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We demonstrated experimentally an on-chip Fourier transform spectrometer based on an ultra-low half-wave voltage electro-optic modulator fabricated on thin film lithium niobate platform. The spectrometer has a pair of identical folded modulation arms with a waveguide length of 15.34 cm and an electrode length of 11.2 cm, showing a half-wave voltage as low as 0.266 V at 1550 nm wavelength. The wavelength-dependent losses of the fabricated spectrometer were measured and hence the transfer function of the spectrometer was obtained. Further, by applying a ramp voltage ranging from −100 V to 100 V to the electrodes, the intensity-voltage interferogram was obtained with a photodetector. The spectrum of the input light was retrieved by performing a Fourier transform on the interferogram combined with the wavelength-dependent equation of the half-wave voltage of the spectrometer. The results indicate that our fabricated spectrometer can achieve a resolution of 5.32 nm, an operation bandwidth beyond 100 nm, and a sub-microsecond measurement time.

Neuroligin-3 (Nlgn3) is an autism-associated cell-adhesion molecule that interacts with neurexins and is robustly expressed in both neurons and astrocytes. Neuronal Nlgn3is an essential regulator of synaptic transmission but the function of astrocytic Nlgn3is largely unknown. Given the high penetrance of Nlgn3mutations in autism and the emerging role of astrocytes in neuropsychiatric disorders, we here asked whether astrocytic Nlgn3might shape neural circuit properties in the cerebellum similar to neuronal Nlgn3. Imaging of tagged Nlgn3 protein produced by CRISPR/Cas9-mediated genome editing showed that Nlgn3 is enriched in the cell body but not the fine processes of cerebellar astrocytes (Bergmann glia). Astrocyte-specific knockout of Nlgn3did not detectably alter the number of synapses, synaptic transmission, or astrocyte morphology in mouse cerebellum. However, spatial transcriptomic analyses revealed a significant shift in gene expression among multiple cerebellar cell types after the deletion of astrocytic Nlgn3. Hence, in contrast to neuronal Nlgn3, astrocytic Nlgn3in the cerebellum is not involved in shaping synapses but may modulate gene expression in specific brain areas.

Air-to-ground (A2G) communication is a fundamental technology for integration of unmanned aerial vehicle (UAV) in the intelligent transportation system (ITS), where accurate analysis and modeling of UAV A2G wireless channel are of great importance for communication algorithm development. In this letter, we present a comprehensive analysis and modeling of low-altitude UAV A2G channel at 2.4 and 5.9 GHz based on multilink channel measurement campaign. The value of path loss as a function of the elevation angle and distance is proposed. Further, the shadow fading is analyzed for different frequency bands and the spatial correlation is evaluated. Particularly, it is found that the influence of UAV altitude on shadowing is significant and should be considered when developing A2G communication system.

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)–related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

The intricate processes of microbiota-gut-brain communication in modulating human cognition and emotion, especially in the context of mood disorders, have remained elusive. Here we performed faecal metagenomic, serum metabolomics and neuroimaging studies on a cohort of 109 unmedicated patients with depressed bipolar disorder (BD) patients and 40 healthy controls (HCs) to characterise the microbial-gut-brain axis in BD. Across over 12,000 measured metabolic features, we observed a large discrepancy (73.54%) in the serum metabolome between BD patients and HCs, spotting differentially abundant microbial-derived neuroactive metabolites including multiple B-vitamins, kynurenic acid, gamma-aminobutyric acid and short-chain fatty acids. These metabolites could be linked to the abundance of gut microbiota presented with corresponding biosynthetic potentials, including Akkermansia muciniphila, Citrobacter spp. (Citrobacter freundiiand Citrobacter werkmanii), Phascolarctobacterium spp., Yersinia spp. (Yersinia frederikseniiand Yersinia aleksiciae), Enterobacter spp. (Enterobacter cloacaeand Enterobacter kobei) and Flavobacterium spp. Based on functional neuroimaging, BD-related neuroactive microbes and metabolites were discovered as potential markers associated with BD-typical features of functional connectivity of brain networks, hinting at aberrant cognitive function, emotion regulation, and interoception. Our study combines gut microbiota and neuroactive metabolites with brain functional connectivity, thereby revealing potential signalling pathways from the microbiota to the gut and the brain, which may have a role in the pathophysiology of BD.

Quinoa (Chenopodium quinoaWilld.) with a history of 5000 years as food is extremely rich in nutrients and bioactive compounds, including γ-aminobutyric acid (GABA), a natural four-carbon non-protein amino acid with great benefits to human health. In quinoa, GABA generally increases with the germination time, but the underlying molecular mechanism is unclear. Here, we found that the GABA content in quinoa varied significantly among 25 varieties using an automatic amino acid analyzer. Next, six varieties (three low-GABA and three high-GABA varieties) were used for further analyses. The content of GABA in six varieties all showed an increasing trend after germination. In addition, Pearson’s correlation analysis showed that the changes in GABA content were closely related to the transcript level or enzyme activity of three key enzymes including glutamate decarboxylase (GAD), GABA transaminase (GABA-T), and succinate-semialdehyde dehydrogenase (SSADH) in the GABA shunt, especially GAD. Based on RNA-sequencing analysis, eight GADgenes, two GABA-Tgenes, one SSADHgene, nine polyamine oxidase (PAO) genes, five diamine oxidase (DAO) genes, four 4-aminobutyraldehyde dehydrogenase (BADH) genes, and three thermospermine synthase ACAULIS5 (ACL5) genes were identified. Among these, CqGAD8 and CqGABA-T2 may make a greater contribution to GABA accumulation during quinoa germination.

Interlayers have a significant impact on the mechanical properties and integrity of 3D printed concrete structures. The interlayer shear strength of 3D printed recycled mortar (3DPRM) was tested at interval times of 0 min-24 h, considering the effects of moisture, pore structure, and hydration products of the interlayer. Furthermore, the enhancement mechanism of superabsorbent polymer (SAP) incorporation on the interlayer adhesion of 3DPRM was also investigated. The findings indicated that as the time intervals increased, there was a corresponding increase in the yield stress of the bottom filament, leading to an increase in thickness and degradation of pore structures in the interlayer region. Additionally, there was a loss in moisture and a reduction in unhydrated particles, resulting in a decrease in the amount of C-S-H. As the bottom filament progressed from its fresh state to the final setting, the dominant factor in interlayer adhesion changed from moisture to pore structure. This conclusion provides a theoretical basis for solving the interlayer cold joint problem at different time intervals. The incorporation of 0.3% SAP completely offset the negative effect of recycled sand incorporation on interlayer adhesion strength and has good potential for practical application.

Synthesis of hollow polydopamine bowl-shaped nanoparticles (nanobowls), as small as 80 nm in diameter, via a one-pot template-free rapid method is reported. Addition of dopamine to a solution of 0.606 mg/mL tris(hydroxymethyl)aminomethane in an ethanol/water mixed solvent resulted in the formation of hollow spherical nanocapsules within 2 h. At longer reaction times, the formation of conventional solid nanospheres dominated the reaction. The wall thickness of the nanocapsules increased with increasing dopamine concentration in the reaction medium. Wall thickness was also influenced by oxygen availability during the reaction. Nanocapsules with thin walls were prone to collapse. When dried, over 90% of the nanocapsules with wall thickness on the order of 11 nm collapsed. Also, the degree of collapse of individual nanoparticles changed from complete to partial to no collapse as the wall thickness was increased. Varying the ethanol content affected the cavity size and overall dimension of the nanocapsules produced but did not result in a significant change to the wall thickness. A mechanism describing the formation of the nanocapsules and their subsequent collapse into nanobowls is presented. The shape-tunable nanobowls prepared through this green, rapid, and affordable method are expected to have applications in the biomedical, electrochemical, and catalytic fields.

With the rapid development of unmanned aerial vehicle (UAV) and autonomous driving technology, wireless communication between UAV and vehicles has become one of the hotspots in the research of intelligent transportation systems (ITS). Particularly, link-level UAV-based communication requires correlation characteristics of propagation channel. In the current channel measurement, the transmitter or receiver of the ground is fixed, which ignores the high dynamics of the vehicle and the complexity of the environment in the ITS scene. Therefore, it is necessary to conduct a dynamic channel measurement and analysis for UAV. In this paper, we carry out an UAV-to-Vehicle (U2V) measurement campaign in S- and C-band for multiple scenarios of low-altitude UAV and mobile vehicles propagation and provide a comprehensive investigation of channel fading characteristics. Based on the measurement data, the statistics of large-scale fading (path loss, shadow fading and its autocorrelation) and small-scale fading (amplitude distribution) for several typical measurement scenarios are extracted first, which are compared with other air-to-ground (A2G) and standard terrestrial propagation scenarios to analyze the U2V propagation characteristics in various scenarios. A comprehensive analysis and comparative study of all considered channel parameters extracted is then performed to reflect the physical laws behind the measurements. The analysis results reveal that the Log-distance model outperforms the considered typical models in terms of predicting the path loss, and the proposed autocorrelation model shows better performance than traditional models. The quantitative results are essential for modeling and realizing reliable communications in U2V wireless systems and analyzing the performance for UAV-enabled ITS.

An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.

Silver chalcogenides demonstrate great potential as flexible thermoelectric materials due to their excellent ductility and tunable electrical and thermal transport properties. In this work, we report that the amorphous/crystalline phase ratio and thermoelectric properties of the Ag2SxTe1–x(x= 0.55–0.75) samples can be modified by altering the S content. The room-temperature power factor of the Ag2S0.55Te0.45sample is 4.9 μW cm–1K–2, and a higher power factor can be achieved by decreasing the carrier concentration as predicted by the single parabolic band model. The addition of a small amount of excessive Te into Ag2S0.55Te0.45(Ag2S0.55Te0.45+y) not only enhances the power factor by decreasing the carrier concentration but also reduces the total thermal conductivity due to decreased electronic thermal conductivity. Owing to the effectively optimized carrier concentration, the thermoelectric power factor and dimensionless figure of merit zTof the sample with y= 0.007 reaches, respectively, 6.2 μW cm–1K–2and 0.39, while the excellent plastic deformability is well maintained, demonstrating its promising potential as a flexible thermoelectric material at room temperature.

Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMsto assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.

Biological age (BA) has been proposed to evaluate the aging status instead of chronological age (CA). Our study shows evidence that there might be multiple “clocks” within the whole-body system: systemic aging drivers/clocks overlaid with organ/tissue-specific counterparts. We utilize multi-omics data, including clinical tests, immune repertoire, targeted metabolomic molecules, gut microbiomes, physical fitness examinations, and facial skin examinations, to estimate the BA of different organs (e.g., liver, kidney) and systems (immune and metabolic system). The aging rates of organs/systems are diverse. People’s aging patterns are different. We also demonstrate several applications of organs/systems BA in two independent datasets. Mortality predictions are compared among organs' BA in the dataset of the United States National Health and Nutrition Examination Survey. Polygenic risk score of BAs constructed in the Chinese Longitudinal Healthy Longevity Survey cohort can predict the possibility of becoming centenarian.

A tubular-shaped Janus nanoparticle based on polydopamine that responds to near-infrared, magnetic, and pH stimuli is reported. The robust tubular polydopamine structure was obtained by optimizing the halloysite template-to-dopamine ratio during synthesis. The inner and outer surfaces of the tube were exposed at different steps of the template–sonication–-etching process, enabling the differential surface modification of these surfaces. Poly(ethylene glycol) (PEG) and poly(N-isopropylacrylamide) (PNIPAM) were grafted to the outer and inner surface of the nanotube, respectively. The PEG-coated surface limited aggregation of the nanoparticles at elevated temperatures. The PNIPAM-coated interior enhanced doxorubicin loading and endowed the nanoparticle with temperature-responsive behavior. The deposition of precipitated Fe3O4nanoparticles further modified the nanoparticles. The resulting magnetic Janus nanoparticles responded to pH, temperature, and magnetic fields. Temperature changes could be induced by near-infrared laser, and all three stimuli were found to influence release rates of adsorbed doxorubicin from the nanoparticles. The interaction of the stimuli on release kinetics was elucidated using a linear mixed model; reduced pH and NIR irradiation enhanced release while applying a static magnetic field retarded release. Furthermore, the mechanism was shifted toward Fickian behavior by applying a static magnetic field and low pH conditions. However, NIR irradiation only shifted the behavior toward Fickian behavior at low pH.

The immune system of skin develops in stages in mice. However, the developmental dynamics of immune cells in human skin remains elusive. Here, we perform transcriptome profiling of CD45+hematopoietic cells in human fetal skin at an estimated gestational age of 10–17 weeks by single-cell RNA sequencing. A total of 13 immune cell types are identified. Skin macrophages show dynamic heterogeneity over the course of skin development. A major shift in lymphoid cell developmental states occurs from the first to the second trimester that implies an in situdifferentiation process. Gene expression analysis reveals a typical developmental program in immune cells in accordance with their functional maturation, possibly involving metabolic reprogramming. Finally, we identify transcription factors (TFs) that potentially regulate cellular transitions by comparing TFs and TF target gene networks. These findings provide detailed insight into how the immune system of the human skin is established during development.