A review of tazarotene in the treatment of photodamaged skin

Chronic sun exposure leads to photodamage, which is characterized clinically by fine and coarse wrinkles, dyspigmentation, telangiectasia, laxity, roughness and a sallow appearance. Many treatments claim to reduce the signs of photodamage, however evidence from randomized controlled trials (RCT) to support these claims is limited. The use of topical retinoids, particularly tretinoin, isotretinoin and tazarotene, has been shown to significantly reduce signs of photodamage both clinically and histologically. Over recent years a number of RCTs, have affirmed that topical tazarotene is an effective and safe treatment for photodamaged skin

Error estimates for DeepOnets: A deep learning framework in infinite dimensions

DeepOnets have recently been proposed as a framework for learning nonlinear operators mapping between infinite dimensional Banach spaces. We analyze DeepOnets and prove estimates on the resulting approximation and generalization errors. In particular, we extend the universal approximation property of DeepOnets to include measurable mappings in non-compact spaces. By a decomposition of the error into encoding, approximation and reconstruction errors, we prove both lower and upper bounds on the total error, relating it to the spectral decay properties of the covariance operators, associated with the underlying measures. We derive almost optimal error bounds with very general affine reconstructors and with random sensor locations as well as bounds on the generalization error, using covering number arguments. We illustrate our general framework with four prototypical examples of nonlinear operators, namely those arising in a nonlinear forced ODE, an elliptic PDE with variable coefficients and nonlinear parabolic and hyperbolic PDEs. In all these examples, we prove that DeepOnets break the curse of dimensionality, thus demonstrating the efficient approximation of infinite-dimensional operators with this machine learning framework

The cellular response to ocean warming in Emiliania huxleyi

Marine phytoplankton contribute substantially to the global flux of carbon from the atmosphere to the deep ocean. Sea surface temperatures will inevitably increase in line with global climate change, altering the performance of marine phytoplankton. Differing sensitivities of photosynthesis and respiration to temperature, will likely shift the strength of the future oceanic carbon sink. To further clarify the molecular mechanisms driving these alterations in phytoplankton function, shotgun proteomic analysis was carried out on the globally-occurring coccolithophore Emiliania huxleyi exposed to moderate- (23°C) and elevated- (28°C) warming. Compared to the control (17°C), growth of E. huxleyi increased under elevated temperatures, with higher rates recorded under moderate- relative to elevated- warming. Proteomic analysis revealed a significant modification of the E. huxleyi cellular proteome as temperatures increased: at lower temperature, ribosomal proteins and photosynthetic machinery appeared abundant, as rates of protein translation and photosynthetic performance are restricted by low temperatures. As temperatures increased, evidence of heat stress was observed in the photosystem, characterized by a relative down-regulation of the Photosystem II oxygen evolving complex and ATP synthase. Acclimation to elevated warming (28°C) revealed a substantial alteration to carbon metabolism. Here, E. huxleyi made use of the glyoxylate cycle and succinate metabolism to optimize carbon use, maintain growth and maximize ATP production in heat-damaged mitochondria, enabling cultures to maintain growth at levels significantly higher than those recorded in the control (17°C). Based on the metabolic changes observed, we can predict that warming may benefit photosynthetic carbon fixation by E. huxleyi in the sub-optimal to optimal thermal range. Past the thermal optima, increasing rates of respiration and costs of repair will likely constrain growth, causing a possible decline in the contribution of this species to the oceanic carbon sink depending on the evolvability of these temperature thresholds

Shotgun proteomics reveals temperature-dependent regulation of major nutrient metabolism in coastal Synechococcus sp. WH5701

Marine cyanobacteria are major contributors to the oceanic carbon sink and are predicted to increase in numbers in the future warmed ocean. As a result, the influence of marine cyanobacteria on marine biogeochemical cycling will likely be enhanced. Associated with elevations in temperature the ocean will undergo increased stratification, reducing supply of essential nutrients to upper phototrophic layers. It is therefore critical that we resolve the manners by which cyanobacteria respond to variations in temperature, and consequences for major nutrient metabolism which may ultimately direct global biogeochemistry and trophic transfer. In this study we use the coastal Synechococcus sp. WH5701 to examine proteomic alterations in major nutrient (C, N and P) metabolic pathways following exposure to varying temperature. In response to temperature treatments, Synechococcus displayed higher rates of growth and photosynthetic efficiency when temperatures were raised from 17 °C, to 23 °C and 28 °C, associated with a significant ∼30–40 % alteration in the cellular proteome. As temperatures increased, proteomic investment towards photosynthetic machinery appeared up-regulated, whilst abundance of RuBisCO was reduced, associated with an apparent alteration in CCM composition and carbon metabolism. N demand appeared to increase in-line with temperature, associated with alterations in the GS-GOGAT pathway, likely due to increased demand for and efficiency of protein synthesis. In contrast, P demand at the highest temperature appeared reduced as investment in the ribosome declines due to improved translation efficiency, whilst luxury P-storage appeared a feature of growth at low temperature. It appears likely that as seawater temperatures rise under ocean warming, the biochemical composition of cyanobacteria will be altered, increasing cellular C- and N- to P ratios, ultimately impacting upon their contribution to oceanic biogeochemical cycling

THE ROLE OF TIP LEAKAGE FLOW IN SPIKE-TYPE ROTATING STALL INCEPTION

This paper describes the role of tip leakage flow in creating the leading edge separation necessary for onset of spike-type compressor rotating stall. A series of unsteady multi-passage simulations, supported by experimental data, are used to define and illustrate the two competing mechanisms that cause the high incidence responsible for this separation: blockage from a casing-suction-surface corner separation and forward spillage of the tip leakage jet. The axial momentum flux in the tip leakage flow determines which mechanism dominates. At zero tip clearance, corner separation blockage dominates. As clearance is increased, the leakage flow reduces blockage, moving the stall flow coefficient to lower flow, i.e. giving a larger unstalled flow range. Increased clearance, however, means increased leakage jet momentum and contribution to leakage jet spillage. There is thus a clearance above which jet spillage dominates in creating incidence, so the stall flow coefficient increases and flow range decreases with clearance. As a consequence there is a clearance for maximum flow range; for the two rotors in this study, the value was approximately 0.5% chord. The chord-wise distribution of the leakage axial momentum is also important in determining stall onset. Shifting the distribution towards the trailing edge increases flow range for a leakage jet dominated geometry and reduces flow range for a corner separation dominated geometry. Guidelines are developed for flow range enhancement through control of tip leakage flow axial momentum magnitude and distribution. An example is given of how this might be achieved.Mitsubishi Heavy Industries, Ltd

AI facilitated fluoro-electrochemical phytoplankton classification

Marine phytoplankton is extremely diverse. Counting and characterising phytoplankton is essential for understanding climate change and ocean health not least since phytoplankton extensively biomineralize carbon dioxide whilst generating 50% of the planet's oxygen. We report the use of fluoro-electrochemical microscopy to distinguish different taxonomies of phytoplankton by the quenching of their chlorophyll-a fluorescence using chemical species oxidatively electrogenerated in situin seawater. The rate of chlorophyll-a quenching of each cell is characteristic of the species-specific structural composition and cellular content. But with increasing diversity and extent of phytoplankton species under study, human interpretation and distinction of the resulting fluorescence transients becomes increasingly and prohibitively difficult. Thus, we further report a neural network to analyse these fluorescence transients, with an accuracy >95% classifying 29 phytoplankton strains to their taxonomic orders. This method transcends the state-of-the-art. The success of the fluoro-electrochemical microscopy combined with AI provides a novel, flexible and highly granular solution to phytoplankton classification and is adaptable for autonomous ocean monitoring

Calcifying coccolithophore: an evolutionary advantage against extracellular oxidative damage

The evolutionary advantages afforded by phytoplankton calcification remain enigmatic. In this work, fluoroelectrochemical experiments reveal that the presence of a CaCO3 shell of a naturally calcifying coccolithophore, Coccolithus braarudii, offers protection against extracellular oxidants as measured by the time required for the switch-off in their chlorophyll signal, compared to the deshelled equivalents, suggesting the shift toward calcification offers some advantages for survival in the surface of radical-rich seawater

Unravelling the Specificity of Laminaribiose Phosphorylase from Paenibacillus sp. YM‐1 towards Donor Substrates Glucose/Mannose 1‐Phosphate by Using X‐ray Crystallography and Saturation Transfer Difference NMR Spectroscopy

Glycoside phosphorylases (GPs) carry out a reversible phosphorolysis of carbohydrates into oligosaccharide acceptors and the corresponding sugar 1‐phosphates. The reversibility of the reaction enables the use of GPs as biocatalysts for carbohydrate synthesis. Glycosyl hydrolase family 94 (GH94), which only comprises GPs, is one of the most studied GP families that have been used as biocatalysts for carbohydrate synthesis, in academic research and in industrial production. Understanding the mechanism of GH94 enzymes is a crucial step towards enzyme engineering to improve and expand the applications of these enzymes in synthesis. In this work with a GH94 laminaribiose phosphorylase from Paenibacillus sp. YM‐1 (PsLBP), we have demonstrated an enzymatic synthesis of disaccharide 1 (β‐d‐mannopyranosyl‐(1→3)‐d‐glucopyranose) by using a natural acceptor glucose and noncognate donor substrate α‐mannose 1‐phosphate (Man1P). To investigate how the enzyme recognises different sugar 1‐phosphates, the X‐ray crystal structures of PsLBP in complex with Glc1P and Man1P have been solved, providing the first molecular detail of the recognition of a noncognate donor substrate by GPs, which revealed the importance of hydrogen bonding between the active site residues and hydroxy groups at C2, C4, and C6 of sugar 1‐phosphates. Furthermore, we used saturation transfer difference NMR spectroscopy to support crystallographic studies on the sugar 1‐phosphates, as well as to provide further insights into the PsLBP recognition of the acceptors and disaccharide products

A novel fluoro-electrochemical technique for classifying diverse marine nanophytoplankton

To broaden our understanding of pelagic ecosystem responses to environmental change, it is essential that we improve the spatiotemporal resolution of in situ monitoring of phytoplankton communities. A key challenge for existing methods is in classifying and quantifying cells within the nanophytoplankton size range (2–20 μm). This is particularly difficult when there are similarities in morphology, making visual differentiation difficult for both trained taxonomists and machine learning-based approaches. Here we present a rapid fluoro-electrochemical technique for classifying nanophytoplankton, and using a library of 52 diverse strains of nanophytoplankton we assess the accuracy of this technique based on two measurements at the individual level: charge required to reduce per cell chlorophyll a fluorescence by 50% and cell radius. We demonstrate a high degree of accuracy overall (92%) in categorizing cells belonging to widely recognized key functional groups; however, this is reduced when we consider the broader diversity of “nano-phytoflagellates'.” Notably, we observe that some groups, for example, calcifying Isochrysidales, have much greater resilience to electrochemically driven oxidative conditions relative to others of a similar size, making them more easily categorized by the technique. The findings of this study present a promising step forward in advancing our toolkit for monitoring phytoplankton communities. We highlight that, for improved categorization accuracy, future iterations of the method can be enhanced by measuring additional predictor variables with minimal adjustments to the set-up. In doing so, we foresee this technique being highly applicable, and potentially invaluable, for in situ classification and enumeration of the nanophytoplankton size fraction