Systematic Identification of Spontaneous Preterm Birth-Associated RNA Transcripts in Maternal Plasma

<div><h3>Background</h3><p>Spontaneous preterm birth (SPB, before 37 gestational weeks) is a major cause of perinatal mortality and morbidity, but its pathogenesis remains unclear. Studies on SPB have been hampered by the limited availability of markers for SPB in predelivery clinical samples that can be easily compared with gestational age-matched normal controls. We hypothesize that SPB involves aberrant placental RNA expression, and that such RNA transcripts can be detected in predelivery maternal plasma samples, which can be compared with gestational age-matched controls.</p> <h3>Principal Findings</h3><p>Using gene expression microarray to profile essentially all human genes, we observed that 426 probe signals were changed by >2.9-fold in the SPB placentas, compared with the spontaneous term birth (STB) placentas. Among the genes represented by those probes, we observed an over-representation of functions in RNA stabilization, extracellular matrix binding, and acute inflammatory response. Using RT-quantitative PCR, we observed differences in the RNA concentrations of certain genes only between the SPB and STB placentas, but not between the STB and term elective cesarean delivery placentas. Notably, 36 RNA transcripts were observed at placental microarray signals higher than a threshold, which indicated the possibility of their detection in maternal plasma. Among them, the <em>IL1RL1</em> mRNA was tested in plasma samples taken from 37 women. It was detected in 6 of 10 (60%) plasma samples collected during the presentation of preterm labor (≤32.9 weeks) in women eventually giving SPB, but was detected in only 1 of 27 (4%) samples collected during matched gestational weeks from women with no preterm labor (Fisher exact test, p = 0.00056).</p> <h3>Conclusion</h3><p>We have identified 36 SPB-associated RNA transcripts, which are possibly detectable in maternal plasma. We have illustrated that the <em>IL1RL1</em> mRNA was more frequently detected in predelivery maternal plasma samples collected from women resulting in SPB than the gestational-age matched controls.</p> </div

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Prognostic Model of COVID-19 Severity and Survival among Hospitalized Patients Using Machine Learning Techniques

We conducted a statistical study and developed a machine learning model to triage COVID-19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on their medical records and test results (features) collected during their hospitalization. The correlation between the values of these features is studied against discharge status and disease severity as a preliminary step to identify those features with a more pronounced effect on the patient outcome. Once identified, they constitute the inputs of four machine learning models, Decision Tree, Random Forest, Gradient and RUSBoosting, which predict both the Mortality and Severity associated with the disease. We test the accuracy of the models when the number of input features is varied, demonstrating their stability; i.e., the models are already highly predictive when run over a core set of (6) features. We show that Random Forest and Gradient Boosting classifiers are highly accurate in predicting patients&rsquo; Mortality (average accuracy &sim;99%) as well as categorize patients (average accuracy &sim;91%) into four distinct risk classes (Severity of COVID-19 infection). Our methodical and broad approach combines statistical insights with various machine learning models, which paves the way forward in the AI-assisted triage and prognosis of COVID-19 cases, which is potentially generalizable to other seasonal flus

Vitamin D3 and carbamazepine protect against Clostridioides difficile infection in mice by restoring macrophage lysosome acidification

Clostridioides difficile infection (CDI) is a common cause of nosocomial diarrhea. TcdB is a major C. difficile exotoxin that activates macrophages to promote inflammation and epithelial damage. Lysosome impairment is a known trigger for inflammation. Herein, we hypothesize that TcdB could impair macrophage lysosomal function to mediate inflammation during CDI. Effects of TcdB on lysosomal function and the downstream pro-inflammatory SQSTM1/p62-NFKB (nuclear factor kappa B) signaling were assessed in cultured macrophages and in a murine CDI model. Protective effects of two lysosome activators (i.e., vitamin D3 and carbamazepine) were assessed. Results showed that TcdB inhibited CTNNB1/β-catenin activity to downregulate MITF (melanocyte inducing transcription factor) and its direct target genes encoding components of lysosomal membrane vacuolar-type ATPase, thereby suppressing lysosome acidification in macrophages. The resulting lysosomal dysfunction then impaired autophagic flux and activated SQSTM1-NFKB signaling to drive the expression of IL1B/IL-1β (interleukin 1 beta), IL8 and CXCL2 (chemokine (C-X-C motif) ligand 2). Restoring MITF function by enforced MITF expression or restoring lysosome acidification with 1α,25-dihydroxyvitamin D3 or carbamazepine suppressed pro-inflammatory cytokine expression in vitro. In mice, gavage with TcdB-hyperproducing C. difficile or injection of TcdB into ligated colon segments caused prominent MITF downregulation in macrophages. Vitamin D3 and carbamazepine lessened TcdB-induced lysosomal dysfunction, inflammation and histological damage. In conclusion, TcdB inhibits the CTNNB1-MITF axis to suppress lysosome acidification and activates the downstream SQSTM1-NFKB signaling in macrophages during CDI. Vitamin D3 and carbamazepine protect against CDI by restoring MITF expression and lysosomal function in mice. Abbreviations: ATP6V0B: ATPase H+ transporting V0 subunit b; ATP6V0C: ATPase H+ transporting V0 subunit c; ATP6V0E1: ATPase H+ transporting V0 subunit e1; ATP6V1H: ATPase H+ transporting V1 subunit H; CBZ: carbamazepine; CDI: C. difficile infection; CXCL: chemokine C-X-X motif ligand; IL: interleukin; LAMP1: lysosomal-associated membrane protein 1; LC3: microtubule-associated protein 1 light chain 3; LEF: lymphoid enhancer binding factor 1; MITF: melanocyte inducing transcription factor; NFKB: nuclear factor kappa B; PMA: phorbol 12-myristate 13-acetate; TcdA: Clostridial toxin A; TcdB: Clostridial toxin B; TFE3: transcription factor E3; TFEB: transcription factor EB.Published versionThis work was supported by the National Natural Science Foundation of China [82070576] and the Hong Kong Food and Health Bureau (FHB) Commissioned Health and Medical Research Fund [CID-CUHK-C]