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In humans, gamma-band oscillations in the primary somatosensory cortex (S1) correlate with subjective pain perception. However, functional contributions to pain and the nature of underlying circuits are unclear. Here we report that gamma oscillations, but not other rhythms, are specifically strengthened independently of any motor component in the S1 cortex of mice during nociception. Moreover, mice with inflammatory pain show elevated resting gamma and alpha activity and increased gamma power in response to sub-threshold stimuli, in association with behavioral nociceptive hypersensitivity. Inducing gamma oscillations via optogenetic activation of parvalbumin-expressing inhibitory interneurons in the S1 cortex enhances nociceptive sensitivity and induces aversive avoidance behavior. Activity mapping identified a network of prefrontal cortical and subcortical centers whilst morphological tracing and pharmacological studies demonstrate the requirement of descending serotonergic facilitatory pathways in these pain-related behaviors. This study thus describes a mechanistic framework for modulation of pain by specific activity patterns in the S1 cortex. Gamma oscillations in somatosensory areas in humans correlate with pain perception and pain stimulus intensity, but could also reflect cognitive processes such as attention. Here the authors provide evidence in mice that these oscillations causally contribute to pain perception.

Fungal biofilms are complex microbial structures associated with persistent and progressive infections, such as cryptococcal meningitis, invasive aspergillosis, and invasive candidiasis, leading to thousands of deaths annually. The prevalence of fungal biofilm formation during infections, with its heightened resistance to antifungal drugs, highlights the urgency for the discovery and development of new antifungals with antibiofilm activity. Current advances in mass spectrometry-based proteomics and computational platforms provide a powerful toolkit to accelerate drug discovery from target identification to optimization of a lead molecule. In this review, we highlight fungal biofilms of four critical priority fungal pathogens (as deemed by the World Health Organization) and define important technological considerations for proteomics and computational methodologies. Additionally, we explore recent proteomics and computational applications within fungal biofilms for the identification and elucidation of biological mechanisms underscoring biofilm formation as well as the discovery of novel putative antibiofilm targets.

Eastern boundary upwelling ecosystems (EBUEs) are among the most productive marine regions in the world's oceans. Understanding the degree of interannual to decadal variability in the Mauritania upwelling system is crucial for the prediction of future changes of primary productivity and carbon sequestration in the Canary Current EBUE as well as in similar environments. A multiyear sediment trap experiment was conducted at the mooring site CBmeso (“Cape Blanc mesotrophic”, ca. 20∘ N, ca. 20∘40′ W) in the highly productive coastal waters off Mauritania. Here, we present results on fluxes of diatoms and the species-specific composition of the assemblage for the time interval between March 1988 and June 2009. The temporal dynamics of diatom populations allows the proposal of three main intervals: (i) early 1988–late 1996, (ii) 1997–1999, and (iii) early 2002–mid 2009. The Atlantic Multidecadal Oscillation (AMO) appears to be an important driver of the long-term dynamics of diatom population. The long-term AMO-driven trend is interrupted by the occurrence of the strong 1997 El Niño–Southern Oscillation (ENSO). The extraordinary shift in the relative abundance of benthic diatoms in May 2002 suggests the strengthening of offshore advective transport within the uppermost layer of filament waters and in the subsurface and in deeper and bottom-near layers. It is hypothesized that the dominance of benthic diatoms was the response of the diatom community to the intensification of the slope and shelf poleward undercurrents. This dominance followed the intensification of the warm phase of AMO and the associated changes of the Atlantic Meridional Overturning Circulation. Transported valves (siliceous remains) from shallow Mauritanian coastal waters into the bathypelagic should be considered for the calculation and model experiments of bathy- and pelagic nutrients budgets (especially Si), the burial of diatoms, and the paleoenvironmental signal preserved in downcore sediments. Additionally, our 1988–2009 data set contributes to the characterization of the impact of low-frequency climate forcings in the northeastern Atlantic and will be especially helpful for establishing the scientific basis for forecasting and modeling future states of the Canary Current EBUE and its decadal changes.

A painful episode can lead to a life-long increase in an individual’s experience of pain. Fearful anticipation of imminent pain could play a role in this phenomenon, but the neurobiological underpinnings are unclear because fear can both suppress and enhance pain. Here, we show in mice that long-term associative fear memory stored in neuronal engrams in the prefrontal cortex determines whether a painful episode shapes pain experience later in life. Furthermore, under conditions of inflammatory and neuropathic pain, prefrontal fear engrams expand to encompass neurons representing nociception and tactile sensation, leading to pronounced changes in prefrontal connectivity to fear-relevant brain areas. Conversely, silencing prefrontal fear engrams reverses chronically established hyperalgesia and allodynia. These results reveal that a discrete subset of prefrontal cortex neurons can account for the debilitating comorbidity of fear and chronic pain and show that attenuating the fear memory of pain can alleviate chronic pain itself. Can erasing bad memories relieve pain? Stegemann et al. uncover the cellular basis of fear–pain interactions, reporting that fear potentiates pain via memories encoded in prefrontal engrams. Blocking these memory traces reduces chronic pain in mice.

This work focuses on investigating the curing process of an epoxy-based resin—Aerotuf 275-34TM, designed for aerospace applications. To study the curing degree of Aerotuf 275-34TM under processing conditions, woven carbon fiber fabric (WCFF)/Aerotuf 275-34TM composite laminates were produced by compression molding using different processing temperatures (110, 135, 160, and 200 °C) during 15 and 30 min. Then, the mechanical behavior of the composite laminates was evaluated by tensile tests and correlated to the resin curing degree through Fourier-transform infrared spectroscopy (FTIR) analysis. The results show the occurrence of two independent reactions based on the consumption of epoxide groups and maleimide (MI) double bonds. In terms of epoxide groups, a conversion degree of 0.91 was obtained for the composite cured at 160 °C during 15 min, while the measured tensile properties of [±45°] WCFF/Aerotuf 275-34TM laminates confirmed that these epoxy resin curing processing conditions lead to an enhancement of the composite mechanical properties.

Marine diatoms are silica-precipitating microalgae that account for over half of organic carbon burial in marine sediments and thus they play a key role in the global carbon cycle. Their evolutionary expansion during the Cenozoic era (66 Ma to present) has been associated with a superior competitive ability for silicic acid relative to other siliceous plankton such as radiolarians, which evolved by reducing the weight of their silica test. Here we use a mathematical model in which diatoms and radiolarians compete for silicic acid to show that the observed reduction in the weight of radiolarian tests is insufficient to explain the rise of diatoms. Using the lithium isotope record of seawater as a proxy of silicate rock weathering and erosion, we calculate changes in the input flux of silicic acid to the oceans. Our results indicate that the long-term massive erosion of continental silicates was critical to the subsequent success of diatoms in marine ecosystems over the last 40 My and suggest an increase in the strength and efficiency of the oceanic biological pump over this period.

In this work, a previously developed mathematical model to predict bulk density of SLMed (produced via Selective Laser Melting) component is enhanced by taking laser power, scanning speed, hatch spacing, powder’s thermal conductivity and specific heat capacity as independent variables. Experimental data and manufacturing conditions for the selective laser melting (SLM) of metallic materials (which include aluminum, steel, titanium, copper, tungsten and nickel alloys) are adapted from the literature and used to evaluate the validity of the proposed enhanced model. A strong relation between dependent and independent dimensionless products is observed throughout the studied materials. The proposed enhanced mathematical model shows to be highly accurate since the computed root-mean-square-error values (RMSE) does not exceed 5 × 10−7. Furthermore, an analytical expression for the prediction of bulk density of SLMed components was developed. From this, an expression for determining the needed scanning speed, with respect to laser power, to achieve highly dense components produced via SLM, is derived.

Ascorbyl palmitate, an ascorbic acid ester, is an important amphipathic antioxidant that has several applications in foods, pharmaceuticals, and cosmetics. The enzymatic synthesis of ascorbyl palmitate is very attractive, but few efforts have been made to address its process scale-up and implementation. This study aimed at evaluating the enzymatic synthesis of ascorbyl palmitate in a rotating basket reactor operated in sequential batches. Different commercial immobilized lipases were tested, and the most suitable reaction conditions were established. Among those lipases studied were Amano Lipase PS, Lipozyme® TL IM, Lipozyme® Novo 40086, Lipozyme® RM IM and Lipozyme® 435. Initially, the enzymes were screened based on previously defined synthesis conditions, showing clear differences in behavior. Lipozyme® 435 proved to be the best catalyst, reaching the highest values of initial reaction rate and yield. Therefore, it was selected for the following studies. Among the solvents assayed, 2-methyl-2-butanol and acetone showed the highest yields, but the operational stability of the catalyst was better in 2-methyl-2-butanol. The tests in a basket reactor showed great potential for large-scale application. Yields remained over 80% after four sequential batches, and the basket allowed for easy catalyst recycling. The results obtained in basket reactor are certainly a contribution to the enzymatic synthesis of ascorbyl palmitate as a competitive alternative to chemical synthesis. This may inspire future cost-effectiveness studies of the process to assess its potential as a viable alternative to be implemented.

In this paper, entity contextual pre-filtering is proposed to refine dataset relevance assessment and streamline data discovery. Heterogeneous Graph Neural Networks are used to exploit the local context embedded within graph-based schemas. The proposed pre-filtering approach is versatile and does not rely on any specific similarity metric, making it applicable to a wide range of data discovery methods. The proposed technique increases data discovery precision by reducing false positives and identifying significant data relationships. This method has been empirically validated across a variety of real-world datasets to improve data discovery efficiency and accuracy.