Effects of exogenous steroid hormones on growth, body color, and gonadal development in the Opsariichthys bidens.

To investigate the effects of exogenous steroid hormones on growth, body color, and gonadal development in the Opsariichthys bidens (O. bidens), synthetic methyltestosterone (MT) and 17ß-estradiol (E2) were used for 28 days' treatment of 4-month-old O. bidens before the breeding season. Our results suggested that MT had a significant growth-promoting effect (P < 0.05), whereas E2 played an inhibitory role. On the body surface, the females in the MT group showed gray stripes, and the fish in other groups showed no obvious stripes. The males with MT treatment displayed brighter blue-green stripes compared to the CK and E2 groups. The histological analysis showed that the MT significantly promoted testes development in males, blocked oocyte development, and caused massive apoptosis in females, whereas the E2 group promoted ovarian development and inhibited testes development. Based on qRT-PCR analysis, in females, the expression of igf-1, dmrt1, and cyp19a1a genes revealed that E2 treatment resulted in down-regulation of igf-1 expression and up-regulation of cyp19a1a expression. In males, igf-1 and dmrt1 were significantly up-regulated after MT treatment, and E2 treatment led to down-regulation of igf-1. Therefore, this study demonstrates that MT and E2 play an important role in reversing the morphological sex characteristics of females and males.

The Treatment of Aquaculture Wastewater with Biological Aerated Filters: From the Treatment Process to the Microbial Mechanism.

Algal cell proliferation has posed significant problems for traditional water treatment facilities; these problems are attributed to surface hydrophilicity and electrostatic repulsion. Biological aerated filters (BAFs) have been extensively used in wastewater treatment to remove pollutants such as algal cells by utilizing the adsorption and separation capabilities of the filter media. In this study, a BAF was supplemented with biological filter medium (Marchantia polymorpha) to assess its effectiveness of pretreating aquaculture wastewater. In terms of process performance, steady and consistent treatment was achieved by the BAF with M. polymorpha (BAF2) under an algal cell density as high as 1.65 × 108 cell/L, with average removal rates for NH4+-N and algae cells of 74.4% and 81.9%, respectively. The photosynthetic activity parameters (rETRmax, α, Fv/Fm, and Ik) of the influent and effluent were quantitatively assessed, and M. polymorpha was found to remove algae by disrupting the photosynthetic system of the algal cells. Furthermore, the addition of the M. polymorpha filter medium enhanced the community structure of the functional microbes in the BAF system. The highest microbial community richness and diversity were observed in the BAF2. Meanwhile, M. polymorpha promoted an increase in the abundance of denitrifying bacteria, including Bdellovibrio and Pseudomonas. Overall, this work offers a unique perspective on the aquaculture wastewater pretreatment process and BAF design.

Grating Interferometer with Redundant Design for Performing Wide-Range Displacement Measurements.

Grating interferometers that use large two-dimensional grating splice modules for performing wide-range measurements have significant advantages for identifying the position of the wafer stage. However, the manufacturing process of large two-dimensional grating splice modules is very difficult. In contrast to existing redundant designs in the grating line dimension, we propose a novel interferometric reading head with a redundant design for obtaining wide-range displacement measurements. This interferometric reading head uses a one-dimensional grating splice module, and it was observed to be compatible with two orthogonal gratings. We designed a grating interferometer system composed of four reading heads to achieve a wide range of measurements and verified it using ZEMAX simulation. By conducting experiments, we were able to verify the compatibility of the reading head with gratings possessing different grating line directions; the measurement noise was found to be less than 0.3 nm.

An electrochemical biosensor for the assessment of tumor immunotherapy based on the detection of immune checkpoint protein programmed death ligand-1.

Although immunotherapy is now well established in cancer management, not every patient responds. Existing methods for assessing tumor immunotherapy responses, such as immunohistochemistry of the immune checkpoint protein programmed death ligand-1 (PD-L1), require destructive tissue analysis; furthermore, real-time in vivo monitoring would be beneficial for assessing tumor responses. Here we establish an electrochemical biosensor which was developed based on molybdenum disulfide (MoS2) and multi-wall carbon nanotubes (MWCNTs) used to modify the electrode and PD-L1 antibody-quantum dot (QD) conjugate as a dual optical and electrochemical label. The compositions, electrochemical performance, specificity of nanocomposite and probe were characterized. Paving the way for clinical application, the prepared biosensor detects differences in PD-L1 levels in diverse tumor cell types, tumors derived from mice or cancer patients, and it is reproducible and selective in both phosphate-buffered saline and serum. This study demonstrates that electrochemical sensing is a desirable technology for the in-situ and dynamic determination of biomarkers on the cellular level of for the assessment of tumor immunotherapy.

Ginsenoside Rg3 determination using an electro-synthesized molecularly imprinted polymer on MWCNT-Ti3C2Tx nanocomposite modified electrode.

Rare ginsenoside Rg3 is a main active ingredient in ginseng, which is more easily absorbed by human body and plays its role. Determination of Rg3 in edible and medicinal samples is a key factor for quality evaluation and effective monitoring of adulteration. In this study, an electrochemical sensor was developed based on molecularly imprinted polymer (MIP) and nanomaterial amplification. MIP was achieved by electro-polymerization with Rg3 as the template molecule and the functional monomer was o-phenylenediamine. Multi-walled carbon nanotubes (MWCNT) and titanium carbide (Ti3C2Tx) nanocomposites formed an excellent porous structure, which exhibited the advantages of increasing the specific surface area and electrical conductivity. The prepared sensor presented a great linear relation of Rg3 in the range of 10-2000 µg mL-1 with a limit of detection (LOD) of 0.34 µg mL-1. Importantly, the sensor was successfully utilized to detect ginsenoside Rg3 in different real samples.

An Electrochemical Sensor Based on Chalcogenide Molybdenum Disulfide-Gold-Silver Nanocomposite for Detection of Hydrogen Peroxide Released by Cancer Cells.

Hydrogen peroxide (H2O2) as a crucial signal molecule plays a vital part in the growth and development of various cells under normal physiological conditions. The development of H2O2 sensors has received great research interest because of the importance of H2O2 in biological systems and its practical applications in other fields. In this study, a H2O2 electrochemical sensor was constructed based on chalcogenide molybdenum disulfide-gold-silver nanocomposite (MoS2-Au-Ag). Transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and energy dispersive spectroscopy (EDS) were utilized to characterize the nanocomposites, and the electrochemical performances of the obtained sensor were assessed by two electrochemical detection methods: cyclic voltammetry and chronoamperometry. The results showed that the MoS2-Au-Ag-modified glassy carbon electrode (GCE) has higher sensitivity (405.24 µA mM-1 cm-2), wider linear detection range (0.05-20 mM) and satisfactory repeatability and stability. Moreover, the prepared sensor was able to detect the H2O2 discharge from living tumor cells. Therefore, this study offers a platform for the early diagnosis of cancer and other applications in the fields of biology and biomedicine.

Application of Electrochemical Sensors Based on Carbon Nanomaterials for Detection of Flavonoids.

Flavonoids have a variety of physiological activities such as anti-free radicals, regulating hormone levels, antibacterial factors, and anti-cancer factors, which are widely present in edible and medicinal plants. Real-time detection of flavonoids is a key step in the quality control of diverse matrices closely related to social, economic, and health issues. Traditional detection methods are time-consuming and require expensive equipment and complicated working conditions. Therefore, electrochemical sensors with high sensitivity and fast detection speed have aroused extensive research interest. Carbon nanomaterials are preferred material in improving the performance of electrochemical sensing. In this paper, we review the progress of electrochemical sensors based on carbon nanomaterials including carbon nanotubes, graphene, carbon and graphene quantum dots, mesoporous carbon, and carbon black for detecting flavonoids in food and drug homologous substances in the last four years. In addition, we look forward to the prospects and challenges of this research field.

Ultraprecision Real-Time Displacements Calculation Algorithm for the Grating Interferometer System.

Grating interferometry is an environmentally stable displacement measurement technique that has significant potential for identifying the position of the wafer stage. A fast and precise algorithm is required for real-time calculation of six degrees-of-freedom (DOF) displacement using phase shifts of interference signals. Based on affine transformation, we analyze diffraction spot displacement and changes in the internal and external effective optical paths of the grating interferometer caused by the displacement of the wafer stage (DOWS); then, we establish a phase shift-DOWS model. To solve the DOWS in real time, we present a polynomial approximation algorithm that uses the frequency domain characteristics of nonlinearities to achieve model reduction. The presented algorithm is verified by experiment and ZEMAX simulation.

Translational displacement computational algorithm of the grating interferometer without geometric error for the wafer stage in a photolithography scanner.

The translational displacement computational algorithm base on a novel phase-shift model is proposed eliminating the geometric error of the grating interferometer for precision positioning of a multi-degree-of-freedom motion stage. Firstly, the mechanism of the geometric error of the grating interferometer is analyzed, and the novel phase-shift model of the grating interferometer is constructed based on rigid body kinematics and affine geometry transformation. High accuracy of the model is demonstrated by ZEMAX simulation. Then, according to Taylor series expansion, the phase-shift model is simplified by polynomial regression to solve the problems of a large amount of computational effort and inability to derive the translational displacement computational algorithm. The availability and accuracy of the translational displacement computational algorithm are verified by ZEMAX simulation and experiment.

Sinusoidal phase-modulating laser diode interferometer for wide range displacement measurement.

A sinusoidal phase-modulating laser diode interferometer for wide range displacement measurement is proposed. To realize wide range displacement measurement, a signal processing method utilizing a look-up table to estimate the dynamic value of the effective sinusoidal phase-modulating depth is detailed, and the error caused by the residual amplitude modulation and the effective sinusoidal phase-modulating depth in wide range displacement measurement can be eliminated. It is discussed that the extended measurement range depends on the monotone intervals of several specific functions. The simulation and experimental results prove that the sinusoidal phase-modulating laser diode interferometer with the proposed method could realize centimeter level displacement measurement range.

Mean-square convergence analysis of ADALINE training with minimum error entropy criterion.

Recently, the minimum error entropy (MEE) criterion has been used as an information theoretic alternative to traditional mean-square error criterion in supervised learning systems. MEE yields nonquadratic, nonconvex performance surface even for adaptive linear neuron (ADALINE) training, which complicates the theoretical analysis of the method. In this paper, we develop a unified approach for mean-square convergence analysis for ADALINE training under MEE criterion. The weight update equation is formulated in the form of block-data. Based on a block version of energy conservation relation, and under several assumptions, we carry out the mean-square convergence analysis of this class of adaptation algorithm, including mean-square stability, mean-square evolution (transient behavior) and the mean-square steady-state performance. Simulation experimental results agree with the theoretical predictions very well.