Leveraging orthology within maize and Arabidopsis QTL to identify genes affecting natural variation in gravitropism.

Plants typically orient their organs with respect to the Earth's gravity field by a dynamic process called gravitropism. To discover conserved genetic elements affecting seedling root gravitropism, we measured the process in a set of Zea mays (maize) recombinant inbred lines with machine vision and compared the results with those obtained in a similar study of Arabidopsis thaliana. Each of the several quantitative trait loci that we mapped in both species spanned many hundreds of genes, too many to test individually for causality. We reasoned that orthologous genes may be responsible for natural variation in monocot and dicot root gravitropism. If so, pairs of orthologous genes affecting gravitropism may be present within the maize and Arabidopsis QTL intervals. A reciprocal comparison of sequences within the QTL intervals identified seven pairs of such one-to-one orthologs. Analysis of knockout mutants demonstrated a role in gravitropism for four of the seven: CCT2 functions in phosphatidylcholine biosynthesis, ATG5 functions in membrane remodeling during autophagy, UGP2 produces the substrate for cellulose and callose polymer extension, and FAMA is a transcription factor. Automated phenotyping enabled this discovery of four naturally varying components of a conserved process (gravitropism) by making it feasible to conduct the same large-scale experiment in two species.

Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences.

The breakthrough high-throughput measurement of the cis-regulatory activity of millions of randomly generated promoters provides an unprecedented opportunity to systematically decode the cis-regulatory logic that determines the expression values. We developed an end-to-end transformer encoder architecture named Proformer to predict the expression values from DNA sequences. Proformer used a Macaron-like Transformer encoder architecture, where two half-step feed forward (FFN) layers were placed at the beginning and the end of each encoder block, and a separable 1D convolution layer was inserted after the first FFN layer and in front of the multi-head attention layer. The sliding k-mers from one-hot encoded sequences were mapped onto a continuous embedding, combined with the learned positional embedding and strand embedding (forward strand vs. reverse complemented strand) as the sequence input. Moreover, Proformer introduced multiple expression heads with mask filling to prevent the transformer models from collapsing when training on relatively small amount of data. We empirically determined that this design had significantly better performance than the conventional design such as using the global pooling layer as the output layer for the regression task. These analyses support the notion that Proformer provides a novel method of learning and enhances our understanding of how cis-regulatory sequences determine the expression values.

Factors associated with impaired psychophysical gustatory function.

OBJECTIVE: To investigate the clinical characteristics associated with measured gustatory dysfunction in patients with chemosensory (smell and taste) discomfort. STUDY DESIGN: Retrospective study. DESIGN: Hospital-based cohort. SETTING: The clinical characteristics associated with the measured diagnosis of gustatory dysfunction were statistically analysed. PARTICIPANTS: Patients who underwent all the psychophysical olfactory and chemical gustatory function tests (YSK olfactory function test and chemical gustometry exam) and the subjective questionnaires between October 2021 and February 2023. MAIN OUTCOME MEASURES: YSK olfactory function test and chemical gustometry results, subjective questionnaire score about chemosensory (smell and taste) functions. The Medical records of patients who visited the smell and taste centre in a tertiary. RESULTS: A total of 219 patients were enrolled; 180 were diagnosed as having normal gustatory function, and 39 were diagnosed as having gustatory dysfunction. Subjective recognition of gustatory function was not associated with the measured gustatory function. Age, sex, measured olfactory function and the threshold and discrimination scores for the olfactory function test were significant factors in the multivariate analysis. When the patients were further divided according to age, the threshold test scores rather than other subsets in the olfactory function test were significantly associated with measured gustatory dysfunction in patients 60 and older. CONCLUSION: In older adult male patients with olfactory dysfunction, gustatory function should be considered regardless of subjective gustatory dysfunction.

Single cell lineage reconstruction using distance-based algorithms and the R package, DCLEAR.

BACKGROUND: DCLEAR is an R package used for single cell lineage reconstruction. The advances of CRISPR-based gene editing technologies have enabled the prediction of cell lineage trees based on observed edited barcodes from each cell. However, the performance of existing reconstruction methods of cell lineage trees was not accessed until recently. In response to this problem, the Allen Institute hosted the Cell Lineage Reconstruction Dream Challenge in 2020 to crowdsource relevant knowledge from across the world. Our team won sub-challenges 2 and 3 in the challenge competition. RESULTS: The DCLEAR package contained the R codes, which was submitted in response to sub-challenges 2 and 3. Our method consists of two steps: (1) distance matrix estimation and (2) the tree reconstruction from the distance matrix. We proposed two novel methods for distance matrix estimation as outlined in the DCLEAR package. Using our method, we find that two of the more sophisticated distance methods display a substantially improved level of performance compared to the traditional Hamming distance method. DCLEAR is open source and freely available from R CRAN and from under the GNU General Public License, version 3. CONCLUSIONS: DCLEAR is a powerful resource for single cell lineage reconstruction.

Time-dependent Pax3-mediated chromatin remodeling and cooperation with Six4 and Tead2 specify the skeletal myogenic lineage in developing mesoderm.

The transcriptional mechanisms driving lineage specification during development are still largely unknown, as the interplay of multiple transcription factors makes it difficult to dissect these molecular events. Using a cell-based differentiation platform to probe transcription function, we investigated the role of the key paraxial mesoderm and skeletal myogenic commitment factors-mesogenin 1 (Msgn1), T-box 6 (Tbx6), forkhead box C1 (Foxc1), paired box 3 (Pax3), Paraxis, mesenchyme homeobox 1 (Meox1), sine oculis-related homeobox 1 (Six1), and myogenic factor 5 (Myf5)-in paraxial mesoderm and skeletal myogenesis. From this study, we define a genetic hierarchy, with Pax3 emerging as the gatekeeper between the presomitic mesoderm and the myogenic lineage. By assaying chromatin accessibility, genomic binding and transcription profiling in mesodermal cells from mouse and human Pax3-induced embryonic stem cells and Pax3-null embryonic day (E)9.5 mouse embryos, we identified conserved Pax3 functions in the activation of the skeletal myogenic lineage through modulation of Hedgehog, Notch, and bone morphogenetic protein (BMP) signaling pathways. In addition, we demonstrate that Pax3 molecular function involves chromatin remodeling of its bound elements through an increase in chromatin accessibility and cooperation with sine oculis-related homeobox 4 (Six4) and TEA domain family member 2 (Tead2) factors. To our knowledge, these data provide the first integrated analysis of Pax3 function, demonstrating its ability to remodel chromatin in mesodermal cells from developing embryos and proving a mechanistic footing for the transcriptional hierarchy driving myogenesis.

DrImpute: imputing dropout events in single cell RNA sequencing data.

BACKGROUND: The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological noise. Because of the low number of RNA transcriptomes and the stochastic nature of the gene expression pattern, there is a high chance of missing nonzero entries as zero, which are called dropout events. RESULTS: We develop DrImpute to impute dropout events in scRNA-seq data. We show that DrImpute has significantly better performance on the separation of the dropout zeros from true zeros than existing imputation algorithms. We also demonstrate that DrImpute can significantly improve the performance of existing tools for clustering, visualization and lineage reconstruction of nine published scRNA-seq datasets. CONCLUSIONS: DrImpute can serve as a very useful addition to the currently existing statistical tools for single cell RNA-seq analysis. DrImpute is implemented in R and is available at https://github.com/gongx030/DrImpute .

Pathologic Stimulus Determines Lineage Commitment of Cardiac C-kit+ Cells.

BACKGROUND: Although cardiac c-kit+ cells are being tested in clinical trials, the circumstances that determine lineage differentiation of c-kit+ cells in vivo are unknown. Recent findings suggest that endogenous cardiac c-kit+ cells rarely contribute cardiomyocytes to the adult heart. We assessed whether various pathological stimuli differentially affect the eventual cell fates of c-kit+ cells. METHODS: We used single-cell sequencing and genetic lineage tracing of c-kit+ cells to determine whether various pathological stimuli would result in different fates of c-kit+ cells. RESULTS: Single-cell sequencing of cardiac CD45-c-kit+ cells showed innate heterogeneity, indicative of the existence of vascular and mesenchymal c-kit+ cells in normal hearts. Cardiac pressure overload resulted in a modest increase in c-kit-derived cardiomyocytes, with significant increases in the numbers of endothelial cells and fibroblasts. Doxorubicin-induced acute cardiotoxicity did not increase c-kit-derived endothelial cell fates but instead induced cardiomyocyte differentiation. Mechanistically, doxorubicin-induced DNA damage in c-kit+ cells resulted in expression of p53. Inhibition of p53 blocked cardiomyocyte differentiation in response to doxorubicin, whereas stabilization of p53 was sufficient to increase c-kit-derived cardiomyocyte differentiation. CONCLUSIONS: These results demonstrate that different pathological stimuli induce different cell fates of c-kit+ cells in vivo. Although the overall rate of cardiomyocyte formation from c-kit+ cells is still below clinically relevant levels, we show that p53 is central to the ability of c-kit+ cells to adopt cardiomyocyte fates, which could lead to the development of strategies to preferentially generate cardiomyocytes from c-kit+ cells.

A Powerful Pathway-Based Adaptive Test for Genetic Association with Common or Rare Variants.

In spite of the success of genome-wide association studies (GWASs), only a small proportion of heritability for each complex trait has been explained by identified genetic variants, mainly SNPs. Likely reasons include genetic heterogeneity (i.e., multiple causal genetic variants) and small effect sizes of causal variants, for which pathway analysis has been proposed as a promising alternative to the standard single-SNP-based analysis. A pathway contains a set of functionally related genes, each of which includes multiple SNPs. Here we propose a pathway-based test that is adaptive at both the gene and SNP levels, thus maintaining high power across a wide range of situations with varying numbers of the genes and SNPs associated with a trait. The proposed method is applicable to both common variants and rare variants and can incorporate biological knowledge on SNPs and genes to boost statistical power. We use extensively simulated data and a WTCCC GWAS dataset to compare our proposal with several existing pathway-based and SNP-set-based tests, demonstrating its promising performance and its potential use in practice.

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. AVAILABILITY AND IMPLEMENTATION: The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Adaptive gene- and pathway-trait association testing with GWAS summary statistics.

BACKGROUND: Gene- and pathway-based analyses offer a useful alternative and complement to the usual single SNP-based analysis for GWAS. On the other hand, most existing gene- and pathway-based tests are not highly adaptive, and/or require the availability of individual-level genotype and phenotype data. It would be desirable to have highly adaptive tests applicable to summary statistics for single SNPs. This has become increasingly important given the popularity of large-scale meta-analyses of multiple GWASs and the practical availability of either single GWAS or meta-analyzed GWAS summary statistics for single SNPs. RESULTS: We extend two adaptive tests for gene- and pathway-level association with a univariate trait to the case with GWAS summary statistics without individual-level genotype and phenotype data. We use the WTCCC GWAS data to evaluate and compare the proposed methods and several existing methods. We further illustrate their applications to a meta-analyzed dataset to identify genes and pathways associated with blood pressure, demonstrating the potential usefulness of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Level of Contamination of Positive Airway Pressure Devices Used in Obstructive Sleep Apnea.

OBJECTIVES: No study has yet evaluated the degree of contamination after the total disassembly of continuous positive airway pressure (CPAP) devices. We investigated the extent of contamination of CPAP devices used daily by patients with obstructive sleep apnea (OSA) by disassembling the systems and identifying the factors that influenced the degree of CPAP contamination. METHODS: We conducted a chart review of the medical records of patients with OSA for whom the CPAP devices were disassembled and cleaned. Two skilled technicians photographed the levels of contamination of each component and scored them using a visual analog scale. Patients' clinical characteristics and records of CPAP device usage were statistically analyzed to identify characteristics that were significantly associated with the degree of CPAP device contamination. RESULTS: Among the 55 participants, both the external components, including the mask and tube, and the internal components, such as the humidifier and the interior of the main body, showed a substantial degree of contamination. The total and average daily duration of usage of the CPAP device did not show significant associations with the degree of contamination. Age was most consistently associated with the degree of contamination, such as in masks, humidifiers, and interior and exterior main parts. The degree of contamination of the internal components of the device was significantly correlated with the degree of contamination of the external components. CONCLUSION: Age-specific guidelines for managing the hygiene of external and internal CPAP components should be prepared.

A community effort to optimize sequence-based deep learning models of gene regulation.

A systematic evaluation of how model architectures and training strategies impact genomics model performance is needed. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. All top-performing models used neural networks but diverged in architectures and training strategies. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide models into modular building blocks. We tested all possible combinations for the top three models, further improving their performance. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets, demonstrating the progress that can be driven by gold-standard genomics datasets.

Evaluation and optimization of sequence-based gene regulatory deep learning models.

Neural networks have emerged as immensely powerful tools in predicting functional genomic regions, notably evidenced by recent successes in deciphering gene regulatory logic. However, a systematic evaluation of how model architectures and training strategies impact genomics model performance is lacking. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast, to best capture the relationship between regulatory DNA and gene expression. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. While some benchmarks produced similar results across the top-performing models, others differed substantially. All top-performing models used neural networks, but diverged in architectures and novel training strategies, tailored to genomics sequence data. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide any given model into logically equivalent building blocks. We tested all possible combinations for the top three models and observed performance improvements for each. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets. Overall, we demonstrate that high-quality gold-standard genomics datasets can drive significant progress in model development.

Mastering data visualization with Python: practical tips for researchers.

Big data have revolutionized the way data are processed and used across all fields. In the past, research was primarily conducted with a focus on hypothesis confirmation using sample data. However, in the era of big data, this has shifted to gaining insights from the collected data. Visualizing vast amounts of data to derive insights is crucial. For instance, leveraging big data for visualization can help identify and predict characteristics and patterns related to various infectious diseases. When data are presented in a visual format, patterns within the data become clear, making it easier to comprehend and provide deeper insights. This study aimed to comprehensively discuss data visualization and the various techniques used in the process. It also sought to enable researchers to directly use Python programs for data visualization. By providing practical visualization exercises on GitHub, this study aimed to facilitate their application in research endeavors.

Gustatory dysfunction is related to Parkinson's disease: A systematic review and meta-analysis.

BACKGROUND: Olfactory dysfunction has been reported to be involved in Parkinson's disease (PD) pathogenesis. However, gustatory dysfunction in PD has not been evaluated as in-depth as olfactory dysfunction. We reviewed the previously published studies regarding gustatory function in PD patients and suggested the possibility that gustatory dysfunction may also be associated with PD. METHODS: MEDLINE, Cochrane Library, Embase, and PubMed databases were searched for studies evaluating gustatory function in PD patients. We used the standardized mean difference and a 95% confidence interval (CI) as the effect analysis index regarding the taste strip test. The relative risk and 95% CI were used as the effect analysis index for the questionnaires and propylthiouracil (PTU)/phenylthiocarbamide (PTC) perception test. Statistical heterogeneity was assessed using forest plots, Cochran's Q, and the I2 statistic; heterogeneity was considered high when I2 was over 75%. Publication bias was assessed by funnel plots and the Egger bias test. RESULTS: We identified 19 articles that reported the results of gustatory function tests in PD patients and healthy controls. Most of these studies used various gustatory tests, including taste strips, questionnaires, taste solutions, PTU/PTC perception tests, and electrogustometry, and reported significantly lower gustatory function in PD patients than in the controls. However, several articles reported contradictory results. CONCLUSIONS: Based on these studies, gustatory dysfunction is closely related to PD. However, the number of studies and enrolled subjects was small, and a unified gustatory function test was lacking. Therefore, further studies with larger populations and normalized gustatory function tests are needed.

MCHeart: Multi-Channel-Based Heart Signal Processing Scheme for Heart Noise Detection Using Deep Learning.

In this study, we constructed a model to predict abnormal cardiac sounds using a diverse set of auscultation data collected from various auscultation positions. Abnormal heart sounds were identified by extracting features such as peak intervals and noise characteristics during systole and diastole. Instead of using raw signal data, we transformed them into log-mel 2D spectrograms, which were employed as input variables for the CNN model. The advancement of our model involves integrating a deep learning architecture with feature extraction techniques based on existing knowledge of cardiac data. Specifically, we propose a multi-channel-based heart signal processing (MCHeart) scheme, which incorporates our proposed features into the deep learning model. Additionally, we introduce the ReLCNN model by applying residual blocks and MHA mechanisms to the LCNN architecture. By adding murmur features with a smoothing function and training the ReLCNN model, the weighted accuracy of the model increased from 79.6% to 83.6%, showing a performance improvement of approximately 4% point compared to the LCNN baseline model.

The PEA Bead Test as a Screening Tool for Olfactory Dysfunction: A Preliminary Study.

This study, conducted in a single tertiary hospital, aimed to evaluate the 2-phenylethyl alcohol (PEA)-based sniffing bead test as a screening tool for olfactory dysfunction suitable for implementation in otorhinolaryngology and other settings, including general practice clinics. A total of 139 patients were enrolled, all of whom underwent both the PEA bead test and conventional psychophysical olfactory function testing. Characteristics such as age, sex, concurrent diseases, smoking history, and presence of gustatory dysfunction were reviewed. Statistical analyses included receiver operating characteristic curve analysis, area under the curve determination, and multivariate linear regression guided by the Akaike information criterion. Significant correlations were found between the PEA bead test and various subsets of the conventional YSK olfactory function test: threshold (r = 0.631), discrimination (r = 0.455), and identification (r = 0.596), as well as the composite threshold-discrimination-identification score (r = 0.686). These correlations remained significant even when adjusting for other clinical characteristics. The PEA bead test showed a sensitivity of 0.778 and a specificity of 0.958 for discriminating olfactory dysfunction at a cutoff value of ≥1. These findings indicate that the PEA bead test could be a valuable screening tool for olfactory dysfunction across diverse clinical settings. Further large-scale, multicenter research is recommended to confirm these preliminary results.

Mortality among adult patients with sepsis and septic shock in Korea: a systematic review and meta-analysis.

OBJECTIVE: To evaluate mortality from sepsis and septic shock in Korea during the past 10 years, we conducted a systematic review and meta-analysis. METHODS: We searched six databases for studies on mortality from sepsis and septic shock in adult patients. Primary outcomes were 28- or 30-day mortality and in-hospital mortality from sepsis and septic shock. To assess the risk of bias, we used the Newcastle-Ottawa Scale and Risk of Bias 2 tools. The protocol is registered in PROSPERO (No. CRD42022365739). RESULTS: A total of 61 studies were included. The mortality rates from sepsis and septic shock at 28 or 30 days were 22.7% (95% confidence interval [CI], 20.0%-25.6%; I2=89%) and 27.6% (95% CI, 22.3%-33.5%; I2=98%), respectively, according to the Sepsis-3 criteria. Furthermore, in accordance with the Sepsis-3 criteria, the in-hospital mortality rates were 28.1% (95% CI, 25.2%-31.1%; I2=87%) and 34.3% (95% CI, 27.2%-42.2%; I2=97%), respectively. CONCLUSION: The mortality rates from sepsis and septic shock in Korea are high. In the case of septic shock, the in-hospital mortality rate is approximately 30%.

The Clinical Application of Machine Learning Models for Risk Analysis of Ramp Lesions in Anterior Cruciate Ligament Injuries.

BACKGROUND: Peripheral tears of the posterior horn of the medial meniscus, known as "ramp lesions," are commonly found in anterior cruciate ligament (ACL)-deficient knees but are frequently missed on routine evaluation. PURPOSE: To predict the presence of ramp lesions in ACL-deficient knees using machine learning methods with associated risk factors. STUDY DESIGN: Cohort study (Diagnosis); Level of evidence, 2. METHODS: This study included 362 patients who underwent ACL reconstruction between June 2010 and March 2019. The exclusion criteria were combined fractures and multiple ligament injuries, except for medial collateral ligament injuries. Patients were grouped according to the presence of ramp lesions on arthroscopic surgery. Binary logistic regression was used to analyze risk factors including age, sex, body mass index, time from injury to surgery (≥3 or <3 months), mechanism of injury (contact or noncontact), side-to-side laxity, pivot-shift grade, medial and lateral tibial/meniscal slope, location of bone contusion, mechanical axis angle, and lateral femoral condyle (LFC) ratio. The receiver operating characteristic curve and area under the curve were also evaluated. RESULTS: Ramp lesions were identified in 112 patients (30.9%). The risk for ramp lesions increased with steeper medial tibial and meniscal slopes, higher knee laxity, and an increased LFC ratio. Comparing the final performance of all models, the random forest model yielded the best performance (area under the curve: 0.944), although there were no significant differences among the models (P > .05). The cut-off values for the presence of ramp lesions on receiver operating characteristic analysis were as follows: medial tibial slope >5.5° (P < .001), medial meniscal slope >5.0° (P < .001), and LFC ratio >71.3% (P = .033). CONCLUSION: Steep medial tibial and meniscal slopes, an increased LFC ratio, and higher knee rotatory laxity were observed risk factors for ramp lesions in patients with an ACL injury. The prediction model of this study could be used as a supplementary diagnostic tool for ramp lesions in ACL-injured knees. In general, care should be taken in patients with ramp lesions and its risk factors during ACL reconstruction.

Differential effect of meteorological factors and particulate matter with ≤ 10-µm diameter on epistaxis in younger and older children.

The differential effect of meteorological factors and air pollutants on pediatric epistaxis in younger and older children has not been evaluated. We evaluated the distribution of pediatric epistaxis cases between younger (0-5 years) and older children (6-18 years). Subsequently, we assessed and compared the effects of meteorological variables and the concentration of particulate matter measuring ≤ 10 µm in diameter (PM10) on hospital epistaxis presentation in younger and older children. This retrospective study included pediatric patients (n = 326) who presented with spontaneous epistaxis between January 2015 and August 2019. Meteorological conditions and PM10 concentration were the exposure variables, and data were obtained from Korea Meteorological Administration 75. The presence and cumulative number of epistaxis presentations per day were considered outcome variables. Air temperature, wind speed, sunshine duration, and PM10 concentration in younger children, and sunshine duration and air pressure in older children, significantly correlated with the presence of and cumulative number of epistaxis presentations per day. The PM10 concentration was not a significant factor in older children. Thus, meteorological factors and PM10 concentration may differentially affect epistaxis in younger (0-5-year-olds) and older (6-18-year-olds) children. Risk factors for pediatric epistaxis should be considered according to age.