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Visual observing muscle tissue regeneration is used to measure experimental effect size in biological research to discover the mechanism of muscle strength decline due to illness or aging. Quantitative computer imaging analysis for support evaluating the recovery phase has not been established because of the localized nature of recovery and the difficulty in selecting image features for cells in regeneration. We constructed MyoRegenTrack for segmenting cells and classifying their regeneration phase in hematoxylin–eosin (HE) stained images. A straightforward approach to classification is supervised learning. However, obtaining detailed annotations for each fiber in a whole slide image is impractical in terms of cost and accuracy. Thus, we propose to learn individual recovery phase classification utilizing the proportions of cell class depending on the days after muscle injection to induce regeneration. We extract implicit multidimensional features from the HE-stained tissue images and train a classifier using weakly supervised learning, guided by their class proportion for elapsed time on recovery. We confirmed the effectiveness of MyoRegenTrack by comparing its results with expert annotations. A comparative study of the recovery relation between two different muscle injections shows that the analysis result using MyoRegenTrack is consistent with findings from previous studies. [ABSTRACT FROM AUTHOR]

The liver is the main gateway from the gut, and the unidirectional sinusoidal flow from portal to central veins constitutes heterogenous zones, including the periportal vein (PV) and the pericentral vein zones1–5. However, functional differences in the immune system in each zone remain poorly understood. Here intravital imaging revealed that inflammatory responses are suppressed in PV zones. Zone-specific single-cell transcriptomics detected a subset of immunosuppressive macrophages enriched in PV zones that express high levels of interleukin-10 and Marco, a scavenger receptor that sequesters pro-inflammatory pathogen-associated molecular patterns and damage-associated molecular patterns, and consequently suppress immune responses. Induction of Marco+ immunosuppressive macrophages depended on gut microbiota. In particular, a specific bacterial family, Odoribacteraceae, was identified to induce this macrophage subset through its postbiotic isoallolithocholic acid. Intestinal barrier leakage resulted in inflammation in PV zones, which was markedly augmented in Marco-deficient conditions. Chronic liver inflammatory diseases such as primary sclerosing cholangitis (PSC) and non-alcoholic steatohepatitis (NASH) showed decreased numbers of Marco+ macrophages. Functional ablation of Marco+ macrophages led to PSC-like inflammatory phenotypes related to colitis and exacerbated steatosis in NASH in animal experimental models. Collectively, commensal bacteria induce Marco+ immunosuppressive macrophages, which consequently limit excessive inflammation at the gateway of the liver. Failure of this self-limiting system promotes hepatic inflammatory disorders such as PSC and NASH.A subset of Macro-positive macrophages is identified to have immunosuppressive functions in the periportal vein zones of the liver to mediate excessive inflammation, and their effects depend on commensal gut bacteria. [ABSTRACT FROM AUTHOR]

Background: In trauma systems, criteria for individualised and optimised administration of tranexamic acid (TXA), an antifibrinolytic, are yet to be established. This study used nationwide cohort data from Japan to evaluate the association between TXA and in-hospital mortality among all patients with blunt trauma based on clinical phenotypes (trauma phenotypes). Methods: A retrospective analysis was conducted using data from the Japan Trauma Data Bank (JTDB) spanning 2019 to 2021. Results: Of 80,463 patients with trauma registered in the JTDB, 53,703 met the inclusion criteria, and 8046 (15.0%) received TXA treatment. The patients were categorised into eight trauma phenotypes. After adjusting with inverse probability treatment weighting, in-hospital mortality of the following trauma phenotypes significantly reduced with TXA administration: trauma phenotype 1 (odds ratio [OR] 0.68 [95% confidence interval [CI] 0.57–0.81]), trauma phenotype 2 (OR 0.73 [0.66–0.81]), trauma phenotype 6 (OR 0.52 [0.39–0.70]), and trauma phenotype 8 (OR 0.67 [0.60–0.75]). Conversely, trauma phenotypes 3 (OR 2.62 [1.98–3.47]) and 4 (OR 1.39 [1.11–1.74]) exhibited a significant increase in in-hospital mortality. Conclusions: This is the first study to evaluate the association between TXA administration and survival outcomes based on clinical phenotypes. We found an association between trauma phenotypes and in-hospital mortality, indicating that treatment with TXA could potentially influence this relationship. Further studies are needed to assess the usefulness of these phenotypes. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer tumors are considered to have intratumoral, as well as human epidermal growth factor receptor 2 (HER2), heterogeneity. Tumors with high intratumoral heterogeneity (ITH) have demonstrated therapeutic resistance. However, studies on cancer heterogeneity as a prognostic factor in breast cancer have been limited. Therefore, we evaluated HER2 ITH, which was manifested by the shape of HER2 fluorescence in situ hybridization amplification distributed histograms (HER2 FISH distributions) with the HER2 gene copy number within a tumor sample. We aimed to determine whether high HER2 heterogeneity is clinically significant for poor prognosis due to resistance to postoperative adjuvant therapy with HER2-targeted agents in primary breast cancer. Indeed, we were able to show herein that high HER2 heterogeneity is significantly associated with poorer prognosis in patients with HER2-positive breast cancer. These results indicated that high HER2 heterogeneity is a factor predicting poor prognosis in patients with HER2-positive breast cancer. Our present observation seemed to be clinically important, because it is expected that our HER2 FISH distribution analysis of heterogeneity might be a convenient and clinically useful method for the prognosis prediction of patients after HER2 adjuvant therapy. Purpose: Breast cancer tumors frequently have intratumoral heterogeneity (ITH). Tumors with high ITH cause therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to a poor prognosis for HER2-targeted adjuvant therapy resistance in primary breast cancers. Methods: This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with the HER2 gene copy number within a tumor sample. Each tumor was classified into a biphasic grade graph (high heterogeneity [HH]) group or a monophasic grade graph (low heterogeneity [LH]) group based on heterogeneity. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up. Results: Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: p < 0.001 (HH:63% vs. LH:91% at 10 years) and for the OS: p = 0.012 (HH:78% vs. LH:95% at 10 years). Conclusions: High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach to heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy. [ABSTRACT FROM AUTHOR]

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories—fluctuations, rapid environmental responses, and long-term changes—converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is now a common disease, but its pathogenesis remains unknown. Blood circulating proteins reflect host defenses against COVID-19. We investigated whether evaluation of longitudinal blood proteomics for COVID-19 and merging with clinical information would allow elucidation of its pathogenesis and develop a useful clinical phenotype. Methods: To achieve the first goal (determining key proteins), we derived plasma proteins related to disease severity by using a first discovery cohort. We then assessed the association of the derived proteins with clinical outcome in a second discovery cohort. Finally, the candidates were validated by enzyme-linked immunosorbent assay in a validation cohort to determine key proteins. For the second goal (understanding the associations of the clinical phenotypes with 28-day mortality and clinical outcome), we assessed the associations between clinical phenotypes derived by latent cluster analysis with the key proteins and 28-day mortality and clinical outcome. Results: We identified four key proteins (WFDC2, GDF15, CHI3L1, and KRT19) involved in critical pathogenesis from the three different cohorts. These key proteins were related to the function of cell adhesion and not immune response. Considering the multicollinearity, three clinical phenotypes based on WFDC2, CHI3L1, and KRT19 were identified that were associated with mortality and clinical outcome. Conclusion: The use of these easily measured key proteins offered new insight into the pathogenesis of COVID-19 and could be useful in a potential clinical application. [ABSTRACT FROM AUTHOR]

Runt-related transcription factor 2 (Runx2), a regulator of osteoblast differentiation, is pathologically involved in vascular calcification; however, the significance of Runx2 in cardiac homeostasis remains unclear. Here, we investigated the roles of Runx2 in cardiac remodeling after myocardial infarction (MI). The expression of Runx2 mRNA and protein was upregulated in murine hearts after MI. Runx2 was expressed in heart-infiltrating myeloid cells, especially in macrophages, at the border zone of post-infarct myocardium. To analyze the biological functions of Runx2 in cardiac remodeling, myeloid cell-specific Runx2 deficient (CKO) mice were exposed to MI. After MI, ventricular weight/tibia length ratio was increased in CKO mice, concomitant with severe cardiac dysfunction. Cardiac fibrosis was exacerbated in CKO mice, consistent with the upregulation of collagen 1a1 expression. Mechanistically, immunohistochemical analysis using anti-CD31 antibody showed that capillary density was decreased in CKO mice. Additionally, conditioned culture media of myeloid cells from Runx2 deficient mice exposed to MI induced the tube formation of vascular endothelial cells to a lesser extent than those from control mice. RNA-sequence showed that the expression of pro-angiogenic or anti-angiogenic factors was altered in macrophages from Runx2-deficient mice. Collectively, Runx2+ myeloid cells infiltrate into post-infarct myocardium and prevent adverse cardiac remodeling, at least partially, by regulating endothelial cell function. [ABSTRACT FROM AUTHOR]

Background: Trauma is a heterogeneous condition, and specific clinical phenotypes may identify target populations that could benefit from certain treatment strategies. In this retrospective study, we determined clinical phenotypes and identified new target populations of trauma patients and their treatment strategies.Methods: We retrospectively analyzed datasets from the Japan Trauma Data Bank and determined trauma death clinical phenotypes using statistical machine learning techniques and evaluation of biological profiles.Results: The analysis included 71,038 blunt trauma patients [median age, 63 (interquartile range [IQR], 40-78) years; 45,479 (64.0%) males; median Injury Severity Score, 13 (IQR, 9-20)], and the derivation and validation cohorts included 42,780 (60.2%) and 28,258 (39.8%) patients, respectively. Of eight derived phenotypes (D-1-D-8), D-8 (n = 2178) had the highest mortality (48.6%) with characteristic severely disturbed consciousness and was further divided into four phenotypes: D-8α, multiple trauma in the young (n = 464); D-8β, head trauma with lower body temperature (n = 178); D-8γ, severe head injury in the elderly (n = 957); and D-8δ, multiple trauma, with higher predicted mortality than actual mortality (n = 579). Phenotype distributions were comparable in the validation cohort. Biological profile analysis of 90 trauma patients revealed that D-8 exhibited excessive inflammation, including enhanced acute inflammatory response, dysregulated complement activation pathways, and impaired coagulation, including downregulated coagulation and platelet degranulation pathways, compared with other phenotypes.Conclusions: We identified clinical phenotypes with high mortality, and the evaluation of the molecular pathogenesis underlying these clinical phenotypes suggests that lethal trauma may involve excessive inflammation and coagulation disorders. [ABSTRACT FROM AUTHOR]

Oxygen plays an important role in diverse biological processes. However, since quantitation of the partial pressure of cellular oxygen in vivo is challenging, the extent of oxygen perturbation in situ and its cellular response remains underexplored. Using two‐photon phosphorescence lifetime imaging microscopy, we determine the physiological range of oxygen tension in osteoclasts of live mice. We find that oxygen tension ranges from 17.4 to 36.4 mmHg, under hypoxic and normoxic conditions, respectively. Physiological normoxia thus corresponds to 5% and hypoxia to 2% oxygen in osteoclasts. Hypoxia in this range severely limits osteoclastogenesis, independent of energy metabolism and hypoxia‐inducible factor activity. We observe that hypoxia decreases ten‐eleven translocation (TET) activity. Tet2/3 cooperatively induces Prdm1 expression via oxygen‐dependent DNA demethylation, which in turn activates NFATc1 required for osteoclastogenesis. Taken together, our results reveal that TET enzymes, acting as functional oxygen sensors, regulate osteoclastogenesis within the physiological range of oxygen tension, thus opening new avenues for research on in vivo response to oxygen perturbation. Synopsis: Within the physiological range of oxygen tension, ten‐eleven translocation (TET) enzymes act as functional oxygen sensors involved in osteoclastogenesis. Oxygen tension ranges from 17.4 to 36.4 mmHg in osteoclasts of live mice.Hypoxia in this range decreases TET activity of osteoclasts but does not affect energy metabolism and HIF activity.Tet2/3 regulate osteoclastogenesis by controlling Prdm1 expression via oxygen‐dependent DNA demethylation. [ABSTRACT FROM AUTHOR]

Skeletal muscles exert remarkable regenerative or adaptive capacities in response to injuries or mechanical loads. However, the cellular networks underlying muscle adaptation are poorly understood compared to those underlying muscle regeneration. We employed single-cell RNA sequencing to investigate the gene expression patterns and cellular networks activated in overloaded muscles and compared these results with those observed in regenerating muscles. The cellular composition of the 4-day overloaded muscle, when macrophage infiltration peaked, closely resembled that of the 10-day regenerating muscle. In addition to the mesenchymal progenitor-muscle satellite cell (MuSC) axis, interactome analyses or targeted depletion experiments revealed communications between mesenchymal progenitors-macrophages and macrophages-MuSCs. Furthermore, granulin, a macrophage-derived factor, inhibited MuSC differentiation, and Granulin -knockout mice exhibited blunted muscle hypertrophy due to the premature differentiation of overloaded MuSCs. These findings reveal the critical role of granulin through the relayed communications of mesenchymal progenitors, macrophages, and MuSCs in facilitating efficient muscle hypertrophy. [Display omitted] • Mesenchymal progenitors recruit monocytes/Møs in overloaded muscle • Number of MuSC-derived myonuclei decreased in Mø-suppressed mice • Mø-derived granulin acts on MuSCs and inhibits myogenic differentiation • Granulin-null mice exhibit blunted muscle hypertrophy Zhang et al. conducted single-cell RNA sequencing of overloaded muscles and revealed the relayed signaling among mesenchymal progenitors-macrophages (Møs)-muscle satellite cells (MuSCs). Among Mø-derived factors, they found that granulin crosses the basal lamina, directly acts on MuSCs, and promotes MuSC expansion by suppressing the expression of MyoD and myogenin. [ABSTRACT FROM AUTHOR]

Osteoclastic bone resorption and osteoblastic bone formation/replenishment are closely coupled in bone metabolism. Anabolic parathyroid hormone (PTH), which is commonly used for treating osteoporosis, shifts the balance from osteoclastic to osteoblastic, although it is unclear how these cells are coordinately regulated by PTH. Here, we identify a serine protease inhibitor, secretory leukocyte protease inhibitor (SLPI), as a critical mediator that is involved in the PTH-mediated shift to the osteoblastic phase. Slpi is highly upregulated in osteoblasts by PTH, while genetic ablation of Slpi severely impairs PTH-induced bone formation. Slpi induction in osteoblasts enhances its differentiation, and increases osteoblast–osteoclast contact, thereby suppressing osteoclastic function. Intravital bone imaging reveals that the PTH-mediated association between osteoblasts and osteoclasts is disrupted in the absence of SLPI. Collectively, these results demonstrate that SLPI regulates the communication between osteoblasts and osteoclasts to promote PTH-induced bone anabolism. The mechanism by which parathyroid hormone mediates the switch from bone resorption to bone formation is unclear. Here, the authors show that SLPI regulates the communication between osteoblasts and osteoclasts to promote the anabolic effect of parathyroid hormone. [ABSTRACT FROM AUTHOR]

Muscle stem cells, also called muscle satellite cells (MuSCs), are responsible for skeletal muscle regeneration and are sustained in an undifferentiated and quiescent state under steady conditions. The calcitonin receptor (CalcR)‐protein kinase A (PKA)‐Yes‐associated protein 1 (Yap1) axis is one pathway that maintains quiescence in MuSCs. Although CalcR signaling in MuSCs has been identified, the critical CalcR signaling targets are incompletely understood. Here, we show the relevance between the ectopic expression of delta‐like non‐canonical Notch ligand 1 (Dlk1) and the impaired quiescent state in CalcR‐conditional knockout (cKO) MuSCs. Dlk1 expression was rarely detected in both quiescent and proliferating MuSCs in control mice, whereas Dlk1 expression was remarkably increased in CalcR‐cKO MuSCs at both the mRNA and protein levels. It is noteworthy that all Ki67+ non‐quiescent CalcR‐cKO MuSCs express Dlk1, and non‐quiescent CalcR‐cKO MuSCs are enriched in the Dlk1+ fraction by cell sorting. Using mutant mice, we demonstrated that PKA‐activation or Yap1‐depletion suppressed Dlk1 expression in CalcR‐cKO MuSCs, which suggests that the CalcR‐PKA‐Yap1 axis inhibits the expression of Dlk1 in quiescent MuSCs. Moreover, the loss of Dlk1 rescued the quiescent state in CalcR‐cKO MuSCs, which indicates that the ectopic expression of Dlk1 disturbs quiescence in CalcR‐cKO. Collectively, our results suggest that ectopically expressed Dlk1 is responsible for the impaired quiescence in CalcR‐cKO MuSCs. [ABSTRACT FROM AUTHOR]

There have been many attempts to visualize the inflamed joints using multiphoton microscopy. However, due to the hypervascular and multilayered structure of the inflamed synovium, intravital imaging of the deep synovial tissue has been difficult. Here, we established original intravital imaging systems to visualize synovial tissue and pathological osteoclasts at the pannus–bone interface using multiphoton microscopy. Combined with fluorescence-labeling of CTLA-4 Ig, a biological agent used for the treatment of rheumatoid arthritis, we identified that CTLA-4 Ig was distributed predominantly within the inflamed synovium and bound to CX3CR1+ macrophages and CD140a+ fibroblasts 6 h after injection, but not to mature osteoclasts. Intravital imaging of blood and lymphatic vessels in the inflamed synovium further showed that extravasated CTLA-4 Ig was immediately drained through lymphatic vessels under acute arthritic conditions, but the drainage activity was retarded under chronic conditions. These results indicate that this intravital synovial imaging system can serve as a platform for exploring the dynamics of immune cells, osteoclasts, and biological agents within the synovial microenvironment in vivo. [ABSTRACT FROM AUTHOR]

Bone morphogenetic protein (BMP)-2 plays a central role in bone-tissue engineering because of its potent bone-induction ability. However, the process of BMP-induced bone formation in vivo remains poorly elucidated. Here, we aimed to establish a method for intravital imaging of the entire process of BMP-2-induced ectopic bone formation. Using multicolor intravital imaging in transgenic mice, we visualized the spatiotemporal process of bone induction, including appearance and motility of osteoblasts and osteoclasts, angiogenesis, collagen-fiber formation, and bone-mineral deposition. Furthermore, we investigated how PTH1-34 affects BMP-2-induced bone formation, which revealed that PTH1-34 administration accelerated differentiation and increased the motility of osteoblasts, whereas it decreased morphological changes in osteoclasts. This is the first report on visualization of the entire process of BMP-2-induced bone formation using intravital imaging techniques, which, we believe, will contribute to our understanding of ectopic bone formation and provide new parameters for evaluating bone-forming activity. [ABSTRACT FROM AUTHOR]

Recent epigenetics research has demonstrated that chromatin conformation plays an important role in various aspects of gene regulation. Chromosome Conformation Capture (3C) technology makes it possible to analyze the spatial organization of chromatin in a cell. Several algorithms for three-dimensional reconstruction of chromatin structure from 3C experimental data have been proposed. Compared to other algorithms, ShRec3D, one of the most advanced algorithms, can reconstruct a chromatin model in the shortest time for high-resolution whole-genome experimental data. However, ShRec3D employs a graph shortest path algorithm, which introduces errors in the resulting model. We propose an improved algorithm that optimizes shortest path distances using a genetic algorithm approach. The proposed algorithm and ShRec3D were compared using in silico 3C experimental data. Compared to ShRec3D, the proposed algorithm demonstrated significant improvement relative to the similarity between the algorithm's output and the original model with a reasonable increase to calculation time. [ABSTRACT FROM AUTHOR]

Fusion genes are involved in cancer, and their detection using RNA-Seq is insufficient given the relatively short reading length. Therefore, we proposed a shifted short-read clustering (SSC) method, which focuses on overlapping reads from the same loci and extends them as a representative sequence. To verify their usefulness, we applied the SSC method to RNA-Seq data from four types of cell lines (BT-474, MCF-7, SKBR-3, and T-47D). As the slide width of the SSC method increased to one, two, five, or ten bases, the read length was extended from 201 bases to 217 (108%), 234 (116%), 282 (140%), or 317 (158%) bases, respectively. Furthermore, fusion genes were investigated using STAR-Fusion, a fusion gene detection tool, with and without the SSC method. When one base was shifted by the SSC method, the reads mapped to multiple loci decreased from 9.7% to 4.6%, and the sensitivity of the fusion gene was improved from 47% to 54% on average (BT-474: from 48% to 57%, MCF-7: 49% to 53%, SKBR-3: 50% to 57%, and T-47D: 43% to 50%) compared with original data. When the reads are shifted more, the positive predictive value was also improved. The SSC method could be an effective method for fusion gene detection. [ABSTRACT FROM AUTHOR]

To clarify the effects of a dipeptidyl peptidase‐4 (DPP‐4) inhibitor on whole‐body energy metabolism, we treated mice fed a high‐fat diet (HFD) with teneligliptin, a clinically available DPP‐4 inhibitor. Teneligliptin significantly prevented HFD‐induced obesity and obesity‐associated metabolic disorders. It also increased oxygen consumption rate and upregulated uncoupling protein 1 (UCP1) expression in both brown adipose tissue (BAT) and inguinal white adipose tissue (iWAT), suggesting that it enhances BAT function. Soluble DPP‐4 inhibited β‐adrenoreceptor‐stimulated UCP1 expression in primary adipocytes, and this inhibition was prevented in the presence of teneligliptin, or an extracellular signal‐related kinase inhibitor. These results indicate that soluble DPP‐4 inhibits β‐adrenoreceptor‐stimulated UCP1 induction and that chronic DPP‐4 inhibitor treatment may prevent obesity through the activation of BAT function. Proposed schema of the preventive effect of teneligliptin on obesity in adipocytes. sDPP‐4‐mediated ERK activation, acting through PAR2, suppresses β‐adrenoreceptor‐stimulated UCP1 upregulation in adipocytes. Teneligliptin treatment can prevent this suppression, suggesting that this mechanism might be related to teneligliptin‐induced activation of BAT function in vivo. Teneligliptin‐activated BAT function enhances energy expenditure, thereby preventing obesity. [ABSTRACT FROM AUTHOR]

Background: Comprehensively understanding the dynamics of biological systems is among the biggest current challenges in biology and medicine. To acquire this understanding, researchers have measured the time-series expression profiles of cell lines of various organisms. Biological technologies have also drastically improved, providing a huge amount of information with support from bioinformatics and systems biology. However, the transitions between the activation and inactivation of gene regulations, at the temporal resolution of single time points, are difficult to extract from time-course gene expression profiles. Results: Our proposed method reports the activation period of each gene regulation from gene expression profiles and a gene regulatory network. The correctness and effectiveness of the method were validated by analyzing the diauxic shift from glucose to lactose in Escherichia coli. The method completely detected the three periods of the shift; 1) consumption of glucose as nutrient source, 2) the period of seeking another nutrient source and 3) consumption of lactose as nutrient source. We then applied the method to mouse adipocyte differentiation data. Cell differentiation into adipocytes is known to involve two waves of the gene regulation cascade, and sub-waves are predicted. From the gene expression profiles of the cell differentiation process from ES to adipose cells (62 time points), our method acquired four periods; three periods covering the two known waves of the cascade, and a final period of gene regulations when the differentiation to adipocytes was completed. Conclusions: Our proposed method identifies the transitions of gene regulations from time-series gene expression profiles. Dynamic analyses are essential for deep understanding of biological systems and for identifying the causes of the onset of diseases such as diabetes and osteoporosis. The proposed method can greatly contribute to the progress of biology and medicine. [ABSTRACT FROM AUTHOR]

Emerging bioimaging technologies enable us to capture various dynamic cellular activities . As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user. [ABSTRACT FROM AUTHOR]

Distinctive survival strategies, specialized in regulation and in quality control, were observed in thermal adaptive evolution with a laboratory Escherichia coli strain. The two specialists carried a single mutation either within rpoH or upstream of gro ESL, which led to the activated global regulation by sigma factor 32 or an increased amount of Gro EL/ ES chaperonins, respectively. Although both specialists succeeded in thermal adaptation, the common winner of the evolution was the specialist in quality control, that is, the strategy of chaperonin-mediated protein folding. To understand this evolutionary consequence, multilevel analyses of cellular status, for example, transcriptome, protein and growth fitness, were carried out. The specialist in quality control showed less change in transcriptional reorganization responding to temperature increase, which was consistent with the finding of that the two specialists showed the biased expression of molecular chaperones. Such repressed changes in gene expression seemed to be advantageous for long-term sustainability because a specific increase in chaperonins not only facilitated the folding of essential gene products but also saved cost in gene expression compared with the overall transcriptional increase induced by rpoH regulation. Functional specialization offered two strategies for successful thermal adaptation, whereas the evolutionary advantageous was more at the points of cost-saving in gene expression and the essentiality in protein folding. [ABSTRACT FROM AUTHOR]

Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments. [ABSTRACT FROM AUTHOR]

Microorganisms in nature are constantly subjected to a limited availability of resources and experience repeated starvation and nutrition. Therefore, microbial life may evolve for both growth fitness and sustainability. By contrast, experimental evolution, as a powerful approach to investigate microbial evolutionary strategies, often targets the increased growth fitness in controlled, steady-state conditions. Here, we address evolutionary changes balanced between growth and maintenance while taking nutritional fluctuations into account. We performed a 290-day-long evolution experiment with a histidine-requiring Escherichia coli strain that encountered repeated histidine-rich and histidine-starved conditions. The cells that experienced seven rounds of starvation and re-feed grew more sustainably under prolonged starvation but dramatically lost growth fitness under rich conditions. The improved sustainability arose from the evolved capability to use a trace amount of histidine for cell propagation. The reduced growth rate was attributed to mutations genetically disturbing the translation machinery, that is, the ribosome, ultimately slowing protein translation. This study provides the experimental demonstration of slow growth accompanied by an enhanced affinity to resources as an evolutionary adaptation to oscillated environments and verifies that it is possible to evolve for reduced growth fitness. Growth economics favored for population increase under extreme resource limitations is most likely a common survival strategy adopted by natural microbes. [ABSTRACT FROM AUTHOR]

Background: Both large deletions in genome and heat shock stress would lead to alterations in the gene expression profile; however, whether there is any potential linkage between these disturbances to the transcriptome have not been discovered. Here, the relationship between the genomic and environmental contributions to the transcriptome was analyzed by comparing the transcriptomes of the bacterium Escherichia coli (strain MG1655 and its extensive genomic deletion derivative, MDS42) grown in regular and transient heat shock conditions. Results: The transcriptome analysis showed the following: (i) there was a reorganization of the transcriptome in accordance with preferred chromosomal periodicity upon genomic or heat shock perturbation; (ii) there was a considerable overlap between the perturbed regulatory networks and the categories enriched for differentially expressed genes (DEGs) following genome reduction and heat shock; (iii) the genes sensitive to genome reduction tended to be located close to genomic scars, and some were also highly responsive to heat shock; and (iv) the genomic and environmental contributions to the transcriptome displayed not only a positive correlation but also a negatively compensated relationship (i.e., antagonistic epistasis). Conclusion: The contributions of genome reduction and heat shock to the Escherichia coli transcriptome were evaluated at multiple levels. The observations of overlapping perturbed networks, directional similarity in transcriptional changes, positive correlation and epistatic nature linked the two contributions and suggest somehow a crosstalk guiding transcriptional reorganization in response to both genetic and environmental disturbances in bacterium E. coli. [ABSTRACT FROM AUTHOR]

Background: Bayesian networks (BNs) have been widely used to estimate gene regulatory networks. Many BN methods have been developed to estimate networks from microarray data. However, two serious problems reduce the effectiveness of current BN methods. The first problem is that BN-based methods require huge computational time to estimate large-scale networks. The second is that the estimated network cannot have cyclic structures, even if the actual network has such structures. Results: In this paper, we present a novel BN-based deterministic method with reduced computational time that allows cyclic structures. Our approach generates all the combinational triplets of genes, estimates networks of the triplets by BN, and unites the networks into a single network containing all genes. This method decreases the search space of predicting gene regulatory networks without degrading the solution accuracy compared with the greedy hill climbing (GHC) method. The order of computational time is the cube of number of genes. In addition, the network estimated by our method can include cyclic structures. Conclusions: We verified the effectiveness of the proposed method for all known gene regulatory networks and their expression profiles. The results demonstrate that this approach can predict regulatory networks with reduced computational time without degrading the solution accuracy compared with the GHC method [ABSTRACT FROM AUTHOR]

The S-system model is one of the nonlinear differential equation models of gene regulatory networks, and it can describe various dynamics of the relationships among genes. If we successfully infer rigorous S-system model parameters that describe a target gene regulatory network, we can simulate gene expressions mathematically. However, the problem of finding an optimal S-system model parameter is too complex to be solved analytically. Thus, some heuristic search methods that offer approximate solutions are needed for reducing the computational time. In previous studies, several heuristic search methods such as Genetic Algorithms (GAs) have been applied to the parameter search of the S-system model. However, they have not achieved enough estimation accuracy. One of the conceivable reasons is that the mechanisms to escape local optima. We applied an Immune Algorithm (IA) to search for the S-system parameters. IA is also a heuristic search method, which is inspired by the biological mechanism of acquired immunity. Compared to GA, IA is able to search large solution space, thereby avoiding local optima, and have multiple candidates of the solutions. These features work well for searching the S-system model. Actually, our algorithm showed higher performance than GA for both simulation and real data analyses. [ABSTRACT FROM AUTHOR]

Background: With the advent of next-generation sequencers, the growing demands to map short DNA sequences to a genome have promoted the development of fast algorithms and tools. The tools commonly used today are based on either a hash table or the suffix array/Burrow-Wheeler transform. These algorithms are the best suited to finding the genome position of exactly matching short reads. However, they have limited capacity to handle the mismatches. To find n-mismatches, they requires O(2n) times the computation time of exact matches. Therefore, acceleration techniques are required. Results: We propose a hash-based method for genome mapping that reduces the number of hash references for finding mismatches without increasing the size of the hash table. The method regards DNA subsequences as words on Galois extension field GF(2²) and each word is encoded to a code word of a perfect Hamming code. The perfect Hamming code defines equivalence classes of DNA subsequences. Each equivalence class includes subsequence whose corresponding words on GF(2²) are encoded to a corresponding code word. The code word is used as a hash key to store these subsequences in a hash table. Specifically, it reduces by about 70% the number of hash keys necessary for searching the genome positions of all 2-mismatches of 21-base-long DNA subsequence. Conclusions: The paper shows perfect hamming code can reduce the number of hash references for hash-based genome mapping. As the computation time to calculate code words is far shorter than a hash reference, our method is effective to reduce the computation time to map short DNA sequences to genome. The amount of data that DNA sequencers generate continues to increase and more accurate genome mappings are required. Thus our method will be a key technology to develop faster genome mapping software. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is a heterogeneous disease with recognized variability in virus infection, genetic features, and clinical outcome. To date, transcriptional profilings of HCC have been used to predict recurrence or survival/prognosis. However, there remains a challenge to identify specific genomic prints associated with HCC recurrence, which could lead to novel therapies or effective treatment. Here we examine the association between biological signals and intrahepatic recurrence using global gene expression profiles and powerful analytical methods. Materials and Methods: Gene expression profiles were generated in 24 HCC patients with hepatitis B infections (B-type HCC) and 60 HCC patients with hepatitis C infections (C-type HCC). Gene set enrichment analysis (GSEA) was applied to the entire ranked gene lists related to early intrahepatic recurrence, based on 'ideal discriminator method.' Results: GSEA revealed Ribosomal Proteins as a common regulatory pathway in B-type ( P < .001) and C-type ( P = .003) HCC recurrence. In addition, Proteasome ( P < .001) and Pentose Phosphate Pathway ( P = .01) were identified as specific pathways in each type of HCC recurrence, respectively. Conclusions: Understanding these biologically common and different mechanisms related to intrahepatic recurrence in B-type and C-type HCC could be useful in the development of new therapeutic strategies in our fight against HCC. [ABSTRACT FROM AUTHOR]

With the advancement of genome research, it is becoming clear that genes are not distributed on the genome in random order. Clusters of genes distributed at localized genome positions have been reported in several eukaryotes. Various correlations have been observed between the expressions of genes in adjacent or nearby positions along the chromosomes depending on tissue type and developmental stage. Moreover, in several cases, their transcripts, which control epigenetic transcription via processes such as transcriptional interference and genomic imprinting, occur in clusters. It is reasonable that genomic regions that have similar mechanisms show similar expression patterns and that the characteristics of expression in the same genomic regions differ depending on tissue type and developmental stage. In this study, we analyzed gene expression patterns using the cap analysis gene expression (CAGE) method for exploring systematic views of the mouse transcriptome. Counting the number of mapped CAGE tags for fixed-length regions allowed us to determine genomic expression levels. These expression levels were normalized, quantified, and converted into four types of descriptors, allowing the expression patterns along the genome to be represented by character strings. We analyzed them using dynamic programming in the same manner as for sequence analysis. We have developed a novel algorithm that provides a novel view of the genome from the perspective of genomic positional expression. In a similarity search of expression patterns across chromosomes and tissues, we found regions that had clusters of genes that showed expression patterns similar to each other depending on tissue type. Our results suggest the possibility that the regions that have sense-antisense transcription show similar expression patterns between forward and reverse strands. [ABSTRACT FROM AUTHOR]

Linking genetic information to population fitness is crucial to understanding living organisms. Despite the abundant knowledge of the genetic contribution to growth, the overall patterns/features connecting genes, their expression, and growth remain unclear. To reveal the quantitative and direct connections, systematic growth assays of single-gene knockout Escherichia coli strains under both rich and poor nutritional conditions were performed; subsequently, the resultant growth rates were associated with the original expression levels of the knockout genes in the parental genome. Comparative analysis of growth and the transcriptome identified not only the nutritionally differentiated fitness cost genes but also a significant correlation between the growth rates of the single-gene knockout strains and the original expression levels of these knockout genes in the parental strain, regardless of the nutritional variation. In addition, the coordinated chromosomal periodicities of the wild-type transcriptome and the growth rates of the strains lacking the corresponding genes were observed. The common six-period periodicity was somehow attributed to the essential genes, although the underlying mechanism remains to be addressed. The correlated chromosomal periodicities associated with the gene expression-growth dataset were highly valuable for bacterial growth prediction and discovering the working principles governing minimal genetic information. [ABSTRACT FROM AUTHOR]