Regioselective Oxidative Arylation of Indoles Bearing N-Alkyl Protecting Groups: Dual C−H Functionalization via a Concerted Metalation−Deprotonation Mechanism

The most direct method for synthesizing 2-arylindoles is oxidative coupling of an arene with an indole. We have shown that both the activity and regioselectivity of this cross-coupling reaction are correlated with the acidity of the medium. This insight has been applied to predict the best conditions for the oxidative cross-coupling of N-alkylindoles, an important class of substrates that has heretofore been incompatible with the harsh conditions required for oxidative cross-coupling. Both experimental and computational data indicate that the mechanism for C−H palladation of both the indoles and simple arenes is best described as concerted metalation−deprotonation, regardless of the substitution on the arene

Photon assisted Levy flights of minority carriers in n-InP

We study the photoluminescence spectra of n-doped InP bulk wafers, both in the reflection and the transmission geometries relative to the excitation beam. From the observed spectra we estimate the spatial distribution of minority carriers allowing for the spectral filtering due to re-absorption of luminescence in the wafer. This distribution unambiguously demonstrates a non-exponential drop-off with distance from the excitation region. Such a behavior evidences an anomalous photon-assisted transport of minority carriers enhanced owing to the high quantum efficiency of emission. It is shown that the transport conforms very well to the so-called Levy-flights process corresponding to a peculiar random walk that does not reduce to diffusion. The index gamma of the Levy flights distribution is found to be in the range gamma = 0.64 to 0.79, depending on the doping. Thus, we propose the high-efficiency direct-gap semiconductors as a remarkable laboratory system for studying the anomalous transport.Comment: 12 pages, 9 figure

Implications of carbon cycle steady state assumption for biogeochemical modeling performance and inverse parameter retrieval

We analyze the impacts of the steady state assumption on inverse model parameter retrieval from biogeochemical models. An inverse model parameterization study using eddy covariance CO2 flux data was performed with the Carnegie Ames Stanford Approach (CASA) model under conditions of strict and relaxed carbon cycle steady state assumption (CCSSA) in order to evaluate both the robustness of the model’s structure for the simulation of net ecosystem carbon fluxes and the assessment of the CCSSA effects on simulations and parameter estimation. Net ecosystem production (NEP) measurements from several eddy covariance sites were compared with NEP estimates from the CASA model driven by local weather station climate inputs as well as by remotely sensed fraction of photosynthetically active radiation absorbed by vegetation and leaf area index. The parameters considered for optimization are directly related to aboveground and belowground modeled responses to temperature and water availability, as well as a parameter (h) that relaxed the CCSSA in the model, allowing for site level simulations to be initialized either as net sinks or sources. A robust relationship was observed between NEP observations and predictions for most of the sites through the range of temporal scales considered (daily, weekly, biweekly, and monthly), supporting the conclusion that the model structure is able to capture the main processes explaining NEP variability. Overall, relaxing CCSSA increased model efficiency (21%) and decreased normalized average error ( 92%). Intersite variability was a major source of variance in model performance differences between fixed (CCSSAf) and relaxed (CCSSAr) CCSSA conditions. These differences were correlated with mean annual NEP observations, where an average increase in modeling efficiency of 0.06 per 100 g Cm 2 a 1 (where a is years) of NEP is observed (a < 0.003). The parameter h was found to be a key parameter in the optimization exercise, generating significant model efficiency losses when removed from the initial parameter set and parameter uncertainties were significantly lower under CCSSAr. Moreover, modeled soil carbon stocks were generally closer to observations once the steady state assumption was relaxed. Finally, we also show that estimates of individual parameters are affected by the steady state assumption. For example, estimates of radiation-use efficiency were strongly affected by the CCSSAf indicating compensation effects for the inadequate steady state assumption, leading to effective and thus biased parameters. Overall, the importance of model structural evaluation in data assimilation approaches is thus emphasize

The phenome analysis of mutant alleles in Leucine-Rich Repeat Receptor-Like Kinase genes in rice reveals new potential targets for stress tolerant cereals

AbstractPlants are constantly exposed to a variety of biotic and abiotic stresses that reduce their fitness and performance. At the molecular level, the perception of extracellular stimuli and the subsequent activation of defense responses require a complex interplay of signaling cascades, in which protein phosphorylation plays a central role. Several studies have shown that some members of the Leucine-Rich Repeat Receptor-Like Kinase (LRR-RLK) family are involved in stress and developmental pathways. We report here a systematic analysis of the role of the members of this gene family by mutant phenotyping in the monocotyledon model plant rice, Oryza sativa. We have then targeted 176 of the ∼320 LRR-RLK genes (55.7%) and genotyped 288 mutant lines. Position of the insertion was confirmed in 128 lines corresponding to 100 LRR-RLK genes (31.6% of the entire family). All mutant lines harboring homozygous insertions have been screened for phenotypes under normal conditions and under various abiotic stresses. Mutant plants have been observed at several stages of growth, from seedlings in Petri dishes to flowering and grain filling under greenhouse conditions. Our results show that 37 of the LRR-RLK rice genes are potential targets for improvement especially in the generation of abiotic stress tolerant cereals

Monitoring Healthy Metabolic Trajectories with Nutritional Metabonomics

Metabonomics is a well established analytical approach for the analysis of physiological regulatory processes via the metabolic profiling of biofluids and tissues in living organisms. Its potential is fully exploited in the field of “nutrimetabonomics” that aims at assessing the metabolic effects of active ingredients and foods in individuals. Yet, one of the greatest challenges in nutrition research is to decipher the critical interactions between mammalian organisms and environmental factors, including the gut microbiota. “Nutrimetabonomics” is today foreseen as a powerful approach for future nutritional programs tailored at health maintenance and disease prevention

Septins Recognize and Entrap Dividing Bacterial Cells for Delivery to Lysosomes.

The cytoskeleton occupies a central role in cellular immunity by promoting bacterial sensing and antibacterial functions. Septins are cytoskeletal proteins implicated in various cellular processes, including cell division. Septins also assemble into cage-like structures that entrap cytosolic Shigella, yet how septins recognize bacteria is poorly understood. Here, we discover that septins are recruited to regions of micron-scale membrane curvature upon invasion and division by a variety of bacterial species. Cardiolipin, a curvature-specific phospholipid, promotes septin recruitment to highly curved membranes of Shigella, and bacterial mutants lacking cardiolipin exhibit less septin cage entrapment. Chemically inhibiting cell separation to prolong membrane curvature or reducing Shigella cell growth respectively increases and decreases septin cage formation. Once formed, septin cages inhibit Shigella cell division upon recruitment of autophagic and lysosomal machinery. Thus, recognition of dividing bacterial cells by the septin cytoskeleton is a powerful mechanism to restrict the proliferation of intracellular bacterial pathogens

Deforestation projections imply range-wide population decline for critically endangered Bornean orangutan

Assessing where wildlife populations are at risk from future habitat loss is particularly important for land-use planning and avoiding biodiversity declines. Combining projections of future deforestation with species density information provides an improved way to anticipate such declines. Using the critically endangered Bornean orangutan (Pongo pygmaeus) as a case study we applied a spatio-temporally explicit deforestation model to forest loss data from 2001-2017 and projected future impacts on orangutans to the 2030s. Our projections point to continued deforestation across the island, amounting to a potential loss of forest habitat for 26,200 orangutans. Populations currently persisting in forests gazetted for industrial timber and oil palm concessions, or unprotected forests outside of concessions, were projected to experience the worst losses within the next 15 years, amounting to 15,400 individuals. Our analysis indicates the importance of protecting orangutan habitat in plantation landscapes, maintaining protected areas and efforts to prevent the conversion of logged forests for the survival of highly vulnerable wildlife. The modeling framework could be expanded to other species with available density or occurrence data. Our findings highlight that species conservation should not only act on the current information, but also anticipate future changes to be effective