Highly integrated automatic injection terahertz microfluidic biosensor based on metasurface and LT-GaAs photoconductive antenna.

In this paper, a highly integrated terahertz (THz) biosensor is proposed and implemented, which pioneered the preparation of low-temperature gallium arsenide (LT-GaAs) thin film photoconductive antenna (PCA) on the sensor for direct generation and detection of THz waves, simplifying complex terahertz time-domain spectroscopy (THz-TDS) systems. A latch type metasurface is deposited in the detection region to produce a resonance absorption peak at 0.6 THz that is independent of polarisation. Microfluidics is utilised and automatic injection is incorporated to mitigate the experimental effects of hydrogen bond absorption of THz waves in aqueous-based environment. Additionally, cell damage is minimised by regulating the cell flow rate. The biosensor was utilised to detect the concentration of three distinct sizes of bacteria with successful results. The assay was executed as a proof of concept to detect two distinct types of breast cancer cells. Based on the experimental findings, it has been observed that the amplitude and blueshift of the resonance absorption peaks have the ability to identify and differentiate various cancer cell types. The findings of this study introduce a novel approach for developing microfluidic THz metasurface biosensors that possess exceptional levels of integration, sensitivity, and rapid label-free detection capabilities.

Carrier Relaxation and Multiplication in Bi Doped Graphene.

By introducing different contents of Bi adatoms to the surface of monolayer graphene, the carrier concentration and their dynamics have been effectively modulated as probed directly by the time- and angle-resolved photoemission spectroscopy technique. The Bi adatoms are found to assist acoustic phonon scattering events mediated by supercollisions as the disorder effectively relaxes the momentum conservation constraint. A reduced carrier multiplication has been observed, which is related to the shrinking Fermi sea for scattering, as confirmed by time-dependent density functional theory simulation. This work gives insight into hot carrier dynamics in graphene, which is crucial for promoting the application of photoelectric devices.

Microinjection-based CRISPR/Cas9 mutagenesis in the decapoda crustaceans Neocaridina heteropoda and Eriocheir sinensis.

CRISPR/Cas9 technology has been applied to many arthropods. However, application of this technology to crustaceans remains limited because of the unique characteristics of embryos. Our group has developed a microinjection system to introduce the CRISPR/Cas9 system into Neocaridina heteropoda embryos (one-cell stage). Using the developed method, we mutated the target gene Nh-scarlet (N. heteropoda scarlet), which functions in eye development and pigmentation. The results showed that both eye color and shape were altered in individuals in which Nh-scarlet was knocked out. Furthermore, this system was also successfully applied to another decapod crustacean, Eriocheir sinensis. DNA sequencing revealed that the zoeae with red eyes had an edited version of Es-scarlet. This study provides a stable microinjection method for freshwater crustaceans, and will contribute to functional genomics studies in various decapods.

Pleasantness Recognition Induced by Different Odor Concentrations Using Olfactory Electroencephalogram Signals.

Olfactory-induced emotion plays an important role in communication, decision-making, multimedia, and disorder treatment. Using electroencephalogram (EEG) technology, this paper focuses on (1) exploring the possibility of recognizing pleasantness induced by different concentrations of odors, (2) finding the EEG rhythm wave that is most suitable for the recognition of different odor concentrations, (3) analyzing recognition accuracies with concentration changes, and (4) selecting a suitable classifier for this classification task. To explore these issues, first, emotions induced by five different concentrations of rose or rotten odors are divided into five kinds of pleasantness by averaging subjective evaluation scores. Then, the power spectral density features of EEG signals and support vector machine (SVM) are used for classification tasks. Classification results on the EEG signals collected from 13 participants show that for pleasantness recognition induced by pleasant or disgusting odor concentrations, considerable average classification accuracies of 93.5% or 92.2% are obtained, respectively. The results indicate that (1) using EEG technology, pleasantness recognition induced by different odor concentrations is possible; (2) gamma frequency band outperformed other EEG rhythm-based frequency bands in terms of classification accuracy, and as the maximum frequency of the EEG spectrum increases, the pleasantness classification accuracy gradually increases; (3) for both rose and rotten odors, the highest concentration obtains the best classification accuracy, followed by the lowest concentration.

Direct Observation of Global Elastic Intervalley Scattering Induced by Impurities on Graphene.

The scattering process induced by impurities in graphene plays a key role in transport properties. Especially, the disorder impurities can drive the ordered state with a hexagonal superlattice on graphene by electron-mediated interaction at a transition temperature. Using angle-resolved photoemission spectroscopy (ARPES), we reveal that the epitaxial monolayer and bilayer graphene with various impurities display global elastic intervalley scattering and quantum interference below the critical temperature (34 K), which leads to a set of new folded Dirac cones at the Brillouin-zone center by mixing two inequivalent Dirac cones. The Dirac electrons generated from intervalley scattering without chirality can be due to the breaking of the sublattice symmetry. In addition, the temperature-dependent ARPES measurements indicate the thermal damping of quantum interference patterns from Dirac electron scattering on impurities. Our results demonstrate that the electron scattering and interference induced by impurities can completely modulate the Dirac bands of graphene.

Constructing Uranyl-Specific Nanofluidic Channels for Unipolar Ionic Transport to Realize Ultrafast Uranium Extraction.

High-speed capturing of uranyl (UO22+) ions from seawater elicits unprecedented interest for the sustainable development of the nuclear energy industry. However, the ultralow concentration (∼3.3 µg L-1) of uranium element leads to the slow ion diffusion inside the adsorbent particle, especially after the transfer paths are occupied by the coexisted interfering ions. Considering the geometric dimension of UO22+ ion (a maximum length of 6.04-6.84 Å), the interlayer spacing of graphene sheets was covalently pillared with phenyl-based units into twice the ionic length (13 Å) to obtain uranyl-specific nanofluidic channels. Applying a negative potential (-1.3 V), such a charge-governed region facilitates a unipolar ionic transport, where cations are greatly accelerated and co-ions are repelled. Notably, the resulting adsorbent gives the highest adsorption velocity among all reported materials. The adsorption capacity measured after 56 days of exposure in natural seawater is evaluated to be ∼16 mg g-1. This novel concept with rapid adsorption, high capacity, and facile operating process shows great promise to implement in real-world uranium extraction.

[Application of PDCA circulation in reduction of the turnaround time of semen samples in the andrology laboratory].

OBJECTIVE: To reduce the out-of-threshold (OOT) value of the turnaround time (TAT) of semen samples in the andrology laboratory and improve the clinical diagnosis and patients' satisfaction. METHODS: We retrospectively analyzed the defect rate of TAT of semen samples in the andrology laboratory in the first two quarters of 2018. In the second two quarters, we made a table of countermeasures targeting the causes of the defects using plan-do-check-act (PDCA) circulation and the fishbone diagram drawn with the brainstorm method, followed by supervision of the implementation of the measures and observation of the changes in the OOT value of TAT of semen samples. RESULTS: The OOT rate of TAT of semen samples before seminal examination was significantly lower in the third and fourth than in the first and second quarters of 2018 (0.83% and 0.78% vs 3.43% and 2.07%, P < 0.01), and so was the total OOT rate of TAT (6.36% and 0.87% vs 7.00% and 7.15%, P < 0.01). The median of TAT of semen samples before computer assisted semen analysis was decreased from 22 min in the first to 17 min in the fourth quarter, and the 90th percentile from 54 min to 40 min. The median of total TAT in biochemical analysis was reduced from 387 min in the first to 315 min in the fourth quarter, and the 90th percentile from 1415 min to 1179 min. CONCLUSIONS: The application of PDCA circulation can significantly shorten the turnaround time of semen samples and improve the efficiency of diagnosis and treatment and quality control in the andrology laboratory.

A novel microRNA and its pfk target control growth length in the freshwater shrimp Neocaridina heteropoda.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression and play roles in a wide range of physiological processes, including ontogenesis. Herein, we discovered a novel miRNA, novel miR-26, which inhibits translation of the phosphofructokinase (PFK) gene by targeting the 3' untranslated region (UTR) of pfk directly, thereby inhibiting molting and body length growth of the freshwater shrimp Neocaridina heteropoda Lowering expression of pfk by RNA interference (RNAi) led to a longer ecdysis cycle and smaller individuals. This phenotype was mirrored in shrimps injected with novel miR-26 agomirs, but the opposite phenotype occurred in shrimps injected with novel miR-26 antagomirs (i.e. the ecdysis cycle was shortened and body length was increased). After injection of 20-hydroxyecdysone (ecdysone 20E), expression of the novel miR-26 was decreased, while expression of pfk was up-regulated, and the fructose-1,6-diphosphate metabolite of PFK accumulated correspondingly. Furthermore, expression of eIF2 (eukaryotic initiation factor 2) increased under stimulation with fructose-1,6-diphosphate, suggesting that protein synthesis was stimulated during this period. Taken together, our results suggest that the novel miR-26 regulates expression of pfk and thereby mediates the molting and growth of N. heteropoda.

MMP-14 regulates innate immune responses to Eriocheir sinensis via tissue degradation.

Matrix metalloproteinases (MMPs) are a cluster of enzymes that degrade the extracellular matrix (ECM) and some intracellular proteins; as such, they play an important role in tissue regeneration, infant growth, animal reproduction, and immunity. Most research into MMPs focuses mainly on their effects on the mammalian immune system. However, it is not clear how MMPs affect immune processes in crustaceans. Here, we cloned the open reading frame (ORF) of Eriocheir sinensis (Chinese mitten crab) MMP-14 (EsMMP-14) to explore the role of MMPs in crustacean innate immune responses. RT-PCR results showed that stimulation of crab with LPS and poly I:C upregulated expression of EsMMP-14 markedly. Besides, following the stimulation of 20-Hydroxyecdysone, the expression level of EsMMP-14 increased robustly, suggesting that EsMMP-14 involved in the molt process of E. sinensis. Hematoxylin and eosin staining of hepatopancreas and intestine revealed that knocking down EsMMP-14 maintained morphology following infection by Bacillus thuringiensis. Moreover, downregulated expression of EsMMP-14 increased the survival rate of infected E. sinensis. These results show that EsMMP-14 plays a role in innate immune responses of E. sinensis and fills a gap in our knowledge about the function of MMPs in crustaceans.

[Olfactory electroencephalogram signal recognition based on wavelet energy moment].

Studying the ability of the brain to recognize different odors is of great significance in the assessment and diagnosis of olfactory dysfunction. The wavelet energy moment (WEM) was proposed as a feature of olfactory electroencephalogram (EEG) signal and used for odor classification. Firstly, the olfactory evoked EEG data of 13 odors were collected by an experiment. Secondly, the WEM was extracted from olfactory evoked EEG data as the signal feature, and the power spectrum density (PSD), approximate entropy, sample entropy and wavelet entropy were used as the contrast features. Finally, k-nearest neighbor ( k-NN), support vector machine (SVM), random forest (RF) and decision tree classifier were used to identify different odors. The results showed that using the above four classifiers, the classification accuracy of WEM feature was higher than other features, and the k-NN classifier combined with WEM feature had the highest classification accuracy (91.07%). This paper further explored the characteristics of different EEG frequency bands, and found that most of the classification accuracy based on the features of γ band was better than that of the full band and other bands, among which the WEM feature of the γ band combined with the k-NN classifier had the highest classification accuracy (93.89 %). The research results of this paper could provide a new objective basis for the evaluation of olfactory function. On the other hand, it could also provide new ideas for the study of olfactory-induced emotions.

Bursicon homodimers induce innate immune by activating the expression of anti-microbial peptide genes in the shrimp Neocaridina heteropoda.

Bursicon is a neurohormone belonging to the cystine knot protein family. It consists of two subunits (burs α and burs ß) and plays a pivotal role in cuticle tanning and wing expansion in insects. Recent studies show that homologous crustacean bursicon stimulates cuticle thickening and granulation of hemocytes in the crab Callinectes sapidus. Here we investigate whether bursicon homodimers function in immunoprotective defense systems of shrimp. We found that abdominal ganglion was the main neurohemal release site of bursicon in Neocaridina heteropoda. Bacterial infections induced overexpression of burs α (bursicon α) and burs ß (bursicon ß). RNAi of burs α, burs ß or both inhibited the expression of anti-microbial peptide (AMP) genes. Treating shrimp adults with r-bursicon (recombinant bursicon) homodimers led to up-regulation of three AMP genes. Besides, through the induced AMPs, r-bursicon homodimers enhanced the bacteriostasis of shrimp in vivo and in vitro. These findings demonstrate a novel function of bursicon in crustacean that it induces innate immune via up-regulating the expression of genes encoding AMPs.

Chemical Source Searching by Controlling a Wheeled Mobile Robot to Follow an Online Planned Route in Outdoor Field Environments.

In this paper, we present an estimation-based route planning (ERP) method for chemical source searching using a wheeled mobile robot and validate its effectiveness with outdoor field experiments. The ERP method plans a dynamic route for the robot to follow to search for a chemical source according to time-varying wind and an estimated chemical-patch path (C-PP), where C-PP is the historical trajectory of a chemical patch detected by the robot, and normally different from the chemical plume formed by the spatial distribution of all chemical patches previously released from the source. Owing to the limitations of normal gas sensors and actuation capability of ground mobile robots, it is quite hard for a single robot to directly trace the intermittent and rapidly swinging chemical plume resulting from the frequent and random changes of wind speed and direction in outdoor field environments. In these circumstances, tracking the C-PP originating from the chemical source back could help the robot approach the source. The proposed ERP method was tested in two different outdoor fields using a wheeled mobile robot. Experimental results indicate that the robot adapts to the time-varying airflow condition, arriving at the chemical source with an average success rate and approaching effectiveness of about 90% and 0.4~0.6, respectively.

A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks.

Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors' speeds and rotorcraft's acceleration and position. Then the wind disturbance is scaled to calculate the airspeed vector, which is substituted into a wind triangle to obtain the wind velocity. Easy-to-implement methods for calculating the rotorcraft's thrust and drag coefficient are also proposed, which are important parameters to obtain the wind drag and the airspeed, respectively. Simulations and experiments using a quadrotor in both hovering and flight conditions have validated the proposed method.

Stacked Sparse Auto-Encoders (SSAE) Based Electronic Nose for Chinese Liquors Classification.

This paper presents a stacked sparse auto-encoder (SSAE) based deep learning method for an electronic nose (e-nose) system to classify different brands of Chinese liquors. It is well known that preprocessing; feature extraction (generation and reduction) are necessary steps in traditional data-processing methods for e-noses. However, these steps are complicated and empirical because there is no uniform rule for choosing appropriate methods from many different options. The main advantage of SSAE is that it can automatically learn features from the original sensor data without the steps of preprocessing and feature extraction; which can greatly simplify data processing procedures for e-noses. To identify different brands of Chinese liquors; an SSAE based multi-layer back propagation neural network (BPNN) is constructed. Seven kinds of strong-flavor Chinese liquors were selected for a self-designed e-nose to test the performance of the proposed method. Experimental results show that the proposed method outperforms the traditional methods.

Learning to rapidly re-contact the lost plume in chemical plume tracing.

Maintaining contact between the robot and plume is significant in chemical plume tracing (CPT). In the time immediately following the loss of chemical detection during the process of CPT, Track-Out activities bias the robot heading relative to the upwind direction, expecting to rapidly re-contact the plume. To determine the bias angle used in the Track-Out activity, we propose an online instance-based reinforcement learning method, namely virtual trail following (VTF). In VTF, action-value is generalized from recently stored instances of successful Track-Out activities. We also propose a collaborative VTF (cVTF) method, in which multiple robots store their own instances, and learn from the stored instances, in the same database. The proposed VTF and cVTF methods are compared with biased upwind surge (BUS) method, in which all Track-Out activities utilize an offline optimized universal bias angle, in an indoor environment with three different airflow fields. With respect to our experimental conditions, VTF and cVTF show stronger adaptability to different airflow environments than BUS, and furthermore, cVTF yields higher success rates and time-efficiencies than VTF.

Distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks.

This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

Torenia sp. Extracts Contain Multiple Potent Antitumor Compounds with Nematocidal Activity, Triggering an Activated DNA Damage Checkpoint and Defective Meiotic Progression.

Previously, we analyzed 316 herbal extracts to evaluate their potential nematocidal properties in Caenorhabditis elegans. In this study, our attention was directed towards Torenia sp., resulting in reduced survival and heightened larval arrest/lethality, alongside a noticeable decrease in DAPI-stained bivalent structures and disrupted meiotic progression, thus disrupting developmental processes. Notably, Torenia sp. extracts activated a DNA damage checkpoint response via the ATM/ATR and CHK-1 pathways, hindering germline development. LC-MS analysis revealed 13 compounds in the Torenia sp. extracts, including flavonoids, terpenoids, tanshinones, an analog of resveratrol, iridoids, carotenoids, fatty acids, and alkaloids. Of these, 10 are known for their antitumor activity, suggesting the potential of Torenia species beyond traditional gardening, extending into pharmaceutical and therapeutic applications.

miR-142-3p alleviates neuronal apoptosis in Parkinson's disease via negatively regulating C9orf72.

Although microRNA (miRNA) have important clinical prospects in the early diagnosis and treatment of PD, the functions and mechanisms of miRNAs in PD models remain poorly defined. In this study, we screened 9 miRNAs that differently expressed in PD patients and found that miR-142-3p expression was downregulated in both animal and cell models of PD. We showed that overexpression of miR-142-3p significantly alleviates the neuronal damage induced by MPP+, while knockdown of miR-142-3p exacerbates the neuronal damage caused by MPP+. We further found that miR-142-3p targets and inhibits the expression of C9orf72. Knockdown of C9orf72 mitigated neuronal autophagy dysfunction by reducing excessive activation of the AKT/mTOR pathway after MPP+ stimulation, thereby exerted neuroprotective effects. This study reveals that miR-142-3p protects neuron in PD pathogenesis via negatively regulating C9orf72 and enhancing autophagy. Our findings provides an insight into the development of potential biomarkers and therapeutic targets for PD.

TrueTH: A user-friendly deep learning approach for robust dopaminergic neuron detection.

Parkinson's disease (PD) entails the progressive loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNc), leading to movement-related impairments. Accurate assessment of DA neuron health is vital for research applications. Manual analysis, however, is laborious and subjective. To address this, we introduce TrueTH, a user-friendly and robust pipeline for unbiased quantification of DA neurons. Existing deep learning tools for tyrosine hydroxylase-positive (TH+) neuron counting often lack accessibility or require advanced programming skills. TrueTH bridges this gap by offering an open-sourced and user-friendly solution for PD research. We demonstrate TrueTH's performance across various PD rodent models, showcasing its accuracy and ease of use. TrueTH exhibits remarkable resilience to staining variations and extreme conditions, accurately identifying TH+ neurons even in lightly stained images and distinguishing brain section fragments from neurons. Furthermore, the evaluation of our pipeline's performance in segmenting fluorescence images shows strong correlation with ground truth and outperforms existing models in accuracy. In summary, TrueTH offers a user-friendly interface and is pretrained with a diverse range of images, providing a practical solution for DA neuron quantification in Parkinson's disease research.

Novel studies on Drosophila melanogaster model reveal the roles of JNK-Jak/STAT axis and intestinal microbiota in insulin resistance.

The JNK pathway play a critical role in insulin resistance induced by a long-term high-sugar diet. However, the roles of up- and downstream molecules of the JNK pathway in insulin resistance are less known in vertebrates and invertebrates. As a classical organism in biological research, Drosophila melanogaster (D. melanogaster) has been widely applied to the studies of mechanism of insulin resistance. Based on previous studies, we found a novel predictive mechanism of the formation of insulin resistance in D. melanogaster. We found that JNK activated by high-sugar diet and dysregulated intestinal microbiota could mediate inflammation, and then the activated JNK released Upd3, which in turn stimulated Jak/STAT pathway to release ImpL2. ImpL2 can compete with Drosophila insulin-like peptides (Dilps) for binding with the insulin receptor and inhibit the activation of insulin pathway. In this study, we reviewed novel studies on the insulin signalling pathway based on the D. melanogaster model. The findings support our hypothesis. We, therefore, described how a long-term high-sugar diet disrupts intestinal microbiota to induce inflammation and the disruption of JNK-Jak/STAT axis. This description may offer some new clues to the formation of insulin resistance.