Detecting genetic effects on phenotype variability to capture gene-by-environment interactions: a systematic method comparison.

Genetically associated phenotypic variability has been widely observed across organisms and traits, including in humans. Both gene-gene and gene-environment interactions can lead to an increase in genetically associated phenotypic variability. Therefore, detecting the underlying genetic variants, or variance Quantitative Trait Loci (vQTLs), can provide novel insights into complex traits. Established approaches to detect vQTLs apply different methodologies from variance-only approaches to mean-variance joint tests, but a comprehensive comparison of these methods is lacking. Here, we review available methods to detect vQTLs in humans, carry out a simulation study to assess their performance under different biological scenarios of gene-environment interactions, and apply the optimal approaches for vQTL identification to gene expression data. Overall, with a minor allele frequency (MAF) of less than 0.2, the squared residual value linear model (SVLM) and the deviation regression model (DRM) are optimal when the data follow normal and non-normal distributions, respectively. In addition, the Brown-Forsythe (BF) test is one of the optimal methods when the MAF is 0.2 or larger, irrespective of phenotype distribution. Additionally, a larger sample size and more balanced sample distribution in different exposure categories increase the power of BF, SVLM, and DRM. Our results highlight vQTL detection methods that perform optimally under realistic simulation settings and show that their relative performance depends on the phenotype distribution, allele frequency, sample size, and the type of exposure in the interaction model underlying the vQTL.

Using machine learning to detect the differential usage of novel gene isoforms.

BACKGROUND: Differential isoform usage is an important driver of inter-individual phenotypic diversity and is linked to various diseases and traits. However, accurately detecting the differential usage of different gene transcripts between groups can be difficult, in particular in less well annotated genomes where the spectrum of transcript isoforms is largely unknown. RESULTS: We investigated whether machine learning approaches can detect differential isoform usage based purely on the distribution of reads across a gene region. We illustrate that gradient boosting and elastic net approaches can successfully identify large numbers of genes showing potential differential isoform usage between Europeans and Africans, that are enriched among relevant biological pathways and significantly overlap those identified by previous approaches. We demonstrate that diversity at the 3' and 5' ends of genes are primary drivers of these differences between populations. CONCLUSION: Machine learning methods can effectively detect differential isoform usage from read fraction data, and can provide novel insights into the biological differences between groups.

[The value of circulating microRNA-1 in the early diagnosis of coronary atherosclerotic plaque rupture in patients with stable coronary heart disease].

OBJECTIVE: To evaluate the diagnostic value of circulating microRNA-1 (miR-1) in early coronary artery plaque rupture in patients with stable coronary artery disease (SCAD). METHODS: A prospective cohort study was conducted. Sixty-seven patients with SCAD admitted to the department of cardiology of the Third Affiliated Hospital of Soochow University from January to June in 2019 were enrolled. All patients had completed coronary angiography (CAG), percutaneous coronary intervention (PCI) single stent implantation or only CAG was performed according to the CAG results. Blood samples were collected before (0 hour) and 3 hours after the procedure. The expression of plasma miR-1 was detected by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR), and electrocardiogram was used to detect cardiac troponin I (cTnI) levels. The difference of miR-1 and cTnI levels in PCI or CAG patients before and after procedure were compared, and the value for early diagnosis of coronary artery plaque rupture in SCAD patients was evaluated. The diagnostic efficacy was evaluated by the receiver operating characteristic curve (ROC curve). RESULTS: There were 38 CAG patients and 29 PCI patients. There were no significant differences in gender, age, previous history (without hypertension history) and baseline data of cardiac function between the two groups. The expression of miR-1 after PCI was significantly higher than that before PCI [2-ΔΔCt: 2.11 (1.56, 2.73) vs. 1.26 (1.07, 1.92), P < 0.01], and there was no significant difference in cTnI level before and after PCI [µg/L: 0.00 (0.00, 0.02) vs. 0.00 (0.00, 0.02), P > 0.05]. There were no significant differences in miR-1 and cTnI levels before and after procedure in the CAG group [miR-1 (2-ΔΔCt): 1.09 (1.00, 1.40) vs. 1.21 (1.00, 1.71), cTnI (µg/L): 0.00 (0.00, 0.02) vs. 0.00 (0.00, 0.02), both P > 0.05]. ROC curve analysis showed that the area under ROC curve (AUC) and 95% confidence interval (95%CI) of miR-1 in the diagnosis of coronary plaque rupture were 0.794 (0.687-0.900), P < 0.01, the sensitivity was 82.8%, the specificity was 68.4%, and the optimal cut-off value was 1.51. The AUC and 95%CI of the difference of miR-1 before and after operation (ΔmiR-1) were 0.704 (0.567-0.842), P = 0.004, the sensitivity was 62.1%, the specificity was 84.2%, and the optimal cut-off value was 0.39. The efficancy of miR-1 and ΔmiR-1 after procedure to diagnose coronary plaque rupture in patients with SCAD was similar (Z = 1.287, P = 0.198). However, baseline miR-1 might not predict whether patients with SCAD need PCI or not (AUC = 0.630, P > 0.05). Multivariate binary Logistic regression analysis showed that increased postoperative miR-1 expression was an independent risk factor for coronary plaque rupture in SCAD patients [odds ratios (OR) = 2.887, 95%CI was 1.044-7.978, P = 0.041]. CONCLUSIONS: Circulating miR-1 might have the value for early diagnosis of coronary artery plaque rupture in SCAD patients.

An accurate method for locating the joint line during revision total knee arthroplasty: A radiologic study in the Chinese population.

BACKGROUND: The systems for precisely locating the joint line during primary and revision total knee arthroplasty are still controversial, and they should be better evaluated in the Chinese population. METHODS: A total of 451 standard anteroposterior knee radiographs from 451 healthy Chinese people (283 males and 168 females, the average age of 33.26 years, range 20-50 years) were included to measure the femoral width (FW) and the distances from the adductor tubercle (AT), the medial epicondyle (ME), the lateral epicondyle (LE), and the fibular head (FH) to the joint line (JL). Correlation between FW and distances from landmarks to the joint line was evaluated using Pearson correlation coefficient, and the ratios of ATJL, MEJL, LEJL, FHJL to FW were calculated. RESULTS: The average distances from the AT, the ME, the LE, the FH to the JL were 49.4 ± 5.0 mm, 28.3 ± 3.1 mm, 26.9 ± 2.9 mm, 20.0 ± 4.0 mm, respectively. An excellent linear correlation was found between FW and the distance from AT to the joint line (R = 0.836, R2 = 0.698); it was more reliable than the LE (R = 0.686, R2 = 0.471) and the ME (R = 0.672, R2 = 0.452). The average ratios of ATJL/FW, MEJL/FW, LEJL/FW were 0.553, 0.317, and 0.302, respectively. There were significant differences between our results and the studies based on the Western people. CONCLUSION: The AT can be used as a reliable landmark to locate the JL precisely by the formula (ATJL = 0.548 × FW in males; ATJL = 0.562 × FW in females) in the Chinese population. The LE and ME can be the second choices. Moreover, it may be better to use ratios from the research based on the same race.

Value of circulating miRNA-1 detected within 3 h after the onset of acute chest pain in the diagnosis and prognosis of acute myocardial infarction.

BACKGROUND: To explore the significance of circulating miRNA-1 (miR-1) released within 3 h after the onset of acute chest pain in the diagnosis and prognosis of acute myocardial infarction (AMI). METHODS: A total of 337 patients with acute chest pain within 3 h were enrolled in this study and divided into AMI group and non-AMI group. The AMI diagnostic efficacy of miR-1 was determined and compared with that of cardiac troponin I (cTnI). The patients were followed up for 720 d after treatment. The significance of circulating miR-1 in AMI prognosis was assessed using univariate and COX regression analysis. RESULTS: There were 174 patients in AMI group, 163 in non-AMI group. Circulating miR-1 level was significantly higher in AMI group than in non-AMI group (P < 0.001). The AMI diagnostic efficacy of miR-1 and cTnI were similar (P > 0.05). We established two AMI diagnostic models, the AUC values of which were larger than that of cTnI or miR-1 (P < 0.05). When miR-1 combined with CK-MB, cTnI, and other clinical and laboratory parameters (model 2), the AUC was the largest (AUC: 0.961) and had the highest diagnostic efficiency. Circulating miR-1, Killip classification, and treatment method were influencing factors for AMI prognosis (P < 0.05). CONCLUSIONS: Circulating miR-1 within 3 h of acute chest pain has the potential diagnostic value for AMI, and which is an independent risk factor for the prognosis of AMI and can be used to predict AMI prognosis.

Initial Concentrations of miR-1 MicroRNA Precursor and High-Sensitivity Troponin in the Diagnosis of Non-ST Myocardial Infarction among Patients with and Those without Chronic Kidney Disease.

BACKGROUND: The early diagnosis of non-ST-segment elevation myocardial infarction (NSTEMI) in patients with chronic kidney disease (CKD) remains a challenge. METHODS: The study consecutively enrolled patients who had suffered from chest pain within 3 h whose electrocardiogram had no elevation in the ST segment. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2, and the diagnostic criteria for NSTEMI were defined according to the recommended guideline. Circulating microRNA-1 was collected and determined by quantitative real-time reverse transcription polymerase chain reaction. RESULTS: A total of 456 patients with suspected NSTEMI were included. There were 115 patients in the CKD group, including 67 with NSTEMI, 20 with stable angina, 7 with unstable angina, 18 with heart failure, and 3 with other disorders. Compared with the NSTEMI group, the non-NSTEMI group just had significant differences in microRNA-1 and high-sensitivity cardiac troponin I (hs-cTnI) (both p < 0.05). The relative expression of microRNA-1 was significantly increased in the NSTEMI group as compared with that in the other disease groups (all p < 0.05). A receiver operating characteristic (ROC) curve analysis suggested that microRNA-1 and hs-cTnI had advantages in the early diagnosis of NSTEMI with CKD (AUC [area under the ROC curve] 0.879 and 0.812, respectively, both p < 0.05). Compared with that in the non-CKD group, the accuracy of microRNA-1 was almost as good in the CKD group (84.3 vs. 89.4%, p > 0.05). However, the diagnostic accuracy of hs-cTnI was significantly decreased (79.1 vs. 91.5%, p < 0.05), as was its specificity (75.0 vs. 95.5%, p < 0.05). There was no significant difference in the correlation between microRNA-1 and eGFR (p > 0.05), but a statistically significantly negative correlation between hs-cTnI and eGFR (p < 0.05). CONCLUSION: Circulating microRNA-1 is capable of early diagnosis of NSTEMI in patients with CKD suffering from chest pain.

Circulating microRNA-1 in the diagnosis and predicting prognosis of patients with chest pain: a prospective cohort study.

BACKGROUND: To investigate the early diagnostic and prognostic value of microRNA-1 in patients with acute chest pain. METHODS: This study enrolled 341 patients attacked by chest pain within 3 h, and another 100 volunteers as control group. Circulating microRNA-1 was collected and determined by real-time quantitative reverse transcription-polymerase chain reaction. The clinical follow-up period was 720 days. RESULTS: There were 174 patients in acute myocardial infarction (AMI) group, 167 in non-AMI group. The relative expression of microRNA-1 was significantly increased within 3 h in AMI group, and it continued rising within 12 h, lower at 24 h than that 12 h in AMI group without reperfusion therapy. Otherwise, microRNA-1 concentration was markedly low at 12 h after primary percutaneous coronary intervention in AMI group. The 95% reference range of circulating microRNA-1 was 0.171-0.653. It was significantly available for microRNA-1 to early diagnose AMI with an optimal cutoff value of 2.215 and diagnostic accuracy could be improved when combined with cardiac troponin I. It was not statistically significant for microRNA-1 to forecast future AMI but might prognose mortality of 720 days in chest pain patients. In patients with chest pain, microRNA-1 concentration was high with major adverse cardiac events within 30 days, low with high overall survival within 720 days. CONCLUSIONS: Circulating microRNA-1 might diagnose early AMI and predict the prognosis of patients with chest pain.

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

Nanocrystalline copper films are never flat.

We used scanning tunneling microscopy to study low-angle grain boundaries at the surface of nearly planar copper nanocrystalline (111) films. The presence of grain boundaries and their emergence at the film surface create valleys composed of dissociated edge dislocations and ridges where partial dislocations have recombined. Geometric analysis and simulations indicated that valleys and ridges were created by an out-of-plane grain rotation driven by reduction of grain boundary energy. These results suggest that in general, it is impossible to form flat two-dimensional nanocrystalline films of copper and other metals exhibiting small stacking fault energies and/or large elastic anisotropy, which induce a large anisotropy in the dislocation-line energy.

Potential cancer-fighting Ocimum gratissimum (OG) leaf extracts: increased anti-proliferation activity of partially purified fractions and their spectral fingerprints.

INTRODUCTION: Cancer causes about 13% of all deaths. According to the American Cancer Society, world-wide cancer deaths were 7.6 million in 2007. African Americans and other minorities are disproportionately affected. Effective cancer chemotherapy is scarce. This study is part of an ongoing search for potential cancer-fighting agents in medicinal herbs. In previous in-vitro studies, we have shown that the aqueous extracts of the medicinal herb Ocimum gratissimum (Og) inhibit the proliferation of several cancer cell lines, especially prostate adenocarcinoma (PC-3) cells. Therefore, Og leaf extracts may harbor novel cancer-fighting compounds that need to be isolated, purified and characterized. METHODS: Partially purified Og fractions were obtained from sequential extraction of Og powder with organic solvents of different polarities. The hypothesis that the anti-proliferation activity of the fractions will be significantly greater than that of either aqueous or ethanol extracts was tested by treating PC-3 cells with 1.61 mg/mL of each fraction. Spectral analysis of the fractions was also conducted. RESULTS: Activity of the fractions was P2>P(3-2)>P(4-2)>P(3-1)>P(4-1). Fractions P2, P(3-2) and P(4-2) were 725, 75 and 2.3 times more active than the aqueous extract, respectively. Spectral analysis revealed peaks for: P(3-2) and aqueous extract at 208 nm, P2 and P(4-2) at 210 nm, and P(3-1) at 220 nm. CONCLUSIONS: These findings suggest that fractions P2, P(3-2) and P(4-2) could be potential sources of Og's bioactive component(s) that warrant further purification and characterization.