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Global climate change is likely to constrain low latitude range edges across many taxa and habitats. Such is the case for NE Atlantic marine macroalgal forests, important ecosystems whose main structuring species is the annual kelp Saccorhiza polyschides. We coupled ecological niche modelling with simulations of potential dispersal and delayed development stages to infer the major forces shaping range edges and to predict their dynamics. Models indicated that the southern limit is set by high winter temperatures above the physiological tolerance of overwintering microscopic stages and reduced upwelling during recruitment. The best range predictions were achieved assuming low spatial dispersal (5 km) and delayed stages up to two years (temporal dispersal). Reconstructing distributions through time indicated losses of similar to 30% from 1986 to 2014, restricting S. polyschides to upwelling regions at the southern edge. Future predictions further restrict populations to a unique refugium in northwestern Iberia. Losses were dependent on the emissions scenario, with the most drastic one shifting similar to 38% of the current distribution by 2100. Such distributional changes might not be rescued by dispersal in space or time (as shown for the recent past) and are expected to drive major biodiversity loss and changes in ecosystem functioning.

Climate change is producing shifts in the distribution and abundance of marine species. Such is the case of kelp forests, important marine ecosystem-structuring species whose distributional range limits have been shifting worldwide. Synthesizing long-term time series of kelp forest observations is therefore vital for understanding the drivers shaping ecosystem dynamics and for predicting responses to ongoing and future climate changes. Traditional methods of mapping kelp from satellite imagery are time-consuming and expensive, as they require high amount of human effort for image processing and algorithm optimization. Here we propose the use of mask region-based convolutional neural networks (Mask R-CNN) to automatically assimilate data from open-source satellite imagery (Landsat Thematic Mapper) and detect kelp forest canopy cover. The analyses focused on the giant kelp Macrocystis pyrifera along the shorelines of southern California and Baja California in the northeastern Pacific. Model hyper-parameterization was tuned through cross-validation procedures testing the effect of data augmentation, and different learning rates and anchor sizes. The optimal model detected kelp forests with high performance and low levels of overprediction (Jaccard’s index: 0.87 ± 0.07; Dice index: 0.93 ± 0.04; over prediction: 0.06) and allowed reconstructing a time series of 32 years in Baja California (Mexico), a region known for its high variability in kelp owing to El Niño events. The proposed framework based on Mask R-CNN now joins the list of cost-efficient tools for long-term marine ecological monitoring, facilitating well-informed biodiversity conservation, management and decision making.

Information on population structure and connectivity of targeted species is key for proper implementation of spatial conservation measures. We used a combination of genomics, biophysical modelling, and biotelemetry to infer the population structure and connectivity of Atlantic meagre, an important fisheries resource throughout its distribution. Genetic samples from previously identified Atlantic spawning locations (Gironde, Tejo, Guadalquivir, Banc d’Arguin) and two additional regions (Algarve and Senegal) were analysed using genome-wide SNP-genotyping and mitochondrial DNA analyses. Biophysical models were conducted to investigate larval dispersal and connectivity from the known Atlantic spawning locations. Additionally, thirteen fish were double-tagged with biotelemetry transmitters off the Algarve (Portugal) to assess movement patterns and connectivity of adult individuals. This multidisciplinary approach provided a robust overview of meagre population structure and connectivity in the Atlantic. Nuclear SNP-genotyping showed a clear differentiation between the European and African populations, with significant isolation of the few known Atlantic spawning sites. The limited level of connectivity between these subpopulations is potentially driven by adults, capable of wide-ranging movements and connecting sites 500 km apart, as evidenced by tagging studies, whilst larval dispersal inferred by modelling is much more limited (average of 52 km; 95% of connectivity events up to 174 km). Our results show sufficient evidence of population structure, particularly between Africa and Europe but also within Europe, for the meagre to be managed as separate stocks. Additionally, considering the low degree of larvae connectivity, the implementation of marine protected areas in key spawning sites could be crucial towards species sustainability.

The cyclic AMP (cAMP)-dependent protein kinase A (PKA) signaling pathway is well conserved across eukaryotes, and previous work has shown that it plays an important role in regulating development, growth, and virulence in a number of fungi. PKA is activated in response to extracellular nutrients and acts to regulate metabolism and growth. While a number of components in the PKA pathway have been defined in filamentous fungi, current understanding does not provide a global perspective on PKA function. Thus, this work is significant in that it comprehensively identifies proteins and functional pathways regulated by PKA in a model filamentous fungus. This information enhances our understanding of PKA action and may provide information on how to manipulate it for specific purposes. In filamentous fungi, an important kinase responsible for adaptation to changes in available nutrients is cyclic AMP (cAMP)-dependent protein kinase (protein kinase A [PKA]). This kinase has been well characterized at a molecular level, but its systemic action and direct/indirect targets are generally not well understood in filamentous fungi. In this work, we used a pkaA deletion strain (Δ pkaA ) to identify Aspergillus nidulans proteins for which phosphorylation is dependent (either directly or indirectly) on PKA. A combination of phosphoproteomic and transcriptomic analyses revealed both direct and indirect targets of PKA and provided a global perspective on its function. One of these targets was the transcription factor CreA, the main repressor responsible for carbon catabolite repression (CCR). In the Δ pkaA strain, we identified a previously unreported phosphosite in CreA, S319, which (based on motif analysis) appears to be a direct target of Stk22 kinase (AN5728). Upon replacement of CreA S319 with an alanine (i.e., phosphonull mutant), the dynamics of CreA import to the nucleus are affected. Collectively, this work provides a global overview of PKA function while also providing novel insight regarding significance of a specific PKA-mediated phosphorylation event. IMPORTANCE The cyclic AMP (cAMP)-dependent protein kinase A (PKA) signaling pathway is well conserved across eukaryotes, and previous work has shown that it plays an important role in regulating development, growth, and virulence in a number of fungi. PKA is activated in response to extracellular nutrients and acts to regulate metabolism and growth. While a number of components in the PKA pathway have been defined in filamentous fungi, current understanding does not provide a global perspective on PKA function. Thus, this work is significant in that it comprehensively identifies proteins and functional pathways regulated by PKA in a model filamentous fungus. This information enhances our understanding of PKA action and may provide information on how to manipulate it for specific purposes.

Microbial species capable of co-existing with healthy individuals, such as the commensal fungus Candida albicans, exploit multifarious strategies to evade our immune defenses. These strategies include the masking of immunoinflammatory pathogen-associated molecular patterns (PAMPs) at their cell surface. We reported previously that C. albicans actively reduces the exposure of the proinflammatory PAMP, β-1,3-glucan, at its cell surface in response to host-related signals such as lactate and hypoxia. Here, we show that clinical isolates of C. albicans display phenotypic variability with respect to their lactate- and hypoxia-induced β-1,3-glucan masking. We have exploited this variability to identify responsive and non-responsive clinical isolates. We then performed RNA sequencing on these isolates to reveal genes whose expression patterns suggested potential association with lactate- or hypoxia-induced β-1,3-glucan masking. The deletion of two such genes attenuated masking: PHO84 and NCE103. We examined NCE103-related signaling further because NCE103 has been shown previously to encode carbonic anhydrase, which promotes adenylyl cyclase-protein kinase A (PKA) signaling at low CO2 levels. We show that while CO2 does not trigger β-1,3-glucan masking in C. albicans, the Sch9-Rca1-Nce103 signaling module strongly influences β-1,3-glucan exposure in response to hypoxia and lactate. In addition to identifying a new regulatory module that controls PAMP exposure in C. albicans, our data imply that this module is important for PKA signaling in response to environmental inputs other than CO2.IMPORTANCEOur innate immune defenses have evolved to protect us against microbial infection in part via receptor-mediated detection of “pathogen-associated molecular patterns” (PAMPs) expressed by invading microbes, which then triggers their immune clearance. Despite this surveillance, many microbial species are able to colonize healthy, immune-competent individuals, without causing infection. To do so, these microbes must evade immunity. The commensal fungus Candida albicans exploits a variety of strategies to evade immunity, one of which involves reducing the exposure of a proinflammatory PAMP (β-1,3-glucan) at its cell surface. Most of the β-1,3-glucan is located in the inner layer of the C. albicans cell wall, hidden by an outer layer of mannan fibrils. Nevertheless, some β-1,3-glucan can become exposed at the fungal cell surface. However, in response to certain specific host signals, such as lactate or hypoxia, C. albicans activates an anticipatory protective response that decreases β-1,3-glucan exposure, thereby reducing the susceptibility of the fungus to impending innate immune attack. Here, we exploited the natural phenotypic variability of C. albicans clinical isolates to identify strains that do not display the response to β-1,3-glucan masking signals observed for the reference isolate, SC5314. Then, using genome-wide transcriptional profiling, we compared these non-responsive isolates with responsive controls to identify genes potentially involved in β-1,3-glucan masking. Mutational analysis of these genes revealed that a sensing module that was previously associated with CO2 sensing also modulates β-1,3-glucan exposure in response to hypoxia and lactate in this major fungal pathogen of humans.

To investigate the biomechanical factors associated with patellofemoral pain in children and adolescents. A cross-sectional, population-based study conducted in Brazil from 2019 to 2023, involving students from public schools. Adjusted prevalence ratios and their respective 95% confidence intervals for the outcome in relation to independent variables were calculated for association analysis, adopting a significance level of 5%. Out of the total of 283 students, 152 were female and 182 were aged between 16 and 18 years old. A positive association was observed between the presence of patellofemoral pain and a poor movement quality in both lower limbs (right side: p  = 0.04 and left side: p  = 0.04) as well as with dynamic valgus of the left lower limb ( p  < 0.01). Patellofemoral pain in children and adolescents is associated with poor movement quality in the lower limbs and dynamic valgus of the left lower limb. Actions targeting these biomechanical factors may be crucial for early diagnosis and clinical treatment of this disfunction.

Samples of black pepper root with the presence of galls from the most southern region of the State of Bahia, Brazil, were characterized biochemically and morphologically using three criteria: i) observation of the anterior region of the males; ii) analysis of female perineal configuration and iii) polyacrylamide gel electrophoresis technique. was found. This is the first report of this pathosystem in the State.

Despite the promising results indicating the beneficial outcomes associated with the application of probiotics in corals and some scarce knowledge regarding the identity of bacterial cells found within the coral tissue, the correlation between these two aspects is still missing. This gap limits our understanding of the actual diversity of coral-associated bacteria and whether these symbionts are beneficial. Some researchers, for example, have been suggesting that probiotic screening should only focus on the very few known tissue-associated bacteria, such as Endozoicomonas sp., assuming that the currently tested probiotics are not tissue-associated. Here, we provide specific FISH probes for Halomonas sp. and Cobetia sp., expand our knowledge of the identity of coral-associated bacteria and confirm the probiotic status of the tested probiotics. The presence of these beneficial microorganisms for corals (BMCs) inside host tissues and gastric cavities also supports the notion that direct interactions with the host may underpin their probiotic role. This is a new breakthrough; these results argue against the possibility that the positive effects of BMCs are due to factors that are not related to a direct symbiotic interaction, for example, that the host simply feeds on inoculated bacteria or that the bacteria change the water quality.

The use of digital images could be a faster and cheaper alternative technique to assess BW, HCW, and body composition of beef cattle. The objective of this study was to develop equations to predict body and carcass weight and body fat content of young bulls using digital images obtained through a Microsoft Kinect device. Thirty-five bulls with an initial BW of 383 (±5.38) kg (20 Black Angus, 390 [±7.48] kg initial BW, and 15 Nellore, 377 [±8.66] kg initial BW) were used. The Kinect sensor, installed on the top of a cattle chute, was used to take infrared light-based depth videos, recorded before the slaughter. For each animal, a quality control was made, running and pausing the video at the moment that the animal was standing with its body and head in line. One frame from recorded videos was selected and used to analyze the following body measurements: chest width, thorax width, abdomen width, body length, dorsal height, and dorsal area. From these body measurements, 23 indexes were generated and tested as potential predictors. The BW and HCW were assessed with a digital scale, whereas empty body fat (EBF) was estimated through ground samples of all tissues. To better understand the relationship among the measurements, the correlations between final BW (488 [±10.4] kg), HCW (287 [±12.5] kg), EBF (14 [±0.610] % empty BW) content, body measurements (taken through digital images), and developed indexes were evaluated. The REG procedure was used to develop the regressions, and the important independent variables were identified using the options STEPWISE and Mallow's Cp in the SELECTION statement. Chest width was the trait most related to weights and the correlations between this measurement and BW and HCW were above 0.85. The analysis of linear regressions between observed and predicted values showed that all models pass through the origin and have a slope of unity (null hypothesis [H]: = 0 and = 1; ≥ 0.993). The models to estimate BW and HCW of Angus and Nellore presented between 0.69 and 0.84 ( < 0.001), whereas from equations to estimate the EBF were lower ( = 0.43-0.45; ≤ 0.006). Index I5 [(chest width) × body length], related to the animal volume, was significant in all models created to estimate BW and HCW, and it explained more than 70% of the variation. This study indicates that digital images taken through a Microsoft Kinect system have the potential to be used as a tool to estimate body and carcass weight of beef cattle.

Most microbes have developed responses that protect them against stresses relevant to their niches. Some that inhabit reasonably predictable environments have evolved anticipatory responses that protect against impending stresses that are likely to be encountered in their niches–termed “adaptive prediction”. Unlike yeasts such as Saccharomyces cerevisiae , Kluyveromyces lactis and Yarrowia lipolytica and other pathogenic Candida species we examined, the major fungal pathogen of humans, Candida albicans , activates an oxidative stress response following exposure to physiological glucose levels before an oxidative stress is even encountered. Why? Using competition assays with isogenic barcoded strains, we show that “glucose-enhanced oxidative stress resistance” phenotype enhances the fitness of C . albicans during neutrophil attack and during systemic infection in mice. This anticipatory response is dependent on glucose signalling rather than glucose metabolism. Our analysis of C . albicans signalling mutants reveals that the phenotype is not dependent on the sugar receptor repressor pathway, but is modulated by the glucose repression pathway and down-regulated by the cyclic AMP-protein kinase A pathway. Changes in catalase or glutathione levels do not correlate with the phenotype, but resistance to hydrogen peroxide is dependent on glucose-enhanced trehalose accumulation. The data suggest that the evolution of this anticipatory response has involved the recruitment of conserved signalling pathways and downstream cellular responses, and that this phenotype protects C . albicans from innate immune killing, thereby promoting the fitness of C . albicans in host niches.