Immunofunctional assay of human growth hormone (hGH) in serum: A possible consensus for quantitative hGH measurement

Confirmation of the diagnosis of GH deficiency in adults and children involves provocative testing for human (h) GH. Different commercially available immunoassays yield largely discrepant results in the measurement of GH levels in human serum. These discrepancies result in doubtful relevance of cut-off levels proposed for GH provocative testing. We have developed an immunofunctional assay method that allows quantitation of only those GH forms in circulation that possess both binding sites of the hormone for its receptor and thus can initiate a biological signal in target cells. An anti-hGH monoclonal antibody recognizing binding site 2 of hGH is immobilized and used to capture hGH from the serum sample. Biotin-labeled recombinant GH-binding protein in a second incubation step forms a complex with those hGH molecular isoforms that have both binding sites for the receptor. The signal is detected after a short third incubation step with labeled streptavidin. The assay is sensitive (detection range, 0.1-100 micrograms/L) and has average inter- and intraassay precisions of 10.3% and 7.3% respectively. Endogenous GH-binding protein does not interfere with the hGH result; placental lactogen slows no detectable cross-reaction in this immunofunctional assay. The degree of immunofunctionally active hGH forms in serum samples, calculated by comparison of immunofunctional assay and RIA results, varied between 52-93%. We propose this immunofunctional assay for GH measurement as a new reference method for hGH quantitation in serum. The immunofunction assay translates only hGH forms into an assay signal that are capable of dimerizing GH receptors and, thus, of initiating a biological effect in target cells

Joint State and Input Estimation of Agent Based on Recursive Kalman Filter Given Prior Knowledge

Modern autonomous systems are purposed for many challenging scenarios, where agents will face unexpected events and complicated tasks. The presence of disturbance noise with control command and unknown inputs can negatively impact robot performance. Previous research of joint input and state estimation separately studied the continuous and discrete cases without any prior information. This paper combines the continuous and discrete input cases into a unified theory based on the Expectation-Maximum (EM) algorithm. By introducing prior knowledge of events as the constraint, inequality optimization problems are formulated to determine a gain matrix or dynamic weights to realize an optimal input estimation with lower variance and more accurate decision-making. Finally, statistical results from experiments show that our algorithm owns 81\% improvement of the variance than KF and 47\% improvement than RKF in continuous space; a remarkable improvement of right decision-making probability of our input estimator in discrete space, identification ability is also analyzed by experiments

Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies

The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for doctors' annotations in AI development. However, collecting high-quality annotations from doctors is costly and time-consuming, creating a bottleneck in AI progress. This study investigates eye-tracking as a cost-effective technology to collect doctors' behavioral data for AI training with a focus on the pathology task of mitosis detection. One major challenge in using eye-gaze data is the low signal-to-noise ratio, which hinders the extraction of meaningful information. We tackled this by levering the properties of inter-observer eye-gaze consistencies and creating eye-gaze labels from consistent eye-fixations shared by a group of observers. Our study involved 14 non-medical participants, from whom we collected eye-gaze data and generated eye-gaze labels based on varying group sizes. We assessed the efficacy of such eye-gaze labels by training Convolutional Neural Networks (CNNs) and comparing their performance to those trained with ground truth annotations and a heuristic-based baseline. Results indicated that CNNs trained with our eye-gaze labels closely followed the performance of ground-truth-based CNNs, and significantly outperformed the baseline. Although primarily focused on mitosis, we envision that insights from this study can be generalized to other medical imaging tasks.Comment: Accepted by IEEE International Conference on Healthcare Informatics 202

T cell immunity rather than antibody mediates cross-protection against Zika virus infection conferred by a live attenuated Japanese encephalitis SA14-14-2 vaccine.

Zika virus (ZIKV) and Japanese encephalitis virus (JEV) are closely related to mosquito-borne flaviviruses. Japanese encephalitis (JE) vaccine SA14-14-2 has been in the Chinese national Expanded Program on Immunization since 2007. The recent recognition of severe disease syndromes associated with ZIKV, and the identification of ZIKV from mosquitoes in China, prompts an urgent need to investigate the potential interaction between the two. In this study, we showed that SA14-14-2 is protective against ZIKV infection in mice. JE vaccine SA14-14-2 triggered both Th1 and Th2 cross-reactive immune responses to ZIKV; however, it was cellular immunity that predominantly mediated cross-protection against ZIKV infection. Passive transfer of immune sera did not result in significant cross-protection but did mediate antibody-dependent enhancement in vitro, though this did not have an adverse impact on survival. This study suggests that the SA14-14-2 vaccine can protect against ZIKV through a cross-reactive T cell response. This is vital information in terms of ZIKV prevention or precaution in those ZIKV-affected regions where JEV circulates or SA14-14-2 is in widespread use, and opens a promising avenue to develop a novel bivalent vaccine against both ZIKV and JEV. KEY POINTS: • JEV SA14-14-2 vaccine conferred cross-protection against ZIKV challenge in mice. • T cell immunity rather than antibody mediated the cross-protection. • It provides important information in terms of ZIKV prevention or precaution

Sex-specific and inter-individual differences in biomarkers of selenium status identified by a calibrated ELISA for selenoprotein P

Selenoprotein P (SELENOP) is a liver-derived transporter of selenium (Se) in blood, and a meaningful biomarker of Se status. Se is an essential trace element for the biosynthesis of enzymatically-active selenoproteins, protecting the organism from oxidative damage. The usage of uncalibrated assays hinders the comparability of SELENOP concentrations and their pathophysiological interpretation across different clinical studies. On this account, we established a new sandwich SELENOP-ELISA and calibrated against a standard reference material (SRM1950). The ELISA displays a wide working range (11.6–538.4 µg/L), high accuracy (2.9%) and good precision (9.3%). To verify whether SELENOP correlates to total Se and to SELENOP-bound Se, serum samples from healthy subjects and age-selected participants from the Berlin Aging Study II were analyzed by SELENOP-ELISA and Se quantification. SELENOP was affinity-purified and its Se content was determined from a subset of samples. There was a high correlation of total Se and SELENOP concentrations in young and elderly men, and in elderly women, but not in young women, indicating a specific sexual dimorphism in these biomarkers of Se status in young subjects. The Se content of isolated SELENOP was independent of sex and age (mean±SD: 5.4±0.5). By using this calibrated SELENOP-ELISA, prior reports on pathological SELENOP concentrations in diabetes and obesity are challenged as the reported values are outside reasonable limits. Biomarkers of Se status in clinical research need to be measured by validated assays in order to avoid erroneous data and incorrect interpretations, especially when analyzing young women. The Se content of circulating SELENOP differs between individuals and may provide some important diagnostic information on Se metabolism and status

Sex-specific and inter-individual differences in biomarkers of selenium status identified by a calibrated ELISA for selenoprotein P

Selenoprotein P (SELENOP) is a liver-derived transporter of selenium (Se) in blood, and a meaningful biomarker of Se status. Se is an essential trace element for the biosynthesis of enzymatically-active selenoproteins, protecting the organism from oxidative damage. The usage of uncalibrated assays hinders the comparability of SELENOP concentrations and their pathophysiological interpretation across different clinical studies. On this account, we established a new sandwich SELENOP-ELISA and calibrated against a standard reference material (SRM1950). The ELISA displays a wide working range (11.6–538.4 µg/L), high accuracy (2.9%) and good precision (9.3%). To verify whether SELENOP correlates to total Se and to SELENOP-bound Se, serum samples from healthy subjects and age-selected participants from the Berlin Aging Study II were analyzed by SELENOP-ELISA and Se quantification. SELENOP was affinity-purified and its Se content was determined from a subset of samples. There was a high correlation of total Se and SELENOP concentrations in young and elderly men, and in elderly women, but not in young women, indicating a specific sexual dimorphism in these biomarkers of Se status in young subjects. The Se content of isolated SELENOP was independent of sex and age (mean±SD: 5.4±0.5). By using this calibrated SELENOP-ELISA, prior reports on pathological SELENOP concentrations in diabetes and obesity are challenged as the reported values are outside reasonable limits. Biomarkers of Se status in clinical research need to be measured by validated assays in order to avoid erroneous data and incorrect interpretations, especially when analyzing young women. The Se content of circulating SELENOP differs between individuals and may provide some important diagnostic information on Se metabolism and status

Immunogenicity, toxicology, pharmacokinetics and pharmacodynamics of growth hormone ligand-receptor fusions A B S T R A C T

A fundamental concern for all new biological therapeutics is the possibility of inducing an immune response. We have recently demonstrated that an LR-fusion (ligand-receptor fusion) of growth hormone generates a potent long-acting agonist; however, the immunogenicity and toxicity of these molecules have not been tested. To address these issues, we have designed molecules with low potential as immunogens and undertaken immunogenicity and toxicology studies in Macaca fascicularis and pharmacokinetic and pharmacodynamic studies in rats. Two variants of the LR-fusion, one with a flexible linker (GH-LRv2) and the other without (GH-LRv3), were tested. Comparison was made with native human GH (growth hormone). GH-LRv2 and GHLRv3 demonstrated similar pharmacokinetics in rats, showing reduced clearance compared with native GH and potent agonist activity with respect to body weight gain in a hypophysectomized rat model. In M. fascicularis, a low level of antibodies to GH-LRv2 was found in one sample, but there was no other evidence of any immunogenic response to the other fusion protein. There were no toxic effects and specifically no changes in histology at injection sites after two repeated administrations. The pharmacokinetic profiles in monkeys confirmed long half-lives for both GHLRv2 and GH-LRv3 representing exceptionally delayed clearance over rhGH (recombinant human GH). The results suggest that repeated administration of a GH LR-fusion is safe, non-toxic, and the pharmacokinetic profile suggests that two to three weekly administrations is a potential therapeutic regimen for humans

RELIABILITY ANALYSIS ON HYBRID SURROGATE MODEL OF RADIAL BASIS FUNCTION AND SPARSE POLYNOMIAL CHAOS EXPANSION (MT)

To resolve the poor universality and low accuracy of the existing surrogate models for reliability analysis, a hybrid surrogate model based on radial basis function（RBF） and sparse polynomial chaotic expansion（SPCE） was proposed. It realized rapid and accurate prediction of performance functions to improve the engineering applicability and the accuracy of structural reliability analysis. Importantly, the orthogonal matching pursuit technology was applied to obtain the important terms in PCE, and an SPCE model could be established directly to form the RBF-SPCE model for improving the prediction accuracy of surrogate model. Subsequently, the reliability analysis of complex structures is carried out based on Monte Carlo simulation（MCS）. In this work, three simulation cases were implemented to compare the performance of the proposed method with the traditional RBF model and augmented RBF model. The results illustrated that the proposed method has higher accuracy and efficiency for structural reliability analysis. Finally, a vehicle side impact engineering example illustrated that the proposed method has good engineering applicability for complex problems

Downscaling estimation of NEP in the ecologically-oriented county based on multi-source remote sensing data

Net ecosystem productivity (NEP) serves as a pivotal metric for quantitatively elucidating the carbon sink function of terrestrial ecosystems. As a prototype county for the development of an ecological civilization in China, the quantitative estimation of the ecotypic county’s ecosystem carbon sink capacity holds immense significance in comprehending the carbon cycle and facilitating the sustainable advancement of regional ecosystems. This study undertook the estimation of NEP in Wuning County from 2000 to 2020, employing a fusion of multi-source remote sensing data, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), the improved Carnegie-Ames-Stanford Approach model, and the soil respiration model. Furthermore, we delved into the differences in NEP across various types of land cover. In addition, we employed the Theil-Sen Median trend analysis and Mann-Kendall test to discern the spatio-temporal trends of NEP. The findings indicated the following: (1) The downscaled NDVI generated by STARFM exhibited a remarkable consistency with Landsat NDVI overall (R2 > 0.95, P  grassland > cropland. The application of STARFM has provided valuable insights into the methodology for precise delineation of spatio-temporal dynamics of NEP at the county scale. The outcomes of this study have furnished support for implementing climate change mitigation strategies in ecologically-oriented counties and the bottom-up promotion of China's carbon peaking and carbon neutrality goals

Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning

Mean Field Games (MFGs) have the ability to handle large-scale multi-agent systems, but learning Nash equilibria in MFGs remains a challenging task. In this paper, we propose a deep reinforcement learning (DRL) algorithm that achieves population-dependent Nash equilibrium without the need for averaging or sampling from history, inspired by Munchausen RL and Online Mirror Descent. Through the design of an additional inner-loop replay buffer, the agents can effectively learn to achieve Nash equilibrium from any distribution, mitigating catastrophic forgetting. The resulting policy can be applied to various initial distributions. Numerical experiments on four canonical examples demonstrate our algorithm has better convergence properties than SOTA algorithms, in particular a DRL version of Fictitious Play for population-dependent policies