Prenatal acetaminophen exposure and the developing ovary: Time, dose, and course consequences for fetal mice.

Acetaminophen is an emerging endocrine disrupting chemical and has been detected in various natural matrices. Numerous studies have documented developmental toxicity associated with prenatal acetaminophen exposure (PAcE). In this study, we established a PAcE Kunming mouse model at different time (middle pregnancy and third trimester), doses (low, middle, high) and courses (single or multi-) to systematically investigate their effects on fetal ovarian development. The findings indicated PAcE affected ovarian development, reduced fetal ovarian oocyte number and inhibited cell proliferation. A reduction in mRNA expression was observed for genes associated with oocyte markers (NOBOX and Figlα), follicular development markers (BMP15 and GDF9), and pre-granulosa cell steroid synthase (SF1 and StAR). Notably, exposure in middle pregnancy, high dose, multi-course resulted in the most pronounced inhibition of oocyte development; exposure in third trimester, high dose and multi-course led to the most pronounced inhibition of follicular development; and in third trimester, low dose and single course, the inhibition of pre-granulosa cell function was most pronounced. Mechanistic investigations revealed that PAcE had the most pronounced suppression of the ovarian Notch signaling pathway. Overall, PAcE caused fetal ovarian multicellular toxicity and inhibited follicular development with time, dose and course differences.

Single-test Ritchey-Common interferometry.

The Ritchey-Common test is widely adopted to measure large optical flats. The traditional Ritchey-Common test eliminates the defocus error with multiple tests by changing the position of the mirrors, which suffers from cumbersome steps, poor repeatability, coupled system error, extra mirror deformation, and potential overturning. The above problems increase the test time, decrease the reliability and accuracy, increase the test cost, and threaten manufacturing safety. We propose a single-test Ritchey-Common interferometry to avoid the obligatory position change in the traditional method. A sub-aperture of test flat is directly measured by a small-aperture interferometer before the test, which is easy to implement, to replace the extra system wavefront measurement in different positions. The defocus is calculated in sub-aperture at exactly the same position as the full-field measurement without the position change, then the surface form under test can be obtained with accurate optical path modeling. Measurement experiments for 100 mm and 2050 mm aperture flats were performed to demonstrate the feasibility of this method. Compared with a direct test in a standard Zygo interferometer, the peak to valley (PV) and root mean square (RMS) errors were 0.0889 λ and 0.0126 λ (λ=632.8 nm), respectively, which reaches the upper limit of accuracy of the interferometer. To the best of our knowledge, this is the first proposal of the Ritchey-Common test that can eliminate the defocus error and realize high accuracy measurement in a single test. Our work paves the way for reliable and practical optical metrology for large optical flats.

Highly Breathable, Stretchable, and Tailorable TPU Foam for Flexible Gas Sensors.

Continuous real-time monitoring of air quality is of great significance in the realms of environmental monitoring, personal safety, and healthcare. Recently, flexible gas sensors have gained great popularity for their potential to be integrated into various smart wearable electronics and display devices. However, the development of gas sensors with superior sensitivity, breathability, and stretchability remains a challenge. Here, a new high porosity thermoplastic polyurethane (HP-TPU) foam was reported for gas sensors, which exhibited large three-dimensional network structures and excellent mechanical properties. The HP-TPU foam was achieved by using a simple steam-induced method, which was suitable for mass production. The unique structure endowed this foam with 77.5% porosity, 260% strain ability, and 0.45 MPa Young's modulus, which improved 35, 31, and 80%, respectively, compared to previously reported traditional TPU foam (T-TPU) prepared by the drying method. In addition, the foam presented high gas permeability (312 g/m-2, 24 h) and excellent stability, and it remained undamaged even after 2000 cycles at 70% strain. The sensing material was coated on a PET flexible interdigital electrode and sandwiched between two HP-TPU foam layers for a gas sensitivity test. Due to the easy diffusion of gas between the pores and contact with the sensing materials, the HP-TPU foam exhibited a significant reduction of 85% in average response time and 46% in average recovery time, compared to the T-TPU foam. A wearable sensing device, comprising sensing, data processing, and wireless transmission modules, was successfully developed to enable outdoor testing and achieved a detection range at the ppb level. Finally, the cytotoxicity test results confirmed that this flexible gas sensor did not harm human health. These results proved that this HP-TPU foam was an ideal matrix for the flexible gas sensor, exhibiting great application potential in the fields of seamless human-machine integration.

Deep-Growing Neural Network With Manifold Constraints for Hyperspectral Image Classification.

In the absence of sufficient labels, deep neural networks (DNNs) are prone to overfitting, resulting in poor performance and difficulty in training. Thus, many semisupervised methods aim to use unlabeled sample information to compensate for the lack of label quantity. However, as the available pseudolabels increase, the fixed structure of traditional models has difficulty in matching them, limiting their effectiveness. Therefore, a deep-growing neural network with manifold constraints (DGNN-MC) is proposed. It can deepen the corresponding network structure with the expansion of a high-quality pseudolabel pool and preserve the local structure between the original and high-dimensional data in semisupervised learning. First, the framework filters the output of the shallow network to obtain pseudolabeled samples with high confidence and adds them to the original training set to form a new pseudolabeled training set. Second, according to the size of the new training set, it increases the depth of the layers to obtain a deeper network and conducts the training. Finally, it obtains new pseudolabeled samples and deepens the layers again until the network growth is completed. The growing model proposed in this article can be applied to other multilayer networks, as their depth can be transformed. Taking HSI classification as an example, a natural semisupervised problem, the experimental results demonstrate the superiority and effectiveness of our method, which can mine more reliable information for better utilization and fully balance the growing amount of labeled data and network learning ability.

Toxic effect window of ovarian development in female offspring mice induced by prenatal prednisone exposure with different doses and time.

BACKGROUND: Prednisone is one of the most used synthetic glucocorticoids during pregnancy. Epidemiological investigations suggested that prenatal prednisone therapy could affect fetal development, but systematic studies on its effects on ovarian development and the "toxic effect window" remained scarce. METHODS: In this study, by simulating clinical application characteristics, Kunming mice were given prednisone by oral gavage with different doses (0.25 or 1.0 mg/kg·d) or at different time gestational days (GD) (GD0-9, GD10-18, or GD0-18). Blood and ovaries of fetal mice were collected on GD18, and the serum estradiol level and the related function indexes of ovarian granulosa cells and oocytes were detected. RESULTS: Compared with the control group, prenatal prednisone exposure (PPE) induced pathological injury and enhanced cell proliferation in fetal mice ovary. Furthermore, the expression of steroid synthesis functional genes in pre-granulosa cells, the oocyte function markers, and developmentally related genes was enhanced with different doses or at different time of PPE. The Hippo signaling was activated in the fetal ovary of PPE groups. The above changes were most significant in the low or high-dose and full-term PPE groups. CONCLUSION: PPE caused various cell developmental toxicity in the fetal ovary, especially in the low or high-dose, full-term exposure groups. The potential mechanism might be related to the activation of the Hippo signaling pathway.

SIRT3 ameliorates polycystic ovary syndrome through FOXO1/PGC-1α signaling pathway.

BACKGROUND: Current studies have shown that Sirtuin3 (SIRT3) plays a key role in oocyte maturation. Polycystic ovary syndrome (PCOS) is a common disease caused by endocrine and metabolic abnormalities. The specific regulatory role and mechanism of SIRT3 in PCOS have not been reported. METHODS: SIRT3 was overexpressed in dihydrotestosterone (DHT)-induced PCOS model in mice. Ovary morphology, serum hormone level, and apoptosis of tissue cells were detected. The expression of SIRT3/Forkhead box protein O1 (FOXO1)/peroxlsome proliferator-activated receptor-γ coactlvat-1α (PGC-1α)-related proteins was detected. Then SIRT3 was overexpressed in DHT-induced human granulosa-like tumor cell line KGN. After the detection of the pathway-associated proteins, PGC-1α specific inhibitor SR-18292 was added to detect cell apoptosis, mitochondrial membrane potential, mitochondrial ROS (MitoROS) levels, and other mitochondrial-related indicators RESULTS: The expression of SIRT3 in PCOS model was significantly decreased. Overexpression of SIRT3 could significantly improve ovarian morphology and serum sex hormone levels in DHT-induced PCOS mice and inhibit apoptosis both in vitro and in vivo. Overexpression of SIRT3 also could improve mitochondrial dysfunction in DHT-induced KGN cells via FOXO1/PGC-1α signaling pathway. And PGC-1α inhibitor SR-18292 reversed the protective effect of SIRT3 overexpression on apoptosis and mitochondrial function damage of DHT-induced KGN cells. CONCLUSION: SIRT3 regulated FOXO1/PGC-1α signaling pathway to reduce mitochondrial dysfunction in PCOS, thereby improving PCOS.

A Semi-Analytical Method for Designing a Runner System of a Multi-Cavity Mold for Injection Molding.

Multi-cavity mold design is an efficient approach to achieving mass production and is frequently used in plastic injection applications. The runner system of a multi-cavity mold delivers molten plastic to each cavity evenly and makes the molded product from each individual cavity possess an equivalent quality. Not only the dimensions, but also the invisible quality, e.g., the internal stress of the product is of great concern in regard to molding quality. Using commercial software to find an optimal solution for the runner system may be time-consuming in respect to iterations if the engineers lack empirical rules. The H-type runner system is often used due to an inherently balanced filling in multi-cavities. However, the shear heat inducing an imbalanced flow behavior requires the H-type runner system to be improved as the number of the cavities is increased. This work develops a methodology based on the rheological concept to determine the runner system of a multi-cavity mold semi-analytically. As the relation of the viscosity with respect to shear rate is known, the runner system can be constructed step-by-step via this method. The use of the proposed method helps to focus attention on the connection between the physical situation and its related mathematical model. The influences of the melt temperature and resin type can be easily investigated. Three design examples, a 16-cavity mold with a fishbone runner system, an 8-cavity mold with an arbitrary runner layout, and the influences of melt temperature and resin type on the runner design are demonstrated and validated by the commercial software. The proposed method shows its great benefit when a new runner design project is launched in the initial design stage and then cooperates with the commercial software for further modifications.

A Dynamic Multiobjective Evolutionary Algorithm Based on Decision Variable Classification.

In recent years, dynamic multiobjective optimization problems (DMOPs) have drawn increasing interest. Many dynamic multiobjective evolutionary algorithms (DMOEAs) have been put forward to solve DMOPs mainly by incorporating diversity introduction or prediction approaches with conventional multiobjective evolutionary algorithms. Maintaining a good balance of population diversity and convergence is critical to the performance of DMOEAs. To address the above issue, a DMOEA based on decision variable classification (DMOEA-DVC) is proposed in this article. DMOEA-DVC divides the decision variables into two and three different groups in static optimization and changes response stages, respectively. In static optimization, two different crossover operators are used for the two decision variable groups to accelerate the convergence while maintaining good diversity. In change response, DMOEA-DVC reinitializes the three decision variable groups by maintenance, prediction, and diversity introduction strategies, respectively. DMOEA-DVC is compared with the other six state-of-the-art DMOEAs on 33 benchmark DMOPs. The experimental results demonstrate that the overall performance of the DMOEA-DVC is superior or comparable to that of the compared algorithms.

Transient Early Fine Motor Abnormalities in Infants Born to COVID-19 Mothers Are Associated With Placental Hypoxia and Ischemia.

Background: Long-term effects of Coronavirus Disease 2019 (COVID-19) on infants born to infected mothers are not clear. Fine motor skills are crucial for the development of infant emotional regulation, learning ability and social skills. Methods: Clinical information of 100 infants born to 98 mothers (COVID-19 n = 31, non-COVID-19 n = 67) were collected. Infants were follow-up up to 9 months post-partum. The placental tissues were examined for SARS-CoV-2 infection, pathological changes, cytokines, and mtDNA content. Results: Decreased placental oxygen and nutrient transport capacity were found in infected pregnant women. Increased IL-2, IL-6, TNF-α, and IFN-γ were detected in trophoblast cells and maternal blood of COVID-19 placentas. Elevated early fine motor abnormal-ities and increased serum TNI (troponin I) levels at delivery were observed in infants born to mothers with COVID-19. Increased abnormal mitochondria and elevated mtDNA content were found in the placentas from infected mothers. The placental mtDNA content of three infants with abnormal DDST were increased by 4, 7, and 10%, respectively, compared to the mean of the COVID-19 group. The Maternal Vascular Malperfusion (MVM), elevated cytokines and increased placental mtDNA content in mothers with COVID-19 might be associated with transient early fine motor abnormalities in infants. These abnormalities are only temporary, and they could be corrected by daily training. Conclusions: Babies born to COVID-19 mothers with mild symptoms appeared to have little or no excess long-term risks of abnormal physical and neurobehavioral development as compared with the infants delivered by non-COVID-19 mothers.

Bisphosphine-Stabilized Gold Nanoclusters with the Crown/Birdcage-Shaped Au11 Cores: Structures and Optical Properties.

To estimate the effect of bisphosphine ligands on the formation of the isomeric core structures of gold nanoclusters, the different ligation of bisphosphine ligands is usually used to participate in the construction of gold nanoclusters. Here, the selection of the different bisphosphine ligands, DPEphos and Xantphos, is performed to construct two novel gold nanoclusters, [Au11(DPEphos)4Cl2]Cl (1) and [Au11(Xantphos)4Cl2]Cl(2), which have been characterized by IR, 1H and 31P NMR, ESI-MS, XRD, SEM, XPS, TG, UV-vis, and X-ray crystal structure analysis. The structural analyses indicate that the ligation of bisphosphine ligands play a crucial role in the formation of the fascinating Au11 cores: gold nanocluster 1 includes a birdcage-shaped Au11 core with eight electrons, while gold nanocluster 2 contains a crown-shaped Au11 core with eight electrons. Meanwhile, DOS and PDOS studies indicate that the Au11 cores have a strong effect on the composition of HOMO and LUMO orbitals of gold nanoclusters. Furthermore, the different Au11 core structures lead to different optical absorption characteristics (1: 456 nm; 2: 427 nm). All these demonstrate that the ligation of bisphosphine ligands may have an important influence on constructing the stability of the isomeric core structures of gold nanoclusters.

Development and Characterization of a Novel Anti-idiotypic Monoclonal Antibody to Growth Hormone, Which Can Mimic Physiological Functions of Growth Hormone in Primary Porcine Hepatocytes.

B-32 is one of a panel of monoclonal anti-idiotypic antibodies to growth hormone (GH) that we developed. To characterize and identify its potential role as a novel growth hormone receptor (GHR) agonist, we determined that B-32 behaved as a typical Ab2ß based on a series of enzyme-linked immunosorbent assay assays. The results of fluorescence-activated cell sorting, indirect immunofluorescence and competitive receptor binding assays demonstrated that B-32 specifically binds to the GHR expressed on target cells. Next, we examined the resulting signal transduction pathways triggered by this antibody in primary porcine hepatocytes. We found that B-32 can activate the GHR and Janus kinase (2)/signal transducers and activators of transcription (JAK2/STAT5) signalling pathways. The phosphorylation kinetics of JAK2/STAT5 induced by either GH or B-32 were analysed in dose-response and time course experiments. In addition, B32 could also stimulate porcine hepatocytes to secrete insulin-like growth factors-1. Our work indicates that a monoclonal anti-idiotypic antibody to GH (B-32) can serve as a GHR agonist or GH mimic and has application potential in domestic animal (pig) production.

Differential intracellular signalling properties of the growth hormone receptor induced by the activation of an anti-GHR antibody.

A series of studies have reported that anti-GHR antibody can function as a GHR agonist and may serve as an attractive tool for studying the mechanisms of GHR activation. However, to date, there is relatively little information about intracellular signalling triggered by anti-GHR antibody. Therefore, in this work, we have developed a panel of monoclonal antibodies to GHBP, among which one Mab, termed CG-172, was selected for further characterisation because of its signalling properties. The results from FACS assays, receptor binding and immunoprecipitation assays and western blotting demonstrated that CG-172 specifically binds to GHR expressed on target cells. Subsequently, epitope mapping studies that used receptor binding analysis showed that CG-172 specifically binds subdomain 1 of GHR ECD. We next examined the resulting signal transduction pathways triggered by this antibody in CHO-GHR638 cells and rat hepatocytes. We found that CG-172 can activate JAK2, AKT, ERK1/2 and STAT1/3 but not STAT5. The phosphorylation kinetics of STAT1/3, AKT and ERK1/2 induced by either GH or CG-172 were analysed in dose-response and time course experiments. Our observations demonstrated that an anti-GHR monoclonal antibody (CG-172) can serve as an attractive tool to study the mechanism(s) of GHR-mediated intracellular signalling pathways and may lead to the production of signal-specific molecules that are capable of inducing different biochemical responses.