Latent inter-organ mechanism of idiopathic pulmonary fibrosis unveiled by a generative computational approach.

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disease characterized by complex lung pathogenesis affecting approximately three million people worldwide. While the molecular and cellular details of the IPF mechanism is emerging, our current understanding is centered around the lung itself. On the other hand, many human diseases are the products of complex multi-organ interactions. Hence, we postulate that a dysfunctional crosstalk of the lung with other organs plays a causative role in the onset, progression and/or complications of IPF. In this study, we employed a generative computational approach to identify such inter-organ mechanism of IPF. This approach found unexpected molecular relatedness of IPF to neoplasm, diabetes, Alzheimer's disease, obesity, atherosclerosis, and arteriosclerosis. Furthermore, as a potential mechanism underlying this relatedness, we uncovered a putative molecular crosstalk system across the lung and the liver. In this inter-organ system, a secreted protein, kininogen 1, from hepatocytes in the liver interacts with its receptor, bradykinin receptor B1 in the lung. This ligand-receptor interaction across the liver and the lung leads to the activation of calmodulin pathways in the lung, leading to the activation of interleukin 6 and phosphoenolpyruvate carboxykinase 1 pathway across these organs. Importantly, we retrospectively identified several pre-clinical and clinical evidence supporting this inter-organ mechanism of IPF. In conclusion, such feedforward and feedback loop system across the lung and the liver provides a unique opportunity for the development of the treatment and/or diagnosis of IPF. Furthermore, the result illustrates a generative computational framework for machine-mediated synthesis of mechanisms that facilitates and complements the traditional experimental approaches in biomedical sciences.

Bayesian traction force estimation using cell boundary-dependent force priors.

Understanding the principles of cell migration necessitates measurements of the forces generated by cells. In traction force microscopy (TFM), fluorescent beads are placed on a substrate's surface and the substrate strain caused by the cell traction force is observed as displacement of the beads. Mathematical analysis can estimate traction force from bead displacement. However, most algorithms estimate substrate stresses independently of cell boundary, which results in poor estimation accuracy in low-density bead environments. To achieve accurate force estimation at low density, we proposed a Bayesian traction force estimation (BTFE) algorithm that incorporates cell-boundary-dependent force as a prior. We evaluated the performance of the proposed algorithm using synthetic data generated with mathematical models of cells and TFM substrates. BTFE outperformed other methods, especially in low-density bead conditions. In addition, the BTFE algorithm provided a reasonable force estimation using TFM images from the experiment.

Latent disease similarities and therapeutic repurposing possibilities uncovered by multi-modal generative topic modeling of human diseases.

Motivation: Human diseases are characterized by multiple features such as their pathophysiological, molecular and genetic changes. The rapid expansion of such multi-modal disease-omics space provides an opportunity to re-classify diverse human diseases and to uncover their latent molecular similarities, which could be exploited to repurpose a therapeutic-target for one disease to another. Results: Herein, we probe this underexplored space by soft-clustering 6955 human diseases by multi-modal generative topic modeling. Focusing on chronic kidney disease and myocardial infarction, two most life-threatening diseases, unveiled are their previously underrecognized molecular similarities to neoplasia and mental/neurological-disorders, and 69 repurposable therapeutic-targets for these diseases. Using an edit-distance-based pathway-classifier, we also find molecular pathways by which these targets could elicit their clinical effects. Importantly, for the 17 targets, the evidence for their therapeutic usefulness is retrospectively found in the pre-clinical and clinical space, illustrating the effectiveness of the method, and suggesting its broader applications across diverse human diseases. Availability and implementation: The code reported in this article is available at: https://github.com/skozawa170301ktx/MultiModalDiseaseModeling. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Associations of pulmonary and extrapulmonary computed tomographic manifestations with impaired physical activity in symptomatic patients with chronic obstructive pulmonary disease.

In patients with chronic obstructive pulmonary disease (COPD), emphysema, airway disease, and extrapulmonary comorbidities may cause various symptoms and impair physical activity. To investigate the relative associations of pulmonary and extrapulmonary manifestations with physical activity in symptomatic patients, this study enrolled 193 patients with COPD who underwent chest inspiratory/expiratory CT and completed COPD assessment test (CAT) and the Life-Space Assessment (LSA) questionnaires to evaluate symptom and physical activity. In symptomatic patients (CAT ≥ 10, n = 100), emphysema on inspiratory CT and air-trapping on expiratory CT were more severe and height-adjusted cross-sectional areas of pectoralis muscles (PM index) and adjacent subcutaneous adipose tissue (SAT index) on inspiratory CT were smaller in those with impaired physical activity (LSA < 60) than those without. In contrast, these findings were not observed in less symptomatic patients (CAT < 10). In multivariable analyses of the symptomatic patients, severe air-trapping and lower PM index and SAT index, but not CT-measured thoracic vertebrae bone density and coronary artery calcification, were associated with impaired physical activity. These suggest that increased air-trapping and decreased skeletal muscle and subcutaneous adipose tissue quantity are independently associated with impaired physical activity in symptomatic patients with COPD.

Deep learning-based reconstruction of chest ultra-high-resolution computed tomography and quantitative evaluations of smaller airways.

The full-iterative model reconstruction generates ultra-high-resolution computed tomography (U-HRCT) images comprising a 1024 × 1024 matrix and 0.25 mm thickness while suppressing image noises, allowing evaluating small airways 1-2 mm in diameter. However, this technique imposes huge computational burdens and requires a long reconstruction time. This study evaluated whether a recently-established deep learning-based reconstruction, Advanced intelligent Clear-IQ Engine (AiCE), allows quantitative morphological analyses of smaller airways with equal or better quality than the full-iterative model reconstruction while shortening the reconstruction time. In phantom tubes mimicking small airways, the measurement error of 0.5-mm-thickness wall was smaller on the AiCE-based than the full-iterative model-based U-HRCT. Moreover, in five patients with chronic obstructive pulmonary disease, the AiCE-based U-HRCT decreased the reconstruction time approximately by 90% with a modest improvement in image noise, contrast, and sharpness compared to the full-iterative model-based U-HRCT. Therefore, the AiCE-based U-HRCT can be readily used clinically for morphologically evaluating peripheral small airways.

Influence of Asthma Onset on Airway Dimensions on Ultra-high-resolution Computed Tomography in Chronic Obstructive Pulmonary Disease.

PURPOSE: Asthma onset before the age of 40 years is associated with distinct clinical manifestations in chronic obstructive pulmonary disease (COPD) patients, but its morphologic features remain unestablished. This study aimed to explore airway morphology in COPD patients with asthma onset before 40 years of age using ultra-high-resolution computed tomography (U-HRCT), which allows a more accurate quantitation of the lumen and the wall in smaller airways than using conventional CT. MATERIALS AND METHODS: Clinical data of 500 consecutive patients undergoing full inspiratory U-HRCT (1024×1024 matrix and 0.25 mm slice thickness) were retrospectively analyzed. COPD patients without asthma, COPD patients with asthma onset at age below or 40 years and above, and non-COPD smoker controls (N=137, 29, 34, and 22, respectively) were enrolled. The length, lumen area (LA), wall thickness and area (WA), and wall area percent (WA%) of the segmental (third-generation) to sub-subsegmental (fifth-generation) bronchus and the low attenuation volume percent (LAV%) were measured. RESULTS: LA and WA were smaller in the fourth and fifth generation in COPD patients than in non-COPD controls, regardless of the age of asthma onset. LA was smaller and WA% was larger in the fourth-generation and fifth-generation airways in COPD with asthma onset before 40 years than COPD without asthma, whereas WA did not differ between them. In multivariate analyses, asthma onset before 40 years was associated with smaller LA in COPD patients independent of demographics, use of inhaled corticosteroids and long-acting bronchodilators, airflow limitation, and LAV%. CONCLUSIONS: Asthma onset before 40 years of age could be associated with greater lumen narrowing of the airways in COPD.

Lobar distribution of non-emphysematous gas trapping and lung hyperinflation in chronic obstructive pulmonary disease.

BACKGROUND: Lung hyperinflation in chronic obstructive pulmonary disease (COPD) is closely associated with emphysema and non-emphysematous gas trapping, termed functional small airway disease (fSAD), on inspiratory and expiratory computed tomography (CT). Because the cranial-caudal emphysema distribution affects pulmonary function and fSAD may precede emphysema on CT, we tested the hypothesis that lobar fSAD distribution would affect lung hyperinflation differently in COPD with minimal and established emphysema. METHODS: The volume percentages of fSAD and emphysema (fSAD% and Emph%) over the upper and lower lobes were measured using inspiratory and expiratory CT in 70 subjects with COPD. Subjects were divided into those with minimal and established emphysema (n = 36 and 34) using a threshold of 10% Emph% in the whole lung. RESULTS: In the minimal emphysema group, fSAD% in the upper and lower lobes was positively correlated with functional residual capacity (FRC) and residual volume to total lung capacity ratio (RV/TLC), and the correlation of fSAD% with RV/TLC was greater in the lower lobes. Conversely, in the established emphysema group, fSAD% in the upper and lower lobes was correlated with RV/TLC, but not with FRC. In multivariate analysis, fSAD% in the lower lobes, but not in the upper lobes, was associated with RV/TLC in subjects with minimal emphysema after adjusting for age, smoking status, and bronchodilator use. CONCLUSION: Non-emphysematous gas trapping in the upper and lower lobes has a distinct physiological effect, especially in COPD with minimal emphysema. This local evaluation might allow sensitive detection of changes in lung hyperinflation in COPD.

Predicting Human Clinical Outcomes Using Mouse Multi-Organ Transcriptome.

Approximately 90% of pre-clinically validated drugs fail in clinical trials owing to unanticipated clinical outcomes, costing over several hundred million US dollars per drug. Despite such critical importance, translating pre-clinical data to clinical outcomes remain a major challenge. Herein, we designed a modality-independent and unbiased approach to predict clinical outcomes of drugs. The approach exploits their multi-organ transcriptome patterns induced in mice and a unique mouse-transcriptome database "humanized" by machine learning algorithms and human clinical outcome datasets. The cross-validation with small-molecule, antibody, and peptide drugs shows effective and efficient identification of the previously known outcomes of 5,519 adverse events and 11,312 therapeutic indications. In addition, the approach is adaptable to deducing potential molecular mechanisms underlying these outcomes. Furthermore, the approach identifies previously unsuspected repositioning targets. These results, together with the fact that it requires no prior structural or mechanistic information of drugs, illustrate its versatile applications to drug development process.

Direct evaluation of peripheral airways using ultra-high-resolution CT in chronic obstructive pulmonary disease.

PURPOSE: Disease in small airways <2 mm in diameter is a major pathology of chronic obstructive pulmonary disease (COPD). However, compared to airways <1 mm in diameter, the pathophysiological role of airways 1-2 mm in diameter remains unclear. This study analysed phantom and human COPD data to test the hypothesis that ultra-high-resolution computed tomography (U-HRCT) can accurately measure peripheral airways that are difficult to measure with conventional CT. METHOD: The lower limit of lumen sizes measurable on U-HRCT was determined using phantom tubes. In the cross-sectional data of 110 males with COPD who underwent U-HRCT (1024 × 1024 matrix, 0.25 mm slice thickness) and spirometry, all 3rd (segmental) to 6th generation airways of the right apical and basal posterior bronchus (RB1 and RB10) were analysed. RESULTS: The errors in measuring the lumen area (LA) of phantom tubes ≥1.3 and 1.0 mm in diameter were within ±10 and -24%, respectively. The internal diameters for 70 and 62% of the 6th generation RB1 and RB10 airways were <2 mm. The numbers of 6th generation RB1 and RB10 airways decreased as the airflow limitation severity increased. Among the mean LA and sum of LA(sum-LA) of the 3rd to 6th generation airways, the sum-LA of the 6th generation had the largest impact on airflow limitation. CONCLUSIONS: U-HRCT enables accurate and direct evaluation of peripheral airways 1-2 mm in diameter. The 6th generation airways are commonly <2 mm in diameter, and the sum-LA can be a useful CT biomarker that reflects airflow limitation in COPD.

Tumour volume comparison between 16-row multi-detector computed tomography and 320-row area-detector computed tomography in patients with small lung tumours treated with stereotactic body radiotherapy: Effect of respiratory motion.

PURPOSE: We compared image quality and volume of a moving simulated tumour and of lung tumours in patients who were treated with stereotactic body radiotherapy (SBRT) in a 16-row multi-detector CT (MDCT) versus a 320-row area-detector CT (ADCT). Tumour volumes in each respiratory phase were also evaluated. MATERIALS AND METHODS: We acquired static and four-dimensional CT (4DCT) images of a moving phantom with 10- and 30-mm amplitudes with three periods of patterns (2, 4, and 6 s). Breath-hold and 4DCT images were acquired for 12 lung tumour patients who underwent SBRT. Image data were acquired via MDCT and ADCT. The tumours were delineated in each respiratory phase and their volumes in end-expiratory/end-inspiratory phase and mid-respiratory phase were compared. RESULTS: In the phantom study, tumour volumes were smaller and closer to the static image when evaluated by ADCT than by MDCT. In the clinical study, average tumour volumes ± standard deviations were 9.58 ± 1.07 cm3 with MDCT (2.5-mm slice), and 7.12 ± 0.23 cm3 with ADCT (p < 0.01). Tumour volumes were closer to that of the breath hold CT in all patients evaluated by ADCT than by MDCT. Unlike MDCT, tumour volumes acquired by ADCT were smaller in end-expiratory or end-inspiratory phase than in the mid-respiratory phase. CONCLUSIONS: Tumour volumes in each of the respiratory phases in ADCT were significantly smaller and closer to the static image than the corresponding volumes in MDCT. This suggests that treated volume can be reduced if ADCT is used in treatment planning.

Quantitative measurement of airway dimensions using ultra-high resolution computed tomography.

BACKGROUND: Quantitative measurement of airway dimensions using computed tomography (CT) is performed in relatively larger airways due to the limited resolution of CT scans. Nevertheless, the small airway is an important pathological lesion in lung diseases such as chronic obstructive pulmonary disease (COPD) and asthma. Ultra-high resolution scanning may resolve the smaller airway, but its accuracy and limitations are unclear. METHODS: Phantom tubes were imaged using conventional (512 × 512) and ultra-high resolution (1024 × 1024 and 2048 × 2048) scans. Reconstructions were performed using the forward-projected model-based iterative reconstruction solution (FIRST) algorithm in 512 × 512 and 1024 × 1024 matrix scans and the adaptive iterative dose reduction 3D (AIDR-3D) algorithm for all scans. In seven subjects with COPD, the airway dimensions were measured using the 1024 × 1024 and 512 × 512 matrix scans. RESULTS: Compared to the conventional 512 × 512 scan, variations in the CT values for air were increased in the ultra-high resolution scans, except in the 1024×1024 scan reconstructed through FIRST. The measurement error of the lumen area of the tube with 2-mm diameter and 0.5-mm wall thickness (WT) was minimal in the ultra-high resolution scans, but not in the conventional 512 × 512 scan. In contrast to the conventional scans, the ultra-high resolution scans resolved the phantom tube with ≥ 0.6-mm WT at an error rate of < 11%. In seven subjects with COPD, the WT showed a lower value with the 1024 × 1024 scans versus the 512 × 512 scans. CONCLUSIONS: The ultra-high resolution scan may allow more accurate measurement of the bronchioles with smaller dimensions compared with the conventional scan.

The Body-wide Transcriptome Landscape of Disease Models.

Virtually all diseases affect multiple organs. However, our knowledge of the body-wide effects remains limited. Here, we report the body-wide transcriptome landscape across 13-23 organs of mouse models of myocardial infarction, diabetes, kidney diseases, cancer, and pre-mature aging. Using such datasets, we find (1) differential gene expression in diverse organs across all models; (2) skin as a disease-sensor organ represented by disease-specific activities of putative gene-expression network; (3) a bone-skin cross talk mediated by a bone-derived hormone, FGF23, in response to dysregulated phosphate homeostasis, a known risk-factor for kidney diseases; (4) candidates for the signature activities of many more putative inter-organ cross talk for diseases; and (5) a cross-species map illustrating organ-to-organ and model-to-disease relationships between human and mouse. These findings demonstrate the usefulness and the potential of such body-wide datasets encompassing mouse models of diverse disease types as a resource in biological and medical sciences. Furthermore, the findings described herein could be exploited for designing disease diagnosis and treatment.

Re-evaluating the functional landscape of the cardiovascular system during development.

The cardiovascular system facilitates body-wide distribution of oxygen, a vital process for the development and survival of virtually all vertebrates. However, the zebrafish, a vertebrate model organism, appears to form organs and survive mid-larval periods without a functional cardiovascular system. Despite such dispensability, it is the first organ to develop. Such enigma prompted us to hypothesize other cardiovascular functions that are important for developmental and/or physiological processes. Hence, systematic cellular ablations and functional perturbations were performed on the zebrafish cardiovascular system to gain comprehensive and body-wide understanding of such functions and to elucidate the underlying mechanisms. This approach identifies a set of organ-specific genes, each implicated for important functions. The study also unveils distinct cardiovascular mechanisms, each differentially regulating their expressions in organ-specific and oxygen-independent manners. Such mechanisms are mediated by organ-vessel interactions, circulation-dependent signals, and circulation-independent beating-heart-derived signals. A comprehensive and body-wide functional landscape of the cardiovascular system reported herein may provide clues as to why it is the first organ to develop. Furthermore, these data could serve as a resource for the study of organ development and function.

Internal evaluation of impregnation treatment of waterlogged wood; relation between concentration of internal materials and relaxation time using magnetic resonance imaging.

The purpose of this study is to clarify the degree of impregnation resulting from treatment of internal waterlogged wood samples using MRI. On a 1.5T MR scanner, T1 and T2 measurements were performed using inversion recovery and spin-echo sequences, respectively. The samples were cut waterlogged pieces of wood treated with various impregnation techniques which were divided into different concentrations of trehalose (C12H22O11) and polyethylene glycol (PEG; HO-(C2H4O)n-H) solutions. Then these samples underwent impregnation treatment every two weeks. From the results, we found that the slope of the T1-concentration curve using linear fitting showed the value of the internal area for PEG to be higher than the external area; internal, -2.73ms/wt% (R2=0.880); external, -1.50ms/wt% (R2=0.887). Furthermore, the slope of the T1-concentration curve using linear fitting showed the values for trehalose to have almost no difference when comparing the internal and the external areas; internal, -2.79ms/wt% (R2=0.759); external, -3.02ms/wt% (R2=0.795). However, the slope of the T2-concentration curve using linear fitting for PEG showed that there was only a slight change between the internal and the external areas; internal, 0.26ms/wt% (R2=0.642); external, 0.18ms/wt% (R2=0.920). The slope of the T2-concentration curve did not show a change in linear relationship between the internal and the external areas; internal, 0.06ms/wt% (R2=0.175); external, -0.14ms/wt% (R2=0.043). In conclusion, using visualization of relaxation time T1, it is possible to obtain more detail information noninvasively concerning the state of impregnation treatment of internal waterlogged wood.

Feasibility and diagnostic performance of fractional flow reserve measurement derived from coronary computed tomography angiography in real clinical practice.

Non-invasive fractional flow reserve measured by coronary computed tomography angiography (FFRCT) has demonstrated a high diagnostic accuracy for detecting coronary artery disease (CAD) in selected patients in prior clinical trials. However, feasibility of FFRCT in unselected population have not been fully evaluated. Among 60 consecutive patients who had suspected significant CAD by coronary computed tomography angiography (CCTA) and were planned to undergo invasive coronary angiography, 48 patients were enrolled in this study comparing FFRCT with invasive fractional flow reserve (FFR) without any exclusion criteria for the quality of CCTA image. FFRCT was measured in a blinded fashion by an independent core laboratory. FFRCT value was evaluable in 43 out of 48 (89.6 %) patients with high prevalence of severe calcification in CCTA images [calcium score (CS) >400: 40 %, and CS > 1000: 19 %). Per-vessel FFRCT value showed good correlation with invasive FFR value (Spearman's rank correlation = 0.69, P < 0.001). The area under the receiver operator characteristics curve (AUC) of FFRCT was 0.87. Per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 68.6, 92.9, 52.4, 56.5, and 91.7 %, respectively. Even in eight patients (13 vessels) with extremely severely calcified lesions (CS > 1000), per-vessel FFRCT value showed a diagnostic performance similar to that in patients with CS ≤ 1000 (Spearman's rank correlation = 0.81, P < 0.001). FFRCT could be measured in the majority of consecutive patients who had suspected significant CAD by CCTA in real clinical practice and demonstrated good diagnostic performance for detecting hemodynamically significant CAD even in patients with extremely severe calcified vessels.

Real-time prediction of cell division timing in developing zebrafish embryo.

Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation-thus, presenting a new opportunity for in vivo experimental systems.

Shootin1-cortactin interaction mediates signal-force transduction for axon outgrowth.

Motile cells transduce environmental chemical signals into mechanical forces to achieve properly controlled migration. This signal-force transduction is thought to require regulated mechanical coupling between actin filaments (F-actins), which undergo retrograde flow at the cellular leading edge, and cell adhesions via linker "clutch" molecules. However, the molecular machinery mediating this regulatory coupling remains unclear. Here we show that the F-actin binding molecule cortactin directly interacts with a clutch molecule, shootin1, in axonal growth cones, thereby mediating the linkage between F-actin retrograde flow and cell adhesions through L1-CAM. Shootin1-cortactin interaction was enhanced by shootin1 phosphorylation by Pak1, which is activated by the axonal chemoattractant netrin-1. We provide evidence that shootin1-cortactin interaction participates in netrin-1-induced F-actin adhesion coupling and in the promotion of traction forces for axon outgrowth. Under cell signaling, this regulatory F-actin adhesion coupling in growth cones cooperates with actin polymerization for efficient cellular motility.

Conversion of a signal into forces for axon outgrowth through Pak1-mediated shootin1 phosphorylation.

Soluble guidance cues can direct cellular protrusion and migration by modulating adhesion and cytoskeletal dynamics. Actin filaments (F-actins) polymerize at the leading edge of motile cells and depolymerize proximally [1, 2]; this, together with myosin II activity, induces retrograde flow of F-actins [3-5]. It has been proposed that the traction forces underlying cellular motility may be regulated by the modulation of coupling efficiency between F-actin flow and the extracellular substrate via "clutch" molecules [6-10]. However, how cell signaling controls the coupling efficiency remains unknown. Shootin1 functions as a linker molecule that couples F-actin retrograde flow and the substrate at neuronal growth cones to promote axon outgrowth [11]. Here we show that shootin1 is located at a critical interface, transducing a chemical signal into traction forces for axon outgrowth. We found that a chemoattractant, netrin-1, positively regulates traction forces at axonal growth cones via Pak1-mediated shootin1 phosphorylation. This phosphorylation enhanced the interaction between shootin1 and F-actin retrograde flow, thereby promoting F-actin-substrate coupling, force generation, and concomitant filopodium extension and axon outgrowth. These results suggest that dynamic actin-substrate coupling can transduce chemical signals into mechanical forces to control cellular motility and provide a molecular-level description of how this transduction may occur.