Enhanced Optic Nerve Expansion and Altered Ultrastructure of Elastic Fibers Induced by Lysyl Oxidase Inhibition in a Mouse Model of Marfan Syndrome.

Two major constituents of exfoliation material, fibrillin-1 and lysyl oxidase-like 1 (encoded by FBN1 and LOXL1), are implicated in exfoliation glaucoma, yet their individual contributions to ocular phenotype are minor. To test the hypothesis that a combination of FBN1 mutation and LOXL1 deficiency exacerbates ocular phenotypes, the pan-lysyl oxidase inhibitor ß-aminopropionitrile (BAPN) was used to treat adult wild-type (WT) mice and mice heterozygous for a missense mutation in Fbn1 (Fbn1C1041G/+) for 8 weeks and their eyes were examined. Although intraocular pressure did not change and exfoliation material was not detected in the eyes, BAPN treatment worsened optic nerve and axon expansion in Fbn1C1041G/+ mice, an early sign of axonal damage in rodent models of glaucoma. Disruption of elastic fibers was detected only in Fbn1C1041G/+ mice, which increased with BAPN treatment, as shown by histologic and immunohistochemical staining of the optic nerve pia mater. Transmission electron microscopy showed that Fbn1C1041G/+ mice had fewer microfibrils, smaller elastin cores, and a lower density of elastic fibers compared with WT mice in control groups. BAPN treatment led to elastin core expansion in both WT and Fbn1C1041G/+ mice, but an increase in the density of elastic fiber was confined to Fbn1C1041G/+ mice. LOX inhibition had a stronger effect on optic nerve and elastic fiber parameters in the context of Fbn1 mutation, indicating the Marfan mouse model with LOX inhibition warrants further investigation for exfoliation glaucoma pathogenesis.

Sequence characteristics, genetic diversity and phylogenetic analysis of the Cucurbita ficifolia (Cucurbitaceae) chloroplasts genome.

BACKGROUND: Curcubita ficifolia Bouché (Cucurbitaceae) has high value as a food crop and medicinal plant, and also has horticultural value as rootstock for other melon species. China is home to many different cultivars, but the genetic diversity of these resources and the evolutionary relationships among them, as well as the differences between C. ficifolia and other Cucurbita species, remain unclear. RESULTS: We investigated the chloroplast (cp) genomes of 160 C. ficifolia individuals from 31 populations in Yunnan, a major C. ficifolia production area in China. We found that the cp genome of C. ficifolia is ~151 kb and contains 128 genes, of which 86 are protein coding genes, 34 encode tRNA, and eight encode rRNAs. We also identified 64 SSRs, mainly AT repeats. The cp genome was found to contain a total of 204 SNP and 57 indels, and a total of 21 haplotypes were found in the 160 study individuals. The reverse repeat (IR) region of C. ficifolia contained a few differences compared with this region in the six other Cucurbita species. Sequence difference analysis demonstrated that most of the variable regions were concentrated in the single copy (SC) region. Moreover, the sequences of the coding regions were found to be more similar among species than those of the non-coding regions. The phylogenies reconstructed from the cp genomes of 61 representative species of Cucurbitaceae reflected the currently accepted classification, in which C. ficifolia is sister to the other Cucurbita species, however, different interspecific relationships were found between Cucurbita species. CONCLUSIONS: These results will be valuable in the classification of C. ficifolia genetic resources and will contribute to our understanding of evolutionary relationships within the genus Cucurbita.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as "DeepDOC", and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Effects of aflatoxin and fumonisin on gene expression of growth factors and inflammation-related genes in a human hepatocyte cell line.

Aflatoxin B1 (AFB1) and fumonisin B1 (FB1) are mycotoxins widely distributed in maize and maized-based products, often occurring together. The implications of co-exposure to aflatoxin and fumonsin for human health are numerous, but a particular concern is the potential of FB1 to modulate AFB1 hepatotoxicity. This study evaluated the toxicity of these mycotoxins, alone or combined, in a human non-tumorigenic liver cell line, HHL-16 cells, and assessed the effects of AFB1 and FB1 on expression of genes involved in immune and growth factor pathways. The results demonstrated that in HHL-16 cells, both AFB1 and FB1 had dose-dependent and time-dependent toxicity, and the combination of them showed a synergistic toxicity in the cells. Moreover, AFB1 caused upregulation of IL6, CCL20, and BMP2, and downregulation of NDP. In combination of AFB1 with FB1, gene expression levels of IL6 and BMP2 were significantly higher compared to individual FB1 treatment, and had a tendency to be higher than individual AFB1 treatment. This study shows that FB1 may increase the hepatoxicity of AFB1 through increasing the inflammatory response and disrupting cell growth pathways.

A slow-releasing donor of hydrogen sulfide inhibits neuronal cell death via anti-PANoptosis in rats with spinal cord ischemia‒reperfusion injury.

BACKGROUND: Spinal cord ischemia‒reperfusion injury (SCIRI) can lead to paraplegia, which leads to permanent motor function loss. It is a disastrous complication of surgery and causes tremendous socioeconomic burden. However, effective treatments for SCIRI are still lacking. PANoptosis consists of three kinds of programmed cell death, pyroptosis, apoptosis, and necroptosis, and may contribute to ischemia‒reperfusion-induced neuron death. Previous studies have demonstrated that hydrogen sulfide (H2S) exerts a neuroprotective effect in many neurodegenerative diseases. However, whether H2S is anti-PANoptosis and neuroprotective in the progression of acute SCIRI remains unclear. Thus, in this study we aimed to explore the role of H2S in SCIRI and its underlying mechanisms. METHODS: Measurements of lower limb function, neuronal activity, microglia/macrophage function histopathological examinations, and biochemical levels were performed to examine the efficacy of H2S and to further demonstrate the mechanism and treatment of SCIRI. RESULTS: The results showed that GYY4137 (a slow-releasing H2S donor) treatment attenuated the loss of Nissl bodies after SCIRI and improved the BBB score. Additionally, the number of TUNEL-positive and cleaved caspase-3-positive cells was decreased, and the upregulation of expression of cleaved caspase-8, cleaved caspase-3, Bax, and Bad and downregulation of Bcl-2 expression were reversed after GYY4137 administration. Meanwhile, both the expression and activation of p-MLKL, p-RIP1, and p-RIP3, along with the number of PI-positive and RIP3-positive neurons, were decreased in GYY4137-treated rats. Furthermore, GYY4137 administration reduced the expression of NLRP3, cleaved caspase-1 and cleaved GSDMD, decreased the colocalization NeuN/NLRP3 and Iba1/interleukin-1ß-expressing cells, and inhibited proinflammatory factors and microglia/macrophage polarization. CONCLUSIONS: H2S ameliorated spinal cord neuron loss, prevented motor dysfunction after SCIRI, and exerted a neuroprotective effect via the inhibition of PANoptosis and overactivated microglia-mediated neuroinflammation in SCIRI.

TetR family regulator AbrT controls lincomycin production and morphological development in Streptomyces lincolnensis.

BACKGROUND: The TetR family of transcriptional regulators (TFRs), serving as crucial regulators of diverse cellular processes, undergo conformational changes induced by small-molecule ligands, which either inhibit or activate them to modulate target gene expression. Some ligands of TFRs in actinomycetes and their regulatory effects have been identified and studied; however, regulatory mechanisms of the TetR family in the lincomycin-producing Streptomyces lincolnensis remain poorly understood. RESULTS: In this study, we found that AbrT (SLCG_1979), a TetR family regulator, plays a pivotal role in regulating lincomycin production and morphological development in S. lincolnensis. Deletion of abrT gene resulted in increased lincomycin A (Lin-A) production, but delayed mycelium formation and sporulation on solid media. AbrT directly or indirectly repressed the expression of lincomycin biosynthetic (lin) cluster genes and activated that of the morphological developmental genes amfC, whiB, and ftsZ. We demonstrated that AbrT bound to two motifs (5'-CGCGTACTCGTA-3' and 5'-CGTACGATAGCT-3') present in the bidirectional promoter between abrT and SLCG_1980 genes. This consequently repressed abrT itself and its adjacent gene SLCG_1980 that encodes an arabinose efflux permease. D-arabinose, not naturally occurring as L-arabinose, was identified as the effector molecule of AbrT, reducing its binding affinity to abrT-SLCG_1980 intergenic region. Furthermore, based on functional analysis of the AbrT homologue in Saccharopolyspora erythraea, we inferred that the TetR family regulator AbrT may play an important role in regulating secondary metabolism in actinomycetes. CONCLUSIONS: AbrT functions as a regulator for governing lincomycin production and morphological development of S. lincolnensis. Our findings demonstrated that D-arabinose acts as a ligand of AbrT to mediate the regulation of lincomycin biosynthesis in S. lincolnensis. Our findings provide novel insights into ligand-mediated regulation in antibiotic biosynthesis.

The combination of Butyricicoccus pullicaecorum and 3-hydroxyanthranilic acid prevents postmenopausal osteoporosis by modulating gut microbiota and Th17/Treg.

BACKGROUND: Postmenopausal osteoporosis (PMO) is a chronic condition characterized by decreased bone strength. This study aims to investigate the effects and mechanisms of the combination of Butyricicoccus pullicaecorum (Bp) and 3-hydroxyanthranilic acid (3-HAA) on PMO. METHODS: The effects of Bp and 3-HAA on PMO were evaluated in ovariectomized (OVX) rats by assessing stereological parameters, femur microstructure, and autophagy levels. The T helper (Th) 17/Regulatory T (Treg) cells of rats were detected using flow cytometric analysis. Furthermore, the impact of Bp and 3-HAA on the gut microbiota of rats was assessed using 16S rRNA gene sequencing. The correlation between the gut microbiota of rats and Th17/Treg immune factors, as well as femoral stereo parameters, was separately assessed using Spearman rank correlation analysis. RESULTS: Bp and 3-HAA treatments protected OVX rats by promoting osteogenesis and inhibiting autophagy. Compared to the Sham group, OVX rats showed an increase in Th17 cells and a decrease in Treg cells. Bp and 3-HAA reversed these changes. Enterorhabdus and Pseudomonas were significantly enriched in OVX rats. Bp and 3-HAA regulated the gut microbiota of OVX rats, enriching pathways related to nutrient metabolism and immune function. There was a correlation between the gut microbiota and the Th17/Treg, as well as femoral stereo parameters. The concurrent administration of Bp and 3-HAA medication facilitated the enrichment of gut microbiota associated with the improvement of PMO. CONCLUSION: The combination therapy of Bp and 3-HAA can prevent PMO by modulating the gut microbiota and restoring Th17/Treg immune homeostasis.

Developing a novel causal inference algorithm for personalized biomedical causal graph learning using meta machine learning.

BACKGROUND: Modeling causality through graphs, referred to as causal graph learning, offers an appropriate description of the dynamics of causality. The majority of current machine learning models in clinical decision support systems only predict associations between variables, whereas causal graph learning models causality dynamics through graphs. However, building personalized causal graphs for each individual is challenging due to the limited amount of data available for each patient. METHOD: In this study, we present a new algorithmic framework using meta-learning for learning personalized causal graphs in biomedicine. Our framework extracts common patterns from multiple patient graphs and applies this information to develop individualized graphs. In multi-task causal graph learning, the proposed optimized initial guess of shared commonality enables the rapid adoption of knowledge to new tasks for efficient causal graph learning. RESULTS: Experiments on one real-world biomedical causal graph learning benchmark data and four synthetic benchmarks show that our algorithm outperformed the baseline methods. Our algorithm can better understand the underlying patterns in the data, leading to more accurate predictions of the causal graph. Specifically, we reduce the structural hamming distance by 50-75%, indicating an improvement in graph prediction accuracy. Additionally, the false discovery rate is decreased by 20-30%, demonstrating that our algorithm made fewer incorrect predictions compared to the baseline algorithms. CONCLUSION: To the best of our knowledge, this is the first study to demonstrate the effectiveness of meta-learning in personalized causal graph learning and cause inference modeling for biomedicine. In addition, the proposed algorithm can also be generalized to transnational research areas where integrated analysis is necessary for various distributions of datasets, including different clinical institutions.

Clinical decision making under uncertainty: a bootstrapped counterfactual inference approach.

BACKGROUND: Learning policies for decision-making, such as recommending treatments in clinical settings, is important for enhancing clinical decision-support systems. However, the challenge lies in accurately evaluating and optimizing these policies for maximum efficacy. This paper addresses this gap by focusing on two key aspects of policy learning: evaluation and optimization. METHOD: We develop counterfactual policy learning algorithms for practical clinical applications to suggest viable treatment for patients. We first design a bootstrap method for counterfactual assessment and enhancement of policies, aiming to diminish uncertainty in clinical decisions. Building on this, we introduce an innovative adversarial learning algorithm, inspired by bootstrap principles, to further advance policy optimization. RESULTS: The efficacy of our algorithms was validated using both semi-synthetic and real-world clinical datasets. Our method outperforms baseline algorithms, reducing the variance in policy evaluation by 30% and the error rate by 25%. In policy optimization, it enhances the reward by 1% to 3%, highlighting the practical value of our approach in clinical decision-making. CONCLUSION: This study demonstrates the effectiveness of combining bootstrap and adversarial learning techniques in policy learning for clinical decision support. It not only enhances the accuracy and reliability of policy evaluation and optimization but also paves avenues for leveraging advanced counterfactual machine learning in healthcare.

New targets of TetR-type regulator SLCG_2919 for controlling lincomycin biosynthesis in Streptomyces lincolnensis.

The transcription factor (TF)-mediated regulatory network controlling lincomycin production in Streptomyces lincolnensis is yet to be fully elucidated despite several types of associated TFs having been reported. SLCG_2919, a tetracycline repressor (TetR)-type regulator, was the first TF to be characterized outside the lincomycin biosynthetic cluster to directly suppress the lincomycin biosynthesis in S. lincolnensis. In this study, improved genomic systematic evolution of ligands by exponential enrichment (gSELEX), an in vitro technique, was adopted to capture additional SLCG_2919-targeted sequences harboring the promoter regions of SLCG_6675, SLCG_4123-4124, SLCG_6579, and SLCG_0139-0140. The four DNA fragments were confirmed by electrophoretic mobility shift assays (EMSAs). Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) showed that the corresponding target genes SLCG_6675 (anthranilate synthase), SLCG_0139 (LysR family transcriptional regulator), SLCG_0140 (beta-lactamase), SLCG_6579 (cytochrome P450), SLCG_4123 (bifunctional DNA primase/polymerase), and SLCG_4124 (magnesium or magnesium-dependent protein phosphatase) in ΔSLCGL_2919 were differentially increased by 3.3-, 4.2-, 3.2-, 2.5-, 4.6-, and 2.2-fold relative to those in the parental strain S. lincolnensis LCGL. Furthermore, the individual inactivation of these target genes in LCGL reduced the lincomycin yield to varying degrees. This investigation expands on the known DNA targets of SLCG_2919 to control lincomycin production and lays the foundation for improving industrial lincomycin yields via genetic engineering of this regulatory network.

Identifying patients with cognitive motor dissociation using resting-state temporal stability.

Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness.

Decoding subject's own name in the primary auditory cortex.

Current studies have shown that perception of subject's own name (SON) involves multiple multimodal brain regions, while activities in unimodal sensory regions (i.e., primary auditory cortex) and their interaction with multimodal regions during the self-processing remain unclear. To answer this, we combined multivariate pattern analysis and dynamic causal modelling analysis to explore the regional activation pattern and inter-region effective connection during the perception of SON. We found that SON and other names could be decoded from the activation pattern in the primary auditory cortex. In addition, we found an excitatory effect of SON on connections from the anterior insula/inferior frontal gyrus to the primary auditory cortex, and to the temporoparietal junction. Our findings extended the current knowledge of self-processing by showing that primary auditory cortex could discriminate SON from other names. Furthermore, our findings highlighted the importance of influence of the insula on the primary auditory cortex during self-processing.

Effects of 12-week escitalopram treatment on resting-state functional connectivity of large-scale brain networks in major depressive disorder.

In this study, the effects of antidepressants on large-scale brain networks and the neural basis of individual differences in response were explored. A total of 41 patients with major depressive disorder (MDD) and 42 matched healthy controls (HCs) were scanned by resting-state functional magnetic resonance imaging separately at baseline and after a 12-week follow-up. The patients with MDD received escitalopram for 12 weeks. After treatment, patients were classified into those with MDD in remission [MDDr, endpoint 17-item Hamilton Depression Rating Scale (HAMD) total score ≤7] and those in nonremission (MDDnr). The human Brainnetome Atlas was used to define large-scale networks and compute within- and between-network resting-state functional connectivity (rsFC). Results showed the decreased subcortical network (SCN)-ventral attention network (VAN) connectivity at baseline increased in patients with MDD after 12-week treatment, and it was comparable with that of HCs. This change was only observed in patients with MDDr. However, the decreased within-network rsFC in SCN and default mode network (DMN) persisted in all patients with MDD, including those with MDDr and MDDnr, after treatment. The strength of SCN-VAN connectivity at baseline was significantly negatively correlated with the reduction rate of HAMD score in all patients with MDD. Thus, SCN-VAN connectivity may be an antidepressant target associated with depressive state changes and a predictor of treatment response to serotonin reuptake inhibitors. The within-network rsFC in SCN and DMN may reflect a trait-like abnormality in MDD. These findings provide further insights into the mechanism of antidepressants and their individual differences in response. The trial name is "Appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement" (URL: http://www.chictr.org.cn/showproj.aspx?proj=21377; registration number: ChiCTR-OOC-17012566).

The effect of environmental factors on the genetic differentiation of Cucurbita ficifolia populations based on whole-genome resequencing.

BACKGROUND: Cucurbita ficifolia is one of the squash species most resistant to fungal pathogens, and has especially high resistance to melon Fusarium wilt. This species is therefore an important germplasm resource for the breeding of squash and melon cultivars. RESULTS: Whole-genome resequencing of 223 individuals from 32 populations in Yunnan Province, the main cucurbit production area in China, was performed and 3,855,120 single-nucleotide polymorphisms (SNPs) and 1,361,000 InDels were obtained. SNP analysis suggested that levels of genetic diversity in C. ficifolia were high, but that different populations showed no significant genetic differentiation or geographical structure, and that individual C. ficifolia plants with fruit rinds of a similar color did not form independent clusters. A Mantel test conducted in combination with geographical distance and environmental factors suggested that genetic distance was not correlated with geographical distance, but had a significant correlation with environmental distance. Further associations between the genetic data and five environmental factors were analyzed using whole-genome association analysis. SNPs associated with each environmental factor were investigated and genes 250 kb upstream and downstream from associated SNPs were annotated. Overall, 15 marker-trait-associated SNPs (MTAs) and 293 genes under environmental selection were identified. The identified genes were involved in cell membrane lipid metabolism, macromolecular complexes, catalytic activity and other related aspects. Ecological niche modeling was used to simulate the distribution of C. ficifolia across time, from the present and into the future. We found that the area suitable for C. ficifolia changed with the changing climate in different periods. CONCLUSIONS: Resequencing of the C. ficifolia accessions has allowed identification of genetic markers, such as SNPs and InDels. The SNPs identified in this study suggest that environmental factors mediated the formation of the population structure of C. ficifolia in China. These SNPs and Indels might also contribute to the variation in important pathways of genes for important agronomic traits such as yield, disease resistance and stress tolerance. Moreover, the genome resequencing data and the genetic markers identified from 223 accessions provide insight into the genetic variation of the C. ficifolia germplasm and will facilitate a broad range of genetic studies.

Novel Mechanisms of Perioperative Neurocognitive Disorders: Ferroptosis and Pyroptosis.

Perioperative neurocognitive disorders (PNDs) are some of the most common postoperative complications among the elderly and susceptible individuals, which significantly worsens the clinical outcome of patients. However, the prevention and treatment strategies of PNDs are difficult to determine and implement since the pathogenesis of PNDs is not well understood. The development of living organisms is associated with active and organized cell death, which is essential for maintaining the homeostasis of life. Ferroptosis is a programmed cell death (different from apoptosis and necrosis) mainly caused by an imbalance in the generation and degradation of intracellular lipid peroxides due to iron overload. Pyroptosis is an inflammatory cell death characterized by the creation of membrane holes mediated by the gasdermin (GSDM) family, followed by cell lysis and the release of pro-inflammatory cytokines. Ferroptosis and pyroptosis are involved in the pathogenesis of various central nervous system (CNS) diseases. Furthermore, ferroptosis and pyroptosis are closely associated with the occurrence and development of PNDs. This review summarizes the main regulatory mechanisms of ferroptosis and pyroptosis and the latest related to PNDs. Based on the available evidence, potential intervention strategies that can alleviate PNDs by inhibiting ferroptosis and pyroptosis have also been provided.

Enhancing THz fingerprint detection by the stretchable substrate with a dielectric metagrating.

The terahertz (THz) wave contains abundant spectrum resources and is still in the early stages of development. It has great application potential in biomedical engineering and public security. However, in these areas there are difficulties to overcome like measuring the wide band absorption of a trace mount sample. In this paper, a THz absorption enhancing method is suggested by a multiplexing strategy. By gradually expanding the stretchable substrate of the dielectric metagrating with an oblique THz wave incidence, the resonance peak frequencies can cover the frequency range of 0.48-0.58 THz. Also, the corresponding envelope built by the peaks of the metagrating absorption spectrum with the 0.2 µm α-lactose film can demonstrate 71.55 times boosting compared to the original absorption amplitude of the film. The investigation witnesses possibilities for the detection of biomacromolecular materials.

High-efficiency genetic engineering toolkit for virus based on lambda red-mediated recombination.

PURPOSE: Viruses, such as Ebola virus (EBOV), evolve rapidly and threaten the human health. There is a great demand to exploit efficient gene-editing techniques for the identification of virus to probe virulence mechanism for drug development. METHODS: Based on lambda Red recombination in Escherichia coli (E. coli), counter-selection, and in vitro annealing, a high-efficiency genetic method was utilized here for precisely engineering viruses. EBOV trVLPs assay and dual luciferase reporter assay were used to further test the effect of mutations on virus replication. RESULTS: Considering the significance of matrix protein VP24 in EBOV replication, the types of mutations within vp24, including several single-base substitutions, one double-base substitution, two seamless deletions, and one targeted insertion, were generated on the multi-copy plasmid of E. coli. Further, the length of the homology arms for recombination and in vitro annealing, and the amount of DNA cassettes and linear plasmids were optimized to create a more elaborate and cost-efficient protocol than original approach. The effects of VP24 mutations on the expression of a reporter gene (luciferase) from the EBOV minigenome were determined, and results indicated that mutations of key sites within VP24 have significant impacts on EBOV replication. CONCLUSION: This precise mutagenesis method will facilitate effective and simple editing of viral genes in E. coli.

Vertical fate of Cd in soil under phytoremediation by Indian mustard and tall fescue.

Soil columns were designed to investigate the vertical migration of Cd in Indian mustard (IM) and tall fescue (TF). The TF biomass was greater than the IM biomass, and the Cd content in IM was higher in the shoots but lower in the roots than that in TF. Both IM and TF released N and absorbed P and K during outdoor growth, differing from the results of the previous experiment in which plants were grown in greenhouses. TF was more absorbent and had less upward attraction than IM. The IM soil was more favorable for Cd precipitation than was the TF soil. Leaching remained the dominant effect, with only 2.28-3.40% and 2.65-3.90% of Cd absorbed by IM and TF, respectively. The present study on the vertical migration of Cd provides new insights into the phytoremediation mechanisms of IM and TF. HIGHLIGHTSVertical migration rate of Cd in soil was calculated.Cd precipitation in IM soil was greater and more excellence than TF soil.TF was more absorbent and had less upward attraction than IM.Leaching remained the dominant effect with only small absorb.

On-Chip Arbitrary Manipulation of Single Particles by Acoustic Resonator Array.

Effective and arbitrary manipulation of particles in liquid has attracted substantial interest. Acoustic tweezers, a new and promising tool, exhibit high biocompatibility, universality, and precision but lack arbitrariness. In this work, we report a gigahertz (GHz) bulk acoustic streaming tweezer (AST)-based micro-manipulation platform capable of efficiently translating acoustic energy to fluid kinetic energy, creating a controllable, quick-response, and stable flow field and precisely, arbitrarily, and universally manipulating a single particle to move like a microrobot. Through controlling the radio frequency signals applied on these resonators, the intensity and direction of the acoustic streaming flow can be quickly and arbitrarily adjusted. Consequently, the particle dispersed at the bottom can be arbitrarily and steadily driven along the predesigned route to the target position by the acoustic streaming drag force (ASF). We utilized four resonators cooperated as a work group to manipulate single SiO2 particles to complete nearly uniform linear motions and U-shaped motions, as well as playing billiards and exploring a maze, demonstrating the enormous potential of this GHz AST-based single-particle manipulation platform for separation, assembly, sensing, enriching, transporting, and so forth.

Paracandidimonas lactea sp. nov., a urea-utilizing bacterium isolated from landfill.

A urea-utilizing bacterium, designated Q2-2 T, was isolated from landfill. Cells of strain Q2-2 T were Gram stain-negative, aerobic, short-rod bacteria. Strain Q2-2 T was observed to grow at a temperature range of 15-37℃ (optimum 30 â„ƒ), a pH range of 5.5-9.5 (optimum pH 8.0) and 0-4% (w/v) NaCl (optimum 1%). The major respiratory quinone was Q-8, and the major polar lipids were diphosphatidyl glycerol, phosphatidylethanolamine, phosphatidylmethylethanolamine, and phosphatidyl glycerol. Based on the 16S rRNA gene sequence, strain Q2-2 T had the highest similarity with Paracandidimonas caeni 24 T (98.0%), followed by Pusillimonas soli MJ07T (97.5%), Parapusillimonas granuli Ch07T (97.2%), Pusillimonas ginsengisoli DCY25T (97.1%) and Paracandidimonas soli IMT-305 T (96.4%). The ANI values between strain Q2-2 T and the above related type strains were 71.02%, 73.52%, 74.32%, 74.59% and 72.29%, respectively. The DNA G + C content of strain Q2-2 T was 61.1%. Therefore, strain Q2-2 T represents a novel species of the genus Paracandidimonas, for which the name Paracandidimonas lactea sp. nov. (type strain Q2-2 T = CGMCC 1.19179 T = JCM 34906 T) is proposed.