sectional study.

BACKGROUND: Kidney cortical interstitial fibrosis (IF) is highly predictive of renal prognosis and is currently assessed by the evaluation of a biopsy. Diffusion magnetic resonance imaging (MRI) is a promising tool to evaluate kidney fibrosis via the apparent diffusion coefficient (ADC), but suffers from inter-individual variability. We recently applied a novel MRI protocol to allow calculation of the corticomedullary ADC difference (ΔADC). We here present the validation of ΔADC for fibrosis assessment in a cohort of 164 patients undergoing biopsy and compare it with estimated glomerular filtration rate (eGFR) and other plasmatic parameters for the detection of fibrosis. METHODS: This monocentric cross-sectional study included 164 patients undergoing renal biopsy at the Nephrology Department of the University Hospital of Geneva between October 2014 and May 2018. Patients underwent diffusion-weighted imaging, and T1 and T2 mappings, within 1 week after biopsy. MRI results were compared with gold standard histology for fibrosis assessment. RESULTS: Absolute cortical ADC or cortical T1 values correlated poorly to IF assessed by the biopsy, whereas ΔADC was highly correlated to IF (r=-0.52, P < 0.001) and eGFR (r = 0.37, P < 0.01), in both native and allograft patients. ΔT1 displayed a lower, but significant, correlation to IF and eGFR, whereas T2 did not correlate to IF nor to eGFR. ΔADC, ΔT1 and eGFR were independently associated with kidney fibrosis, and their combination allowed detection of extensive fibrosis with good specificity. CONCLUSION: ΔADC is better correlated to IF than absolute cortical or medullary ADC values. ΔADC, ΔT1 and eGFR are independently associated to IF and allow the identification of patients with extensive IF.

Glutathione Transferases: Surrogate Targets for Discovering Biologically Active Compounds.

Glutathione transferases comprise a large class of multifunctional enzymes, some involved in detoxification pathways. Since these enzymes are able to interact with potentially toxic molecules, they could be used as targets to screen for compounds with biological activity. To test this hypothesis, glutathione transferases (GSTs) from the white-rot fungus Trametes versicolor have been used to screen for antifungal molecules from a library of tropical wood extracts. The interactions between a set of six GSTs from the omega class and 116 extracts from 21 tropical species were quantified using a high-throughput thermal shift assay. A correlation between these interactions and the antifungal properties of the tested extracts was demonstrated. This approach has been extended to the fractionation of an Andira coriacea extract and led to the detection of maackiain and lapachol in this wood. Altogether, the present results supported the hypothesis that such detoxification enzymes could be used to detect biologically active molecules.

Bee pollination outperforms pesticides for oilseed crop production and profitability.

Nature-based agriculture that reduces dependency on chemical inputs requires using ecological principles for sustainable agro-ecosystems, aiming to balance ecology, economics and social justice. There is growing evidence that pollinator-dependent crops with high insect, particularly bee, pollination service can give higher yields. However, the interacting effects between insect pollination and agricultural inputs on crop yields and farm economics remain to be established to reconcile food production with biodiversity conservation. We quantified individual and combined effects of pesticides, insect pollination and soil quality on oilseed rape (Brassica napus L.) yield and gross margin, using a total of 294 farmers' fields surveyed between 2013 and 2016. We show that yield and gross margins are greater (15-40%) in fields with higher pollinator abundance than in fields with reduced pollinator abundance. This effect is, however, strongly reduced by pesticide use. Greater yields may be achieved by either increasing agrochemicals or increasing bee abundance, but crop economic returns were only increased by the latter, because pesticides did not increase yields while their costs reduced gross margins.

Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning.

OBJECTIVES: Distinguishing between kidney stones and phleboliths can constitute a diagnostic challenge in patients undergoing unenhanced low-dose CT (LDCT) for acute flank pain. We sought to investigate the accuracy of radiomics and a machine-learning classifier in differentiating between kidney stones and phleboliths on LDCT. METHODS: Radiomics features were extracted following a semi-automatic segmentation of kidney stones and phleboliths for two independent consecutive cohorts of patients undergoing LDCT for acute flank pain. Radiomics features from the first cohort of patients (n = 369) were ultimately used to train a machine-learning model designed to distinguish kidney stones (n = 211) from phleboliths (n = 201). Classification performance was assessed on the second independent cohort (i.e., testing set) (kidney stones n = 24; phleboliths n = 23) using positive and negative predictive values (PPV and NPV), area under the receiver operating curves (AUC), and permutation testing. RESULTS: Our machine-learning classification model trained on radiomics features achieved an overall accuracy of 85.1% on the independent testing set, with an AUC of 0.902, PPV of 81.5%, and NPV of 90.0%. Classification accuracy was significantly better than chance on permutation testing (p < 0.05, permutation p value). CONCLUSION: Radiomics and machine learning enable accurate differentiation between kidney stones and phleboliths on LDCT in patients presenting with acute flank pain. KEY POINTS: • Combining a machine-learning algorithm with radiomics features extracted for abdominopelvic calcification on LDCT offers a highly accurate method for discriminating phleboliths from kidney stones. • Our radiomics and machine-learning model proved robust for CT acquisition and reconstruction protocol when tested in comparison with an external independent cohort of patients with acute flank pain. • The high performance of the radiomics-based automatic classification model in differentiating phleboliths from kidney stones indicates its potential as a future diagnostic tool for equivocal abdominopelvic calcifications in the setting of suspected renal colic.

Enzyme Activities of Two Recombinant Heme-Containing Peroxidases, TvDyP1 and TvVP2, Identified from the Secretome of Trametes versicolor.

Trametesversicolor is a wood-inhabiting agaricomycete known for its ability to cause strong white-rot decay on hardwood and for its high tolerance of phenolic compounds. The goal of the present work was to gain insights into the molecular biology and biochemistry of the heme-including class II and dye-decolorizing peroxidases secreted by this fungus. Proteomic analysis of the secretome of T. versicolor BRFM 1218 grown on oak wood revealed a set of 200 secreted proteins, among which were the dye-decolorizing peroxidase TvDyP1 and the versatile peroxidase TvVP2. Both peroxidases were heterologously produced in Escherichia coli, biochemically characterized, and tested for the ability to oxidize complex substrates. Both peroxidases were found to be active against several substrates under acidic conditions, and TvDyP1 was very stable over a relatively large pH range of 2.0 to 6.0, while TvVP2 was more stable at pH 5.0 to 6.0 only. The thermostability of both enzymes was also tested, and TvDyP1 was globally found to be more stable than TvVP2. After 180 min of incubation at temperatures ranging from 30 to 50°C, the activity of TvVP2 drastically decreased, with 10 to 30% of the initial activity retained. Under the same conditions, TvDyP1 retained 20 to 80% of its enzyme activity. The two proteins were catalytically characterized, and TvVP2 was shown to accept a wider range of reducing substrates than TvDyP1. Furthermore, both enzymes were found to be active against two flavonoids, quercetin and catechin, found in oak wood, with TvVP2 displaying more rapid oxidation of the two compounds. They were tested for the ability to decolorize five industrial dyes, and TvVP2 presented a greater ability to oxidize and decolorize the dye substrates than TvDyP1.IMPORTANCETrametesversicolor is a wood-inhabiting agaricomycete known for its ability to cause strong white-rot decay on hardwood and for its high tolerance of phenolic compounds. Among white-rot fungi, the basidiomycete T. versicolor has been extensively studied for its ability to degrade wood, specifically lignin, thanks to an extracellular oxidative enzymatic system. The corresponding oxidative system was previously studied in several works for classical lignin and manganese peroxidases, and in this study, two new components of the oxidative system of T. versicolor, one dye-decolorizing peroxidase and one versatile peroxidase, were biochemically characterized in depth and compared to other fungal peroxidases.

Comparison of readout-segmented and conventional single-shot for echo-planar diffusion-weighted imaging in the assessment of kidney interstitial fibrosis.

PURPOSE: To compare readout-segmented echo-planar imaging (EPI) (RESOLVE) to single-shot EPI (ss-EPI) diffusion-weighted imaging (DWI) for the assessment of renal interstitial fibrosis. MATERIALS AND METHODS: A phantom, eight healthy volunteers (under 30 years to avoid age-fibrosis related) and 27 chronic kidney disease (CKD) patients (scheduled for kidney biopsy) were scanned (at 3T) with ss-EPI and 5-shot RESOLVE DWI (resolution: 2 × 2 × 5 mm3 , 10 b-values). The cortico-medullary difference for each DW parameter from a monoexponential fit (ΔADC) or, segmented biexponential fit (ΔD, ΔD*, ΔFp ) were compared between both sequences. A fibrosis threshold of 40% was defined to separate all 35 subjects into low and high fibrosis groups. The linear relationship between DW parameters and percentage fibrosis (up to 80%) from Masson trichrome was assessed with the Pearson product-moment correlation coefficient. Fisher Z-transform was used for R2 correlation comparison. RESULTS: A coefficient of variation between ADCs of 3% was measured between both sequences in the phantom. In healthy volunteers, no significant difference was measured for all DW parameters. Both sequences separated low to high level of fibrosis with a significant decrease of ΔADC (RESOLVE P = 3.1 × 10-6 , ss-EPI P = 0.003) and ΔD (RESOLVE P = 8.2 × 10-5 , ss-EPI P = 0.02) in the high level of fibrosis. However, RESOLVE ΔADC had a stronger negative correlation (P = 0.04 for R2 comparison) with fibrosis than ss-EPI ΔADC (RESOLVE R2 = 0.65, P = 5.9 × 10-9 , ss-EPI R2 = 0.29, P = 8.9 × 10-4 ). ΔD (RESOLVE) was correlated (moderately) with fibrosis (R2 = 0.29, P = 9.2 × 10-4 ); however, ΔD* and ΔFp did not show, in our population, a significant correlation with interstitial fibrosis (0.01 < R2 < 0.08). CONCLUSION: ΔADC derived from both sequences correlated with fibrosis. ΔADC from RESOLVE showed better correlation with fibrosis than ΔADC from ss-EPI and therefore has potential to monitor CKD. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1631-1640.

Transrectal Ultrasound-Guided Prostate Biopsy for Cancer Detection: Performance of 2D-, 3D- and 3D-MRI Fusion Targeted Techniques.

INTRODUCTION: The study aimed to evaluate 3 different modalities of transrectal ultrasound (TRUS)-guided prostate biopsies (PBs; 2D-, 3D- and targeted 3D-TRUS with fusion to MRI - T3D). Primary end point was the detection rate of prostate cancer (PC). Secondary end point was the detection rate of insignificant PC according to the Epstein criteria. PATIENTS AND METHODS: Inclusion of 284 subsequent patients who underwent 2D-, 3D- or T3D PB from 2011 to 2015. All patients having PB for initial PC detection with a serum prostate-specific antigen value ≤20 ng/ml were included. Patients with T4 and/or clinical and/or radiological metastatic disease, so as these under active surveillance were excluded. RESULTS: Patients with T3D PB had a significantly higher detection rate of PC (58 vs. 19% for 2D and 38% for 3D biopsies; p = 0.001), with no difference in Gleason score distribution (p = 0.644), as well as detection rate of low-risk cancers (p = 0.914). Main predictive factor for positive biopsies was the technique used, with respectively a 3- and 8-fold higher detection rate in the 3D- and T3D group. For T3D-PB, there was a significant correlation between radiological cancer suspicion (Prostate Imaging Reporting and Data System Score) and cancer detection rate (p = 0.02). CONCLUSIONS: T3D PB should be preferred over 2D PB and 3D PB in patients with suspected PC as it improves the cancer detection rate.

The evolution of the competition-dispersal trade-off affects α- and ß-diversity in a heterogeneous metacommunity.

Difference in dispersal ability is a key driver of species coexistence in metacommunities. However, the available frameworks for interpreting species diversity patterns in natura often overlook trade-offs and evolutionary constraints associated with dispersal. Here, we build a metacommunity model accounting for dispersal evolution and a competition-dispersal trade-off. Depending on the distribution of carrying capacities among communities, species dispersal values are distributed either around a single strategy (evolutionarily stable strategy, ESS), or around distinct strategies (evolutionary branching, EB). We show that limited dispersal generates spatial aggregation of dispersal traits in ESS and EB scenarios, and that the competition-dispersal trade-off strengthens the pattern in the EB scenario. Importantly, individuals in larger (respectively (resp.) smaller) communities tend to harbour lower (resp. higher) dispersal, especially under the EB scenario. We explore how dispersal evolution affects species diversity patterns by comparing those from our model to the predictions of a neutral metacommunity model. The most marked difference is detected under EB, with distinctive values of both α- and ß-diversity (e.g. the dissimilarity in species composition between small and large communities was significantly larger than neutral predictions). We conclude that, from an empirical perspective, jointly assessing community carrying capacity with species dispersal strategies should improve our understanding of diversity patterns in metacommunities.

Diffusion in prostate cancer detection on a 3T scanner: How many b-values are needed?

PURPOSE: To assess the influence of perfusion on apparent coefficient diffusion (ADC) maps, the contribution of b-value images, and the number of b-values needed in prostate cancer detection by diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Patients scheduled for prostatectomy were scanned by 3T magnetic resonance imaging (MRI) with DWI based on b-values 0-500-1000-1500 s/mm(2) . A monoexponential model was fitted to obtain ADC using multiple b-values, with or without b0 (perfusion-sensitive ADC4b-b0-500-1000-1500 , perfusion-insensitive ADC3b-b500-1000-1500 ), or two b-values (ADC2b-b0-500 , ADC2b-b0-1000 , ADC2b-b0-1500 ). Prostate and cancer foci were segmented to label voxels as normal or tumoral, according to histology. Areas under receiver operating characteristic curves (AUC) were calculated for each ADC and b-value, then for multivariate logistic regression models combining them. A threshold of 85 tumoral voxels (=0.5 cm(3) ) was used to stratify AUC analysis. RESULTS: In all, 21 patients were selected. Segmentation collected 143,665 prostatic voxels including 10,069 tumoral voxels. In five patients, tumor segmentation provided fewer than 85 voxels, resulting in an ADC with AUC inferior to 0.52. In 16 patients with larger tumors, perfusion-sensitive ADC4b-b0-500-1000-1500 performed better than perfusion-insensitive ADC3b-b500-1000-1500 and similar to ADC2b-b0-1500 (AUC of 0.840, 0.809, and 0.838, respectively). In comparison to the ADC alone, models combining ADC4b-b0-500-1000-1500 or ADC2b-b0-1500 with b1500 improved performance, leading to similar AUCs of 0.884 and 0.883, respectively. In both models, ADC and b1500 were significant markers (P < 0.001). CONCLUSION: Including b0 in ADC calculation provided superior ADC maps for prostate cancer detection. b1500 images as a combined parameter with ADC also improved performance. Using more than two b-values showed no improvement. J. Magn. Reson. Imaging 2016;44:601-609.

Potential of hybrid ¹8F-fluorocholine PET/MRI for prostate cancer imaging.

PURPOSE: To report the first results of hybrid (18)F-fluorocholine PET/MRI imaging for the detection of prostate cancer. METHODS: This analysis included 26 consecutive patients scheduled for prostate PET/MRI before radical prostatectomy. The examinations were performed on a hybrid whole-body PET/MRI scanner. The MR acquisitions which included T2-weighted, diffusion-weighted and dynamic contrast-enhanced sequences were followed during the same session by whole-body PET scans. Parametric maps were constructed to measure normalized T2-weighted intensity (nT2), apparent diffusion coefficient (ADC), volume transfer constant (K (trans)), extravascular extracellular volume fraction (v e) and standardized uptake values (SUV). With pathology as the gold standard, ROC curves were calculated using logistic regression for each parameter and for the best combination with and without PET to obtain a MR model versus a PETMR model. RESULTS: Of the 26 patients initially selected, 3 were excluded due to absence of an endorectal coil (2 patients) or prosthesis artefacts (1 patient). In the whole prostate, the area under the curve (AUC) for SUVmax, ADC, nT2, K (trans) and v e were 0.762, 0.756, 0.685, 0.611 and 0.529 with a best threshold at 3.044 for SUVmax and 1.075 × 10(-3) mm(2)/s for ADC. The anatomical distinction between the transition zone and the peripheral zone showed the potential of the adjunctive use of PET. In the peripheral zone, the AUC of 0.893 for the PETMR model was significantly greater (p = 0.0402) than the AUC of 0.84 for the MR model only. In the whole prostate, no relevant correlation was observed between ADC and SUVmax. The SUVmax was not affected by the Gleason score. CONCLUSION: The performance of a hybrid whole-body (18)F-fluorocholine PET/MRI scan in the same session combined with a prostatic MR examination did not interfere with the diagnostic accuracy of the MR sequences. The registration of the PET data and the T2 anatomical MR sequence data allowed precise localization of hypermetabolic foci in the prostate. While in the transition zone the adenomatous hyperplasia interfered with cancer detection by PET, the quantitative analysis tool performed well for cancer detection in the peripheral zone.

[Opening of the Geneva University Hospital Prostate Cancer Center]. / Création du Centre du cancer de la prostate des HUG.

In 2014, Geneva University Hospital has opened the first certified prostate cancer Center of western Switzerland. It incorporates 29 entities implicated in the diagnosis and treatment of this disease, thereby assuring that all available ressources are made available to patients, regardless of the division to which they were initially referred. The main strength of the Center lies in the synergy generated by its multidisciplinary tumor board. Furthermore, regular conferences, staff meetings, propectively held registers and the yearly re-certification audit support its constant quality improvement.

Emerging trends in production of plant natural products and new-to-nature biopharmaceuticals in yeast.

Natural products represent an inestimable source of valuable compounds for human health. Notably, those produced by plants remain challenging to access due to their low production. Potential shortages of plant-derived biopharmaceuticals caused by climate change or pandemics also regularly tense the market trends. Thus, biotechnological alternatives of supply based on synthetic biology have emerged. These innovative strategies mostly rely on the use of engineered microbial systems for compound synthesis. In this regard, yeasts remain the easiest-tractable eukaryotic models and a convenient chassis for reconstructing whole biosynthetic routes for the heterologous production of plant-derived metabolites. Here, we highlight the recent discoveries dedicated to the bioproduction of new-to-nature compounds in yeasts and provide an overview of emerging strategies for optimising bioproduction.

Temporal and spatial trends of imidacloprid-related hazards in France.

Neonicotinoids are the top-selling insecticides worldwide. Because of their method of use, mainly to coat seeds, neonicotinoids have been found to widely contaminate the environment. Their high toxicity has been shown to be a major concern in terms of impact on biodiversity, and the use of these insecticides has been associated with population declines of species in different countries. Despite the widespread recognition of the risk of neonicotinoids to biodiversity, their temporal and spatial use remains poorly known in many countries. Yet this information is essential to address the potential impacts of these pesticides on biodiversity and to inform measures to establish protected areas or biodiversity restoration. The present study relied a large publicly available dataset to characterise the temporal and spatial use in France of imidacloprid, the most widely used neonicotinoid worldwide, as well as analysed water contamination surveys between 2005 and 2022 to assess the contamination of the environment. The results show that imidacloprid was the main neonicotinoid used in France over the study period. This use was spatially structured, with higher use in northern and western France, particularly related to cereal and beet crops area. The water contamination survey indicated that imidacloprid has widely contaminated the environment and consequently increased the risk to biodiversity, especially in counties crossed by the Loire, Seine and Vilaine rivers. This risk increased between 2005 and 2018 due to the higher use of imidacloprid and decreased sharply after 2018 due to its ban, although it was reauthorized by derogation for sugar beet in 2021. This study is the first assessment of imidacloprid pressure on biodiversity in France and shows the spatial and temporal correlation between agricultural practices and the freshwater contamination level. These results will help to identify priority areas for mitigation and restoration measures.

Gaining access to acetyl-CoA by peroxisomal surface display.

Synthetic biology is constantly making progress for producing compounds on demand. Recently, Yocum and collaborators have developed an outstanding approach based on the anchoring of biosynthetic enzymes to the peroxisomal membrane. This allowed access to an untapped resource of acetyl-CoA and stimulated the synthesis of a valuable polyketide.

Emerging Roles of ß-Glucanases in Plant Development and Adaptative Responses.

Plant ß-glucanases are enzymes involved in the synthesis, remodelling and turnover of cell wall components during multiple physiological processes. Based on the type of the glycoside bond they cleave, plant ß-glucanases have been grouped into three categories: (i) ß-1,4-glucanases degrade cellulose and other polysaccharides containing 1,4-glycosidic bonds to remodel and disassemble the wall during cell growth. (ii) ß-1,3-glucanases are responsible for the mobilization of callose, governing the symplastic trafficking through plasmodesmata. (iii) ß-1,3-1,4-glucanases degrade mixed linkage glucan, a transient wall polysaccharide found in cereals, which is broken down to obtain energy during rapid seedling growth. In addition to their roles in the turnover of self-glucan structures, plant ß-glucanases are crucial in regulating the outcome in symbiotic and hostile plant-microbe interactions by degrading non-self glucan structures. Plants use these enzymes to hydrolyse ß-glucans found in the walls of microbes, not only by contributing to a local antimicrobial defence barrier, but also by generating signalling glucans triggering the activation of global responses. As a counterpart, microbes developed strategies to hijack plant ß-glucanases to their advantage to successfully colonize plant tissues. This review outlines our current understanding on plant ß-glucanases, with a particular focus on the latest advances on their roles in adaptative responses.

Diffusion-Weighted MRI in the Genitourinary System.

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence's usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging-Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.