Genetic data visualization using literature text-based neural networks: Examples associated with myocardial infarction.

Data visualization is critical to unraveling hidden information from complex and high-dimensional data. Interpretable visualization methods are critical, especially in the biology and medical fields, however, there are limited effective visualization methods for large genetic data. Current visualization methods are limited to lower-dimensional data and their performance suffers if there is missing data. In this study, we propose a literature-based visualization method to reduce high-dimensional data without compromising the dynamics of the single nucleotide polymorphisms (SNP) and textual interpretability. Our method is innovative because it is shown to (1) preserves both global and local structures of SNP while reducing the dimension of the data using literature text representations, and (2) enables interpretable visualizations using textual information. For performance evaluations, we examined the proposed approach to classify various classification categories including race, myocardial infarction event age groups, and sex using several machine learning models on the literature-derived SNP data. We used visualization approaches to examine clustering of data as well as quantitative performance metrics for the classification of the risk factors examined above. Our method outperformed all popular dimensionality reduction and visualization methods for both classification and visualization, and it is robust against missing and higher-dimensional data. Moreover, we found it feasible to incorporate both genetic and other risk information obtained from literature with our method.

Language-Independent Sleepy Speech Detection.

Prolonged sleepiness can lead to impairment of cognitive and physical performance and may cause unfortunate accidents. Speech signals are easily accessible using a simple microphone or other means, hence, automated approaches for accurate sleepiness detection from speech signals are desired to prevent degradation in human performance and accidental injury. Sleepiness is known to affect acoustic patterns of speech so that they are different from those of normal speech, and this change is also independent of the language being spoken. To date, there have been no studies examining linguistic-independent sleepy speech detection. We used two different languages, English and German, to detect sleepy speech, where the former was used to train/validate and the latter to test the effectiveness of machine and deep learning models. Specifically, we trained ResNet50, a deep learning model, and five machine learning models with relevant vocal features. Speech data segments from three English-speaking subjects were used for training the model and segments from an English-speaking subject were used for validation. We then tested ResNet50 and the five different machine-learning models using speech data segments from one German-speaking subject. Deep learning far outperformed all of the machine learning approaches. The accuracy, sensitivity, specificity, and geometric mean values were found to be 0.96, 0.92, 0.99, and 0.95, respectively, using ResNet50 on the test data. Our preliminary results suggest that sleepiness can be accurately detected independently from linguistic speech. Clinical Relevance-It is not known if sleepiness can be detected regardless of the language spoken. Our results show the feasibility of accurate sleepiness detection using deep learning even when tested with a different language than trained on.

An in-depth look at ventilator-associated pneumonia in trauma patients and efforts to increase bundle compliance, education and documentation in a surgical trauma critical care unit.

BACKGROUND: Ventilator-associated pneumonia (VAP) is considered the most common hospital acquired infection seen in critical care settings and leading cause of death in Intensive Care Units (ICU). The objective of this study was to assess whether specimen collection impacted diagnosis and if implementation of a VAP bundle would decrease rates at our center. METHODS: This single center study design is a retrospective chart review from 2017 to 2020 utilizing the electronic medical record. A pre-/postintervention comparison was performed following implementation of a unit wide VAP bundle and nursing education. Descriptive statistics and continuous variables were analyzed with independent group t -tests, and categorical variables were analyzed with chi-squared tests. RESULTS: Ventilator-associated pneumonia rates decreased in the postimplementation time (20.8%, n = 74 vs 12.2%, n = 15; P = .03). There were no significant differences in the patient profile of those who acquired VAP (ie, males 79.7% vs 86.7%, blunt injuries 63.5% vs 86.7% and severity scores 24.8 vs 25.1, pre vs postimplementation, respectively, all P-values greater than .05). DISCUSSION/CONCLUSIONS: Reduction in VAP rates were achieved by implementing a standardized, evidence based, prevention protocol. Further research is warranted as studies have noted that patients requiring mechanical ventilation are at greater risk for VAP than other ICU patients due to the nature of their injuries and increased risk of prolonged mechanical ventilation ≥ 21 days.

Preliminary Analysis of the Risk Factor Identification Embedding Model for Cardiovascular Disease.

Cardiovascular Disease (CVD) is responsible for a large part of healthcare costs every year, but susceptibility to it is affected by complex biological and physiological variables including patients' genetics and lifestyles. There has not been much work to develop a framework that incorporates these important and clinically relevant risk factors into a comprehensive model for CVD research. Moreover, the data labeling required to do so, such as annotating gene functions, is an extremely challenging, tedious, and time-consuming process. In this work, our goal was to develop and validate a risk factor embedding model, which incorporates genotype, phenotype without pre-labeled information to identify various risk factors of CVD. We hypothesize that (1) the knowledge background that does not require data labeling could be gathered from published abstract data, (2) the phenotype, genotype risk factors could be represented in an embedding vector space. We collected 1,363,682 published abstracts from PubMed using the keyword "heart" and 19,264 human gene names, then trained our model using the collected abstracts. We evaluated our CVD risk factor identification model using both intrinsic and extrinsic evaluations: for the intrinsic evaluation, we examined whether or not the captured top-10 words and genes have references related to the input query "myocardial infarction", as one of CVDs, and our model correctly identified them. For the extrinsic evaluation, we used our model to the dimensionality reduction task for classifications, and our method outperformed other popular methods. These results show the feasibility of our approach for disease-associated risk factors of CVD which incorporates genotype, phenotype.Clinical Relevance-Our model provides a comprehensive tool to incorporate various risk factors without any a priori data labeling knowledge for CVD. Our approach shows a potential to provide discovered knowledge that contributes to better understanding and treatment of CVD.

Effects of postnatal alcohol exposure on hippocampal gene expression and learning in adult mice.

Fetal alcohol syndrome (FAS) is a condition resulting from excessive drinking by pregnant women. Symptoms of FAS include abnormal facial features, stunted growth, intellectual deficits and attentional dysfunction. Many studies have investigated FAS, but its underlying mechanisms remain unknown. This study evaluated the relationship between alcohol exposure during the synaptogenesis period in postnatal mice and subsequent cognitive function in adult mice. We delivered two injections, separated by 2 h, of ethanol (3 g/kg, ethanol/saline, 20% v/v) to ICR mice on postnatal day 7. After 10 weeks, we conducted a behavioral test, sacrificed the animals, harvested brain tissue and analyzed hippocampal gene expression using a microarray. In ethanol-treated mice, there was a reduction in brain size and decreased neuronal cell number in the cortex, and also cognitive impairment. cDNA microarray results indicated that 1,548 genes showed a > 2-fold decrease in expression relative to control, whereas 974 genes showed a > 2-fold increase in expression relative to control. Many of these genes were related to signal transduction, synaptogenesis and cell membrane formation, which are highlighted in our findings.

Effects of guanine bases at the central loop on stabilization of the quadruplex DNAs and their interactions with Meso-tetrakis(N-methylpyridium-4-yl)porphyrin.

The thermal stability of the G-quadruplex formed from the thrombin-binding aptamer, 5'G2T2G2TGTG2T2G2, in which the guanine (G) base at the central loop was replaced with an adenine (A) or inosine (I) base, was examined to determine the role of the central G base in stabilizing the quadruplex. Replacement of the central G base by the I base resulted in a slight decrease in thermal stability. On the other hand, the stability of the G-quadruplex decreased to a significant extent when it was replaced with the A base. The optimized structure of the G-quadruplex, which was obtained by a molecular dynamic simulation, showed that the carbonyl group of the C5 position of the central G base could form hydrogen bonds with the G1 amine group at the C7 position on the upper G-quartet. This formation of a hydrogen bond contributes to the stability of the G-quadruplex. The spectral property of meso-tetrakis(N-methylpyridium-4yl)porphyrin (TMPyP) associated with the G-quadruplex was characterized by a moderate red shift and hypochromism in the absorption spectrum, a positive CD signal, and two emission maxima in the fluorescence emission spectrum, suggesting that TMPyP binds at the exterior of the G-quadruplex. Spectral properties were slightly altered when the G base at the central loop was replaced with A or I, while the fluorescence decay times of TMPyP associated with the G-quadruplex were identical. Observed spectral properties removes the possibility of intercalation binding mode for TMPyP. TMPyP binds at the exterior of the quadruplex. Whether it stacks on the central loop or binds at the side of the quadruplex is unclear at this stage.

Effects of deficient of the Hoogsteen base-pairs on the G-quadruplex stabilization and binding mode of a cationic porphyrin.

BACKGROUND: In stabilization of the G-quadruplex, formation of a Hoogsteen base-pair between the guanine (G) bases is essential. However, the contribution of each Hoogsteen base-pair at different positions to whole stability of the G-quadruplex has not been known. In this study, the effect of a deficiency of the Hoogsteen type hydrogen bond in the G-quadruplex stability was investigated. Spectral properties of meso-tetrakis(1-methylpyridinium-4-yl)porphyrin (TMPyP) associated with various G-quadruplexes were also examined. METHODS: The thermal stability of the thrombin-binding DNA aptamer 5'G1G2TTG5G6TG8TG10G11TTG14G15 G-quadruplex, in which the guanine (G) base at 1, 2, 5, 6 and 8th positions was replaced with an inosine (I) base, one at a time, was investigated by circular dichroism (CD). The absorption, CD and fluorescence decay curve for the G-quadruplex associated TMPyP were also measured. RESULTS: The transition from the G-quadruplex to a single stranded form was endothermic and induced by an increase in entropy. The order in stability was 0>8>6>2>5>1, where the numbers denote the position of the replacement and 0 represents no replacements of the G base, suggesting the significant contribution of the G1 base in the stability of the G-quadruplex. Alteration in the spectral property of TMPyP briefly followed the order in thermal stability. CONCLUSIONS: Replacement of a G base with an I base resulted in destabilization of the G-quadruplex. The missing hydrogen bond at position 1 destabilized the G-quadruplex most efficiently. TMPyP binds near the I base-replaced location namely, the side of the G-quadruplex. GENERAL SIGNIFICANCE: The Hoogsteen base-pairing is confirmed to be essential in stabilization of G-quadruplex. When G is replaced with I, the latter base is mobile to interact with cationic porphyrin.

Egr1 mediated the neuronal differentiation induced by extremely low-frequency electromagnetic fields.

AIM: There is a specific frequency of extremely low-frequency electromagnetic field (ELF-EMF) that promotes neuronal differentiation. Although several mechanisms are known to regulate ELF-EMF-induced neuronal differentiation, a key factor that mediates neurogenic potentials by the ELF-EMF is largely unknown. Also, the potential use of ELF-EMF exposure in cell transplantation assays is yet to be determined, including their possible use in ELF-EMF based therapy of neurological diseases. The aim of this study is to understand the underlying mechanisms that mediate ELF-EMF-induced neuronal differentiation and also to harness these mechanisms for cell transplantation assays. MAIN METHOD: Human bone marrow-mesenchymal stem cells (hBM-MSCs) were exposed to ELF-EMF (50 Hz frequency, 1mT intensity) for 8 days. The hBM-MSC derived neurons were then analyzed by general molecular biology techniques including immunofluorescence and quantitative RT-PCR. To assess changes in gene expression induced by ELF-EMF exposure, we analyzed the transcriptome of neuronal cells after an 8-day ELF-EMF exposure (50 Hz, 1 mT) and compared the transcriptional profiles to control cells. KEY FINDING: We found that early growth response protein 1 (Egr1) is one of the key transcription factors in ELF-EMF-induced neuronal differentiation. In addition, we show that transplantations of ELF-EMF-induced neurons significantly alleviate symptoms in mouse models of neurodegenerative disease. SIGNIFICANCE: These findings indicate that a specific transcriptional factor, Egr1, mediates ELF-EMF-induced neuronal differentiations, and demonstrate the promise of ELF-EMF based cell replacement therapies for neurodegenerative diseases.

Application of RAPD and SCAR markers for purity testing of F1 hybrid seed in chili pepper (Capsicum annuum).

A simpler and better method for purity testing of hybrid pepper seed was developed. The simplest method for extracting genomic DNA, the NaOH method, was chosen. Two RAPD markers identifying male and female parents were also developed, and the PCR products of male- and female-specific RAPD markers were cloned and sequenced. From these sequences, new longer primers were constructed for conversion into SCAR markers. In blind tests the RAPD and SCAR markers were able to reliably detect contaminating exotic seeds. These PCR-based markers are therefore directly applicable for purity testing by seed companies. In addition, the PCR products of the SCAR markers could be identified by direct staining methods such as ethidium bromide and pellet painting without electrophoresis.

Disruption of a guard cell-expressed protein phosphatase 2A regulatory subunit, RCN1, confers abscisic acid insensitivity in Arabidopsis.

Pharmacological studies have led to a model in which the phytohormone abscisic acid (ABA) may be positively transduced via protein phosphatases of the type 1 (PP1) or type 2A (PP2A) families. However, pharmacological evidence also exists that PP1s or PP2As may function as negative regulators of ABA signaling. Furthermore, recessive disruption mutants in protein phosphatases that function in ABA signal transduction have not yet been identified. A guard cell-expressed PP2A gene, RCN1, which had been characterized previously as a molecular component affecting auxin transport and gravity response, was isolated. A T-DNA disruption mutation in RCN1 confers recessive ABA insensitivity to Arabidopsis. The rcn1 mutation impairs ABA-induced stomatal closing and ABA activation of slow anion channels. Calcium imaging analyses show a reduced sensitivity of ABA-induced cytosolic calcium increases in rcn1, whereas mechanisms downstream of cytosolic calcium increases show wild-type responses, suggesting that RCN1 functions in ABA signal transduction upstream of cytosolic Ca(2+) increases. Furthermore, rcn1 shows ABA insensitivity in ABA inhibition of seed germination and ABA-induced gene expression. The PP1 and PP2A inhibitor okadaic acid phenocopies the rcn1 phenotype in wild-type plants both in ABA-induced cytosolic calcium increases and in seed germination, and the wild-type RCN1 genomic DNA complements rcn1 phenotypes. These data show that RCN1 functions as a general positive transducer of early ABA signaling.