LncRNA TONSL-AS1 participates in coronary artery disease by interacting with miR-197.

BACKGROUND: It has been reported that high expression levels of miR-197 can predict coronary artery disease (CAD). Our bioinformatics analysis showed that miR-197 may bind to long non-coding RNA (lncRNA) TONSL-AS1. This study aimed to investigate the role of TONSL-AS1 in CAD. METHODS: This study included 60 CAD patients and 60 healthy controls. Coronary angiography was performed to diagnose CAD. The interaction between TONSL-AS1 and miR-197 was predicted by IntaRNA2.0. Western-blot analysis was performed to illustrate the effect of MTONSL-AS1, miR-197 and BCL2 on human primary coronary artery endothelial cells (HCAECs). Cell migration assay was performed to explore the roles of MTONSL-AS1, miR-197 and BCL2 in regulating cell migration. Cell apoptosis assay was performed to investigate the role of MTONSL-AS1, miR-197 and BCL2 in regulating the apoptosis of HCAECs. RESULT: Significant differences in high-density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and gensini score were observed in patients with CAD. In addition, TONSL-AS1 was downregulated in CAD. Follow-up study revealed that low expression levels of TONSL-AS1 and high expression levels of miR-197 predicted poor survival of CAD patients. Overexpression experiments showed that TONSL-AS1 and miR-197 had no significant effect on the expression of each other. We speculated that MAFG-AS1 may sponge miR-145. Moreover, overexpression of TONSL-AS1 increased, while overexpression of miR-197 decreased the expression levels of BCL2. Furthermore, overexpression of TONSL-AS1 attenuated the effects of overexpression of miR-197 on migration and apoptosis of HCAECs. CONCLUSIONS: Therefore, the expression of TONSL-AS1 predicted the survival of CAD patients and it sponged miR-197 to inhibit the apoptosis of HCAECs.

Antibiotic pollution promotes dominance by harmful cyanobacteria: A case study examining norfloxacin exposure in competition experiments.

Cyanobacterial harmful algal blooms (cyanoHABs) in freshwater lakes across the globe are often combined with other stressors. Pharmaceutical pollution, especially antibiotics in water bodies, poses a potential hazard in aquatic ecosystems. However, how antibiotics influence the risk of cyanoHABs remains unclear. Here, we investigated the effects of norfloxacin (NOR), one of the most widely used antibiotics globally, to a bloom-forming cyanobacterium (Microcystis aeruginosa) and a common green alga (Scenedesmus quadricauda), under both mono- and coculture conditions. Taxon-specific responses to NOR were evaluated in monoculture. In addition, the growth rate and change in ratio of cyanobacteria to green algae when cocultured with exposure to NOR were determined. In monocultures of Microcystis, exposure to low concentrations of NOR resulted in decreases in biomass, chlorophyll a and soluble protein content, while superoxide anion content and superoxide dismutase activity increased. However, NOR at high concentration only slightly affected Scenedesmus. During the co-culture trials of Microcystis and Scenedesmus, the 5 µg · L-1 NOR treatment increased the ratio of Microcystis to co-cultured Scenedesmus by 47.2%. Meanwhile, although Scenedesmus growth was enhanced by 4.2% under NOR treatment in monoculture, it was conversely inhibited by 63.4% and 38.2% when co-cultured with Microcystis with and without NOR, respectively. Our results indicate that antibiotic pollution has a potential risk to enhance the perniciousness of cyanoHABs by disturbing interspecific interaction between cyanobacteria and green algae. These results reinforce the need for scientists and managers to consider the influence of xenobiotics in shaping the outcome of interactions among multiple species in aquatic ecosystems.

Self-calibrated atom-interferometer gyroscope by modulating atomic velocities.

Atom-interferometer gyroscopes have attracted much attention for their long-term stability and extremely low drift. For such high-precision instruments, self-calibration to achieve an absolute rotation measurement is critical. In this work, we propose and demonstrate the self-calibration of an atom-interferometer gyroscope. This calibration is realized by using the detuning of the laser frequency to control the atomic velocity, thus modulating the scale factor of the gyroscope. The modulation determines the order and the initial phase of the interference stripe, thus eliminating the ambiguity caused by the periodicity of the interferometric signal. This self-calibration method is validated through a measurement of the Earth's rotation rate, and a relative uncertainty of 162 ppm is achieved. Long-term stable and self-calibrated atom-interferometer gyroscopes have important applications in the fields of fundamental physics, geophysics, and long-time navigation.

Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia.

This study aims to develop and validate a machine learning (ML) predictive model for assessing mortality in patients with malignant tumors and hyperkalemia (MTH). We extracted data on patients with MTH from the Medical Information Mart for Intensive Care-IV, version 2.2 (MIMIC-IV v2.2) database. The dataset was split into a training set (75%) and a validation set (25%). We used the Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify potential predictors, which included clinical laboratory indicators and vital signs. Pearson correlation analysis tested the correlation between predictors. In-hospital death was the prediction target. The Area Under the Curve (AUC) and accuracy of the training and validation sets of 7 ML algorithms were compared, and the optimal 1 was selected to develop the model. The calibration curve was used to evaluate the prediction accuracy of the model further. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) enhanced model interpretability. 496 patients with MTH in the Intensive Care Unit (ICU) were included. After screening, 17 clinical features were included in the construction of the ML model, and the Pearson correlation coefficient was <0.8, indicating that the correlation between the clinical features was small. eXtreme Gradient Boosting (XGBoost) outperformed other algorithms, achieving perfect scores in the training set (accuracy: 1.000, AUC: 1.000) and high scores in the validation set (accuracy: 0.734, AUC: 0.733). The calibration curves indicated good predictive calibration of the model. SHAP analysis identified the top 8 predictive factors: urine output, mean heart rate, maximum urea nitrogen, minimum oxygen saturation, minimum mean blood pressure, maximum total bilirubin, mean respiratory rate, and minimum pH. In addition, SHAP and LIME performed in-depth individual case analyses. This study demonstrates the effectiveness of ML methods in predicting mortality risk in ICU patients with MTH. It highlights the importance of predictors like urine output and mean heart rate. SHAP and LIME significantly enhanced the model's interpretability.

Compact multi-channel radio frequency pulse-sequence generator with fast-switching capability for cold-atom interferometers.

Cold-atom interferometers have matured into a powerful tool for fundamental physics research, and they are currently moving from realizations in the laboratory to applications in the field. A radio frequency (RF) generator is an indispensable component of these devices for controlling lasers and manipulating atoms. In this work, we developed a compact RF generator for fast switching and sweeping the frequencies and amplitudes of atomic-interference pulse sequences. In this generator, multi-channel RF signals are generated using a field-programmable gate array (FPGA) to control eight direct digital synthesizers (DDSs). We further propose and demonstrate a method for pre-loading the parameters of all the RF pulse sequences to the DDS registers before their execution, which eliminates the need for data transfer between the FPGA and DDSs to change RF signals. This sharply decreases the frequency-switching time when the pulse sequences are running. Performance characterization showed that the generated RF signals achieve a 100 ns frequency-switching time and a 40 dB harmonic-rejection ratio. The generated RF pulse sequences were applied to a cold-atom-interferometer gyroscope, and the contrast of atomic interference fringes was found to reach 38%. This compact multi-channel generator with fast frequency/amplitude switching and/or sweeping capability will be beneficial for applications in field-portable atom interferometers.

Proteomics Study on the Differentially Expressed Proteins in c-fos-silenced Cells Exposed to PM 2.5.

OBJECTIVE: To investigate the effect of c-fos gene silencing on differentially expressed proteins (DEPs) in human bronchial epithelial (HBE) cells after exposure to fine particulate matter (PM 2.5). METHODS: HBE cells and c-fos-silenced HBE cells were exposed to 50 µg/mL PM 2.5, LC-MS/MS and tandem mass tag (TMT) labeling methods were combined with bioinformatics methods, and DEPs and interaction networks were identified. RESULTS: In the HBE group, 414 DEPs were screened, of which 227 were up-regulated and 187 down-regulated. In the c-fos silenced HBE group, 480 DEPs were screened, including 240 up-regulated proteins and 240 down-regulated proteins. KEGG annotations showed that DEPs in the HBE group are mainly concentrated in the glycolysis/gluconeogenesis pathway and those in the c-fos silenced group are concentrated mainly in endoplasmic reticulum and the processing of proteins. Additionally, the abnormal expression of GPRC5C, DKK4, and UBE2C was identified in top 15 DEPs. After constructing the protein interaction network, 20 Hub proteins including HNRNPA2B1, HNRNPL, RPS15A, and RPS25 were screened from the HBE group and the c-fos silenced HBE group. CONCLUSION: c-fos gene affected the expression of cancer-related proteins. Our results provided a scientific basis for further study of PM 2.5-induced carcinogenesis mechanism.

Study on DNA methylation in HEB cells exposed to PM(2.5) by application of methylation chip technology / 中华劳动卫生职业病杂志

Objective: To screen the differential methylation sites, genes and pathways of air pollution fine particles (PM(2.5)) on human bronchial epithelial (HBE) cells by methylation chip and bioinformation technology, so as to provide scientific basis for further study of the toxicological mechanism of PM(2.5) on HBE cells. Methods: In August 2020, HBE cells were infected with 10 μg/ml and 50 μg/ml PM(2.5) aqueous solution for 24 h, namely PM(2.5) 10 μg/ml exposure group (low dose group) and PM(2.5) 50 μg/ml exposure group (high dose group) ; uninfected HBE cells were used as control group. The DNA fragments were hybridized with the chip, the chip scanned and read the data, analyzed the data, screened the differential methylation sites, carried out GO analysis and KEGG analysis of the differential methylation sites, and analyzed the interaction relationship of the overall differential methylation sites by functional epigenetic modules (FEMs). Results: Compared with the control group, 127 differential methylation sites were screened in the low-dose group, including 89 genes, including 55 sites with increased methylation level and 72 sites with decreased methylation level. The differential methylation sites were mainly concentrated in the Body region and UTR region. Compared with the control group, 238 differential methylation sites were screened in the high-dose group, including 168 genes, of which 127 sites had increased methylation level and 111 sites had decreased methylation level. The differential heterotopic sites were mainly concentrated in the Body region and UTR region. Through FEMs analysis, 8 genes with the most interaction were screened, of which 6 genes had significant changes in methylation level. MALT1 gene related to apoptosis was found in the heterotopic site of methylation difference in low-dose group; PIK3CA and ARID1A genes related to carcinogenesis were found in the heterotopic sites of methylation difference in high-dose group; TNF genes related to tumor inhibition were found in the results of FEMs analysis. Conclusion: After PM(2.5) exposure to HBE cells, the DNA methylation level is significantly changed, and genes related to apoptosis and carcinogenesis are screened out, suggesting that the carcinogenic mutagenic effect of PM(2.5) may be related to DNA methylation.