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Using the factors of soil formation to assess stable carbon isotope disequilibrium in late Pleistocene (MIS 3) buried soils of the Great Plains, North America
Get PDFThe stable carbon isotope composition of both soil organic matter (SOM) and pedogenic carbonate are widely used as paleoenvironmental proxies. This study utilizes δ13C analyses to reconstruct bioclimatic change from a series of buried soils in the central Great Plains of North America that developed between ca. 44–24 ka. Results revealed a paradoxical isotopic disequilibrium between the isotopic composition of bulk SOM (δ13CSOM) and pedogenic carbonate (δ13Ccarb). Specifically, Δ13C values are 0.1 to 6.3 per mil greater than the highest expected equilibrium value of 17 per mil in the Bk horizons. In contrast, Δ13C values are 0.1 to 4.8 per mil lower than the lowest expected equilibrium value of 14 per mil in the Ak horizons. A soil-forming factor approach was utilized to establish multiple working hypotheses regarding the influence of climate, vegetation, parent material, and time on the observed isotopic disequilibrium.
Of the various hypotheses presented, we suggest that the following most likely explain the observed isotopic disequilibrium. The greater-than-expected Δ13C values in the Bk horizons most likely reflects seasonal bias in pedogenic carbonate formation, resulting in an apparent C4-biased signal. The lower-than-expected Δ13C values in the Ak horizons remains perplexing. The most likely explanation is that detrital carbonate contributions affected the δ13Ccarb record or that the δ13Ccarb and δ13CSOM records are asynchronous. Overall, it appears that different factors have affected the δ13CSOM and δ13Ccarb records independently and therefore results of this study highlight the importance of assessing pedogenic carbonates for isotopic equilibrium as well as the need to understand past environmental conditions (i.e., soil-forming factors) when interpreting isotopic trends
The HRA2pl fusion peptide exerts in vitro antiviral activity against human respiratory paramyxoviruses and pneumoviruses
Get PDFAcute respiratory infections are a group of diseases caused by viruses, bacteria, and parasites that mainly affect children until the age of 5 and immunocompromised senior adults. In Mexico, these infections are the main cause of morbidity in children, with more than 26 million cases of respiratory infections reported by the Secretariat of Health, in 2019. The human respiratory syncytial virus (hRSV), the human metapneumovirus (hMPV), and the human parainfluenza-2 (hPIV-2) are responsible for many respiratory infections. Currently, palivizumab, a monoclonal antibody against the fusion protein F, is the treatment of choice against hRSV infections. This protein is being studied for the design of antiviral peptides that act by inhibiting the fusion of the virus and the host cell. Therefore, we examined the antiviral activity of the HRA2pl peptide, which competes the heptad repeat A domain of the F protein of hMPV. The recombinant peptide was obtained using a viral transient expression system. The effect of the fusion peptide was evaluated with an in vitro entry assay. Moreover, the effectiveness of HRA2pl was examined in viral isolates from clinical samples obtained from patients with infections caused by hRSV, hMPV, or hPIV-2, by evaluating the viral titer and the syncytium size. The HRA2pl peptide affected the viruses’ capacity of entry, resulting in a 4-log decrease in the viral titer compared to the untreated viral strains. Additionally, a 50% reduction in the size of the syncytium was found. These results demonstrate the antiviral potential of HRA2pl in clinical samples, paving the way toward clinical trials
Discovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligence
Get PDFDeep brain stimulation is a treatment that controls symptoms by changing brain activity. The complexity of how to best treat brain dysfunction with deep brain stimulation has spawned research into artificial intelligence approaches. Machine learning is a subset of artificial intelligence that uses computers to learn patterns in data and has many healthcare applications, such as an aid in diagnosis, personalized medicine, and clinical decision support. Yet, how machine learning models make decisions is often opaque. The spirit of explainable artificial intelligence is to use machine learning models that produce interpretable solutions. Here, we use topic modeling to synthesize recent literature on explainable artificial intelligence approaches to extracting domain knowledge from machine learning models relevant to deep brain stimulation. The results show that patient classification (i.e., diagnostic models, precision medicine) is the most common problem in deep brain stimulation studies that employ explainable artificial intelligence. Other topics concern attempts to optimize stimulation strategies and the importance of explainable methods. Overall, this review supports the potential for artificial intelligence to revolutionize deep brain stimulation by personalizing stimulation protocols and adapting stimulation in real time
Simulating the dynamics of dispersal and dispersal ability in fragmented populations with mate-finding Allee effects
Get PDFWe consider the spatial propagation and genetic evolution of model populations comprising multiple subpopulations, each distinguished by its own characteristic dispersal rate. Mate finding is modeled in accord with the assumption that reproduction is based on random encounters between pairs of individuals, so that the frequency of interbreeding between two subpopulations is proportional to the product of local population densities of each. The resulting nonlinear growth term produces an Allee effect, whereby reproduction rates are lower in sparsely populated areas; the distribution of dispersal rates that evolves is then highly dependent upon the population's initial spatial distribution. In a series of numerical test cases, we consider how these dynamics affect lattice-like arrangements of population fragments, and investigate how a population's initial fragmentation determines the dispersal rates that evolve as a habitat is colonized. First, we consider a case where initial population fragments coincide with habitat islands, within which death rates differ from those that apply outside; the presence of inhospitable exterior regions exaggerates Allee effect-driven reductions in dispersal ability. We then examine how greater distances separating adjacent population fragments lead to more severe reductions in dispersal ability. For populations of a fixed initial magnitude, fragmentation into smaller, denser patches leads not only to greater losses of dispersal ability, but also helps ensure the population's long-term persistence, emphasizing the trade-offs between the benefits and risks of rapid dispersal under Allee effects. Next, simulations of well-established populations disrupted by localized depopulation events illustrate how mate-finding Allee effects and spatial heterogeneity can drive a population's dispersal ability to evolve either downward or upward depending on conditions, highlighting a qualitative distinction between population fragmentation and habitat heterogeneity. A final test case compares populations that are fragmented across multiple scales, demonstrating how differences in the relative scales of micro- and macro-level fragmentation can lead to qualitatively different evolutionary outcomes
Cross-species activation of hydrogen cyanide production by a promiscuous quorum-sensing receptor promotes Chromobacterium subtsugae competition in a dual-species model
Get PDFMany saprophytic bacteria have LuxR-I-type acyl-homoserine lactone (AHL) quorum-sensing systems that may be important for competing with other bacteria in complex soil communities. LuxR AHL receptors specifically interact with cognate AHLs to cause changes in expression of target genes. Some LuxR-type AHL receptors have relaxed specificity and are responsive to non-cognate AHLs. These promiscuous receptors might be used to sense and respond to AHLs produced by other bacteria by eavesdropping. We are interested in understanding the role of eavesdropping during interspecies competition. The soil saprophyte Chromobacterium subtsugae has a single AHL circuit, CviR-I, which produces and responds to N-hexanoyl-HSL (C6-HSL). The AHL receptor CviR can respond to a variety of AHLs in addition to C6-HSL. In prior studies we have utilized a coculture model with C. subtsugae and another soil saprophyte, Burkholderia thailandensis. Using this model, we previously showed that promiscuous activation of CviR by B. thailandensis AHLs provides a competitive advantage to C. subtsugae. Here, we show that B. thailandensis AHLs activate transcription of dozens of genes in C. subtsugae, including the hcnABC genes coding for production of hydrogen cyanide. We show that hydrogen cyanide production is population density-dependent and demonstrate that the cross-induction of hydrogen cyanide by B. thailandensis AHLs provides a competitive advantage to C. subtsugae. Our results provide new information on C. subtsugae quorum sensing and are the basis for future studies aimed at understanding the role of eavesdropping in interspecies competition
Effects of presenilin-1 familial Alzheimer’s disease mutations on γ-secretase activation for cleavage of amyloid precursor protein
Get PDFPresenilin-1 (PS1) is the catalytic subunit of γ-secretase which cleaves within the transmembrane domain of over 150 peptide substrates. Dominant missense mutations in PS1 cause early-onset familial Alzheimer’s disease (FAD); however, the exact pathogenic mechanism remains unknown. Here we combined Gaussian accelerated molecular dynamics (GaMD) simulations and biochemical experiments to determine the effects of six representative PS1 FAD mutations (P117L, I143T, L166P, G384A, L435F, and L286V) on the enzyme-substrate interactions between γ-secretase and amyloid precursor protein (APP). Biochemical experiments showed that all six PS1 FAD mutations rendered γ-secretase less active for the endoproteolytic (ε) cleavage of APP. Distinct low-energy conformational states were identified from the free energy profiles of wildtype and PS1 FAD-mutant γ-secretase. The P117L and L286V FAD mutants could still sample the “Active” state for substrate cleavage, but with noticeably reduced conformational space compared with the wildtype. The other mutants hardly visited the “Active” state. The PS1 FAD mutants were found to reduce γ-secretase proteolytic activity by hindering APP residue L49 from proper orientation in the active site and/or disrupting the distance between the catalytic aspartates. Therefore, our findings provide mechanistic insights into how PS1 FAD mutations affect structural dynamics and enzyme-substrate interactions of γ-secretase and APP
Crystal orientation fabric anisotropy causes directional hardening of the Northeast Greenland Ice Stream
Get PDFThe dynamic mass loss of ice sheets constitutes one of the biggest uncertainties in projections of ice-sheet evolution. One central, understudied aspect of ice flow is how the bulk orientation of the crystal orientation fabric translates to the mechanical anisotropy of ice. Here we show the spatial distribution of the depth-averaged horizontal anisotropy and corresponding directional flow-enhancement factors covering a large area of the Northeast Greenland Ice Stream onset. Our results are based on airborne and ground-based radar surveys, ice-core observations, and numerical ice-flow modelling. They show a strong spatial variability of the horizontal anisotropy and a rapid crystal reorganisation on the order of hundreds of years coinciding with the ice-stream geometry. Compared to isotropic ice, parts of the ice stream are found to be more than one order of magnitude harder for along-flow extension/compression while the shear margins are potentially softened by a factor of two for horizontal-shear deformation
Exploring individual differences in musical rhythm and grammar skills in school-aged children with typically developing language
Get PDFA growing number of studies have shown a connection between rhythmic processing and language skill. It has been proposed that domain-general rhythm abilities might help children to tap into the rhythm of speech (prosody), cueing them to prosodic markers of grammatical (syntactic) information during language acquisition, thus underlying the observed correlations between rhythm and language. Working memory processes common to task demands for musical rhythm discrimination and spoken language paradigms are another possible source of individual variance observed in musical rhythm and language abilities. To investigate the nature of the relationship between musical rhythm and expressive grammar skills, we adopted an individual differences approach in N = 132 elementary school-aged children ages 5–7, with typical language development, and investigated prosodic perception and working memory skills as possible mediators. Aligning with the literature, musical rhythm was correlated with expressive grammar performance (r = 0.41, p < 0.001). Moreover, musical rhythm predicted mastery of complex syntax items (r = 0.26, p = 0.003), suggesting a privileged role of hierarchical processing shared between musical rhythm processing and children’s acquisition of complex syntactic structures. These relationships between rhythm and grammatical skills were not mediated by prosodic perception, working memory, or non-verbal IQ; instead, we uncovered a robust direct effect of musical rhythm perception on grammatical task performance. Future work should focus on possible biological endophenotypes and genetic influences underlying this relationship
Interspecific hybridization explains rapid gorget colour divergence in Heliodoxa hummingbirds (Aves: Trochilidae)
Get PDFHybridization is a known source of morphological, functional and communicative signal novelty in many organisms. Although diverse mechanisms of established novel ornamentation have been identified in natural populations, we lack an understanding of hybridization effects across levels of biological scales and upon phylogenies. Hummingbirds display diverse structural colours resulting from coherent light scattering by feather nanostructures. Given the complex relationship between feather nanostructures and the colours they produce, intermediate coloration does not necessarily imply intermediate nanostructures. Here, we characterize nanostructural, ecological and genetic inputs in a distinctive Heliodoxa hummingbird from the foothills of eastern Peru. Genetically, this individual is closely allied with Heliodoxa branickii and Heliodoxa gularis, but it is not identical to either when nuclear data are assessed. Elevated interspecific heterozygosity further suggests it is a hybrid backcross to H. branickii. Electron microscopy and spectrophotometry of this unique individual reveal key nanostructural differences underlying its distinct gorget colour, confirmed by optical modelling. Phylogenetic comparative analysis suggests that the observed gorget coloration divergence from both parentals to this individual would take 6.6–10 My to evolve at the current rate within a single hummingbird lineage. These results emphasize the mosaic nature of hybridization and suggest that hybridization may contribute to the structural colour diversity found across hummingbirds
Life and times of data access: Regarding Native Lands
Get PDFIt is challenging to understand the full and detailed story of Native People’s lands in the United States. In this article, we contend that reliable and accessible data regarding Native People’s lands complicate and perpetuate those challenges. Stemming from the implications of colonial ideologies, such as the General Allotment Act of 1887, Native Peoples’ land-based data are difficult to access for Tribal Nations and researchers. Land data have been and continue to be obscured by U.S. federal processes and are dependent on unreliable systems of outdated and exclusive practices that consistently marginalize Native Peoples. Therefore, those data do not adequately inform Tribal land planning initiatives. In this article we recommend new processes that strengthen Tribal data sovereignty as the fundamental underpinnings to an inclusive and protected data in the future