Upregulated CD8+ MAIT cell differentiation and KLRD1 gene expression after inactivated SARS-CoV-2 vaccination identified by single-cell sequencing

BackgroundThe primary strategy for reducing the incidence of COVID-19 is SARS-CoV-2 vaccination. Few studies have explored T cell subset differentiation and gene expressions induced by SARS-CoV-2 vaccines. Our study aimed to analyze T cell dynamics and transcriptome gene expression after inoculation with an inactivated SARS-CoV-2 vaccine by using single-cell sequencing.MethodsSingle-cell sequencing was performed after peripheral blood mononuclear cells were extracted from three participants at four time points during the inactivated SARS-CoV-2 vaccination process. After library preparation, raw read data analysis, quality control, dimension reduction and clustering, single-cell T cell receptor (TCR) sequencing, TCR V(D)J sequencing, cell differentiation trajectory inference, differentially expressed genes, and pathway enrichment were analyzed to explore the characteristics and mechanisms of postvaccination immunodynamics.ResultsInactivated SARS-CoV-2 vaccination promoted T cell proliferation, TCR clone amplification, and TCR diversity. The proliferation and differentiation of CD8+ mucosal-associated invariant T (MAIT) cells were significantly upregulated, as were KLRD1 gene expression and the two pathways of nuclear-transcribed mRNA catabolic process, nonsense-mediated decay, and translational initiation.ConclusionUpregulation of CD8+ MAIT cell differentiation and KLRD1 expression after inactivated SARS-CoV-2 vaccination was demonstrated by single-cell sequencing. We conclude that the inactivated SARS-CoV-2 vaccine elicits adaptive T cell immunity to enhance early immunity and rapid response to the targeted virus

Multielements determination and metal transfer investigation in herb medicine Bupleuri Radix by inductively coupled plasma‐mass spectrometry

Bupleuri Radix is a famous traditional Chinese medicine (TCM ) and an important raw material in TCM patent prescriptions. It is widely used in several countries, including China, Japan, South Korea, and America. However, the impact of heavy metal transfer rules on TCM s remains unknown. In this study, a total of 45 paired original medicines (OM s), decoction pieces (DP s), and vinegar‐processed (VP s) samples were simultaneously determined via inductively coupled plasma‐mass spectrometry after a microwave digestion. The concentrations of the elements were shown at three levels: (a) Al and Fe at the mg/g level; (b) Pb, Cu, Ba, Mn, Cr, and Ni at the mg/kg level; (c) Co, As, Cd, and Hg at μg/kg level. It is worth noting that the Cu levels were found to exceed the maximum concentration set by Chinese legislation (20.0 mg/kg). In addition, Mn, Ni, and Cu levels were higher in samples from the Gansu province than those from other provinces. The accumulation of the heavy metals decreased in the order of OM s > DP s > VP s; this was especially true for the Al and Fe levels. Furthermore, the results indicate that decocting the samples may reduce the intake of heavy metals. The element transfer ratios for decoctions were under 50% compared to herbal medicines and decreased in the order of Co > As > Mn > Hg > other metals. Our study strongly suggests that long‐term and regular monitoring for heavy metals in the plant is necessary

Accumulation of Arsenic Speciation and In Vivo Toxicity Following Oral Administration of a Chinese Patent Medicine Xiao-Er-Zhi-Bao-Wan in Rats

Realgar-containing traditional Chinese medicines such as Xiao-Er-Zhi-Bao-Wan (XEZBW), have been widely used for thousands of years. However, events associated with arsenic-induced ailments have increasingly become a public concern. To address the toxicity of XEZBW, we studied the histopathology and blood biochemistry of rats exposed to XEZBW using technology like high-performance liquid chromatography-inductively coupled mass spectrometry to determine arsenic speciation. Our results demonstrated that dimethylarsinic acid (DMA) increased from 18.57 ± 7.45 to 22.74 ± 7.45 ng/g in rat kidney after oral administration for 7 and 14 days, which was 10-fold higher than the levels observed in controls. Trivalent arsenite As(III) showed a large increase on day 7 (26.99 ± 1.98 ng/g), followed by a slight decrease on day 14 (13.67 ± 6.48 ng/g). Total arsenic levels on day 7 (185.52 ± 24.56 ng/g) and day 14 (198.57 ± 26.26 ng/g) were nearly twofold higher than that in the control group (92.77 ± 14.98 ng/g). Histopathological analysis showed mild injury in the liver and kidney of rats subjected to oral administration of realgar for 14 days. As in the XEZBW groups, a mild injury in these organs was observed after administration for 14 days. This study inferred that the toxicity of arsenic was concentration- and time-dependent. The accumulation of DMA, a byproduct of choline metabolism, was responsible for inducing higher toxicity. Therefore, we concluded that measuring the levels of DMA, instead of total arsenic, might be more suitable for evaluating the toxicity of realgar-containing traditional Chinese medicines

Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe

To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions

A Rapid Label-Free Fluorescent Aptasensor PicoGreen-Based Strategy for Aflatoxin B1 Detection in Traditional Chinese Medicines

Aflatoxin B1 (AFB1) is a very hazardous carcinogen, readily contaminating foodstuffs and traditional Chinese medicines (TCMs) that has inspired increasing health concerns due to dietary exposure. Colloidal nanocrystals have been proposed as optical labels for aptasensor assembly, but these typically require tedious multistep conjugation and suffer from unsatisfactory robustness when used for complex matrices. In the present study, we report a rapid and sensitive method for screening for trace AFB1 levels in TCMs using a label-free fluorescent aptasensor PicoGreen dye-based strategy. Using PicoGreen to selectively measure complementary double-stranded DNA, fluorescence enhancement due to dsDNA is ‘turned off’ in the presence of AFB1 due binding of aptamer target over complementary sequence. Self-assembly of a label-free fluorescent aptasensor based on AFB1 aptamer and PicoGreen dye was performed. Due to competition between the complementary sequence and AFB1 target, this rapid method was capable of highly sensitive and selective screening for AFB1 in five types of TCMs. This proposed approach had a limit of detection as low as 0.1 μg·L−1 and good linearity with a range of 0.1–10 μg·L−1 (0.1–10 ppb). Among the 20 samples tested, 6 batches were found to be contaminated with AFB1 using this method, which was confirmed using sophisticated liquid chromatography-electrospray ionization-tandem mass spectrometry/mass spectrometry analysis. The results of this study indicate the developed method has the potential to be a simple, quick, and sensitive tool for detecting AFB1 in TCMs

A metabolic map and artificial intelligence-aided identification of nasopharyngeal carcinoma via a single-cell Raman platform

Nasopharyngeal carcinoma (NPC) is a complex cancer influenced by various factors. This study explores the use of single-cell Raman spectroscopy as a potential diagnostic tool for investigating biomolecular changes associated with NPC carcinogenesis. Seven NPC cell lines, one immortalised nasopharyngeal epithelial cell line, six nasopharyngeal mucosa tissues and seven NPC tissue samples were analysed by performing confocal Raman spectroscopic measurements and imaging. The single-cell Raman spectral dataset was used to quantify relevant biomolecules and build machine learning classification models. Metabolomic profiles were investigated using ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). By generating a metabolic map of seven NPC cell lines, we identified an interplay of altered metabolic processes involving nucleic acids, amino acids, lipids and sugars. The results from spatially resolved Raman maps and UPLC-MS/MS metabolomics were consistent, revealing an increase of unsaturated fatty acids in cancer cells, particularly in highly metastatic 5-8F and poorly differentiated CNE2 cells. The classification model achieved a nearly perfect classification when identifying NPC and non-NPC cells with an ROC-AUC of 0.99 and a value of 0.97 when identifying 13 tissue samples. This study unveils a complex interplay of metabolic network and highlights the potential roles of unsaturated fatty acids in NPC progression and metastasis. This renders further research to provide deeper insights into NPC pathogenesis, identify new metabolic targets and improve the efficacy of targeted therapies in NPC. Artificial intelligence-aided analysis of single-cell Raman spectra has achieved high accuracies in the classification of both cancer cells and patient tissues, paving the way for a simple, less invasive and accurate diagnostic test

Redefining the Incidence and Profile of Fluoropyrimidine-Associated Cardiotoxicity in Cancer Patients: A Systematic Review and Meta-Analysis

Aim: The cardiac toxicity that occurs during administration of anti-tumor agents has attracted increasing concern. Fluoropyrimidines have been used for more than half a century, but their cardiotoxicity has not been well clarified. In this study, we aimed to assess the incidence and profile of fluoropyrimidine-associated cardiotoxicity (FAC) comprehensively based on literature data. Methods: A systematic literature search was performed using PubMed, Embase, Medline, Web of Science, and Cochrane library databases and clinical trials on studies investigating FAC. The main outcome was a pooled incidence of FAC, and the secondary outcome was specific treatment-related cardiac AEs. Random or fixed effects modeling was used for pooled meta-analyses according to the heterogeneity assessment. PROSPERO registration number: (CRD42021282155). Results: A total of 211 studies involving 63,186 patients were included, covering 31 countries or regions in the world. The pooled incidence of FAC, by meta-analytic, was 5.04% for all grades and 1.5% for grade 3 or higher. A total of 0.29% of patients died due to severe cardiotoxicities. More than 38 cardiac AEs were identified, with cardiac ischemia (2.24%) and arrhythmia (1.85%) being the most frequent. We further performed the subgroup analyses and meta-regression to explore the source of heterogeneity, and compare the cardiotoxicity among different study-level characteristics, finding that the incidence of FAC varied significantly among different publication decades, country/regions, and genders. Patients with esophagus cancer had the highest risk of FAC (10.53%), while breast cancer patients had the lowest (3.66%). The treatment attribute, regimen, and dosage were significantly related to FAC. When compared with chemotherapeutic drugs or targeted agents, such a risk was remarkably increased (χ2 = 10.15, p 2 = 10.77, p < 0.01). The continuous 5-FU infusion for 3–5 consecutive days with a high dosage produced the highest FAC incidence (7.3%) compared with other low-dose administration patterns. Conclusions: Our study provides comprehensive global data on the incidence and profile of FAC. Different cancer types and treatment appear to have varying cardiotoxicities. Combination therapy, high cumulative dose, addition of anthracyclines, and pre-existing heart disease potentially increase the risk of FAC