Human iN neuronal model of schizophrenia displays dysregulation of chromogranin B and related neuropeptide transmitter signatures.

Schizophrenia (SZ) is a serious mental illness and neuropsychiatric brain disorder with behavioral symptoms that include hallucinations, delusions, disorganized behavior, and cognitive impairment. Regulation of such behaviors requires utilization of neurotransmitters released to mediate cell-cell communication which are essential to brain functions in health and disease. We hypothesized that SZ may involve dysregulation of neurotransmitters secreted from neurons. To gain an understanding of human SZ, induced neurons (iNs) were derived from SZ patients and healthy control subjects to investigate peptide neurotransmitters, known as neuropeptides, which represent the major class of transmitters. The iNs were subjected to depolarization by high KCl in the culture medium and the secreted neuropeptides were identified and quantitated by nano-LC-MS/MS tandem mass spectrometry. Several neuropeptides were identified from schizophrenia patient-derived neurons, including chromogranin B (CHGB), neurotensin, and natriuretic peptide. Focusing on the main secreted CHGB neuropeptides, results revealed differences in SZ iNs compared to control iN neurons. Lower numbers of distinct CHGB peptides were found in the SZ secretion media compared to controls. Mapping of the peptides to the CHGB precursor revealed peptides unique to either SZ or control, and peptides common to both conditions. Also, the iNs secreted neuropeptides under both KCl and basal (no KCl) conditions. These findings are consistent with reports that chromogranin B levels are reduced in the cerebrospinal fluid and specific brain regions of SZ patients. These findings suggest that iNs derived from SZ patients can model the decreased CHGB neuropeptides observed in human SZ.

Identifying robust adaptive irrigation operating policies to balance deeply uncertain economic food production and groundwater sustainability trade-offs.

Increasing irrigation demand has heavily relied on groundwater use, especially in places with highly variable water supplies that are vulnerable to drought. Groundwater management in agriculture is becoming increasingly challenging given the growing effects from overdraft and groundwater depletion worldwide. However, multiple challenges emerge when seeking to develop sustainable groundwater management in irrigated systems, such as trade-offs between the economic revenues from food production and groundwater resources, as well as the broad array of uncertainties in food-water systems. In this study we explore the applicability of Evolutionary Multi-Objective Direct Policy Search (EMODPS) to identify adaptive irrigation policies that water agencies and farmers can implement including operational decisions related to land use and groundwater use controls as well as groundwater pumping fees. The EMODPS framework yields state-aware, adaptive policies that respond dynamically as system state conditions change, for example with variable surface water (e.g., shifting management strategies across wet versus dry years). For this study, we focus on the Semitropic Water Storage district located in the San Joaquin Valley, California to provide broader insights relevant to ongoing efforts to improve groundwater sustainability in the state. Our findings demonstrate that adaptive irrigation policies can achieve sufficiently flexible groundwater management to acceptably balance revenue and sustainability goals across a wide range of uncertain future scenarios. Among the evaluated policy decisions, pumping restrictions and reductions in inflexible irrigation demands from tree crops are actions that can support dry-year pumping while maximizing groundwater storage recovery during wet years. Policies suggest that an adaptive pumping fee is the most flexible decision to control groundwater pumping and land use.

Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States.

Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.

Genetic correlates of phenotypic heterogeneity in autism.

The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic individuals (nmax = 12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic individuals. Furthermore, in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic individuals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms.

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional-structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional-structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

µ-Crystallin in Mouse Skeletal Muscle Promotes a Shift from Glycolytic toward Oxidative Metabolism.

µ-Crystallin, encoded by the CRYM gene, binds the thyroid hormones, T3 and T4. Because T3 and T4 are potent regulators of metabolism and gene expression, and CRYM levels in human skeletal muscle can vary widely, we investigated the effects of overexpression of Crym. We generated transgenic mice, Crym tg, that expressed Crym protein specifically in skeletal muscle at levels 2.6-147.5 fold higher than in controls. Muscular functions, Ca2+ transients, contractile force, fatigue, running on treadmills or wheels, were not significantly altered, although T3 levels in tibialis anterior (TA) muscle were elevated ~190-fold and serum T4 was decreased 1.2-fold. Serum T3 and thyroid stimulating hormone (TSH) levels were unaffected. Crym transgenic mice studied in metabolic chambers showed a significant decrease in the respiratory exchange ratio (RER) corresponding to a 13.7% increase in fat utilization as an energy source compared to controls. Female but not male Crym tg mice gained weight more rapidly than controls when fed high fat or high simple carbohydrate diets. Although labeling for myosin heavy chains showed no fiber type differences in TA or soleus muscles, application of machine learning algorithms revealed small but significant morphological differences between Crym tg and control soleus fibers. RNA-seq and gene ontology enrichment analysis showed a significant shift towards genes associated with slower muscle function and its metabolic correlate, ß-oxidation. Protein expression showed a similar shift, though with little overlap. Our study shows that µ-crystallin plays an important role in determining substrate utilization in mammalian muscle and that high levels of µ-crystallin are associated with a shift toward greater fat metabolism.

Impacts of irrigation efficiency on water-dependent sectors are heavily controlled by region-specific institutions and infrastructures.

Farmers' investment in more efficient irrigation systems represents a primary adaptation strategy when confronting climate change. However, the regional benefits of these investments and their influence on the conflicting demands among different water dependent stakeholders for intensely irrigated regions remains an open question. Using the Pacific Northwest of the United States as an illustrative region of focus, we show that higher irrigation efficiency has diverse effects across stakeholders that are contingent on many local climatic, institutional and infrastructural factors such as the availability of water storage, the location of hydropower generators, and water rights. These complexities limit simple abstractions of irrigation efficiency as broader policy challenge and are central to its inclusion within the class of "wicked problems". Additionally, we argue that the widely used rebound effect concept, which implicitly discourages irrigation efficiency supporting policies, should not be assumed to fully capture the nuances of the complex suite of regional impacts that emerge from irrigation efficiency investments. Consequently, the evaluation of irrigation efficiency investments requires a broader framing across a diversity of perspectives. policies and actions that are pluralistic, context-specific, and closely engage various groups of stakeholders in the policymaking process.

Incorporation of a nucleoside analog maps genome repair sites in postmitotic human neurons.

Neurons are the longest-lived cells in our bodies and lack DNA replication, which makes them reliant on a limited repertoire of DNA repair mechanisms to maintain genome fidelity. These repair mechanisms decline with age, but we have limited knowledge of how genome instability emerges and what strategies neurons and other long-lived cells may have evolved to protect their genomes over the human life span. A targeted sequencing approach in human embryonic stem cell-induced neurons shows that, in neurons, DNA repair is enriched at well-defined hotspots that protect essential genes. These hotspots are enriched with histone H2A isoforms and RNA binding proteins and are associated with evolutionarily conserved elements of the human genome. These findings provide a basis for understanding genome integrity as it relates to aging and disease in the nervous system.

Evaluating the economic impact of water scarcity in a changing world.

Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems' adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems.

Water rights shape crop yield and revenue volatility tradeoffs for adaptation in snow dependent systems.

Irrigated agriculture in snow-dependent regions contributes significantly to global food production. This study quantifies the impacts of climate change on irrigated agriculture in the snow-dependent Yakima River Basin (YRB) in the Pacific Northwest United States. Here we show that increasingly severe droughts and temperature driven reductions in growing season significantly reduces expected annual agricultural productivity. The overall reduction in mean annual productivity also dampens interannual yield variability, limiting yield-driven revenue fluctuations. Our findings show that farmers who adapt to climate change by planting improved crop varieties may potentially increase their expected mean annaul productivity in an altered climate, but remain strongly vulnerable to irrigation water shortages that substantially increase interannual yield variability (i.e., increasing revenue volatility). Our results underscore the importance for crop adaptation strategies to simultaneously capture the biophysical effects of warming as well as the institutional controls on water availability.

De Novo SOX6 Variants Cause a Neurodevelopmental Syndrome Associated with ADHD, Craniosynostosis, and Osteochondromas.

SOX6 belongs to a family of 20 SRY-related HMG-box-containing (SOX) genes that encode transcription factors controlling cell fate and differentiation in many developmental and adult processes. For SOX6, these processes include, but are not limited to, neurogenesis and skeletogenesis. Variants in half of the SOX genes have been shown to cause severe developmental and adult syndromes, referred to as SOXopathies. We here provide evidence that SOX6 variants also cause a SOXopathy. Using clinical and genetic data, we identify 19 individuals harboring various types of SOX6 alterations and exhibiting developmental delay and/or intellectual disability; the individuals are from 17 unrelated families. Additional, inconstant features include attention-deficit/hyperactivity disorder (ADHD), autism, mild facial dysmorphism, craniosynostosis, and multiple osteochondromas. All variants are heterozygous. Fourteen are de novo, one is inherited from a mosaic father, and four offspring from two families have a paternally inherited variant. Intragenic microdeletions, balanced structural rearrangements, frameshifts, and nonsense variants are predicted to inactivate the SOX6 variant allele. Four missense variants occur in residues and protein regions highly conserved evolutionarily. These variants are not detected in the gnomAD control cohort, and the amino acid substitutions are predicted to be damaging. Two of these variants are located in the HMG domain and abolish SOX6 transcriptional activity in vitro. No clear genotype-phenotype correlations are found. Taken together, these findings concur that SOX6 haploinsufficiency leads to a neurodevelopmental SOXopathy that often includes ADHD and abnormal skeletal and other features.

Low cost satellite constellations for nearly continuous global coverage.

Satellite services are fundamental to the global economy, and their design reflects a tradeoff between coverage and cost. Here, we report the discovery of two alternative 4-satellite constellations with 24- and 48-hour periods, both of which attain nearly continuous global coverage. The 4-satellite constellations harness energy from nonlinear orbital perturbation forces (e.g., Earth's geopotential, gravitational effects of the sun and moon, and solar radiation pressure) to reduce their propellant and maintenance costs. Our findings demonstrate that small sacrifices in global coverage at user-specified longitudes allow operationally viable constellations with significantly reduced mass-to-orbit costs and increased design life. The 24-hour period constellation reduces the overall required vehicle mass budget for propellant by approximately 60% compared to a geostationary Earth orbit constellation with similar coverage over typical satellite lifetimes. Mass savings of this magnitude permit the use of less expensive launch vehicles, installation of additional instruments, and substantially improved mission life.

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management.

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.

Skill (or lack thereof) of data-model fusion techniques to provide an early warning signal for an approaching tipping point.

Many coupled human-natural systems have the potential to exhibit a highly nonlinear threshold response to external forcings resulting in fast transitions to undesirable states (such as eutrophication in a lake). Often, there are considerable uncertainties that make identifying the threshold challenging. Thus, rapid learning is critical for guiding management actions to avoid abrupt transitions. Here, we adopt the shallow lake problem as a test case to compare the performance of four common data assimilation schemes to predict an approaching transition. In order to demonstrate the complex interactions between management strategies and the ability of the data assimilation schemes to predict eutrophication, we also analyze our results across two different management strategies governing phosphorus emissions into the shallow lake. The compared data assimilation schemes are: ensemble Kalman filtering (EnKF), particle filtering (PF), pre-calibration (PC), and Markov Chain Monte Carlo (MCMC) estimation. While differing in their core assumptions, each data assimilation scheme is based on Bayes' theorem and updates prior beliefs about a system based on new information. For large computational investments, EnKF, PF and MCMC show similar skill in capturing the observed phosphorus in the lake (measured as expected root mean squared prediction error). EnKF, followed by PF, displays the highest learning rates at low computational cost, thus providing a more reliable signal of an impending transition. MCMC approaches the true probability of eutrophication only after a strong signal of an impending transition emerges from the observations. Overall, we find that learning rates are greatest near regions of abrupt transitions, posing a challenge to early learning and preemptive management of systems with such abrupt transitions.

Borg: an auto-adaptive many-objective evolutionary computing framework.

This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-objective, multimodal optimization. The Borg MOEA combines ε-dominance, a measure of convergence speed named ε-progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization framework. A comparative study on 33 instances of 18 test problems from the DTLZ, WFG, and CEC 2009 test suites demonstrates Borg meets or exceeds six state of the art MOEAs on the majority of the tested problems. The performance for each test problem is evaluated using a 1,000 point Latin hypercube sampling of each algorithm's feasible parameterization space. The statistical performance of every sampled MOEA parameterization is evaluated using 50 replicate random seed trials. The Borg MOEA is not a single algorithm; instead it represents a class of algorithms whose operators are adaptively selected based on the problem. The adaptive discovery of key operators is of particular importance for benchmarking how variation operators enhance search for complex many-objective problems.

Optimization of large gel 2D electrophoresis for proteomic studies of skeletal muscle.

We describe improved methods for large format, two-dimensional gel electrophoresis (2DE) that improve protein solubility and recovery, minimize proteolysis, and reduce the loss of resolution due to contaminants and manipulations of the gels, and thus enhance quantitative analysis of protein spots. Key modifications are: (i) the use of 7 M urea and 2 M thiourea, instead of 9 M urea, in sample preparation and in the tops of the gel tubes; (ii) standardized deionization of all solutions containing urea with a mixed bed ion exchange resin and removal of urea from the electrode solutions; and (iii) use of a new gel tank and cooling device that eliminate the need to run two separating gels in the SDS dimension. These changes make 2DE analysis more reproducible and sensitive, with minimal artifacts. Application of this method to the soluble fraction of muscle tissues reliably resolves ~1800 protein spots in adult human skeletal muscle and over 2800 spots in myotubes.

Diagnostic assessment of search controls and failure modes in many-objective evolutionary optimization.

The growing popularity of multiobjective evolutionary algorithms (MOEAs) for solving many-objective problems warrants the careful investigation of their search controls and failure modes. This study contributes a new diagnostic assessment framework for rigorously evaluating the effectiveness, reliability, efficiency, and controllability of MOEAs as well as identifying their search controls and failure modes. The framework is demonstrated using the recently introduced Borg MOEA, [Formula: see text]-NSGA-II, [Formula: see text]-MOEA, IBEA, OMOPSO, GDE3, MOEA/D, SPEA2, and NSGA-II on 33 instances of 18 test problems from the DTLZ, WFG, and CEC 2009 test suites. The diagnostic framework exploits Sobol's variance decomposition to provide guidance on the algorithms' non-separable, multi-parameter controls when performing a many-objective search. This study represents one of the most comprehensive empirical assessments of MOEAs ever completed.

Physiological and histological changes in skeletal muscle following in vivo gene transfer by electroporation.

Electroporation (EP) is used to transfect skeletal muscle fibers in vivo, but its effects on the structure and function of skeletal muscle tissue have not yet been documented in detail. We studied the changes in contractile function and histology after EP and the influence of the individual steps involved to determine the mechanism of recovery, the extent of myofiber damage, and the efficiency of expression of a green fluorescent protein (GFP) transgene in the tibialis anterior (TA) muscle of adult male C57Bl/6J mice. Immediately after EP, contractile torque decreased by ∼80% from pre-EP levels. Within 3 h, torque recovered to ∼50% but stayed low until day 3. Functional recovery progressed slowly and was complete at day 28. In muscles that were depleted of satellite cells by X-irradiation, torque remained low after day 3, suggesting that myogenesis is necessary for complete recovery. In unirradiated muscle, myogenic activity after EP was confirmed by an increase in fibers with central nuclei or developmental myosin. Damage after EP was confirmed by the presence of necrotic myofibers infiltrated by CD68+ macrophages, which persisted in electroporated muscle for 42 days. Expression of GFP was detected at day 3 after EP and peaked on day 7, with ∼25% of fibers transfected. The number of fibers expressing green fluorescent protein (GFP), the distribution of GFP+ fibers, and the intensity of fluorescence in GFP+ fibers were highly variable. After intramuscular injection alone, or application of the electroporating current without injection, torque decreased by ∼20% and ∼70%, respectively, but secondary damage at D3 and later was minimal. We conclude that EP of murine TA muscles produces variable and modest levels of transgene expression, causes myofiber damage due to the interaction of intramuscular injection with the permeabilizing current, and that full recovery requires myogenesis.

Suppressed accumulation of cerebral amyloid {beta} peptides in aged transgenic Alzheimer's disease mice by transplantation with wild-type or prostaglandin E2 receptor subtype 2-null bone marrow.

A complex therapeutic challenge for Alzheimer's disease (AD) is minimizing deleterious aspects of microglial activation while maximizing beneficial actions, including phagocytosis/clearance of amyloid beta (Abeta) peptides. One potential target is selective suppression of microglial prostaglandin E(2) receptor subtype 2 (EP2) function, which influences microglial phagocytosis and elaboration of neurotoxic cytokines. To test this hypothesis, we transplanted bone marrow cells derived from wild-type mice or mice homozygous deficient for EP2 (EP2(-/-)) into lethally irradiated 5-month-old wild-type or APPswe-PS1DeltaE9 double transgenic AD mouse model recipients. We found that cerebral engraftment by bone marrow transplant (BMT)-derived wild-type or EP2(-/-) microglia was more efficient in APPswe-PS1DeltaE9 than in wild-type mice, and APPswe-PS1DeltaE9 mice that received EP2(-/-) BMT had increased cortical microglia compared with APPswe-PS1DeltaE9 mice that received wild-type BMT. We found that myeloablative irradiation followed by bone marrow transplant-derived microglia engraftment, rather than cranial irradiation or BMT alone, was responsible for the approximate one-third reduction in both Abeta plaques and potentially more neurotoxic soluble Abeta species. An additional 25% reduction in cerebral cortical Abeta burden was achieved in mice that received EP2(-/-) BMT compared with mice that received wild-type BMT. Our results provide a foundation for an adult stem cell-based therapy to suppress soluble Abeta peptide and plaque accumulation in the cerebrum of patients with AD.