Boelmaher4947
001). Higher antibody titers were induced by a single dose in previously SARS-CoV-2 infected individuals than those induced in naïve subjects by two doses of the vaccine (p less then 0.0001). Three months after the second dose both groups showed a decline in antibody levels, being more abrupt in unexposed subjects. Overall, our results showed a trend towards lower antibody concentrations over time following BBIBP-CorV vaccination. Sex and age seem to influence the magnitude of the humoral response in unexposed subjects while the combination of exposure to SARS-CoV-2 plus vaccination, whatever the sequence of the events was, produced a sharp increase in antibody levels. Evaluation of the humoral responses over time and the analysis of the induction and persistence of memory B and T cell responses, are needed to assess long-term immune protection induced by BBIBP-CorV vaccine.Surgical resection is the most common and effective option for the clinical treatment of lung cancer. Postoperative pain may activate surgically induced stress response, leading to a decrease in human immune function. However, conventional analgesics such as morphine and its derivatives have been reported to have immunosuppressive side effects. In the critical period after surgery, the immunosuppressive effect of analgesics on patients with lung cancer could promote postoperative cancer recurrence and metastasis. Therefore, it will be an ideal scenario for postoperative pain management to maximize pain relief while minimizing immunosuppression side effects. In this study, we found that a novel mixed agonist-antagonist opioid analgesic, dezocine, significantly promoted the morphological maturation of dendritic cells (DCs), and increase the expression of DCs-related surface markers in postoperative peripheral blood of patients with lung cancer. Furthermore, dezocine-matured DCs increased the general immune response by promoting the secretion of IL-12 and IL-6 cytokines and enhancing the proliferation and cytotoxicity of CD8+ T cells. Then genome-wide transcriptomic profiling analyses were performed to identify the specific gene expression of dezocine-matured DCs. The results of transcriptomic analysis as well as in vitro validation showed that the upregulation of CXCL10, CD3G, and GRB2 were significantly associated with dezocine-induced DCs maturation. Overall, our data showed that dezocine might exhibit unique properties by acting as an immunostimulant, which provides new evidence for its application in postoperative pain management of patients with lung cancer.One of the most laborious for drug discovery is to select compounds from a library for experimental evaluation. Hence, we propose a machine learning model only needs to be trained on a small dataset to predict the inhibition constant (Ki) and half maximal inhibitory concentration (IC50) for a compound. We transfer the prediction task to a simpler binary classification task based on a naive but effective idea that we only need the related rank of a compound to determine whether to take it for further examination. To achieve this, we design a data augmentation strategy to effectively leverage the relationship between the compounds in the training set. After that, we formulate a new reward function for deep reinforcement learning to balance the feature selection and the accuracy. We employ a particle swarm optimized support vector machine for the binary classification task. Finally, a soft voting mechanism is introduced to solve the contradiction from the binary classification. Sufficient experiments show that our model achieves high and reliable accuracy, and is capable of ranking compounds based on a selected set of molecular descriptors. The current results show that our model provides a potential ligand-based in silico approach for prioritizing chemicals for experimental studies.
The development of Cone-beam X-ray luminescence computed tomography (CB-XLCT) has allowed the quantitative in-depth biological imaging, but with a greatly ill-posed and ill-conditioned inverse problem. Although the predefined permissible source region (PSR) is a widely used way to alleviate the problem for CB-XLCT imaging, how to obtain the accurate PSR is still a challenge for the process of inverse reconstruction.
We proposed an optimized prior knowledge via a sparse non-convex approach (OPK_SNCA) for CB-XLCT imaging. Firstly, non-convex L
-norm optimization model was employed for copying with the inverse problem, and an iteratively reweighted split augmented lagrangian shrinkage algorithm was developed to obtain a group of sparse solutions based on different non-convex p values. Secondly, a series of permissible regions (PRs) with different discretized mesh was further achieved, and the intersection operation was implemented on the group of PRs to get a reasonable PSR. After that, the final PSR was adopted as an optimized prior knowledge to enhance the reconstruction quality of inverse reconstruction.
Both simulation experiments and in vivo experiment were performed to evaluate the efficiency and robustness of the proposed method.
The experimental results demonstrated that our proposed method could significantly improve the imaging quality of the distribution of X-ray-excitable nanophosphors for CB-XLCT.
The experimental results demonstrated that our proposed method could significantly improve the imaging quality of the distribution of X-ray-excitable nanophosphors for CB-XLCT.
Torque teno virus (TTV) DNA load in plasma directly associates with the net state of immunosuppression and inflammation in different clinical settings, including transplantation and chronic inflammatory diseases.
We investigated whether plasma TTV DNA load may predict the occurrence of certain infectious events and overall mortality in critically ill COVID-19 patients.
50 patients (median age, 65.5 years) were recruited. MPP+ iodide TTV DNA load was quantitated in serial plasma specimens by real-time PCR. Serum levels of interleukin-6, C-reactive protein, ferritin, lactate dehydrogenase, Gamma-Glutamyl Transferase (GGT), alanine transaminase (ALT) and aspartate transaminase (AST) and absolute lymphocyte counts (ALC) in paired specimens were available. Nosocomial bloodstream infections and ventilator-associated pneumonia and overall mortality were the clinical outcomes.
TTV DNA was detected in 38 patients (76%). A weak inverse correlation (Rho=-0.28; P=0.004) was observed between TTV DNA loads and ALC. No direct correlation was found between TTV DNA load and serum levels of any of the above biomarkers. Patients with detectable TTV DNA had an increased risk of subsequently developing infectious events (HR 9.28; 95% CI, 1.29-69.5; P=0.03). A trend (P=0.05) towards higher TTV DNA area under a curve between days 7 and 17 after ICU admission (AUC
) was observed in patients who died, as compared to survivors.
Our findings suggested that plasma TTV DNA load monitoring may be helpful for predicting the occurrence of severe nosocomial infections and mortality in critically ill COVID-19 patients.
Our findings suggested that plasma TTV DNA load monitoring may be helpful for predicting the occurrence of severe nosocomial infections and mortality in critically ill COVID-19 patients.A meta-analysis of existing and available Illumina 16S rRNA datasets from drinking water source, treatment and drinking water distribution systems (DWDS) were collated to compare changes in abundance and diversity throughout. Samples from bulk water and biofilm were used to assess principles governing microbial community assembly and the value of amplicon sequencing to water utilities. Individual phyla relationships were explored to identify competitive or synergistic factors governing DWDS microbiomes. The relative importance of stochasticity in the assembly of the DWDS microbiome was considered to identify the significance of source and treatment in determining communities in DWDS. Treatment of water significantly reduces overall species abundance and richness, with chlorination of water providing the most impact to individual taxa relationships. The assembly of microbial communities in the bulk water of the source, primary treatment process and DWDS is governed by more stochastic processes, as is the DWDS biofilm. DWDS biofilm is significantly different from bulk water in terms of local contribution to beta diversity, type and abundance of taxa present. Water immediately post chlorination has a more deterministic microbial assembly, highlighting the significance of this process in changing the microbiome, although elevated levels of stochasticity in DWDS samples suggest that this may not be the case at customer taps. 16S rRNA sequencing is becoming more routine, and may have several uses for water utilities, including detection and risk assessment of potential pathogens such as those within the genera of Legionella and Mycobacterium; assessing the risk of nitrification in DWDS; providing improved indicators of process performance and monitoring for significant changes in the microbial community to detect contamination. Combining this with quantitative methods like flow cytometry will allow a greater depth of understanding of the DWDS microbiome.The aim of this study was to investigate the feasibility that the suppression of acidity in anaerobic digestion of kitchen wastes could be alleviated with additional electric field. The results showed that, the accumulation of acidity seriously suppressed methanogenesis, and no methane was detected in the electrode-supplemented digester without applied voltage. In contrast, with applied voltages of 0.6-1.2 V, the suppression of acidity was alleviated, and methane production rates reached 558-669 L/kg-volatile suspended solid that were higher than that previously reported with carbon-based conductive materials, such as granular active carbon and biochar. Although the reduced peak with a potential ranging from -0.3 V to -0.2 V close to the reduced potential of CO2/CH4 detected via cyclic voltammetry, the maximum methane yield derived from cathodic reduction of CO2 only accounted for 0.13-0.33% of total methane yield with applied voltages. Microbial community analysis showed that, Methanosarcina species were specially enriched with applied voltages, accounting for ca. 40-70% of the communities. Together with the increase in the relative abundance of Syntrophomonas species, Methanosarcina species directly accepting electrons from Syntrophomonas species via DIET might be the primary reason for alleviating the suppression of acidity. Further investigations via three-dimensional excitation emission matrix and in-situ electrochemical Fourier transform infrared spectroscopy found that additional electric field stimulated the secretion of EPS primarily comprised of protein-like substance, which might mediate the EET between Syntrophomonas and Methanosarcina species.Viruses are present at low concentrations in wastewater; therefore, an effective method for concentrating virus particles is necessary for accurate wastewater-based epidemiology (WBE). We designed a novel approach to concentrate human and animal viruses from wastewater using porcine gastric mucin-conjugated magnetic beads (PGM-MBs). We systematically evaluated the performances of the PGM-MBs method (sensitivity, specificity, and robustness to environmental inhibitors) with six viral species, including Tulane virus (a surrogate for human norovirus), rotavirus, adenovirus, porcine coronavirus (transmissible gastroenteritis virus or TGEV), and two human coronaviruses (NL63 and SARS-CoV-2) in influent wastewater and raw sewage samples. We determined the multiplication factor (the ratio of genome concentration of the final solution to that of the initial solution) for the PGM-MBs method, which ranged from 1.3 to 64.0 depending on the viral species. Because the recovery efficiency was significantly higher when calculated with virus titers than it was with genome concentration, the PGM-MBs method could be an appropriate tool for assessing the risk to humans who are inadvertently exposed to wastewater contaminated with infectious viruses.
