Adaptive Signal Modulation Evolved by the Inherent Nonlinearity of Phase-Change Quantum-Dot String.

To simulate a topological neural network handling weak signals via stochastic resonance (SR), it is necessary to introduce an inherent nonlinearity into nanoscale devices. We use the self-assembly method to successfully fabricate a phase-change quantum-dot string (PCQDS) crossing Pd/Nb:AlNO/AlNO/Nb:AlNO/Pd multilayer. The inherent nonlinearity of phase change couples with electron tunneling so that PCQDS responds to a long signal sequence in a modulated output style, in which the pulse pattern evolves to that enveloped by two sets of periodic wave characterized by neural action potential. We establish an SR mode consisting of several two-state systems in which dissipative tunneling is coupled to environment. Size oscillations owing to NbO QDs adaptively adjust barriers and wells, such that tunneling can be periodically modulated by either asymmetric energy or local temperature. When the external periodic signals are applied, the system first follows the forcing frequency. Subsequently, certain PCQDs oscillate independently and consecutively to produce complicated frequency and amplitude modulations.

Subtype-Specific Roles of Ellipsoid Body Ring Neurons in Sleep Regulation in Drosophila.

The ellipsoid body (EB) is a major structure of the central complex of the Drosophila melanogaster brain. Twenty-two subtypes of EB ring neurons have been identified based on anatomic and morphologic characteristics by light-level microscopy and EM connectomics. A few studies have associated ring neurons with the regulation of sleep homeostasis and structure. However, cell type-specific and population interactions in the regulation of sleep remain unclear. Using an unbiased thermogenetic screen of EB drivers using female flies, we found the following: (1) multiple ring neurons are involved in the modulation of amount of sleep and structure in a synergistic manner; (2) analysis of data for ΔP(doze)/ΔP(wake) using a mixed Gaussian model detected 5 clusters of GAL4 drivers which had similar effects on sleep pressure and/or depth: lines driving arousal contained R4m neurons, whereas lines that increased sleep pressure had R3m cells; (3) a GLM analysis correlating ring cell subtype and activity-dependent changes in sleep parameters across all lines identified several cell types significantly associated with specific sleep effects: R3p was daytime sleep-promoting, and R4m was nighttime wake-promoting; and (4) R3d cells present in 5HT7-GAL4 and in GAL4 lines, which exclusively affect sleep structure, were found to contribute to fragmentation of sleep during both day and night. Thus, multiple subtypes of ring neurons distinctively control sleep amount and/or structure. The unique highly interconnected structure of the EB suggests a local-network model worth future investigation; understanding EB subtype interactions may provide insight how sleep circuits in general are structured.SIGNIFICANCE STATEMENT How multiple brain regions, with many cell types, can coherently regulate sleep remains unclear, but identification of cell type-specific roles can generate opportunities for understanding the principles of integration and cooperation. The ellipsoid body (EB) of the fly brain exhibits a high level of connectivity and functional heterogeneity yet is able to tune multiple behaviors in real-time, including sleep. Leveraging the powerful genetic tools available in Drosophila and recent progress in the characterization of the morphology and connectivity of EB ring neurons, we identify several EB subtypes specifically associated with distinct aspects of sleep. Our findings will aid in revealing the rules of coding and integration in the brain.

Memristive Behaviors Dominated by Reversible Nucleation Dynamics of Phase-Change Nanoclusters.

One of the important steps for realizing artificial intelligence is identifying elementary units that are beneficial for neural network construction. A type of memristive behavior in which phase-change nanoclusters nucleate adaptively in two adjacent dielectric layers with distinct distribution patterns is demonstrated. This memristive system responds in potentiation to increased stimulation strength and fire action potential after threshold stimulation. Reversible nucleation of phase-change nanoclusters is confirmed after both in situ and ex situ examinations using high-resolution transmission electron microscopy. The dynamics at the nanoscale level dominates the actions of the two dielectric layers. The oscillation response over a long period is due to the competition between crystalline and amorphous phases in the layer near the bottom electrode. Weight mutation, that is, action potential firing, is caused by the blockage of the filament in the layer near the top electrode. The memristive system is compact and able to execute complicated functions of a complete neuron and performs an important role in neuromorphic computing.

Circadian neuron feedback controls the Drosophila sleep--activity profile.

Little is known about the ability of Drosophila circadian neurons to promote sleep. Here we show, using optogenetic manipulation and video recording, that a subset of dorsal clock neurons (DN1s) are potent sleep-promoting cells that release glutamate to directly inhibit key pacemaker neurons. The pacemakers promote morning arousal by activating these DN1s, implying that a late-day feedback circuit drives midday siesta and night-time sleep. To investigate more plastic aspects of the sleep program, we used a calcium assay to monitor and compare the real-time activity of DN1 neurons in freely behaving males and females. Our results revealed that DN1 neurons were more active in males than in females, consistent with the finding that male flies sleep more during the day. DN1 activity is also enhanced by elevated temperature, consistent with the ability of higher temperatures to increase sleep. These new approaches indicate that DN1s have a major effect on the fly sleep-wake profile and integrate environmental information with the circadian molecular program.

Nutrition, Bioactive Components, and Hepatoprotective Activity of Fruit Vinegar Produced from Ningxia Wolfberry.

Wolfberry (Lycium barbarum L.) is a nutritious and medicinal fruit, and deeply processed products of wolfberry needs to be improved. In this study, nutrition, bioactive compounds, and hepaprotective activity were explored in wolfberry vinegar (WFV). The contents of nutrients including total sugar and protein in WFV samples were 2.46 and 0.27 g/100 mL, respectively. Total phenolic and flavonoid contents in WFV were 2.42 mg GAE/mL and 1.67 mg RE/mL, respectively. p-Hydroxybenzoic acid and m-hydroxycinnamic acid were the main polyphenols in WFV. The antioxidant activity of WFV were 20.176 mM Trolox/L (ABTS), 8.614 mM Trolox/L (FRAP), and 26.736 mM Trolox/L (DPPH), respectively. In addition, WFV treatment effectively alleviated liver injury by improving histopathological changes and reducing liver biochemical indexes in CCl4-treated mice. WFV alleviated oxidative damage by inhibiting oxidative levels and increasing antioxidant levels. These results suggest that WFV can be utilized as a functional food to prevent oxidative liver injury.

Regulation of Olfactory Associative Memory by the Circadian Clock Output Signal Pigment-Dispersing Factor (PDF).

Dissociation between the output of the circadian clock and external environmental cues is a major cause of human cognitive dysfunction. While the effects of ablation of the molecular clock on memory have been studied in many systems, little has been done to test the role of specific clock circuit output signals. To address this gap, we examined the effects of mutations of Pigment-dispersing factor (Pdf) and its receptor, Pdfr, on associative memory in male and female Drosophila Loss of PDF signaling significantly decreases the ability to form associative memory. Appetitive short-term memory (STM), which in wild-type (WT) is time-of-day (TOD) independent, is decreased across the day by mutation of Pdf or Pdfr, but more substantially in the morning than in the evening. This defect is because of PDFR expression in adult neurons outside the core clock circuit and the mushroom body (MB) Kenyon cells (KCs). The acquisition of a TOD difference in mutants implies the existence of multiple oscillators that act to normalize memory formation across the day for appetitive processes. Interestingly, aversive STM requires PDF but not PDFR, suggesting that there are valence-specific pathways downstream of PDF that regulate memory formation. These data argue that the circadian clock uses circuit-specific and molecularly diverse output pathways to enhance the ability of animals to optimize responses to changing conditions.SIGNIFICANCE STATEMENT From humans to invertebrates, cognitive processes are influenced by organisms' internal circadian clocks, the pace of which is linked to the solar cycle. Disruption of this link is increasingly common (e.g., jetlag, social jetlag disorders) and causes cognitive impairments that are costly and long lasting. A detailed understanding of how the internal clock regulates cognition is critical for the development of therapeutic methods. Here, we show for the first time that olfactory associative memory in Drosophila requires signaling by Pigment-dispersing factor (PDF), a neuromodulatory signaling peptide produced only by circadian clock circuit neurons. We also find a novel role for the clock circuit in stabilizing appetitive sucrose/odor memory across the day.

Simultaneous visual diagnosis of acute hepatopancreatic necrosis disease and Enterocytozoon hepatopenaei infection in shrimp with duplex recombinase polymerase amplification.

Shrimp is a globally popular seafood. Shrimp farming has been challenged by various infectious diseases that lead to significant economic losses. The prevention of two important shrimp infectious diseases, the acute hepatopancreatic necrosis disease (AHPND) and the Enterocytozoon hepatopenaei (EHP) infection, is highly dependent on early and accurate diagnostic. On-site monitoring of the two diseases in shrimp farming facilities demands point-of-care-testing (POCT) type of diagnostic assays. This study established a duplex recombinase polymerase amplification (RPA) and lateral flow dipstick (LFD) combined assay that could simultaneously diagnose the two diseases. The optimized RPA-LFD assay could finish the diagnostic in 35 min with good specificity, and the sensitivity reached 101 and 102 gene copies per reaction for EHP and AHPND, respectively, which were at the same level as the currently available molecular diagnostic assays. Test results of clinical samples showed 100% agreement of this assay with the industrial standard nested polymerase chain reaction (PCR) assays, and samples with both diseases were simultaneously identified. Because of the isothermal 37℃ amplification and the visual reading of the signal on dipsticks, the dependence on equipment is minimal. This duplex RPA-LFD assay is well suited for simultaneous POCT diagnostic of the two important shrimp infectious diseases. Moreover, the principle can be applied to multiplex POCT diagnostic of other infectious diseases in aquaculture.

Rational design of true monomeric and bright photoactivatable fluorescent proteins.

Monomeric (m)Eos2 is an engineered photoactivatable fluorescent protein widely used for super-resolution microscopy. We show that mEos2 forms oligomers at high concentrations and forms aggregates when labeling membrane proteins, limiting its application as a fusion partner. We solved the crystal structure of tetrameric mEos2 and rationally designed improved versions, mEos3.1 and mEos3.2, that are truly monomeric, are brighter, mature faster and exhibit higher photon budget and label density.

Discovery and structural optimization of 1-phenyl-3-(1-phenylethyl)urea derivatives as novel inhibitors of CRAC channel.

AIM: Ca(2+)-release-activated Ca(2+) (CRAC) channel, a subfamily of store-operated channels, is formed by calcium release-activated calcium modulator 1 (ORAI1), and gated by stromal interaction molecule 1 (STIM1). CRAC channel may be a novel target for the treatment of immune disorders and allergy. The aim of this study was to identify novel small molecule CRAC channel inhibitors. METHODS: HEK293 cells stably co-expressing both ORAI1 and STIM1 were used for high-throughput screening. A hit, 1-phenyl-3-(1-phenylethyl)urea, was identified that inhibited CRAC channels by targeting ORAI1. Five series of its derivatives were designed and synthesized, and their primary structure-activity relationships (SARs) were analyzed. All derivatives were assessed for their effects on Ca(2+) influx through CRAC channels on HEK293 cells, cytotoxicity in Jurkat cells, and IL-2 production in Jurkat cells expressing ORAI1-SS-eGFP. RESULTS: A total of 19 hits were discovered in libraries containing 32 000 compounds using the high-throughput screening. 1-Phenyl-3-(1-phenylethyl)urea inhibited Ca(2+) influx with IC50 of 3.25±0.17 µmol/L. SAR study on its derivatives showed that the alkyl substituent on the α-position of the left-side benzylic amine (R1) was essential for Ca(2+) influx inhibition and that the S-configuration was better than the R-configuration. The derivatives in which the right-side R3 was substituted by an electron-donating group showed more potent inhibitory activity than those that were substituted by electron-withdrawing groups. Furthermore, the free N-H of urea was not necessary to maintain the high potency of Ca(2+) influx inhibition. The N,N'-disubstituted or N'-substituted derivatives showed relatively low cytotoxicity but maintained the ability to inhibit IL-2 production. Among them, compound 5b showed an improved inhibition of IL-2 production and low cytotoxicity. CONCLUSION: 1-Phenyl-3-(1-phenylethyl)urea is a novel CRAC channel inhibitor that specifically targets ORAI1. This study provides a new chemical scaffold for design and development of CRAC channel inhibitors with improved Ca(2+) influx inhibition, immune inhibition and low cytotoxicity.

An aromatic amino acid in the coiled-coil 1 domain plays a crucial role in the auto-inhibitory mechanism of STIM1.

STIM1 (stromal interaction molecule 1) is one of the key elements that mediate store-operated Ca²âº entry via CRAC (Ca²âº- release-activated Ca²âº) channels in immune and non-excitable cells. Under physiological conditions, the intramolecular auto-inhibitions in STIM1 C- and STIM1 N-termini play essential roles in keeping STIM1 in an inactive state. However, the auto-inhibitory mechanism of the STIM1 C-terminus is still unclear. In the present study, we first predicted a short inhibitory domain (residues 310-317) in human STIM1 that might determine the different localizations of human STIM1 from Caenorhabditis elegans STIM1 in resting cells. Next, we confirmed the prediction and further identified an aromatic amino acid residue, Tyr³¹6, that played a crucial role in maintaining STIM1 in a closed conformation in quiescent cells. Full-length STIM1-Y316A formed constitutive clusters near the plasma membrane and activated the CRAC channel in the resting state when co-expressed with Orai1. The introduction of a Y316A mutation caused the higher-order oligomerization of the in vitro purified STIM1 fragment containing both the auto-inhibitory domain and CAD(CRAC-activating domain).We propose that the Tyr³¹6 residue may be involved in the auto-inhibitory mechanism of the STIM1 C-terminus in the quiescent state. This inhibition could be achieved either by interacting with the CAD using hydrogen and/or hydrophobic bonds, or by an intermolecular interaction using repulsive forces, which maintained a dimeric STIM1.

Oriented feature pyramid network for small and dense wheat heads detection and counting.

Wheat head detection and counting using deep learning techniques has gained considerable attention in precision agriculture applications such as wheat growth monitoring, yield estimation, and resource allocation. However, the accurate detection of small and dense wheat heads remains challenging due to the inherent variations in their size, orientation, appearance, aspect ratios, density, and the complexity of imaging conditions. To address these challenges, we propose a novel approach called the Oriented Feature Pyramid Network (OFPN) that focuses on detecting rotated wheat heads by utilizing oriented bounding boxes. In order to facilitate the development and evaluation of our proposed method, we introduce a novel dataset named the Rotated Global Wheat Head Dataset (RGWHD). This dataset is constructed by manually annotating images from the Global Wheat Head Detection (GWHD) dataset with oriented bounding boxes. Furthermore, we incorporate a Path-aggregation and Balanced Feature Pyramid Network into our architecture to effectively extract both semantic and positional information from the input images. This is achieved by leveraging feature fusion techniques at multiple scales, enhancing the detection capabilities for small wheat heads. To improve the localization and detection accuracy of dense and overlapping wheat heads, we employ the Soft-NMS algorithm to filter the proposed bounding boxes. Experimental results indicate the superior performance of the OFPN model, achieving a remarkable mean average precision of 85.77% in oriented wheat head detection, surpassing six other state-of-the-art models. Moreover, we observe a substantial improvement in the accuracy of wheat head counting, with an accuracy of 93.97%. This represents an increase of 3.12% compared to the Faster R-CNN method. Both qualitative and quantitative results demonstrate the effectiveness of the proposed OFPN model in accurately localizing and counting wheat heads within various challenging scenarios.

Cascaded Aggregation Convolution Network for Salient Grain Pests Detection.

Pest infestation poses significant threats to grain storage due to pests' behaviors of feeding, respiration, excretion, and reproduction. Efficient pest detection and control are essential to mitigate these risks. However, accurate detection of small grain pests remains challenging due to their small size, high variability, low contrast, and cluttered background. Salient pest detection focuses on the visual features that stand out, improving the accuracy of pest identification in complex environments. Drawing inspiration from the rapid pest recognition abilities of humans and birds, we propose a novel Cascaded Aggregation Convolution Network (CACNet) for pest detection and control in stored grain. Our approach aims to improve detection accuracy by employing a reverse cascade feature aggregation network that imitates the visual attention mechanism in humans when observing and focusing on objects of interest. The CACNet uses VGG16 as the backbone network and incorporates two key operations, namely feature enhancement and feature aggregation. These operations merge the high-level semantic information and low-level positional information of salient objects, enabling accurate segmentation of small-scale grain pests. We have curated the GrainPest dataset, comprising 500 images showcasing zero to five or more pests in grains. Leveraging this dataset and the MSRA-B dataset, we validated our method's efficacy, achieving a structure S-measure of 91.9%, and 90.9%, and a weighted F-measure of 76.4%, and 91.0%, respectively. Our approach significantly surpasses the traditional saliency detection methods and other state-of-the-art salient object detection models based on deep learning. This technology shows great potential for pest detection and assessing the severity of pest infestation based on pest density in grain storage facilities. It also holds promise for the prevention and control of pests in agriculture and forestry.

Genetically-encoded markers for confocal visualization of single dense core vesicles.

Neuronal dense core vesicles (DCVs) store and release a diverse array of neuromodulators, trophic factors and bioamines. The analysis of single DCVs has largely been possible only using electron microscopy, which makes understanding cargo segregation and DCV heterogeneity difficult. To address these limitations, we developed genetically-encoded markers for DCVs that can be used in combination with standard immunohistochemistry and expansion microscopy, to enable single-vesicle resolution with confocal microscopy.

Modulation of Phase-Locking Characteristics of NbOx Memristor by Ag Doping.

Memristors based on niobium oxide have attracted wide interest due to their applications in artificial neural network. Phase-locking (PL) characteristics of NbOx newly explored roots in complex nonlinear dynamics and exhibits great potential in periodical signal handling because of its bioinspired nature. In this study, we fabricate a Pd/Nb/Ag-NbOx/Nb/Pd memristive structure and study the effects of Ag doping on the PL characteristics. We clearly see that the NbOx memristor responds to signal in three distinct patterns. For the low-frequency input, the memristor fires spike series and locks the phase near π2 during the positive period of sinusoidal input, and it encodes the input features by the spike number per period. For the middle-frequency input, the memristor fires one spike per period at a definite phase. The output has the same frequency as the input. The locked phase is proportional to the input frequency. For the high-frequency input, the memristor transforms high frequency to low frequency signal and locks at a definite phase higher than 2π. We combined the microstructural analysis and chaos dynamics to know that Ag doping will lower the activation energy, enhance the responding rate, and enhance thermal conductivity, which extends the locked frequency to 1.7 times the value of the undoped NbOx memristor. We also obtained the locked frequency of even 40 MHz after modulating the elementary circuit configuration according to the material modification and chaos model. Our study proposes to handle a signal with high efficiency resembling auditory sense and inspires a novel artificial intelligent computation prototype.

Microenvironment modulation of interpenetrating-type hierarchical porous foam carbon by mild-homogeneous activation for H2 storage and CO2 capture under ambient pressure.

Currently, carbon-based porous materials for hydrogen (H2) storage and carbon dioxide (CO2) capture are mostly applied at higher pressures (30-300 bar). However, applications for H2 storage and CO2 capture under ambient pressure conditions are significant for the development of portable, household, and miniaturized H2 energy technologies. This demands a higher standard for the interface microenvironment of adsorbents. Derived from polyurethane foams (PUFs) solid waste, the hierarchical porous foam carbon with interpenetrating-type pore structures exhibits high specific surface area (SBET = 1753 m2/g), abundant oxygen and nitrogen functional groups, and a hierarchical nanopore structure (VUltra = 0.232 cm3/g, VMicro = 0.628 cm3/g and VMeso = 0.186 cm3/g) through the mild-homogeneous sonication-assisted activation process. Under the limited adsorption of pore interface microenvironment composed by hierarchical nanopore structure and dipole-induced interaction (H(Ⅱ)-H(Ⅰ)···N/O and O(Ⅱ) = C(Ⅰ) = O(Ⅱ)···N/O), it exhibits an excellent H2 storage density (2.92 wt% at 77 K, 1 bar) and CO2 capture capacity (5.28 mmol/g at 298 K, 1 bar). This research approach can serve as a reference for the dual-functional design of porous foam carbon, and promote the development of adsorption materials for CO2 capture and energy gas storage under ambient conditions.

FESNet: Frequency-Enhanced Saliency Detection Network for Grain Pest Segmentation.

As insect infestation is the leading factor accounting for nutritive and economic losses in stored grains, it is important to detect the presence and number of insects for the sake of taking proper control measures. Inspired by the human visual attention mechanism, we propose a U-net-like frequency-enhanced saliency (FESNet) detection model, resulting in the pixelwise segmentation of grain pests. The frequency clues, as well as the spatial information, are leveraged to enhance the detection performance of small insects from the cluttered grain background. Firstly, we collect a dedicated dataset, GrainPest, with pixel-level annotation after analyzing the image attributes of the existing salient object detection datasets. Secondly, we design a FESNet with the discrete wavelet transformation (DWT) and the discrete cosine transformation (DCT), both involved in the traditional convolution layers. As current salient object detection models will reduce the spatial information with pooling operations in the sequence of encoding stages, a special branch of the discrete wavelet transformation (DWT) is connected to the higher stages to capture accurate spatial information for saliency detection. Then, we introduce the discrete cosine transform (DCT) into the backbone bottlenecks to enhance the channel attention with low-frequency information. Moreover, we also propose a new receptive field block (NRFB) to enlarge the receptive fields by aggregating three atrous convolution features. Finally, in the phase of decoding, we use the high-frequency information and aggregated features together to restore the saliency map. Extensive experiments and ablation studies on our dataset, GrainPest, and open dataset, Salient Objects in Clutter (SOC), demonstrate that the proposed model performs favorably against the state-of-the-art model.

Optimization of the Winding Layer Structure of High-Pressure Composite Overwrapped Pressure Vessels.

The large thickness COPV is designed by netting theory and the finite element simulation method, but the actual performance is low and the cylinder performance still cannot be improved after increasing the thickness of the composite winding layer. This paper analyzes the reasons for this and puts forward a feasible solution: without changing the thickness of the winding layer, the performance of COPV can be effectively increased by increasing the proportion of annular winding fiber. This method has been verified by tests and is supported by theory.

Effects of Hygrothermal and Salt Mist Ageing on the Properties of Epoxy Resins and Their Composites.

Epoxy and epoxide composites have a wide range of outdoor applications wherein they are affected by ageing. In this study, epoxy casting plates and epoxy-based composite rods for use in overhead conductors were prepared. A concurrent investigation concerning the ageing of epoxy resins and their carbon fibre composites was carried out via artificially accelerated experiments under hygrothermal and salt mist conditions. The moisture penetration along the depth, water absorption, appearance, hardness, density of the epoxy resins, and variation patterns of the impact strength and tensile strength of the epoxy-based composites were investigated. The ageing mechanisms were explored using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Both ageing modes had essentially similar influences on the properties of the resins and their composites; moreover, they did not significantly affect the chemical structure and microstructure of the epoxy resin, with the physical adsorption of water primarily observed during the ageing process. The moisture absorption behaviour of the epoxy obeyed Fick's law. Although the water penetration rate in the salt mist ageing mode was slightly higher than that in the hygrothermal ageing mode during the early ageing stage, it was essentially the same during the later stage. The final moisture absorption rate at saturation was approximately 1.1% under both modes. The flexural strengths and impact strengths of the composites in both ageing modes followed a similar trend. They decreased gradually with the ageing time and then stabilized at almost the same value. The flexural strength was reduced from 803 MPa to 760 MPa and the impact strength from 383 J/m2 to 310 J/m2, indicating a decrease of approximately 5.4% and 19%, respectively. The absorbed water during the ageing process caused micro-cracks at the interface between the fibres and resin, weakening the interfacial strength and reducing the mechanical properties of the composites.

Comparative Genomics Reveals Three Genetic Groups of the Whitefly Obligate Endosymbiont Candidatus Portiera aleyrodidarum.

Maternally inherited obligate endosymbionts codiverge with their invertebrate hosts and reflect their host's evolutionary history. Whiteflies (Hemiptera: Aleyrodidae) harbor one obligate endosymbiont, Candidatus Portiera aleyrodidarum (hereafter Portiera). Portiera was anciently acquired by whitefly and has been coevolving with its host ever since. Uncovering the divergence of endosymbionts provides a fundamental basis for inspecting the coevolutionary processes between the bacteria and their hosts. To illustrate the divergence of Portiera lineages across different whitefly species, we sequenced the Portiera genome from Aleyrodes shizuokensis and conducted a comparative analysis on the basic features and gene evolution with bacterial genomes from five whitefly genera, namely Aleurodicus, Aleyrodes, Bemisia, Pealius, and Trialeurodes. The results indicated that Portiera from Bemisia possessed significantly larger genomes, fewer coding sequences (CDSs), and a lower coding density. Their gene arrangement differed notably from those of other genera. The phylogeny of the nine Portiera lineages resembled that of their hosts. Moreover, the lineages were classified into three distinct genetic groups based on the genetic distance, one from Aleurodicus (Aleurodicinae), one from Bemisia (Aleyrodinae), and another from Aleyrodes, Pealius, and Trialeurrodes (Aleyrodinae). Synonymous and nonsynonymous rate analyses, parity rule 2 plot analyses, neutrality plot analyses, and effective number of codons analyses supported the distinction of the three genetic groups. Our results indicated that Portiera from distant hosts exhibit distinct genomic contents, implying codivergence between hosts and their endosymbionts. This work will enhance our understanding of coevolution between hosts and their endosymbionts.

Slit dual-frequency ultrasound-assisted pulping of Lycium barbarum fresh fruit to improve the dissolution of polysaccharides and in situ real-time monitoring.

In this study, the slit dual-frequency ultrasound-assisted pulping of fresh Lycium barbarum fruit was optimized to improve the dissolution of polysaccharides. The microscopic mechanism of polysaccharide dissolution was explored through establishing polysaccharides dissolution kinetics model and visualizing the multi-physical fields during ultrasonic process, and an in situ real-time monitoring model was established by the relationship between the chemical value and spectral information collected by near-infrared spectroscopy. The results showed that, under optimal conditions, treatment with ultrasound (28-33 kHz, 250 W, 30 min) not only significantly promoted the dissolution rate of polysaccharides in Lycium barbarum pulp (LBPPs, increased by 43.64 %, p < 0.01), reduced its molecular weight, but also improved the arabinose molar ratio, the uniformity of polysaccharide particles, and the antioxidant activity of LBPPs. Correlation analysis indicated that ultrasonic treatment is closely related to LBPPs content, particle size and scavenging capacity against superoxide anion radicals (ptotal sugar content < 0.01, pparticle size < 0.05 and psuperoxide anion scavenging < 0.05). Moreover, the in situ real-time monitoring model for the pulping process could quantitatively predict LBPPs dissolution rate and its superoxide anion radical scavenging capacity with good calibration and prediction performance (Rc = 0.9841, RMSECV = 0.0873, Rp = 0.9772, RMSEP = 0.0530; Rc = 0.9874, RMSECV = 0.1246, Rp = 0.9868, RMSEP = 0.0665). These results indicated that slit dual-frequency ultrasound has great potential in improving the quality of Lycium barbarum pulp, which may provide theoretical support for the industrial development of intelligent systems for polysaccharides preparation.