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ABSTRACT: Mycoplasma synoviae (MS) is an essential pathogenic mycoplasma in poultry worldwide, posing a serious threat to the poultry industry's health. Timely detection is imperative for early diagnosis, prevention, and control of MS infection. Current laboratory methods for MS detection are generally complicated, time-consuming, and require sophisticated equipment. Therefore, a simple and rapid method is urgently needed. This study developed a novel real-time fluorescence-based recombinase-aided amplification (RF-RAA) technique for detecting MS nucleic acids, enabling target gene amplification within 20 min at 39°C. The RF-RAA outcomes are interpretable in 2 modalities: real-time fluorescence monitoring employing a temperature-controlled fluorescence detector or direct visual inspection facilitated by a portable blue light transilluminator. This method exhibits robust specificity, demonstrating no cross-reactivity with various common poultry pathogens, and achieves high sensitivity, detecting as low as 10 copies/μL for the standard plasmid. Seventy-one clinical samples of chicken throat swabs were detected by RF-RAA and real-time fluorescence quantitative polymerase chain reaction (qPCR) methods. The diagnostic coincidence rates of qPCR with RF-RAA (fluorescence monitoring) and RF-RAA (visual observation) were determined to be 100% and 97.2% (69/71), respectively. In conclusion, the RF-RAA method developed in this study provides a rapid and visually observable approach for MS detection, offering a novel technique to diagnosing MS infection, especially in resource-limited settings.

Wireless charging has become increasingly popular in low and medium-power applications, such as motor-driven carriers, unmanned aerial vehicles, electric bicycles, and inspection robots. Nevertheless, pad misalignment can significantly affect the system performance, leading to higher losses and a reduction in the power output. Particularly in the all directions of anti-misalignment strategies, a greater number of inverters and compensations are necessitated, leading to increased system dimensions and heightened complexity. This article proposes a new hybrid coupler that only uses a bipolar pad as the secondary pad and a solenoid (S coil) with an added quadrature coil (Q coil) as the primary pad. We develop and test a 50W prototype in the laboratory. The size of the coupler is 355 mm $ \times 290$ mm. The experimental and simulation results demonstrate that when the distance between the transmitter and receiver is 60 mm, the transmission efficiency remains within a range of 72% to 90% for all directions of anti-misalignment, while the output voltage exhibits fluctuations within a margin of 10%. The results indicate that the coupler has a great potential for use in low and medium power applications, and can even be used in high-power equipment.

The symbiotic relationship between corals and their associated microorganisms is crucial for the health of coral reef eco-environmental systems. Recently, there has been a growing interest in unraveling how the manipulation of symbiont nutrient cycling affects the stress tolerance in the holobiont of coral reefs. However, most studies have primarily focused on coral–Symbiodiniaceae–bacterial interactions as a whole, neglecting the interactions between Symbiodiniaceae and bacteria, which remain largely unexplored. In this study, we proposed a hypothesis that there exists an inner symbiotic loop of Symbiodiniaceae and bacteria within the coral symbiotic loop. We conducted experiments to demonstrate how metabolic exchanges between Symbiodiniaceae and bacteria facilitate the nutritional supply necessary for cellular growth. It was seen that the beneficial bacterium, Ruegeria sp., supplied a nitrogen source to the Symbiodiniaceae strain Durusdinium sp., allowing this dinoflagellate to thrive in a nitrogen-free medium. The Ruegeria sp.–Durusdinium sp. interaction was confirmed through 15N-stable isotope probing–single cell Raman spectroscopy, in which 15N infiltrated into the bacterial cells for intracellular metabolism, and eventually the labeled nitrogen source was traced within the macromolecules of Symbiodiniaceae cells. The investigation into Symbiodiniaceae loop interactions validates our hypothesis and contributes to a comprehensive understanding of the intricate coral holobiont. These findings have the potential to enhance the health of coral reefs in the face of global climate change.

Gentiana zollingeri Fawcett (Gentianaceae) belongs to the most species-rich section, Chondrophyllae, in the Gentianaceae, but its phylogenetic relationship with other members of this section is unclear. To confirm its phylogenetic position, the complete plastid genome of G. zollingeri was determined and analyzed. The plastome was sequenced using the Illumina HiSeq platform, assembled with GetOrganelle, and annotated with GeSeq. The genome is circular with a length of 130,762 bp. It contains a large single-copy (LSC) region of 74,236 bp, a small single-copy (SSC) region of 10,598 bp, and two inverted repeat (IR) regions of 22,964 bp each. The plastome of G. zollingeri shows considerable structural differences from those of other Gentiana plastomes, such as the absence of the ndh gene. In phylogenetic analyses, section Chondrophyllae, including G. zollingeri and its sisters, formed a long branch sistering with section Cruciata. The plastome sequence described here represents an important contribution to phylogenetic and evolutionary studies on Gentiana.

Abstract Background Mountains of the world host a significant portion of all terrestrial biodiversity, and the region of the Qinghai-Tibet Plateau (QTP) stands as one of the most remarkable mountain regions on Earth. Because many explosive radiations occurred there, the QTP is a natural laboratory which is ideal to investigate patterns and processes linked to speciation and diversification. Indeed, understanding how closely related and sympatric species diverged is vital to explore drivers fostering speciation, a topic only rarely investigated in the QTP. By combining genomic and environmental data, we explored the speciation process among three closely related and sympatric species, Gentiana hexaphylla, G. lawrencei and G. veitchiorum in the QTP region. Results Combining genome sizes and cytological data, our results showed that G. hexaphylla and G. veitchiorum are diploid, whereas G. lawrencei is tetraploid. Genetic clustering and phylogenetic reconstruction based on genomic SNPs indicated a clear divergence among the three species. Bayesian clustering, migrant, and D-statistic analyses all showed an obvious signature of hybridization among the three species, in particular between G. lawrencei and both G. hexaphylla and G. veitchiorum in almost all populations. Environmental variables related to precipitation and particularly temperature showed significant differences among the three gentians, and in fact a redundancy analysis confirmed that temperature and precipitation were the major climatic factors explaining the genetic differentiation among the three species. Conclusion Our study suggested that ancient hybridization, polyploidization, geological isolation and the evolution of different climatic preferences were all likely to be involved in the divergence of the three Gentiana species, as may be the case for many other taxa in the QTP region.

Chlorella has been applied in the production of selenium (Se) enriched organic biomass. However, limited information exists regarding heterotrophic selenium tolerance and its incorporation into Chlorella. This study aimed to investigate the potential of using Chlorella vulgaris K-01 for selenium biotransformation. To assess the dose-response effect of Se stress on the strain, time-series growth curves were recorded, growth productivity parameters were calculated, and Gaussian process (GP) regression analysis was performed. The strain’s carbon and energy metabolism were evaluated by measuring residual glucose in the medium. Characterization of different forms of intracellular Se and residual Se in the medium was conducted using inductively coupled plasma-mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometer (ICP-OES). The EC50 value for the strain in response to Se stress was 38.08 mg/L. The maximum biomass productivity was 0.26 g/L/d. GP regression analysis revealed that low-level Se treatment could increase the biomass accumulation and the carrying capacity of Chlorella vulgaris K-01 in a heterotrophic culture. The maximum organic Se in biomass was 154.00 μg/g DW. These findings lay the groundwork for understanding heterotrophic microalgal production of Se-containing nutraceuticals, offering valuable insights into Se tolerance, growth dynamics, and metabolic responses in Chlorella vulgaris K-01.

The growing use of photosynthetic microorganisms for food and food-related applications is driving related biotechnology research forward. Increasing consumer acceptance, high sustainability, demand of eco-friendly sources for food, and considerable global economic concern are among the main factors to enhance the focus on the novel foods. In the cases of not toxic strains, photosynthetic microorganisms not only provide a source of sustainable nutrients but are also potentially healthy. Several published studies showed that microalgae are sources of accessible protein and fatty acids. More than 400 manuscripts were published per year in the last 4 years. Furthermore, industrial approaches utilizing these microorganisms are resulting in new jobs and services. This is in line with the global strategy for bioeconomy that aims to support sustainable development of bio-based sectors. Despite the recognized potential of the microalgal biomass value chain, significant knowledge gaps still exist especially regarding their optimized production and utilization. This review highlights the potential of microalgae and cyanobacteria for food and food-related applications as well as their market size. The chosen topics also include advanced production as mixed microbial communities, production of high-value biomolecules, photoproduction of terpenoid flavoring compounds, their utilization for sustainable agriculture, application as source of nutrients in space, and a comparison with heterotrophic microorganisms like yeast to better evaluate their advantages over existing nutrient sources. This comprehensive assessment should stimulate further interest in this highly relevant research topic.

Abstract Optically active nanostructures consisting of organic compounds and metallic support have shown great promise in phototherapy due to their increased light absorption capacity and high energy conversion. Herein, we conjugated chlorophyll (Chl) to vanadium carbide (V2C) nanosheets for combined photodynamic/photothermal therapy (PDT/PTT), which reserves the advantages of each modality while minimizing the side effects to achieve an improved therapeutic effect. In this system, the Chl from Leptolyngbya JSC-1 extracts acted as an efficient light-harvest antenna in a wide NIR range and photosensitizers (PSs) for oxygen self-generation hypoxia-relief PDT. The available large surface of two-dimensional (2D) V2C showed high Chl loading efficiency, and the interaction between organic Chl and metallic V2C led to energy conversion efficiency high to 78%. Thus, the Chl/ V2C nanostructure showed advanced performance in vitro cell line killing and completely ablated tumors in vivo with 100% survival rate under a single NIR irradiation. Our results suggest that the artificial optical Chl/V2C nanostructure will benefit photocatalytic tumor eradication clinic application. Graphical Abstract

Marine microalgae are widespread in the ocean and play a crucial role in the ecosystem. Automatic identification and location of marine microalgae in microscopy images would help establish marine ecological environment monitoring and water quality evaluation system. We proposed a new dataset for the detection of marine microalgae and a range of detection methods, the dataset including images of different genus of algae and the same genus in different states. We set the number of unbalanced classes in the data set and added images of mixed water samples in the test set to simulate the actual situation in the field. Then we trained, validated and tested the, TOOD, YOLOv5, YOLOv8 and variants of RCNN algorithms on this dataset. The results showed both one-stage and two-stage object detection models can achieve high mean average precision, which proves the ability of computer vision in multi-object detection of microalgae, and provides basic data and models for real-time detection of microalgal cells.

Activated microglia are divided into pro-inflammatory and anti-inflammatory functional states. In anti-inflammatory state, activated microglia contribute to phagocytosis, neural repair and anti-inflammation. Nrf2 as a major endogenous regulator in hematoma clearance after intracerebral hemorrhage (ICH) has received much attention. This study aims to investigate the mechanism underlying Nrf2-mediated regulation of microglial phenotype and phagocytosis in hematoma clearance after ICH. In vitro experiments, BV-2 cells were assigned to normal group and administration group (Nrf2-siRNA, Nrf2 agonists Monascin and Xuezhikang). In vivo experiments, mice were divided into 5 groups: sham, ICH + vehicle, ICH + Nrf2−/−, ICH + Monascin and ICH + Xuezhikang. In vitro and in vivo, 72 h after administration of Monascin and Xuezhikang, the expression of Nrf2, inflammatory-associated factors such as Trem1, TNF-α and CD80, anti-inflammatory, neural repair and phagocytic associated factors such as Trem2, CD206 and BDNF were analyzed by the Western blot method. In vitro, fluorescent latex beads or erythrocytes were uptaken by BV-2 cells in order to study microglial phagocytic ability. In vivo, hemoglobin levels reflect the hematoma volume. In this study, Nrf2 agonists (Monascin and Xuezhikang) upregulated the expression of Trem2, CD206 and BDNF while decreased the expression of Trem1, TNF-α and CD80 both in vivo and in vitro. At the same time, after Monascin and Xuezhikang treatment, the phagocytic capacity of microglia increased in vitro, neurological deficits improved and hematoma volume lessened in vivo. These results were reversed in the Nrf2-siRNA or the Nrf2−/− mice. All these results indicated that Nrf2 enhanced hematoma clearance and neural repair, improved neurological outcomes through enhancing microglial phagocytosis and alleviating neuroinflammation.

Abstract The purpose of this research was to determine the efficacy of iron oxide nanoparticles (Fe3O4-NPs) using microalgal products as a plant growth stimulant and antifungal agent. The work was conducted with the phyco-synthesis and characterization of Fe3O4-NPs using 0.1 M ferric/ferrous chloride solution (2:1 ratio; 65 °C) with aqueous extract of the green microalga Chlorella K01. Protein, carbohydrate and polyphenol contents of Chlorella K01 extract were measured. The synthesized microalgal Fe3O4-NPs made a significant contribution to the germination and vigor index of rice, maize, mustard, green grams, and watermelons. Fe3O4-NPs also exhibited antifungal activity against Fusarium oxysporum, Fusarium tricinctum, Fusarium maniliforme, Rhizoctonia solani, and Phythium sp. Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) scanning electron microscopy (SEM), transmission electron microscopy (TEM), particle size analysers (PSA), and zeta potential (ZP) measurements were used to characterize these green fabricated magnetite NPs. FTIR analysis showed that the synergy of microalgal proteins, carbohydrtates and polyphenols is responsible for the biofabrication of iron nanoparticles. A spheroid dispersion of biosynthesized Fe3O4-NPs with an average diameter of 76.5 nm was produced in the synthetic process.

As a primary goal, cadmium (Cd) is a heavy metal pollutant that is readily adsorbed and retained in rice, and it becomes a serious threat to food safety and human health. Fungi have attracted interest for their ability to remove heavy metals from the environment, although the underlying mechanisms of how fungi defend against Cd toxicity are still unclear. In this study, a Cd-resistant fungus Trametes pubescens (T. pubescens) was investigated. Pot experiments of rice seedlings colonized with T. pubescens showed that their coculture could significantly enhance rice seedling growth and reduce Cd accumulation in rice tissues. Furthermore, integrated transcriptomic and metabolomic analyses were used to explore how T. pubescens would reprogram its metabolic network against reactive oxygen species (ROS) caused by Cd toxicity. Based on multi-omic data mining results, we postulated that under Cd stress, T. pubescens was able to upregulate both the mitogen-activated protein kinase (MAPK) and phosphatidylinositol signaling pathways, which enhanced the nitrogen flow from amino acids metabolism through glutaminolysis to α-ketoglutarate (α-KG), one of the entering points of tricarboxylic acid (TCA) cycle within mitochondria; it thus increased the production of energy equivalents, adenosine triphosphate (ATP) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) for T. pubescens to resist oxidative damage. This study can enable a better understanding of the metabolic rewiring of T. pubescens under Cd stress, and it can also provide a promising potential to prevent the rice paddy fields from Cd toxicity and enhance food safety.

The microbiota in gastrointestinal tracts is recognized to play a pivotal role in the health of their hosts. Music and noise are prevalent environmental factors in human society and animal production and are reported to impact their welfare and physiological conditions; however, the information on the relationship between the microbiota, physiological status, and sound is limited. This study investigated the impact of music and white noise exposure in mice through 16s rRNA gene sequencing, enzyme assay, and qPCR. The results demonstrate that white noise induced oxidative stress in animals by decreasing serum SOD and GSH-PX activity while increasing LDH activity and MDA levels (p < 0.05). Conversely, no oxidative stress was observed in the music treatment group. The relative gene expression of IFN-γ and IL-1β decreased in the white noise group compared to the music and control groups. The 16s rRNA gene amplicon sequencing revealed that Bacteroidetes, Firmicutes, Verrucomicrobia, and Proteobacteria were dominant among all the groups. Furthermore, the proportion of Firmicutes increased in the music treatment group but decreased in the white noise treatment group compared to the control group. In conclusion, white noise has detrimental impacts on the gut microbiota, antioxidant activity, and immunity of mice, while music is potentially beneficial.

The composition of these vaginal microbiome has a significant impact on women's health. However, few studies have characterized the vaginal microbiome of healthy Chinese women using metagenomic sequencing. Here, we carried out a comparative metagenomic analysis to survey taxonomic, functional levels, and microbial communities' genome content in healthy women's vaginal microbiome. Overall, we observed a total of 111 species, including all dominant vaginal Lactobacillus species, such as L. iners, L. crispatus, L. gasseri, and L. jensenii. Unlike microbial taxa, several pathways were ubiquitous and prevalent across individuals, including adenosine ribonucleotides de novo biosynthesis and pyruvate fermentation to acetate and lactate II. Notably, our diversity analysis confirmed a significant difference in healthy women from different ethnic groups. Moreover, we binned vaginal assemblies into 62 high-quality genomes, including 9 L. iners, 7 A. vaginae, 5 L. jensenii, and 5 L. crispatus. We identified the pan and core genomes of L. iners and A. vaginae and revealed the genetic diversity. Primary differences between strains were the hypothetical genes and mobile element-like genes. Our results provide a framework for understanding the implications of the female reproductive tract's composition and functional potential and highlight the importance of genome-resolved metagenomic analysis to further understand the human vaginal microbiome.

With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT–PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients’ prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT–PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC.

Abstract Background Lignin in sugarcane bagasse (SB) hinders its utilization by microorganism, therefore, pretreatment methods are employed to make fermentable components accessible to the microbes. Multivariate analysis of different chemical pretreatment methods can aid to select the most appropriate strategy to valorize a particular biomass. Results Amongst methods tested, the pretreatment by using sodium hydroxide in combination with methyltrioctylammonium chloride, an ionic liquid, (NaOH+IL) was the most significant for xylanase production by Bacillus aestuarii UE25. Investigation of optimal levels of five significant variables by adopting Box-Behnken design (BBD) predicted 20 IU mL− 1 of xylanase and experimentally, a titer of 17.77 IU mL− 1 was obtained which indicated the validity of the model. The production kinetics showed that volumetric productivity of xylanase was much higher after 24 h (833.33 IU L− 1 h− 1) than after 48 h (567.08 IU L− 1 h− 1). The extracted xylan from SB induced more xylanase in the fermentation medium than pretreated SB or commercially purified xylan. Nuclear Magnetic Resonance, Fourier transform infrared spectroscopy and scanning electron microscopy of SB indicated removal of lignin and changes in the structure of SB after NaOH+IL pretreatment and fermentation. Conclusion Combined pretreatment of SB with alkali and methyltrioctylammonium chloride appeared better than other chemical methods for bacterial xylanase production and for the extraction of xylan form SB.

Ferroptosis is a newly defined mode of programmed oxidative cell death. Knowledge of ferroptosis-related long noncoding (lnc) RNA in the tumor immune microenvironment of colon cancer is lacking. We systematically analyzed the correlations between ferroptosis-related lncRNAs and the tumor microenvironment, immune cell infiltration, and patient prognosis for 379 colon cancer samples in the Cancer Genome Atlas (TCGA). Using consensus clustering, we divided the 379 colon cancer patients into two subgroups (clusters 1 and 2) based on the differentially expressed ferroptosis-related lncRNAs. Cluster 1 was preferentially associated with longer overall survival, upregulated immune checkpoint inhibitor expressions, higher immunoscores, higher stromal scores, higher estimated scores, and distinct immune cell infiltration. Cancer- and metabolism-related pathways were enriched by gene set enrichment analyses. We constructed a prognostic signature of 15 ferroptosis-related lncRNAs (ZEB1-AS1, LINC01011, AC005261.3, LINC01063, LINC02381, ELFN1-AS1, AC009283.1, LINC02361, AC105219.1, AC002310.1, AL590483.1, MIR4435-2HG, NKILA, AC021054.1, and AL450326.1) and divided the patients into the high- and low-risk-score groups. The signature was validated using TCGA training and testing cohorts. The risk signature was an independent prognostic factor for predicting survival and excellently predicted the prognoses of patients with colon cancer. Moreover, the risk signature was related to immune characteristics. Chemosensitivity analyses showed that low-risk-score patients were more sensitive to sorafenib. In summary, our work revealed the important role of ferroptosis-related lncRNAs in the tumor microenvironment and immune cell infiltration and may help determine personalized prognoses and treatment for patients with colon cancer.

The study of human gut microbiota has attracted increasing interest in the fields of life science and healthcare. However, the complicated and interconnected associations between gut microbiota and human diseases are still difficult to determine in a predictive fashion. Artificial intelligence such as machine learning (ML) and deep learning can assist in processing and interpreting biological datasets. In this study, we aggregated data from different studies based on the species composition and relative abundance of gut microbiota in children with autism spectrum disorder (ASD) and typically developed (TD) individuals and analyzed the commonalities and differences of ASD-associated microbiota across cohorts. We established a predictive model using an ML algorithm to explore the diagnostic value of the gut microbiome for the children with ASD and identify potential biomarkers for ASD diagnosis. The results indicated that the Shenzhen cohort achieved a higher area under the receiver operating characteristic curve (AUROC) value of 0.984 with 97% accuracy, while the Moscow cohort achieved an AUROC value of 0.81 with 67% accuracy. For the combination of the two cohorts, the average prediction results had an AUROC of 0.86 and 80% accuracy. The results of our cross-cohort analysis suggested that a variety of influencing factors, such as population characteristics, geographical region, and dietary habits, should be taken into consideration in microbial transplantation or dietary therapy. Collectively, our prediction strategy based on gut microbiota can serve as an enhanced strategy for the clinical diagnosis of ASD and assist in providing a more complete method to assess the risk of the disorder.

Roll-bending technology has a high degree of flexibility and does not require special molds. However, based on the existing plastic mechanics theory and finite element simulation, it is difficult to accurately analyze the complex spatial relationship of profile roll forming. Therefore, a fixed-curvature prediction model is constructed based on XGBoost (extreme gradient boosting), and the coupling effect of the process parameters and material performance parameters on the roll-forming process is explored. Combined with a Bayesian optimization algorithm, the hyperparameters of the fixed-curvature prediction model are optimized. In addition, based on the prediction result of the fixed curvature, a variable-curvature prediction model is established using the conditional random field (CRF). To further improve the prediction accuracy, an error compensation network is added after the result of the CRF in order to map the discrete sequence to the continuous sequence. The experimental results show that the mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) predicted by the models above are much smaller than other methods, which verifies the superiority of the prediction models.

This study involves evaluation of two native cyanobacterial strains Euryhalinema and Desertifilum isolated from a mangrove pond in Haikou (China) for their possible phycocyanin (C-PC) production. Maximal growth rate with highest chlorophyll and C-PC accumulation were observed at 28°C and 60 μmol photons m−2 s−1 photon flux density for Euryhalinema sp., while for Desertifilum sp. at 32°C and 80 μmol photons m−2 s−1. Nitrogen and iron concentration trails revealed that double strength concentration of sodium nitrate and ferric ammonium citrate in original BG11 media increased growth rate and accumulation of C-PC for both strains. Three different C-PC extraction methods were tested. The combined extraction protocol of freeze–thaw and ultrasonication markedly increased the C-PC extraction efficiency and attained the food grade purity (A620/A280 ratio >0.7), whereas a higher C-PC yield was found with Na-phosphate buffer. Furthermore, the clarified crude extract was used to purify C-PC by fractional ammonium sulfate [(NH₄)₂SO₄] precipitation, Sephadex G-25 gel filtration chromatography, and DEAE-sephadex ion exchange chromatography and attained analytical grade purity (A620/A280 ratio >3.9). Taken together, both strains showed their potential to be domesticated for valuable phycocyanin production.

Biofuel derived from halophytic biomass is getting attention owing to the concerns of energy versus food crisis. The disadvantages associated with edible bioenergy resources necessitate the need to explore new feedstocks for sustainable biofuel production. In this study, biomass from locally available abundant halophytes (Panicum antidotale, Phragmites karka, Halopyrum mucronatum, and Desmostachya bipinnata) was screened for saccharification by an enzyme cocktail composed of cellulase, xylanase, and pectinase from Brevibacillus borstelensis UE10 and UE27, Bacillus aestuarii UE25, Aneurinibacillus thermoaerophilus UE1, and Bacillus vallismortis MH 1. Two types of pretreatment, i.e., with dilute acid and freeze-thaw, were independently applied to the halophytic biomass. Saccharification of acid-pretreated P. karka biomass yielded maximum reducing sugars (9 mg g–1) as compared to other plants. Thus, the factors (temperature, pH, substrate concentration, and enzyme units) affecting its saccharification were optimized using central composite design. This statistical model predicted 49.8 mg g–1 of reducing sugars that was comparable to the experimental value (40 mg g–1). Scanning electron microscopy and Fourier-transform infrared spectroscopy showed significant structural changes after pretreatment and saccharification. Therefore, halophytes growing in saline, arid, and semi-arid regions can be promising alternative sources for bioenergy production.

Background: Hematoma is the chief culprit in brain injury following intracranial cerebral hemorrhage (ICH). Noninvasive hematoma clearance could be an option to prevent and alleviate early brain injury after ICH. Peroxisome proliferator-activated receptor γ (PPAR-γ) and nuclear factor-erythroid 2 related factor-2 (Nrf2) facilitate removal of hematoma in ICH. Monascin acts as the natural Nrf2 activator with PPAR-γ agonist, and the long-term effects of monascin following ICH have not been elucidated. Methods: ICH in rats was induced by stereotactic, intrastriatal injection of type IV collagenase. Monascin was administered twice daily by gastric perfusion for 14 days after ICH induction. Long-term neurological scores (T maze, Garcia scales, rotor rod test, and Morris water maze), hematoma volume, as well as iron overload around hematoma and brain atrophy were evaluated at 7, 14, and 28 days after ICH. Results: The results showed that monascin improved long-term neurological deficits, spatial memory performance, learning ability, and brain shrinkage after ICH. Monascin also reduced hematoma volume at 7 days and iron content at 7 and 14 days after ICH. Conclusion: PPAR γ and Nrf2 play a crucial role in hematoma clearance after ICH in rat. As a dual agonist of PPAR γ and Nrf2, monascin improved long-term outcomes by facilitating hematoma clearance, and by attenuating iron overload and brain atrophy after experimental ICH.

The scientific consensus is now on developing a biocontrol agent that can cause cellular metabolic reprogramming against agricultural pathogens. Biosynthesis of silver nanoparticles was performed by using phytopathogenic fungi (Alternaria sp.) isolated from banana cultivated soil. Alternaria sp. can grow very fast and produce high enough bioactive compounds. This study aims to biosynthesize silver nanoparticles (AgNPs) using fungal Alternaria sp.’s metabolites as a safe antifungal agent against plant pathogenic fungi (Fusarium spp. and Alternaria sp.). To visualize the formation of AgNPs, analytical instruments were used, such as ultraviolet-visible (UV-Vis) spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, scanning transmission electron microscopy (STEM), energy dispersive X-ray (EDX), and elemental mapping. The UV-visible spectra showed a peak at 435 nm. Analysis of scanning transmission electron microscopy (STEM) micrographs evidenced that the size of synthesized silver nanoparticles ranged between 3 and 10 nm. The resulting AgNPs showed distinct antifungal activity against selected plant pathogenic fungi. Synthesized AgNPs have demonstrated remarkable potential for the use of antifungal compounds to combat plant diseases.

The data presented in this article are related to the research article entitled “Immunomodulatory and Enhanced Antitumor Activity of a Modified Thymosin α1 in Melanoma and Lung Cancer” (Wang et al., 2018). Tα1 has been evaluated as effective in cancer treatment. In order to make it capable to target tumor, a peptide iRGD was introduced to Tα1. The anti-tumor activity was accessed by constructing in vivo melanoma and human non-small-cell lung cancer models treated with Tα1-iRGD to measure the tumor volume over time and tumor weight at the last day. The concentration of IFN-γ and IL-2 in C57BL/6 mice peripheral blood was determined by ELISA. And the immunomodulatory ability of Tα1-iRGD was evaluated in vivo by thymus index and spleen index. Those functions this paper was aimed at may have relationship with its secondary structure, so the circular dichroism spectra of Tα1, iRGD and Tα1-iRGD was performed.

Abstract It has long been speculated that cues on the human face exist that allow observers to make reliable judgments of others’ personality traits. However, direct evidence of association between facial shapes and personality is missing from the current literature. This study assessed the personality attributes of 834 Han Chinese volunteers (405 males and 429 females), utilising the five-factor personality model (‘Big Five’), and collected their neutral 3D facial images. Dense anatomical correspondence was established across the 3D facial images in order to allow high-dimensional quantitative analyses of the facial phenotypes. In this paper, we developed a Partial Least Squares (PLS) -based method. We used composite partial least squares component (CPSLC) to test association between the self-tested personality scores and the dense 3D facial image data, then used principal component analysis (PCA) for further validation. Among the five personality factors, agreeableness and conscientiousness in males and extraversion in females were significantly associated with specific facial patterns. The personality-related facial patterns were extracted and their effects were extrapolated on simulated 3D facial models.

The complete plastid genome of Gentiana trichotoma was determined and analyzed in this work. It had a circular-mapping molecular with the length of 144,759 bp, has similar gene composition with G. section Cruciata but contains 10 more genes than G. section Kudoa. Phylogenetic analysis showed that G. trichotoma clustered together with section Kudoa rather than section Cruciata. The plastome provided in this work would be useful for elucidation of Gentiana evolution.

Improving tracking quality and extending network lifespan are two main objects for target tracking, which are usually contradictory due to limited energy of sensor nodes in wireless sensor networks. This article incorporates this contradiction into a problem of multi-objective optimization in tracking networks where multiple sensor nodes are scheduled for collaborative target tracking by adopting the unscented Kalman filter algorithm. We propose an effective scheme to extend the lifespan of wireless sensor networks while guaranteeing preset tracking quality. More specifically, with regard to practical circumstances, we perform analysis on the target detection probability, as well as residual energy of sensor nodes, when selecting a suitable set of candidate sensor nodes. Then, we put forward a novel energy-balanced sensor nodes scheduling algorithm, Greedy Balance Replace Heuristic Algorithm, to select a near-optimal task sensor set from the candidate sensor node set to balance tracking quality and network lifetime. In addition, we also design an efficient multi-sensor node collaborative method to track a single target and to timely report its state to the remote end. From simulation results, it is demonstrated that the proposed node scheduling scheme can not only maintain the preset tracking accuracy but also extend network lifespan with a low computation complexity.

The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.

Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes.

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

Premise of the study: A set of microsatellite markers were developed to characterize the level of genetic diversity and gene flow in two plant species endemic to the Qinghai–Tibet Plateau, Spiraea alpina and S. mongolica. Methods and Results: Using the Fast Isolation by AFLP of Sequences Containing repeats (FIASCO) method, 16 microsatellite loci showed polymorphisms in both species. In two populations of each species, the number of alleles per locus ranged from three to 18 in S. alpina and from four to 30 in S. mongolica. Conclusions: These microsatellite markers provide an efficient tool for population genetic studies and will be used to assess the genetic diversity and spatial genetic structure of S. alpina and S. mongolica.