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Tri-axis MEMS accelerometers are used in a wide range of applications such as health monitoring, industrial electronics and navigation guidance due to their low cost, high performance and integration. At this stage, the main structure of commercial products of triaxial accelerometers is the integration of three single-axis capacitive accelerometers. However, many reports have shown that resonant accelerometers can achieve better performance than capacitive accelerometers. In this paper, a novel triaxial accelerometer include a dual-axis resonantors and two torsional elements is proposed. The prototype was fabricated using MEMS processing technology and had a footprint of 10.8 mm × 10.8 mm. A non-vacuum package is adopted to guarantee the stability of the torsional accelerometers included. As a result, a low Q value is obtained for each part included. The effect of low Q is analyzed and its control circuit is optimized to obtain excellent stability. Finally, the triaxial accelerometer prototype was tested to evalute its performance, the Q value of each resonantors is lower than 100, the cross-axis coupling coefficient is below than 0.5%, the nonlinearity is belower than 0.053% at a range of ± 10 g and the bias instability at each axis is 5.7 μg, 4.8 μg and 73 μg respectively (X, Y and Z aixs). [ABSTRACT FROM AUTHOR]

Background: Bi-specific T-cell engager (BiTE) antibody is a class of bispecific antibodies designed for cancer immunotherapy. Blinatumomab is the first approved BiTE to treat acute B cell lymphoblastic leukemia (B-ALL). It brings killer T and target B cells into close proximity, activating patient's autologous T cells to kill malignant B cells via mechanisms such as cytolytic immune synapse formation and inflammatory cytokine production. However, the activated T-cell subtypes and the target cell-dependent T cell responses induced by blinatumomab, as well as the mechanisms of resistance to blinatumomab therapy are largely unknown. Results: In this study, we performed single-cell sequencing analysis to identify transcriptional changes in T cells following blinatumomab-induced T cell activation using single cells from both, a human cell line model and a patient-derived model of blinatumomab-mediated cytotoxicity. In total, the transcriptome of 17,920 single T cells from the cell line model and 2271 single T cells from patient samples were analyzed. We found that CD8+ effector memory T cells, CD4+ central memory T cells, naïve T cells, and regulatory T cells were activated after blinatumomab treatment. Here, blinatumomab-induced transcriptional changes reflected the functional immune activity of the blinatumomab-activated T cells, including the upregulation of pathways such as the immune system, glycolysis, IFNA signaling, gap junctions, and IFNG signaling. Co-stimulatory (TNFRSF4 and TNFRSF18) and co-inhibitory (LAG3) receptors were similarly upregulated in blinatumomab-activated T cells, indicating ligand-dependent T cell functions. Particularly, B-ALL cell expression of TNFSF4, which encodes the ligand of T cell co-stimulatory receptor TNFRSF4, was found positively correlated with the response to blinatumomab treatment. Furthermore, recombinant human TNFSF4 protein enhanced the cytotoxic activity of blinatumomab against B-ALL cells. Conclusion: These results reveal a target cell-dependent mechanism of T-cell activation by blinatumomab and suggest that TNFSF4 may be responsible for the resistant mechanism and a potential target for combination therapy with blinatumomab, to treat B-ALL or other B-cell malignancies. [ABSTRACT FROM AUTHOR]

COVID-19 rumor datasets have been collected, e.g., the COVID-19-TweetIDs dataset contains an ongoing collection of tweets IDs associated with the COVID-19 tweets (Chen et al., [7]); the COVID-19-Arabic-Tweets-Dataset contains a collection of Arabic tweets IDs related to the COVID-19 (Alqurashi et al., [3]); the CoAID (Covid-19 healthcare misinformation dataset) is a diverse COVID-19 healthcare misinformation dataset, including fake news on websites and social platforms, along with users' social engagement with such news (Cui and Lee, [13]). Keywords: misinformation; rumor; COVID-19; rumor classification; sentiment analysis; deep learning; fake news detection EN misinformation rumor COVID-19 rumor classification sentiment analysis deep learning fake news detection 1 10 10 06/03/21 20210531 NES 210531 The views, opinions, and/or findings contained in this article are those of the authors and should not be interpreted as representing the official views or policies, either expressed or implied by the Defense Advanced Research Projects Agency, the Department of Defense or the National Science Foundation. Twitter Dataset The Twitter dataset contains rumors posted on Twitter. We separate our collected rumors into two datasets based on their source: (i) a news dataset, containing rumors collected from news websites, and (ii) a Twitter dataset, containing rumors collected from Twitter. [Extracted from the article]

A high-accuracy differential resonant pressure sensor with two similar resonators is proposed using the linear fitting method to guarantee its output linearity without polynomial compensation. Results reveal that the nonlinearity of the differential resonant pressure sensor is largely dependent on the tensile/compressive sensor pressure–stress ratio c when two similar resonators are used separately as compressive and tensile elements. Nonlinearity decreases sharply with an appropriate ratio c. A theoretical model is proposed to obtain minimal nonlinearity and shows satisfactory agreement with the simulation results. The impact factors of ratio c are analyzed to facilitate adjustments with the designed value. Moreover, micromachining methods are used to fabricate sensing chips. Experiment results show that the nonlinearity and measurement sensitivity of the proposed differential resonant pressure sensor are ±0.02% FS and 35.5 Hz kPa−1 with the linear fitting method in a pressure range of 0–200 kPaA and temperature range of −40 °C to +40 °C. The differential linear fitting method largely decreases compensation complexity without polynomial fitting for high-precision pressure measurement. [ABSTRACT FROM AUTHOR]

Background: Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results: Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion: Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo. [ABSTRACT FROM AUTHOR]

In this paper, a novel resonant pressure sensor is developed based on electrostatic excitation and piezoresistive detection. The measured pressure applied to the diaphragm will cause the resonant frequency shift of the resonator. The working mode stress–frequency theory of a double-ended tuning fork with an enhanced coupling beam is proposed, which is compatible with the simulation and experiment. A unique piezoresistive detection method based on small axially deformed beams with a resonant status is proposed, and other adjacent mode outputs are easily shielded. According to the structure design, high-vacuum wafer-level packaging with different doping in the anodic bonding interface is fabricated to ensure the high quality of the resonator. The pressure sensor chip is fabricated by dry/wet etching, high-temperature silicon bonding, ion implantation, and wafer-level anodic bonding. The results show that the fabricated sensor has a measuring sensitivity of ~19 Hz/kPa and a nonlinearity of 0.02% full scale in the pressure range of 0–200 kPa at a full temperature range of −40 to 80 °C. The sensor also shows a good quality factor >25,000, which demonstrates the good vacuum performance. Thus, the feasibility of the design is a commendable solution for high-accuracy pressure measurements. Pressure sensor: Piezoresistive detection The operating principle and experimental realization of a new piezoresistive resonant pressure sensor are shown. Resonant pressure sensors rely on changes in applied pressure to a diaphragm to cause the resonant frequency of the resonator to change. This enables high stability and signal-to-noise ratios, combined with a quasi-digital output; resultantly, resonant pressure sensors are often used in critical applications such as aerospace and for instrument calibration. Here, a team led by Zhuangde Jiang from Xi'an Jiaotong University, China, report a piezoresistive detection-based resonant pressure sensor. They establish the theory for their device operation, verified by both simulations and experiments. Their device shows an accuracy better than 0.02% FS and a resonant quality factor greater than 25,000. [ABSTRACT FROM AUTHOR]

This correction notice is for an article titled "Correction: a novel non-vacuum packaged triaxial accelerometer with differential dual-axis resonantors and torsional elements" published in the journal Microsystems Technologies. The correction addresses an error in the affiliation of one of the authors, Songli Wang. The correct affiliation should be the Aviation Key Laboratory of Science and Technology on Inertial Technology, FACRI, Xi'an, China. The correction also modifies the affiliations of two other authors. The original article has been corrected. Springer Nature, the publisher, remains neutral regarding jurisdictional claims and institutional affiliations. The authors of the article are Jinhui Li, Dunzhu Xia, Songli Wang, Xiuhua Yang, and Bing Zhang. [Extracted from the article]

Active waveband selective switches for the telecommunication wavebands are fabricated and demonstrated. This type of active waveband selective switch is composed of a guided‐mode resonance filter, a twisted nematic liquid crystal (TN‐LC) layer, and a linear polariser. In voltage‐off status, a fabricated active waveband selective switch with grating period of 893.86 nm exhibits high resonance peak with wavelength around 1311.2 nm. In voltage‐on status, this switch exhibits a high resonance peak with wavelength around 1551.3 nm. The measured reflection peaks of another active waveband selective switch with grating period of 872.84 nm are located at 1309.1 and 1549.4 nm in voltage‐on status and voltage‐off status, respectively. Thus, light waveband can be tuned between O‐band and C‐band by electrically driving the TN‐LC layer of this type of active waveband selective switch in real time. [ABSTRACT FROM AUTHOR]

Monocytes are a distinct subset of myeloid cells with diverse functions in early inflammatory immune modulation. While previous studies have surveyed the role of miRNA regulation on different myeloid cell lines and primary cultures, the time-dependent kinetics of inflammatory stimulation on miRNA expression and the relationship between miRNA-to-target RNA expression have not been comprehensively profiled in monocytes. In this study, we use next-generation sequencing and RT-PCR assays to analyze the non-coding small RNA transcriptome of unstimulated and lipopolysaccharide (LPS)-stimulated monocytes at 6 and 24 hours. We identified a miRNA signature consisting of five mature miRNAs (hsa-mir-146a, hsa-mir-155, hsa-mir-9, hsa-mir-147b, and hsa-mir-193a) upregulated by LPS-stimulated monocytes after 6 hours and found that most miRNAs were also upregulated after 24 hours of stimulation. Only one miRNA gene was down-regulated and no other small RNAs were found dysregulated in monocytes after LPS treatment. In addition, novel tRNA-derived fragments were also discovered in monocytes although none showed significant changes upon LPS stimulation. Interrogation of validated miRNA targets by transcriptomic analysis revealed that absolute expression of most miRNA targets implicating in innate immune response decreased over time in LPS-stimulated monocytes although their expression patterns along the treatment were heterogeneous. Our findings reveal a potential role by which selective miRNA upregulation and stable expression of other small RNAs enable monocytes to develop finely tuned cellular responses during acute inflammation. [ABSTRACT FROM AUTHOR]

Obesity and type 2 diabetes (T2D) remain major global healthcare challenges, and developing therapeutics necessitates using nonhuman primate models. Here, we present a transcriptomic and proteomic atlas of all the major organs of cynomolgus monkeys with spontaneous obesity or T2D in comparison to healthy controls. Molecular changes occur predominantly in the adipose tissues of individuals with obesity, while extensive expression perturbations among T2D individuals are observed in many tissues such as the liver and kidney. Immune-response-related pathways are upregulated in obesity and T2D, whereas metabolism and mitochondrial pathways are downregulated. Moreover, we highlight some potential therapeutic targets, including SLC2A1 and PCSK1 in obesity as well as SLC30A8 and SLC2A2 in T2D. Our study provides a resource for exploring the complex molecular mechanism of obesity and T2D and developing therapies for these diseases, with limitations including lack of hypothalamus, isolated islets of Langerhans, longitudinal data, and body fat percentage. [Display omitted] • Cynomolgus monkey models of obesity and type 2 diabetes were studied • Transcriptomics and proteomics of 27 tissues were profiled • Tissue-specific molecular signatures were depicted for obesity and type 2 diabetes • Publicly available web-based resources were created for data mining Zhang et al. studied cynomolgus monkeys with obesity and type 2 diabetes and profiled the transcriptomics and proteomics of 27 tissues. They offer a valuable resource for exploring the complex molecular mechanism underlying obesity and type 2 diabetes as well as prioritizing biomarkers and therapeutic targets for these diseases. [ABSTRACT FROM AUTHOR]

We report the implementation of a parallel microscopy system (96 Eyes) that is capable of simultaneous imaging of all wells on a 96-well plate. The optical system consists of 96 microscopy units, where each unit is made out of a four element objective, made through a molded injection process, and a low cost CMOS camera chip. By illuminating the sample with angle varying light and applying Fourier Ptychography, we can improve the effective brightfield imaging numerical aperture of the objectives from 0.23 to 0.3, and extend the depth of field from ±5 μm to ±15 μm. The use of Fourier Ptychography additionally allows us to computationally correct the objectives' aberrations out of the rendered images, and provides us with the ability to render phase images. The 96 Eyes acquires raw data at a rate of 0.7 frame per second (all wells) and the data are processed with 4 cores of graphical processing units (GPUs; GK210, Nvidia Tesla K80, USA). The system is also capable of fluorescence imaging (excitation = 465 nm, emission = 510 nm) at the native resolution of the objectives. We demonstrate the capability of this system by imaging S1P1-eGFP-Human bone osteosarcoma epithelial (U2OS) cells. [ABSTRACT FROM AUTHOR]