It was found that an exogenous GSH supplementation eliminated excess intracellular ROS and improved the biooxidation activity of the MCAB.Multiple factors including natural and human-induced ones lead to land cover change in the landscape. Therefore, identifying the pattern of land cover change can help inform land-use management and prevent associated issues which can affect the natural resources of the landscape. The aim of this study is to assess land cover change in the Qeshm Island in southern Iran by combining the resulting outputs of multiple modeling methods, cellular automata (CA), Markov chains, and artificial neural networks (ANN) based on land cover maps for the years 1996, 2006, and 2016 that have been extracted from satellite imagery (Landsat 5, 7, and 8). In order to evaluate the accuracy of modeling, the Kappa coefficient was calculated to be 0.8. Then, land cover changes for 2025 were predicted by a hybrid model (CA-Markov-ANN). The results indicate that the classes of built-up areas, vegetation, and mangrove forests have changed more significantly from 1996 to 2016 compared with other classes. Land cover maps generated in this study showed that built-up areas have grown significantly in recent decades due to the region's growing population and development of ports, commercial, and industrial areas. Due to the climate change, the land area covering vegetation has decreased dramatically. The size of the mangrove forests has increased over the time period of the study (1996-2025). The findings of this study can inform land-use planning decisions by providing them with a comprehensive overview of land cover conditions in the future.Ponds, as landscape features, are known to regulate climate. Since ponds proliferate or recede due to natural or anthropogenic factors, a variation of pond numbers implies a variation of their climatic effect. Accordingly, this study investigates the impact of ponds on the local climate of the French Claise watershed. The latter was chosen because it contains a pond dense zone and a pondless zone. This repartition makes the Claise an adequate context to reveal the climatic impact of ponds even in the same landscape. To study the pond-climate effect, the parallel evolution of pond numbers variation and subsequent climatic impact must be tracked. Therefore, the remote sensing-derived Normalized Difference Water Index (NDWI) was extracted from LANDSAT images with different acquisition dates to track changes in pond numbers with time. When compared with a pond map established from aerial photography interpretation, the LANDSAT NDWI map revealed an accuracy of 85.74% for pond count and 75% for pond spatial allocation. This validation showed that NDWI is suitable for mapping the proliferation of ponds through time. In order to study the parallel evolution of the climatic effect, the land surface temperature (LST) index was extracted for each LANDSAT map. LST maps revealed that as a result of pond number variation, surface temperatures varied accordingly. A comparison of air temperatures between the ponded zone and pondless zones also revealed that pond zones had lower air temperatures than their direct surroundings. Accordingly, ponds were shown to buffer local microclimates even within the same landscape.Land use change simulation is an important issue for its role in predicting future trends and providing implications for sustainable land management. Hybrid models have become a recognized strategy to inform decision-makers, but further attempts are needed to warrant the reliability of their projected results. In view of this, three hybrid models, including the cellular automata-Markov chain-artificial neural network, cellular automata-Markov chain-logistic regression, and Markov chain-artificial neural network, were applied to simulate land use change on the largest island in Iran, Qeshm Island. https://www.selleckchem.com/products/Cisplatin.html The Figure of Merit (FOM) was used to measure the modeling accuracy of the simulations, with the FOMs for the three models 6.7, 5.1, and 4.5, respectively. Consequently, the cellular automata-Markov chain-artificial neural network most precisely simulates land use change on Qeshm Island and is, thus, used to simulate land use change until 2026. The simulation shows that the incremental trend of the built-up class will continue in the coming years. Meanwhile, the areas of valuable ecosystems, such as mangroves, tend to decrease. Despite the protection plans for mangroves, these areas require more attention and conservation planning. This study demonstrates a referential example to select the proper land use models for informing planning and management in similar coastal zones.With the COVID-19 pandemic, emergency rooms are faced with major challenges because they act as the interface between outpatient and inpatient care. The dynamics of the pandemic forced emergency care at the University Hospital Münster to extensively adjust their processes, which had to be carried out in the shortest time possible. This included the establishment of an outpatient coronavirus test center and a medical student-operated telephone hotline. Inside the hospital, new isolation capacities in the emergency room and a dedicated COVID-19 ward were set up. The patient flow was reorganized using flow diagrams for both the outpatient and inpatient areas. The general and special emergency management was optimized for the efficient treatment of COVID-19-positive patients and the staff were trained in the use of protective equipment. This report of our experience is intended to support other emergency departments in their preparation for the COVID-19 pandemic.This article examines the competencies required from intensive care nurses and physicians regarding complex patient care in the intensive care unit. Traditional training methods and structures in critical care are put into context with the contemporary educational requirements. The goals are promotion of the interprofessional cooperation between nurses and physicians as well as a comparison between previous educational methods and their implications on the resulting skills. Clinical competences are defined as the result of basic professional training as well as further education, which can improve the quality of patient care. Options for improving teaching are shown through the presentation of the various learning venues for theory and clinical practice. Contemporary skills labs and simulation trainings are discussed as a useful supplement to traditional approaches such as traditional nursing practice instruction. It will also be discussed how collaborative learning between nurses and physicians at all levels of training can lead to better patient care by increasing the individual and shared competences.

fujikuroi by inducing cellular oxidative stress in the pathogen.
Multiple sclerosis (MS) is a prevalent and debilitating neuroinflammatory disease associated with a significant economic burden. Direct healthcare costs, which can average $70,000 a year, have risen rapidly over the last decade and are driven by the escalating cost of disease-modifying therapies (DMTs). Despite a growing number of DMTs, annual increases in price for most DMTs have commonly exceeded 10% over the last 15 years. The high cost of MS DMTs has created economic hardships for patients in terms of high out-of-pocket costs and insurance company-induced barriers. Although generic versions of glatiramer acetate and dimethyl fumarate have provided some lower cost options, the median annual price for branded products currently exceeds $90,000. The goal of this paper is to examine the economic landscape of MS DMTs in the USA.

Recent economic analyses have provided new insights into the relative value of DMTs. Robust economic modeling studies suggest that costs per quality-adjusted life-year for most DMTate are also economically attractive. DMTs provide clinical benefit for patients with MS; however, their high cost can be a financial burden and impede access. High DMT prices are the principal reason why cost-effectiveness studies have indicated the economic value of most DMTs is questionable.The genus Mimosa Linnaeus (Leguminosae) comprises more than 530 species, being one of the most diversified genera in the family. A vast morphologic variability has been described at all infrageneric levels. Considering stomata description, a very low proportion of species have been studied in the genus, and the description was limited to stomata types, but not to variation in the disposition of subsidiary cells. Here we analyze type, length, and distribution of stomatic complexes in 19 taxa of Mimosa subseries Dolentes and subseries Brevipedes, a high variability taxonomic complex, as well as their density on both foliar faces and epidermic pavement cell morphology. We found four different stomatal types, 2 distribution types, and 3 epidermic pavement cell shapes. Some of these features are taxonomically relevant at infraspecific levels, since it adds important information for the separation of the taxa, but also questions supraspecific taxonomic groups of previous proposals of the genus. We also hypothesized about the origin of the variation of some stomata features in relation to ecological and ploidy-level variability in this complex.
Increasing attention has been paid in recent decades to social determinants of health as a risk factor for disease development and disease severity. While traditionally heart disease, family history, lipid profile, and tobacco use have all been associated with increased risk of neurological disease, numerous studies now show that the influence of poverty may be just as strong a risk factor. This study summarizes the recent literature on poverty as it contributes to neurological disease.

Children growing up in poverty have increased risk for cognitive deficits and behavioral disorders as reported by Noble et al. (Dev Sci. 9(6)642-54, 2006) and Farah et al. (Brain Res. 1110(1)166-74, 2006) as well as worse outcomes when it comes to epilepsy management and disease course as discussed by Camfield et al. (Epilepsia. 57(11)1826-33, 2016). In adulthood, as the number of social determinants of health increases, the incidence of stroke and severe stroke increases significantly as reported by Reshetnyak et al. (Strogically significant infectious diseases and incidence of dementia as reported by Sumilo et al. (Rev Med Virol. 18(2)81-95, 2008) and Zuelsdorff et al. (Alzheimer's Dement. https://www.selleckchem.com/products/eft-508.html 6(1)e12039, 2020). Social determinants of health including poverty should be considered a risk factor for disease. More attention is needed from clinicians as well as from a public health perspective to address this disparity.
We aim to summarize the sleep disorders reported in patients affected by primary mitochondrial dysfunctions and describe the association with their clinical and molecular characteristics.

Sleep complaints are prevalent in mitochondrial disorders. Sleep-disordered breathing is the main sleep disorder reported in mitochondrial diseases. OSA and CSA are, respectively, more frequently associated with patients characterized by the prevalent involvement of the skeletal muscle and the predominant involvement of the central nervous system. Other sleep disorders, such as restless legs syndrome, have been rarely described. Sleep disorders are frequently associated with primary mitochondrial disorders, and the clinical phenotypes affect the type of sleep disturbance associated with the mitochondrial dysfunction. A polysomnographic study should be performed in every subject with this neurogenetic disorder both at diagnosis and during follow-up for the numerous adverse clinical outcomes associated with sleep disorders and the frailty of mitochondrial patients.
Sleep complaints are prevalent in mitochondrial disorders. Sleep-disordered breathing is the main sleep disorder reported in mitochondrial diseases. OSA and CSA are, respectively, more frequently associated with patients characterized by the prevalent involvement of the skeletal muscle and the predominant involvement of the central nervous system. Other sleep disorders, such as restless legs syndrome, have been rarely described. Sleep disorders are frequently associated with primary mitochondrial disorders, and the clinical phenotypes affect the type of sleep disturbance associated with the mitochondrial dysfunction. A polysomnographic study should be performed in every subject with this neurogenetic disorder both at diagnosis and during follow-up for the numerous adverse clinical outcomes associated with sleep disorders and the frailty of mitochondrial patients.The current study implements a cellular automata-based model for the development of land use/land cover (LULC) future scenarios using a Remote Sensing (RS) Imagery series (1985 to 2018) as data input and focusing on human activities drivers in a 6700-km2 watershed vital for the water security of Paraiba state, Brazil. The methodology has three stages the first stage is the pre-processing of images and preparing them as data input for the cellular automata land use model built in the R software environment (SIMLANDER); the stage of calibration establishes the variables and verifies the influence of each one on the LULC of the region; the last step corresponds to the validation procedures. After model calibration, land use maps for future scenarios (2019 to 2045) were simulated. The results estimate a reduction of 737 km2 of natural land cover between the years 2019 and 2045. The spatial distribution of anthropogenic interference predicted a more significant degradation in the central region of the basin. This fact can be potentially attributed by the water availability increasing from the São Francisco River diversion.

Adult neurogenesis - the generation of neurons during adulthood - is intensively studied, yet little is known about its consequences at the tissue level. In the teleost fish Apteronotus leptorhynchus, morphometric analysis has revealed that the total number of cells in the spinal cord increases continuously throughout adulthood, driven by the activity of neurogenic stem/progenitor cells in both the ependymal layer at the central canal and in the radially located parenchyma. This net increase in cell numbers demonstrates cellular addition, as opposed to cellular turnover which appears to be the common outcome of adult neurogenesis in mammals. Grounded on https://www.selleckchem.com/products/mmri62.html of quantitative data generated through high-resolution mapping of stem cells and their progeny, we constructed a cellular automata model of the stem-cell-driven growth of the spinal cord. Simulations based on this model suggest that three cellular mechanisms play a critical role for promoting sustained tissue growth and acquisition of correct form of the spinal cord, including the development of the ependymal layer and the parenchyma the number of symmetric stem-cell divisions versus asymmetric divisions; the probability of the progeny of progenitor cells to undergo cell death; and the radial drifting of cells.Ticks are responsible for spreading harmful diseases including Lyme disease and tick-borne encephalitis. Understanding tick population dynamics and predicting risk of tick-borne disease insurgence helps to design preventive actions against the disease spread. Using a compartmental model describing the pathogen transmission among ticks and hosts, we study the influence of host-targeted tick control strategies with chemical insecticides on tick population and disease transmission dynamics. Our analysis shows that in areas with rapid-growing population of ticks, host-targeted controls using chemical insecticides may enhance disease persistence and even turn a disease-free area to a disease endemic area. Therefore, the complex dynamics of pathogen spread among ticks and hosts should be carefully examined when designing tick control strategies.
To analyze the findings of both multichannel intraluminal impedance with pH (MII-pH) and endoscopy/histopathology in children with esophageal atresia at age 1year, according to current recommendations for the evaluation of gastroesophageal reflux disease (GERD) in esophageal atresia.

We retrospectively reviewed both MII-pH and endoscopy/histopathology performed in 1-year-old children with esophageal atresia who were followed up in accordance with international recommendations. Demographic data and clinical characteristics were also reviewed to investigate factors associated with abnormal GERD investigations.

In our study cohort of 48 children with esophageal atresia, microscopic esophagitis was found in 33 (69%) and pathological esophageal acid exposure on MII-pH was detected in 12 (25%). Among baseline variables, only the presence of long-gap esophageal atresia was associated with abnormal MII-pH. Distal baseline impedance was significantly lower in patients with microscopic esophagitis, and it showed a very good diagnostic performance in predicting histological changes.

Histological esophagitis is highly prevalent at 1year after esophageal atresia repair, but our results do not support a definitive causative role of acid-induced GERD. Instead, they support the hypothesis that chronic stasis in the dysmotile esophagus might lead to histological changes. MII-pH may be a helpful tool in selecting patients who need closer endoscopic surveillance and/or benefit from acid suppression.
Histological esophagitis is highly prevalent at 1 year after esophageal atresia repair, but our results do not support a definitive causative role of acid-induced GERD. Instead, they support the hypothesis that chronic stasis in the dysmotile esophagus might lead to histological changes. MII-pH may be a helpful tool in selecting patients who need closer endoscopic surveillance and/or benefit from acid suppression.
To identify exposure pathways to fecal pathogens that are significant contributors to diarrheal diseases and impaired growth in young children, and to evaluate scalable interventions to reduce fecal contamination from these pathways.

Reducing Enteropathy, Undernutrition, and Contamination in the Environment (REDUCE) was a prospective cohort study of 370 children <5years of age was conducted in Walungu Territory, South Kivu, Democratic Republic of the Congo. Child mouthing behaviors were assessed through caregiver reports and 5-hour structured observations. Caregiver reports of child contact with animals and child diarrhea were also obtained. Anthropometric measurements were collected at baseline and at a 6-month follow-up.

Children observed putting soil in their mouth during structured observation at baseline had a significantly higher odds of diarrhea at the 6-month follow-up (OR, 1.79; 95% CI, 1.04 to 3.07). Children observed mouthing feces during structured observation had a significant reduction in height-for-age z-score (HAZ) from baseline to the 6-month follow-up (ΔHAZ, -0.69; 95% CI, -1.34 to -0.04). A significant reduction in HAZ was also observed for children with caregiver reports of touching guinea pigs (-0.33; 95% CI, -0.58 to -0.08) and rabbits (-0.34; 95% CI, -0.64 to -0.04) and children with feces in their sleeping space during unannounced spot checks (-0.41; 95% CI, -0.74 to -0.09).

These findings emphasize the urgent need for infant water, sanitation, and hygiene interventions targeting child mouthing behaviors, fecal contamination in child living spaces, and child contact with domestic animals to reduce exposure to fecal pathogens among susceptible populations.
These findings emphasize the urgent need for infant water, sanitation, and hygiene interventions targeting child mouthing behaviors, fecal contamination in child living spaces, and child contact with domestic animals to reduce exposure to fecal pathogens among susceptible populations.In this work, methods for predicting the distribution of compounds between blood and tissue were investigated using nonlinear regression analysis. For the tissue/blood partition coefficient, 282 compounds and 810 activity data for seven tissues were selected. Twenty-four parameters were studied for each state of the compound. A study set with the most compounds and activity data in similar studies was established, and a model with good prediction ability was obtained. #link# A total of 773 data points were randomly divided into two data sets the training set contained 623 data points (n = 623, r = 0.822, s = 0.438, F = 142.2, and Q = 0.814) and the test set contained 150 data points (n = 150, r = 0.814, and s = 0.334). Furthermore, individual tissue/blood distribution coefficients were also studied in depth to obtain separate models for predicting the distribution coefficient of a drug between blood and a tissue. By applying these models, not only can the tissue/blood distribution coefficient or single tissue/blood distribution coefficient of the seven tissues and organs of the human body be predicted, but the distribution of the drug molecules in different states (neutral, cation, and anion) in the three tissue components can also be predicted.

We extend the recently developed generalized Floquet theory [Phys. Rev. Lett. 110, 170602 (2013)] to systems with infinite memory, i.e., a dependence on the whole previous history. In particular, we show that a lower asymptotic bound exists for the Floquet exponents associated to such cases. As examples, we analyze the cases of an ideal 1D system, a Brownian particle, and a circuit resonator with an ideal transmission line. All these examples show the usefulness of this new approach to the study of dynamical systems with memory, which are ubiquitous in science and technology.In this paper, we present an explicit Darboux transformation of the generalized mixed nonlinear Schrödinger (GMNLS) equation. The compact determinant representation of the n-fold Darboux transformation of the GMNLS equation is constructed and the nth-order solution is built. We further prove that only the even-fold Darboux transformation and the even-order solution of the GMNLS equation can, respectively, be reduced to the Darboux transformation and solution of the Kundu-Eckhaus equation. https://www.selleckchem.com/products/napabucasin.html Furthermore, two different kinds of explicit one-soliton solutions of the GMNLS equation are constructed and discussed.It has been demonstrated that cellular automata had the highest computational capacity at the edge of chaos [N. H. Packard, in Dynamic Patterns in Complex Systems, edited by J. A. S. Kelso, A. J. Mandell, and M. F. Shlesinger (World Scientific, Singapore, 1988), pp. 293-301; C. G. Langton, Physica D 42(1), 12-37 (1990); J. P. Crutchfield and K. Young, in Complexity, Entropy, and the Physics of Information, edited by W. H. Zurek (Addison-Wesley, Redwood City, CA, 1990), pp. 223-269], the parameter at which their behavior transitioned from ordered to chaotic. This same concept has been applied to reservoir computers; a number of researchers have stated that the highest computational capacity for a reservoir computer is at the edge of chaos, although others have suggested that this rule is not universally true. Because many reservoir computers do not show chaotic behavior but merely become unstable, it is felt that a more accurate term for this instability transition is the "edge of stability." Here, I find two examples where the computational capacity of a reservoir computer decreases as the edge of stability is approached in one case because generalized synchronization breaks down and in the other case because the reservoir computer is a poor match to the problem being solved. The edge of stability as an optimal operating point for a reservoir computer is not in general true, although it may be true in some cases.The multiwavelet scale multidimensional recurrence quantification analysis (MWMRQA) method is proposed in this paper, which is a combination of multidimensional recurrence quantification analysis and wavelet packet decomposition. It allows us to quantify the recurrence properties of a single multidimensional time series under different wavelet scales. We apply the MWMRQA method to the Lorenz system and the Chinese stock market, respectively, and show the feasibility of this method as well as the dynamic variation of the Lorenz system and the Chinese stock market under different wavelet scales. This provides another perspective for other disciplines that need to study the recurrence properties of different scales in the future.By developing quasi-discrete multiple-scale method combined with tight-binding approximation, a novel quadratic Riccati differential equation is first derived for the soliton dynamics of the condensed bosons trapped in the optical lattices. For a lack of exact solutions, the trial solutions of the Riccati equation have been analytically explored for the condensed bosons with various scattering length as. When the lattice depth is rather shallow, the results of sub-fundamental gap solitons are in qualitative agreement with the experimental observation. For the deeper lattice potentials, we predict that in the case of as>0, some novel intrinsically localized modes of symmetrical envelope, topological (kink) envelope, and anti-kink envelope solitons can be observed within the bandgap in the system, of which the amplitude increases with the increasing lattice spacing and (or) depth. In the case of as less then 0, the bandgap brings out intrinsically localized gray or black soliton. This well provides experimental protocols to realize transformation between the gray and black solitons by reducing light intensity of the laser beams forming optical lattice.The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanical deformation that occurs in response to electrical excitation. Because heart muscle cells contract upon electrical excitation due to the excitation-contraction coupling mechanism, the resulting deformation of the heart should reflect macroscopic action potential wave phenomena. However, whether the relationship between macroscopic electrical and mechanical phenomena is well-defined and unique enough to be utilized for an inverse imaging technique in which mechanical activation mapping is used as a surrogate for electrical mapping has yet to be determined. Here, we provide a numerical proof-of-principle that deep learning can be used to solve the inverse mechano-electrical problem in phenomenological two- and three-dimensional computer simulations of the contracting heart wall, or in elastic excitable media, with muscle fiber anisotropy. We trained a convolutional autoencoder neural network to learn the complex relationship between electrical excitation, active stress, and tissue deformation during both focal or reentrant chaotic wave activity and, consequently, used the network to successfully estimate or reconstruct electrical excitation wave patterns from mechanical deformation in sheets and bulk-shaped tissues, even in the presence of noise and at low spatial resolutions. We demonstrate that even complicated three-dimensional electrical excitation wave phenomena, such as scroll waves and their vortex filaments, can be computed with very high reconstruction accuracies of about 95% from mechanical deformation using autoencoder neural networks, and we provide a comparison with results that were obtained previously with a physics- or knowledge-based approach.

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.We introduce a systematic method of approximating finite-time transition probabilities for continuous-time insertion-deletion models on sequences. The method uses automata theory to describe the action of an infinitesimal evolutionary generator on a probability distribution over alignments, where both the generator and the alignment distribution can be represented by pair hidden Markov models (HMMs). In general, combining HMMs in this way induces a multiplication of their state spaces; to control this, we introduce a coarse-graining operation to keep the state space at a constant size. This leads naturally to ordinary differential equations for the evolution of the transition probabilities of the approximating pair HMM. The TKF91 model emerges as an exact solution to these equations for the special case of single-residue indels. For the more general case of multiple-residue indels, the equations can be solved by numerical integration. Using simulated data, we show that the resulting distribution over alignments, when compared to previous approximations, is a better fit over a broader range of parameters. We also propose a related approach to develop differential equations for sufficient statistics to estimate the underlying instantaneous indel rates by expectation maximization. Our code and data are available at https//github.com/ihh/trajectory-likelihood.Immunity to viruses requires an array of critical cellular proteins that include IFN regulatory factor 3 (IRF3). Consequently, most viruses that infect vertebrates encode proteins that interfere with IRF3 activation. This review describes the cellular pathways linked to IRF3 activation and where those pathways are targeted by human viral pathogens. https://www.selleckchem.com/products/kn-62.html Moreover, key regulatory pathways that control IRF3 are discussed. Besides viral infections, IRF3 is also involved in resistance to some bacterial infections, in anticancer immunity, and in anticancer therapies involving DNA damage agents. A recent finding shows that IRF3 is needed for T cell effector functions that are involved in anticancer immunity and also in T cell autoimmune diseases. In contrast, unregulated IRF3 activity is clearly not beneficial, considering it is implicated in certain interferonopathies, in which heightened IRF3 activity leads to IFN-β-induced disease. Therefore, IRF3 is involved largely in maintaining health but sometimes contributing to disease.Sensitive and specific severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serologic assays are needed to inform diagnostic, therapeutic, and public health decision-making. We evaluated three commercial serologic assays as stand-alone tests and as components of two-test algorithms. Two nucleocapsid antibody tests (Abbott IgG and Roche total antibody) and one spike protein antibody test (DiaSorin IgG) were included. We assessed sensitivity using 128 serum samples from symptomatic PCR-confirmed coronavirus disease 2019 (COVID-19)-infected patients and specificity using 1,204 samples submitted for routine serology prior to COVID-19's emergence, plus 64 pandemic-era samples from SARS-CoV-2 PCR-negative patients with respiratory symptoms. Assays were evaluated as stand-alone tests and as components of a two-test algorithm in which positive results obtained using one assay were verified using a second assay. The two nucleocapsid antibody tests were more sensitive than the spike protein antibody test overall (70% and 70% versus 57%; P ≤ 0.003), with pronounced differences observed using samples collected 7 to 14 days after symptom onset. All three assays were comparably sensitive (≥89%; P ≥ 0.13) using samples collected >14 days after symptom onset. Specificity was higher using the nucleocapsid antibody tests (99.3% and 99.7%) than using the spike protein antibody test (97.8%; P ≤ 0.002). When any two assays were paired in a two-test algorithm, the specificity was 99.9% (P  less then  0.0001 to 0.25 compared with the individual assays), and the positive predictive value (PPV) improved substantially, with a minimal effect on the negative predictive value (NPV). In conclusion, two nucleocapsid antibody tests outperformed a spike protein antibody test. Pairing two different serologic tests in a two-test algorithm improves the PPV, compared with the individual assays alone, while maintaining the NPV.