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Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern United States, Canada, and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116 (Proc. Natl. Acad. Sci. U.S.A. 116, 24268–24274). The authors note that the following statement should be added to the Acknowledgments: “E.A.M. was supported by NIH Grant R35GM133439.

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner's ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person's own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.

Biodiversity loss is one major outcome of human-mediated ecosystem disturbance. One way that humans have triggered wildlife declines is by transporting disease-causing agents to remote areas of the world. Amphibians have been hit particularly hard by disease due in part to a globally distributed pathogenic chytrid fungus (Batrachochytrium dendrobatidis [Bd]). Prior research has revealed important insights into the biology and distribution of Bd; however, there are still many outstanding questions in this system. Although we know that there are multiple divergent lineages of Bd that differ in pathogenicity, we know little about how these lineages are distributed around the world and where lineages may be coming into contact. Here, we implement a custom genotyping method for a global set of Bd samples. This method is optimized to amplify and sequence degraded DNA from noninvasive skin swab samples. We describe a divergent lineage of Bd, which we call BdASIA3, that appears to be widespread in Southeast Asia. This lineage co-occurs with the global panzootic lineage (BdGPL) in multiple localities. Additionally, we shed light on the global distribution of BdGPL and highlight the expanded range of another lineage, BdCAPE. Finally, we argue that more monitoring needs to take place where Bd lineages are coming into contact and where we know little about Bd lineage diversity. Monitoring need not use expensive or difficult field techniques but can use archived swab samples to further explore the history-and predict the future impacts-of this devastating pathogen.

Diversity of α-helical host defense peptides (αHDPs) contributes to immunity against a broad spectrum of pathogens via multiple functions. Thus, resolving common structure-function relationships among αHDPs is inherently difficult, even for artificial-intelligence-based methods that seek multifactorial trends rather than foundational principles. Here, bioinformatic and pattern recognition methods were applied to identify a unifying signature of eukaryotic αHDPs derived from amino acid sequence, biochemical, and three-dimensional properties of known αHDPs. The signature formula contains a helical domain of 12 residues with a mean hydrophobic moment of 0.50 and favoring aliphatic over aromatic hydrophobes in 18-aa windows of peptides or proteins matching its semantic definition. The holistic α-core signature subsumes existing physicochemical properties of αHDPs, and converged strongly with predictions of an independent machine-learning-based classifier recognizing sequences inducing negative Gaussian curvature in target membranes. Queries using the α-core formula identified 93% of all annotated αHDPs in proteomic databases and retrieved all major αHDP families. Synthesis and antimicrobial assays confirmed efficacies of predicted sequences having no previously known antimicrobial activity. The unifying α-core signature establishes a foundational framework for discovering and understanding αHDPs encompassing diverse structural and mechanistic variations, and affords possibilities for deterministic design of antiinfectives.

Chronic inflammatory milieu in the tumor microenvironment (TME) leads to the recruitment and differentiation of myeloid-derived suppressor cells (MDSCs). Polymorphonuclear (PMN)-MDSCs, which are phenotypically and morphologically defined as a subset of neutrophils, cause major immune suppression in the TME, posing a significant challenge in the development of effective immunotherapies. Despite recent advances in our understanding of PMN-MDSC functions, the mechanism that gives rise to immunosuppressive neutrophils within the TME remains elusive. Both in vivo and in vitro, newly recruited neutrophils into the tumor sites remained activated and highly motile for several days and developed immunosuppressive phenotypes, as indicated by increased arginase 1 (Arg1) and dcTrail-R1 expression and suppressed anticancer CD8 T cell cytotoxicity. The strong suppressive function was successfully recapitulated by incubating naive neutrophils with cancer cell culture supernatant in vitro. Cancer metabolite secretome analyses of the culture supernatant revealed that both murine and human cancers released lipid mediators to induce the differentiation of immunosuppressive neutrophils. Liquid chromatography-mass spectrometry (LC-MS) lipidomic analysis identified platelet-activation factor (PAF; 1-O-alkyl-2-acetyl-sn-glycero-3-phosphocholine) as a common tumor-derived lipid mediator that induces neutrophil differentiation. Lysophosphatidylcholine acyltransferase 2 (LPCAT2), the PAF biosynthetic enzyme, is up-regulated in human pancreatic ductal adenocarcinoma (PDAC) and shows an unfavorable correlation with patient survival across multiple cancer types. Our study identifies PAF as a lipid-driven mechanism of MDSC differentiation in the TME, providing a potential target for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Diana Wall, a respected environmental and sustainability scientist, has passed away at the age of 80. She was a University Distinguished Professor at Colorado State University and made significant contributions to the fields of soil ecology and sustainability science. Diana was a strong advocate for soil biodiversity and emphasized the crucial role of soil organisms in ecosystem processes. Her work has been recognized with numerous awards and honors, and her legacy will continue to inspire and impact the scientific community. Additionally, the given text references several sources that provide valuable insights into the formation of soil and the significance of worms in this process, including Charles Darwin's book "The Formation of Vegetable Mould, Through the Action of Worms, with Observations on Their Habits" published in 1881, a review of this book by W. Gifford et al. in 1882, H. Jenny's book "Factors of Soil Formation – A System of Quantitative Pedology" published in 1941, and a global soil biodiversity atlas by A. Orgiazzi et al. published in 2016. [Extracted from the article]

This article explores the drawbacks of pausing the tenure clock, specifically in relation to extensions granted to faculty members for personal reasons. While extensions can be beneficial for affected faculty, they can also delay salary increases, job security, and recognition of career accomplishments without providing adequate financial support. The article suggests improving extension policies by allowing candidates to opt out, establishing clear tenure standards independent of a timeline, and making extensions more equitable by providing additional funding and addressing long-term salary consequences. The article also discusses the potential negative impacts of extensions on tenure cases and the vulnerability of pre-tenure faculty. Opt-out policies are considered best practice, but cultural norms and expectations around tenure can still present challenges for faculty who choose to opt out. The text further examines the challenges and potential negative outcomes associated with tenure clock extensions in academic institutions. It identifies three undesirable outcomes: administrators having discretion over granting extensions, raising the tenure requirements excessively, and extensions not actually moving the tenure date. The article proposes that tenure clock extensions should function as a safety net rather than an insurance policy and provides policy recommendations to ensure fair and appropriate use of extensions without penalizing faculty. It emphasizes the importance of clear communication, objective tenure standards, extended funding, and financial security for those who require extensions. [Extracted from the article]

Linker histones play an essential role in chromatin packaging by facilitating compaction of the 11-nm fiber of nucleosomal "beads on a string." The result is a heterogeneous condensed state with local properties that range from dynamic, irregular, and liquid-like to stable and regular structures (the 30-nm fiber), which in turn impact chromatin-dependent activities at a fundamental level. The properties of the condensed state depend on the type of linker histone, particularly on the highly disordered C-terminal tail, which is the most variable region of the protein, both between species, and within the various subtypes and cell-type specific variants of a given organism. We have developed an in vitro model system comprising linker histone tail and linker DNA, which although very minimal, displays surprisingly complex behavior, and is sufficient to model the known states of linker histone-condensed chromatin: disordered "fuzzy" complexes ("open" chromatin), dense liquid-like assemblies (dynamic condensates), and higher-order structures (organized 30-nm fibers). A crucial advantage of such a simple model is that it allows the study of the various condensed states by NMR, circular dichroism, and scattering methods. Moreover, it allows capture of the thermodynamics underpinning the transitions between states through calorimetry. We have leveraged this to rationalize the distinct condensing properties of linker histone subtypes and variants across species that are encoded by the amino acid content of their C-terminal tails. Three properties emerge as key to defining the condensed state: charge density, lysine/arginine ratio, and proline-free regions, and we evaluate each separately using a strategic mutagenesis approach. [ABSTRACT FROM AUTHOR]

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.

Agricultural foods and technologies are thought to have eased the mechanical demands of diet-how often or how hard one had to chew-in human populations worldwide. Some evidence suggests correspondingly worldwide changes in skull shape and form across the agricultural transition, although these changes have proved difficult to characterize at a global scale. Here, adapting a quantitative genetics mixed model for complex phenotypes, we quantify the influence of diet on global human skull shape and form. We detect modest directional differences between foragers and farmers. The effects are consistent with softer diets in preindustrial farming groups and are most pronounced and reliably directional when the farming class is limited to dairying populations. Diet effect magnitudes are relatively small, affirming the primary role of neutral evolutionary processes-genetic drift, mutation, and gene flow structured by population history and migrations-in shaping diversity in the human skull. The results also bring an additional perspective to the paradox of why Homo sapiens, particularly agriculturalists, appear to be relatively well suited to efficient (high-leverage) chewing.

Frontotemporal dementia (FTD) is the second most common dementia before 65 years of age. Haploinsufficiency in the progranulin (GRN) gene accounts for 10% of all cases of familial FTD. GRN mutation carriers have an increased risk of autoimmune disorders, accompanied by elevated levels of tissue necrosis factor (TNF) α. We examined behavioral alterations related to obsessive-compulsive disorder (OCD) and the role of TNFα and related signaling pathways in FTD patients with GRN mutations and in mice lacking progranulin (PGRN). We found that patients and mice with GRN mutations displayed OCD and self-grooming (an OCD-like behavior in mice), respectively. Furthermore, medium spiny neurons in the nucleus accumbens, an area implicated in development of OCD, display hyperexcitability in PGRN knockout mice. Reducing levels of TNFα in PGRN knockout mice abolished excessive self-grooming and the associated hyperexcitability of medium spiny neurons of the nucleus accumbens. In the brain, PGRN is highly expressed in microglia, which are a major source of TNFα. We therefore deleted PGRN specifically in microglia and found that it was sufficient to induce excessive grooming. Importantly, excessive grooming in these mice was prevented by inactivating nuclear factor κB (NF-κB) in microglia/myeloid cells. Our findings suggest that PGRN deficiency leads to excessive NF-κB activation in microglia and elevated TNFα signaling, which in turn lead to hyperexcitability of medium spiny neurons and OCD-like behavior.

Iron doping of nickel oxide films results in enhanced activity for promoting the oxygen evolution reaction (OER). Whereas this enhanced activity has been ascribed to a unique iron site within the nickel oxide matrix, we show here that Fe doping influences the Ni valency. The percent of Fe3+ doping promotes the formation of formal Ni4+, which in turn directly correlates with an enhanced activity of the catalyst in promoting OER. The role of Fe3+ is consistent with its behavior as a superior Lewis acid.

Carbapenem-resistant Enterobacteriaceae (CRE) are among the most severe threats to the antibiotic era. Multiple different species can exhibit resistance due to many different mechanisms, and many different mobile elements are capable of transferring resistance between lineages. We prospectively sampled CRE from hospitalized patients from three Boston-area hospitals, together with a collection of CRE from a single California hospital, to define the frequency and characteristics of outbreaks and determine whether there is evidence for transfer of strains within and between hospitals and the frequency with which resistance is transferred between lineages or species. We found eight species exhibiting resistance, with the majority of our sample being the sequence type 258 (ST258) lineage of Klebsiella pneumoniae There was very little evidence of extensive hospital outbreaks, but a great deal of variation in resistance mechanisms and the genomic backgrounds carrying these mechanisms. Local transmission was evident in clear phylogeographic structure between the samples from the two coasts. The most common resistance mechanisms were KPC (K. pneumoniae carbapenemases) beta-lactamases encoded by blaKPC2, blaKPC3, and blaKPC4, which were transferred between strains and species by seven distinct subgroups of the Tn4401 element. We also found evidence for previously unrecognized resistance mechanisms that produced resistance when transformed into a susceptible genomic background. The extensive variation, together with evidence of transmission beyond limited clonal outbreaks, points to multiple unsampled transmission chains throughout the continuum of care, including asymptomatic carriage and transmission of CRE. This finding suggests that to control this threat, we need an aggressive approach to surveillance and isolation.

Efforts to develop an HIV-1 vaccine include those focusing on conserved structural elements as the target of broadly neutralizing monoclonal antibodies. MAb D5 binds to a highly conserved hydrophobic pocket on the gp41 N-heptad repeat (NHR) coiled coil and neutralizes through prevention of viral fusion and entry. Assessment of 17-mer and 36-mer NHR peptides presenting the D5 epitope in rodent immunogenicity studies showed that the longer peptide elicited higher titers of neutralizing antibodies, suggesting that neutralizing epitopes outside of the D5 pocket may exist. Although the magnitude and breadth of neutralization elicited by NHR-targeting antigens are lower than that observed for antibodies directed to other epitopes on the envelope glycoprotein complex, it has been shown that NHR-directed antibodies are potentiated in TZM-bl cells containing the FcγRI receptor. Herein, we report the design and evaluation of covalently stabilized trimeric 51-mer peptides encompassing the complete gp41 NHR. We demonstrate that these peptide trimers function as effective antiviral entry inhibitors and retain the ability to present the D5 epitope. We further demonstrate in rodent and nonhuman primate immunization studies that our 51-mer constructs elicit a broader repertoire of neutralizing antibody and improved cross-clade neutralization of primary HIV-1 isolates relative to 17-mer and 36-mer NHR peptides in A3R5 and FcγR1-enhanced TZM-bl assays. These results demonstrate that sensitive neutralization assays can be used for structural enhancement of moderately potent neutralizing epitopes. Finally, we present expanded trimeric peptide designs which include unique low-molecular-weight scaffolds that provide versatility in our immunogen presentation strategy. [ABSTRACT FROM AUTHOR]

Consumers range from specialists that feed on few resources to generalists that feed on many. Generalism has the clear advantage of having more resources to exploit, but the costs that limit generalism are less clear. We explore two understudied costs of generalism in a generalist amoeba predator, Dictyostelium discoideum, feeding on naturally co-occurring bacterial prey. Both involve costs of combining prey that are suitable on their own. First, amoebas exhibit a reduction in growth rate when they switched to one species of prey bacteria from another compared to controls that experience only the second prey. The effect was consistent across all six tested species of bacteria. These switching costs typically disappear within a day, indicating adjustment to new prey bacteria. This suggests that these costs are physiological. Second, amoebas usually grow more slowly on mixtures of prey bacteria compared to the expectation based on their growth on single prey. There were clear mixing costs in three of the six tested prey mixtures, and none showed significant mixing benefits. These results support the idea that, although amoebas can consume a variety of prey, they must use partially different methods and thus must pay costs to handle multiple prey, either sequentially or simultaneously [ABSTRACT FROM AUTHOR]