Single-cell transcriptomic analysis of decidual immune cell landscape in the occurrence of adverse pregnancy outcomes induced by Toxoplasma gondii infection.

BACKGROUND: Toxoplasma gondii is an obligate intracellular parasite that can lead to adverse pregnancy outcomes, particularly in early pregnancy. Previous studies have illustrated the landscape of decidual immune cells. However, the landscape of decidual immune cells in the maternal-fetal microenvironment during T. gondii infection remains unknown. METHODS: In this study, we employed single-cell RNA sequencing to analyze the changes in human decidual immune cells following T. gondii infection. The results of scRNA-seq were further validated with flow cytometry, reverse transcription-polymerase chain reaction, western blot, and immunofluorescence staining. RESULTS: Our results showed that the proportion of 17 decidual immune cell clusters and the expression levels of 21 genes were changed after T. gondii infection. Differential gene analysis demonstrated that T. gondii infection induced the differential expression of 279, 312, and 380 genes in decidual NK cells (dNK), decidual macrophages (dMφ), and decidual T cells (dT), respectively. Our results revealed for the first time that several previously unknown molecules in decidual immune cells changed following infection. This result revealed that the function of maternal-fetal immune tolerance declined, whereas the killing ability of decidual immune cells enhanced, eventually contributing to the occurrence of adverse pregnancy outcomes. CONCLUSIONS: This study provides valuable resource for uncovering several novel molecules that play an important role in the occurrence of abnormal pregnancy outcomes induced by T. gondii infection.

Dataset of process-structure-property feature relationships for AlSi10Mg material fabricated using laser powder bed fusion additive manufacturing.

This dataset reports microstructure and mechanical property features of AlSi10Mg manufactured using laser powder bed fusion over a wide range of processing conditions. Samples were fabricated with different combinations of laser power, scan speed, and hatch spacing to probe dense regimes as well as porous samples resulting from keyholing and lack of fusion. Pore and grain/sub-grain features for each processing set were quantified. Sample porosity was measured using Archimedes density measurements and X-ray computed tomography (XCT). XCT was also used to characterize the surface roughness of samples along with pore size and morphology. Electron backscatter diffraction (EBSD) was used to characterize the grain size and morphology while scanning electron microscope (SEM) imaging and was used to measure solidification cell size. Uniaxial tension tests were performed to ascertain yield and ultimate tensile strengths, elongation, and elastic modulus, and microhardness was measured using Vickers indentation.

Clinical Application of Individualized 3D-Printed Chest Wall Conformal Device in IMRT for Post-Mastectomy Breast Cancer.

Background Breast cancer is the most common malignant tumour in women. Radical mastectomy with postoperative radiotherapy is now the standard treatment for locally advanced breast cancer. Intensity-modulated radiotherapy (IMRT) has now been developed, which employs linear accelerators to deliver precise radiation to a tumour while minimizing the dose to surrounding normal tissue. It significantly improves the efficacy of breast cancer treatment. However, there are still some flaws that must be addressed. Objective To assess the clinical application of the three-dimensional (3D)-printed chest wall conformal device for breast cancer patients who need to be treated by chest wall intensity modulated radiotherapy (IMRT) after radical mastectomy. Methods The 24 patients were divided into three groups. During a computed tomography (CT) scan, patients in the study group were fixed by a 3D-printed chest wall conformal device, nothing in control group A, and a traditional 1-cm thick silica gel compensatory pad on the chest wall in control group B. The parameters of mean Dmax, Dmean, D2%, D50%, D98%, the conformity index (CI), and the homogeneity index (HI) of the planning target volume (PTV) are compared. Results The study group had the best dose uniformity (HI = 0.092) and the highest conformation (CI = 0.97), the worst in control group A (HI = 0.304, CI = 0.84). The mean Dmax, Dmean, and D2% of the study group were lower than control groups A and B (p<0.05). The mean D50% was higher than control group B (p<0.05), while the mean D98% was higher than control groups A and B (p<0.05). The mean Dmax, Dmean, D2%, and HI of control group A were higher than control group B (p<0.05), whereas the mean D98% and CI were lower than control group B (p<0.05). Conclusion By improving the efficacy of postoperative radiotherapy for breast cancer, using 3D-printed chest wall conformal devices may greatly improve the accuracy of repeating position fixation, increase the dose on the skin surface of the chest wall, optimise the dose distribution of the target area, and thus further reduce tumour recurrence and prolong patients' survival.

Improved optical properties of perovskite solar cells by introducing Ag nanopartices and ITO AR layers.

Embedded noble metal nanostructures and surface anti-reflection (AR) layers affect the optical properties of methylammonium lead iodide (CH3NH3PbI3) perovskite solar cells significantly. Herein, by employing a combined finite element method and genetic algorithm approach, we report five different types of CH3NH3PbI3 perovskite solar cells by introducing embedded Ag nanoparticles within the CH3NH3PbI3 layer and/or top ITO cylinder grating as an AR layer. The maximum photocurrent was optimized to reach 23.56 mA/cm2, which was 1.09/1.17 times higher than Tran's report/ flat cases. It is also comparable with values (23.6 mA/cm2) reported in the literature. The calculations of the electric field and charge carrier generation rate of the optimized solar cell further confirms this improvement than flat cases. It attributes to the synergistic effect of the embedded Ag nanoparticles and ITO AR layer. The results obtained herein hold great promise for future boosting the optical efficiency of perovskite solar cells.

Fabrication of a sandwiched silicalite-1 membrane in a 2D confined space for enhanced alcohol/water separation.

A dense zeolite layer with a thickness of approximately 500 nm was demonstrated by a confined-space strategy in a sandwiched mode of (SiO2)/(silicalite-1)/(SiO2). The gel-free secondary growth methodology bypasses the post-calcination step, avoiding excess energy consumption and possible film damage. Significantly enhanced pervaporation separation was observed with separation factors of 136 and 113, and fluxes of 2.3 and 2.2 kg m-2 h-1 for ethanol/n-butanol aqueous solutions, respectively. In addition, the membrane stability was confirmed by the 14 day pervaporation test.

Numerical investigation of plasmon sensitivity and surface-enhanced Raman scattering enhancement of individual TiN nanosphere multimers.

Titanium nitride (TiN) nanoparticles have recently been considered as potential candidate plasmonic materials; such materials support localized surface plasmon resonances (LSPRs) and show excellent thermal stability with a high melting point. The electromagnetic (EM) field coupling and gap distance between components of individual TiN nanosphere multimers are critical parameters affecting their plasmonic sensitivity and surface-enhanced Raman scattering (SERS) performance, both of which are numerically investigated by the finite element method. It is demonstrated that the fractional shifts of both the dipolar LSPR wavelength [Formula: see text] and the refractive index sensitivity factor S follow the universal 'plasmon ruler' behavior, which is explained well in terms of EM field distribution. The response of the obtained S to [Formula: see text] is also presented and elucidated in terms of the optical response of the dielectric constants of TiN. The maximum S and SERS enhancement (excited by three normally available lasers in experiments) are also predicted; both are comparable to the values for Au dimeric nanoparticles. The present work holds great promise for the development of non-noble metal plasmonic materials in both SERS and plasmonic sensing applications.

A reference peptide database for proteome quantification based on experimental mass spectrum response curves.

Motivation: Mass spectrometry (MS) based quantification of proteins/peptides has become a powerful tool in biological research with high sensitivity and throughput. The accuracy of quantification, however, has been problematic as not all peptides are suitable for quantification. Several methods and tools have been developed to identify peptides that response well in mass spectrometry and they are mainly based on predictive models, and rarely consider the linearity of the response curve, limiting the accuracy and applicability of the methods. An alternative solution is to select empirically superior peptides that offer satisfactory MS response intensity and linearity in a wide dynamic range of peptide concentration. Results: We constructed a reference database for proteome quantification based on experimental mass spectrum response curves. The intensity and dynamic range of over 2 647 773 transitions from 121 318 peptides were obtained from a set of dilution experiments, covering 11 040 gene products. These transitions and peptides were evaluated and presented in a database named SCRIPT-MAP. We showed that the best-responder (BR) peptide approach for quantification based on SCRIPT-MAP database is robust, repeatable and accurate in proteome-scale protein quantification. This study provides a reference database as well as a peptides/transitions selection method for quantitative proteomics. Availability and implementation: SCRIPT-MAP database is available at http://www.firmiana.org/responders/. Supplementary information: Supplementary data are available at Bioinformatics online.

High-throughput absolute quantification of proteins using an improved two-dimensional reversed-phase separation and quantification concatemer (QconCAT) approach.

Stable isotope dilution-selective reaction monitoring-mass spectrometry (SID-SRM-MS) has been widely used for the absolute quantitative analysis of proteins. However, when performing the large-scale absolute quantification of proteins from a more complex tissue sample, such as mouse liver, in addition to a high-throughput approach for the preparation and calibration of large amounts of stable-isotope-labelled internal standards, a more powerful separation method prior to SRM analysis is also urgently needed. To address these challenges, a high-throughput absolute quantification strategy based on an improved two-dimensional reversed-phase (2D RP) separation and quantification concatemer (QconCAT) approach is presented in this study. This strategy can be used to perform the simultaneous quantification of hundreds of proteins from mouse liver within one week of total MS measurement time. By using calibrated synthesised peptides from the protein glutathione S-transferase (GST), large amounts of GST-tagged QconCAT internal standards corresponding to hundreds of proteins can be accurately and rapidly quantified. Additionally, using an improved 2D RP separation method, a mixture containing a digested sample and QconCAT standards can be efficiently separated and absolutely quantified. When a maximum gradient of 72 min is employed in the first LC dimension, resulting in 72 fractions, identification and absolute quantification experiments for all fractions can be completed within one week of total MS measurement time. The quantification approach developed here can further extend the dynamic range and increase the analytical sensitivity of SRM analysis of complex tissue samples, thereby helping to increase the coverage of absolute quantification in a whole proteome.

A fast workflow for identification and quantification of proteomes.

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.

In-depth proteomic characterization of endogenous nuclear receptors in mouse liver.

Nuclear receptors (NRs) are a superfamily of transcription factors that, upon binding to ligands, bind specific DNA sequences and regulate a transcriptional program governing cell proliferation, differentiation, and metabolism. In the liver, by sensing lipid-soluble hormones and dietary lipids and governing the expression of key liver metabolic genes, NR proteins direct a large array of key hepatic functions that include lipid and glucose metabolism, bile secretion, and bile acid homeostasis. Although much has been learned about the physiology of NRs, little is known about their protein expression and DNA binding activity in the liver because of their low abundance and the lack of high-throughput methods for detection at the protein level. Here we report a method for profiling the DNA binding activity of the NR transcription factor superfamily in mouse liver. We use DNA constructs of hormone response elements (HREs) as affinity reagents to enrich NR proteins from nuclear extracts of mouse liver and then identify them using mass spectrometry. We evaluated 20 DNA constructs containing various combinations of HREs for their ability to enrich endogenous NR proteins and found that two different HREs are sufficient to achieve isolation and identification of nearly all endogenous NR proteins from one mouse liver. We have detected proteins for 35 members of the NR family out of 41 that are expressed in mouse liver at mRNA level. Thus, this method allows coverage of most of the whole NR proteome and establishes a practical assay for the investigation of NR actions in mouse liver. We anticipate that this method will find widespread use in future investigations of NR actions in liver biology and pathology. Furthermore, this workflow is a useful tool for NR biologists interested in measuring NR expression, DNA binding, post-translational modifications, cellular localization, and other functional aspects of NRs in organs under normal physiological and pathological conditions, as well as during pharmacological intervention.