Morphological Variations in Developing Ectomycorrhizae of Dryas integrifolia and Five Fungal Species

A comparative study of ectomycorrhiza formation between the host species Dryas integrifolia and four fungal species belonging to the Basidiomycotina ( Laccaria bicolor, L. laccata, Hebeloma cylindrosporum, Paxillus involutus) and one species in the Ascomycotina (Cenococcum geophilum) showed that patterns in ectomycorrhizal development were distinctive enough to characterize each fungal symbiont. Several aspects of hyphal growth on the plant root during colonization were studied in order to demonstrate the usefulness of SEM in observing the ontogeny of ectomycorrhizae. Each fungal species had a different rate of colonization, and varying root and root hair interactions. As a consequence mantle morphology and the overall appearance of mature ectomycorrhizal apices were also characteristic for each fungal species. Results indicate that the mycobiont plays a major role in determining the morphology of mature ectomycorrizae

Scanning Electron Microscopy of Ectomycorrhizae Potential and Limitations

Scanning electron microscopy (SEM) has added considerably to an understanding of the morphology of ectomycorrhizae. Features of the mantle of mature ectomycorrhizae have been studied most frequently. There is considerable variation in arrangement of hyphae and therefore in the appearance of the outer mantle. This variation is due primarily to the fungal symbiont although the host genome may also influence this feature. The Hartig net has been studied from fractured ectomycorrhizal roots and, in the present study, from fractured cryopreserved specimens; general features of the interaction between Hartig net hyphae and contiguous root cells have been described. There are few published accounts of using SEM techniques to study the ontogeny of ectomycorrhizae. This study demonstrates the usefulness of such techniques in studying the initial interaction of hyphae with root hairs and root surfaces, including the extramatrical phase which is normally very difficult to study using other techniques

Decadal changes in Arctic Ocean Chlorophyll a: Bridging ocean color observations from the 1980s to present time

Remotely-sensed Ocean color data offer a unique opportunity for studying variations of bio-optical properties which is especially valuable in the Arctic Ocean (AO) where in situ data are sparse. In this study, we re-processed the raw data from the Sea-viewing Wide Field-of-View (SeaWiFS, 1998–2010) and the MODerate resolution Imaging Spectroradiometer (MODIS, 2003–2016) ocean-color sensors to ensure compatibility with the first ocean color sensor, namely, the Coastal Zone Color Scanner (CZCS, 1979–1986). Based on a bio-regional approach, this study assesses the quality of this new homogeneous pan-Arctic Chl a dataset, which provides the longest (but non-continuous) ocean color time-series ever produced for the AO (37 years long between 1979 and 2016). We show that despite the temporal gaps between 1986 and 1998 due to the absence of ocean color satellite, the time series is suitable to establish a baseline of phytoplankton biomass for the early 1980s, before sea-ice loss accelerated in the AO. More importantly, it provides the opportunity to quantify decadal changes over the AO revealing for instance the continuous Chl a increase in the inflow shelves such as the Barents Sea since the CZCS era

Altered Fungal Morphogenesis During Early Stages of Ectomycorrhiza Formation in Eucalyptus Pilularis

Scanning electron microscopy (SEM) of Eucalyptus pilularis roots inoculated with Pisolithus tinctorius, under controlled conditions, revealed altered morphogenesis of fungal hyphae in contact with the root surface. These changes occurred prior to the formation of a full fungal mantle and resulted in the formation of a compact fungal layer as a consequence of fusion of proliferating, branching hyphae. Although similar growth patterns have been observed in the inner mantle of fully developed ectomycorrhizae using contrast interference microscopy, this is the first time this feature has been observed during early mantle formation using SEM. Changes in fungal morphology during early stages of colonization may be correlated with recognition between the symbionts, and the subsequent establishment of a symbiotic relationship between compatible partners

Ultrafast nonlinear optical response of Dirac fermions in graphene

The speed of solid-state electronic devices, determined by the temporal dynamics of charge carriers, could potentially reach unprecedented petahertz frequencies through direct manipulation by optical fields, consisting in a million-fold increase from state-of-the-art technology. In graphene, charge carrier manipulation is facilitated by exceptionally strong coupling to optical fields, from which stems an important back-action of photoexcited carriers. Here we investigate the instantaneous response of graphene to ultrafast optical fields, elucidating the role of hot carriers on sub-100 fs timescales. The measured nonlinear response and its dependence on interaction time and field polarization reveal the back-action of hot carriers over timescales commensurate with the optical field. An intuitive picture is given for the carrier trajectories in response to the optical-field polarization state. We note that the peculiar interplay between optical fields and charge carriers in graphene may also apply to surface states in topological insulators with similar Dirac cone dispersion relations.Peer ReviewedPostprint (published version

Kinase inhibitors for advanced medullary thyroid carcinoma

The recent availability of molecular targeted therapies leads to a reconsideration of the treatment strategy for patients with distant metastases from medullary thyroid carcinoma. In patients with progressive disease, treatment with kinase inhibitors should be offered

Kidney thrombotic microangiopathy in lupus nephritis: Impact on treatment and prognosis

Introduction Lupus nephritis (LN) may present with thrombotic microangiopathy (TMA) on kidney biopsy, the impact of which on outcomes is unclear. This study examined the prognostic importance of LN with TMA on kidney biopsy, including response to therapy and long-term outcomes. Methods We conducted a single-center, retrospective study of all cases of LN with concomitant TMA on kidney biopsy in the Glomerular Disease Collaborative Network database. Controls were individuals with LN without TMA matched to cases based on demographic and clinical variables. Outcomes were remission at 6- and 12-months, end-stage kidney disease (ESKD) and death. Logistic regression and Cox proportional hazards models were used to ascertain the risks for outcomes, with adjustment for serum creatinine and proteinuria. Results There were 17 cases and 28 controls. Cases had higher creatinine, higher proteinuria and greater chronicity on biopsy at baseline compared to controls. The rates of remission at 6-months and 12-months were similar between cases and controls (6-months 53.9% vs 46.4%, adjusted OR 2.54, 95% CI 0.48, 13.37; 12-months 53.9% vs 50.0%, adjusted OR 2.95, 95% CI 0.44, 19.78). Cases were at greater risk for ESKD in univariate analysis (HR 3.77; 95% CI 1.24, 11.41) but not when adjusting for serum creatinine and proteinuria (HR 2.20; 95% CI 0.63, 7.71). There was no significant difference in the risk of death between cases and controls. Conclusion Lupus nephritis with renal TMA likely responds to therapy similarly to those without TMA; risk for ESKD is not significantly increased, although the influence of renal function and proteinuria in larger samples is needed

Long short-term memory for indoor localization using WI-FI received signal strength and channel state information

Indoor location information is increasing in importance in contemporary communication services and applications. In this paper, we discuss the long short-term memory (LSTM) performance for indoor localization in non-line-of-sight (NLoS) conditions using the received signal strength (RSS) and channel state information (CSI) obtained from Wi-Fi signals. As such, we describe the CSI and RSS acquisition system that is used to build a rich dataset to experiment with classical machine learning and deep learning models. The distance range error matrix is combined with the confusion matrix to obtain the distance range error probability where we have demonstrated that the LSTM model exhibits a maximum range error of less than 5 m with 4% probability