Butyricimonas is a key gut microbiome component for predicting postoperative recurrence of esophageal cancer.

BACKGROUND: Recently, intestinal bacteria have attracted attention as factors affecting the prognosis of patients with cancer. However, the intestinal microbiome is composed of several hundred types of bacteria, necessitating the development of an analytical method that can allow the use of this information as a highly accurate biomarker. In this study, we investigated whether the preoperative intestinal bacterial profile in patients with esophageal cancer who underwent surgery after preoperative chemotherapy could be used as a biomarker of postoperative recurrence of esophageal cancer. METHODS: We determined the gut microbiome of the patients using 16S rRNA metagenome sequencing, followed by statistical analysis. Simultaneously, we performed a machine learning analysis using a random forest model with hyperparameter tuning and compared the data obtained. RESULTS: Statistical and machine learning analyses revealed two common bacterial genera, Butyricimonas and Actinomyces, which were abundant in cases with recurrent esophageal cancer. Butyricimonas primarily produces butyrate, whereas Actinomyces are oral bacteria whose function in the gut is unknown. CONCLUSION: Our results indicate that Butyricimonas spp. may be a biomarker of postoperative recurrence of esophageal cancer. Although the extent of the involvement of these bacteria in immune regulation remains unknown, future research should investigate their presence in other pathological conditions. Such research could potentially lead to a better understanding of the immunological impact of these bacteria on patients with cancer and their application as biomarkers.

systemsDock: a web server for network pharmacology-based prediction and analysis.

We present systemsDock, a web server for network pharmacology-based prediction and analysis, which permits docking simulation and molecular pathway map for comprehensive characterization of ligand selectivity and interpretation of ligand action on a complex molecular network. It incorporates an elaborately designed scoring function for molecular docking to assess protein-ligand binding potential. For large-scale screening and ease of investigation, systemsDock has a user-friendly GUI interface for molecule preparation, parameter specification and result inspection. Ligand binding potentials against individual proteins can be directly displayed on an uploaded molecular interaction map, allowing users to systemically investigate network-dependent effects of a drug or drug candidate. A case study is given to demonstrate how systemsDock can be used to discover a test compound's multi-target activity. systemsDock is freely accessible at http://systemsdock.unit.oist.jp/.

Software for systems biology: from tools to integrated platforms.

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.

[Deceased Schizophrenic Patients--Focus on QT Prolongation].

We retrospectively evaluated factors affecting the lifespan of schizophrenic patients, who are known to have a shorter life expectancy than healthy people, focusing on the relationship with QT prolongation associated with antipsychotics. In a total of 406 patients who died at Asai Hospital the mean age at death was compared between schizophrenic patients and nonpsychiatric patients. In deceased schizophrenic patients, drug-related factors, hematology results, and electrocardiographic findings for 3 years before death were compared with those for the same period in age-matched surviving schizophrenic patients. In addition, QT values in schizophrenic patients and healthy controls were evaluated by age group. The mean age at death was significantly younger in schizophrenic patients (63.4 +/- 2.63 years) than in nonpsychiatric patients (84.0 +/- 0.57 years) (p<0.001). Bivariate analysis between deceased and surviving schizophrenic patients showed significant differences in QT values at 2 years, 1 year, and 0.5 years before death and in AST and ALT values at 0.5.years before death. The incidence of QT prolongation in deceased schizophrenic patients (52.0%) was about twice as high as that in surviving schizophrenic patients (24.5%). Multiple logistic regression analysis suggested that the proportion of deceased patients was higher when QT intervals were longer and ALT values were relatively higher, even if within the normal range. In both schizophrenic patients and medical checkup examinees, QT values were positively correlated with the age (R2 = 0.9061 and 0.9276, respectively), and QT intervals in schizophrenic patients were significantly longer in the 30- to 70-year age groups. In both schizophrenic patients and medical checkup examinees, QT values were positively correlated with the age, and QT intervals in schizophrenic patients were significantly longer than those in medical checkup examinees in the same age groups. Deceased schizophrenic patients showed significantly longer QT intervals from 2 years before death than age-matched surviving schizophrenic patients. QT prolongation may influence the lifespan of schizophrenic patients, which are shorter than those of nonpsychiatric patients. This highlights the importance of following electrocardiographic findings and hematology results of schizophrenic patients over time.

Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions.

Quadratic Phase Coupling (QPC) serves as an essential statistical instrument for evaluating nonlinear synchronization within multivariate time series data, especially in signal processing and neuroscience fields. This study explores the precision of QPC detection using numerical estimates derived from cross-bicoherence and bivariate Granger causality within a straightforward, yet noisy, instantaneous multiplier model. It further assesses the impact of accidental statistically significant bifrequency interactions, introducing new metrics such as the ratio of bispectral quadratic phase coupling and the ratio of bivariate Granger causality quadratic phase coupling. Ratios nearing 1 signify a high degree of accuracy in detecting QPC. The coupling strength between interacting channels is identified as a key element that introduces nonlinearities, influencing the signal-to-noise ratio in the output channel. The model is tested across 59 experimental conditions of simulated recordings, with each condition evaluated against six coupling strength values, covering a wide range of carrier frequencies to examine a broad spectrum of scenarios. The findings demonstrate that the bispectral method outperforms bivariate Granger causality, particularly in identifying specific QPC under conditions of very weak couplings and in the presence of noise. The detection of specific QPC is crucial for neuroscience applications aimed at better understanding the temporal and spatial coordination between different brain regions.

Toward an integrated software platform for systems pharmacology.

Understanding complex biological systems requires the extensive support of computational tools. This is particularly true for systems pharmacology, which aims to understand the action of drugs and their interactions in a systems context. Computational models play an important role as they can be viewed as an explicit representation of biological hypotheses to be tested. A series of software and data resources are used for model development, verification and exploration of the possible behaviors of biological systems using the model that may not be possible or not cost effective by experiments. Software platforms play a dominant role in creativity and productivity support and have transformed many industries, techniques that can be applied to biology as well. Establishing an integrated software platform will be the next important step in the field.

Estimating Culprit Drugs for Adverse Drug Reactions Based on Bayesian Inference.

The utility of big data in spontaneous adverse drug reactions (ADRs) reporting systems has improved the pharmacovigilance process. However, identifying culprit drugs in ADRs remains challenging, although it is one of the foremost steps to managing ADRs. Aiming to estimate the likelihood of prescribed drugs being culprit drugs for given ADRs, we devised a Bayesian estimation model based on the Japanese Adverse Drug Events Reports database. After developing the model, a validation study was conducted with 67 ADR reports with a gross of 1,387 drugs (67 culprit drugs and 1,320 concomitant drugs) prescribed and recorded at Yamaguchi University Hospital. As a result, the model estimated a culprit drug of ADRs with acceptable accuracy (area under the receiver operating characteristic curve 0.93 (95% confidence interval 0.88-0.97)). The estimation results provided by the model to healthcare practitioners can be used as one clue to determine the culprit drugs for various ADRs, which will improve the management of ADRs by shortening the treatment turnaround time and increasing the precision of diagnosis, leading to minimizing the adverse effects on patients.

Non-invasive assessment of arterial stiffness using oscillometric blood pressure measurement.

BACKGROUND: Arterial stiffness is a major contributor to cardiovascular diseases. Because current methods of measuring arterial stiffness are technically demanding, the purpose of this study was to develop a simple method of evaluating arterial stiffness using oscillometric blood pressure measurement. METHODS: Blood pressure was conventionally measured in the left upper arm of 173 individuals using an inflatable cuff. Using the time series of occlusive cuff pressure and the amplitudes of pulse oscillations, we calculated local slopes of the curve between the decreasing cuff pressure and corresponding arterial volume. Whole pressure-volume curve was derived from numerical integration of the local slopes. The curve was fitted using an equation and we identified a numerical coefficient of the equation as an index of arterial stiffness (Arterial Pressure-volume Index, API). We also measured brachial-ankle (baPWV) PWV and carotid-femoral (cfPWV) PWV using a vascular testing device and compared the values with API. Furthermore, we assessed carotid arterial compliance using ultrasound images to compare with API. RESULTS: The slope of the calculated pressure-volume curve was steeper for compliant (low baPWV or cfPWV) than stiff (high baPWV or cfPWV) arteries. API was related to baPWV (r = -0.53, P < 0.05), cfPWV (r = -0.49, P < 0.05), and carotid arterial compliance (r = 0.32, P < 0.05). A stepwise multiple regression analysis demonstrated that baPWV and carotid arterial compliance were the independent determinants of API, and that API was the independent determinant of baPWV and carotid arterial compliance. CONCLUSIONS: These results suggest that our method can simply and simultaneously evaluate arterial stiffness and blood pressure based on oscillometric measurements of blood pressure.

Autologous Multilayered Fibroblast Sheets Can Reinforce Bronchial Stump in a Rat Model.

Bronchopleural fistula is one of the most serious postoperative complications caused by the incomplete healing of a bronchial stump. Fibroblasts play an important role in wound healing by facilitating connective tissue formation and inducing angiogenesis. We developed a method for production of multilayered fibroblast sheets that secreted some growth factors and promoted wound healing. The present study aimed to assess the treatment effect of multilayered fibroblast sheets on bronchial stump healing. In this rat model, left pneumonectomy was performed, and multilayered fibroblast sheets derived from autologous oral mucosal tissues were transplanted to the bronchial stump. The changes in the bronchial stump were examined macroscopically, histologically, and mechanically. The fibroblast sheets promoted the formation of thick connective tissues around the bronchial stump. The formed connective tissues were accompanied by new blood vessels, and fibrosis was observed over time. Then, 7 days after the transplantation of the fibroblast sheets, the bronchial wall became significantly thicker, and the area of the blood vessels for the bronchial wall tissues was significantly larger in the experimental group than in the control group. In addition, the burst pressure in the bronchial stump was significantly higher in the experimental group than in the control group. Bronchial stumps were reinforced by the transplantation of multilayered fibroblast sheets derived from autologous oral mucosal tissues.

Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms.

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the 'dense region'); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the 'diffuse region'). U-Net was trained to segment the fibroglandular tissue region with an adaptive moment estimation optimiser, five-fold cross-validated with 400 training and 100 validation mammograms, and tested with 203 mammograms. The breast density and MGD were calculated using the van Engeland and Dance formulas, respectively, and compared between U-Net and the ground truth with the Dice similarity coefficient and Bland-Altman analysis. Dice similarity coefficients between U-Net and the ground truth were 0.895 and 0.939 for the dense and diffuse regions, respectively. In the Bland-Altman analysis, no proportional or fixed errors were discovered in either the dense or diffuse region for breast density, whereas a slight proportional error was discovered in both regions for the MGD (the slopes of the regression lines were -0.0299 and -0.0443 for the dense and diffuse regions, respectively). Consequently, the U-Net and ground truth were deemed equivalent (interchangeable) for breast density and compatible (interchangeable following four simple arithmetic operations) for MGD. U-Net-based segmentation of the fibroglandular tissue region was satisfactory for both regions, providing reliable segmentation for breast density and MGD calculations. U-Net will be useful in developing a reliable individualised screening-mammography programme, instead of relying on the visual judgement of mammography experts.

Symbiotic bacteria-dependent expansion of MR1-reactive T cells causes autoimmunity in the absence of Bcl11b.

MHC class I-related protein 1 (MR1) is a metabolite-presenting molecule that restricts MR1-reactive T cells including mucosal-associated invariant T (MAIT) cells. In contrast to MAIT cells, the function of other MR1-restricted T cell subsets is largely unknown. Here, we report that mice in which a T cell-specific transcription factor, B-cell lymphoma/leukemia 11B (Bcl11b), was ablated in immature thymocytes (Bcl11b∆iThy mice) develop chronic inflammation. Bcl11b∆iThy mice lack conventional T cells and MAIT cells, whereas CD4+IL-18R+ αß T cells expressing skewed Traj33 (Jα33)+ T cell receptors (TCR) accumulate in the periphery, which are necessary and sufficient for the pathogenesis. The disorders observed in Bcl11b∆iThy mice are ameliorated by MR1-deficiency, transfer of conventional T cells, or germ-free conditions. We further show the crystal structure of the TCR expressed by Traj33+ T cells expanded in Bcl11b∆iThy mice. Overall, we establish that MR1-reactive T cells have pathogenic potential.

The effect of breast density on the missed lesion rate in screening digital mammography determined using an adjustable-density breast phantom tailored to Japanese women.

OBJECTIVE: Despite the high risk of missing lesions in mammography, the missed lesion rate is yet to be clinically established. Further, no breast phantoms with adjustable breast density currently exist. We developed a novel, adjustable-density breast phantom with a composition identical to that of actual breasts, and determined the quantitative relationship between breast density and the missed lesion rate in mammography. METHODS: An original breast phantom consisting of adipose- and fibroglandular-equivalent materials was developed, and a receiver operating characteristic (ROC) study was performed. Breast density, which is the fraction by weight of fibroglandular to total tissue, was adjusted to 25%, 50%, and 75% by arbitrarily mixing the two materials. Microcalcification, mass lesions, and spiculated lesions, each with unique characteristics, were inserted into the phantom. For the above-mentioned fibroglandular densities, 50 positive and 50 negative images for each lesion type were used as case samples for the ROC study. Five certified radiological technologists participated in lesion detection. RESULTS: The mass-lesion detection rate, according to the area under the curve, decreased by 18.0% (p = 0.0001, 95% Confidence intervals [CI] = 0.1258 to 0.1822) and 37.8% (p = 0.0003, 95% CI = 0.2453 to 0.4031) for breast densities of 50% and 75%, respectively, compared to that for a 25% breast density. A similar tendency was observed with microcalcification; however, spiculated lesions did not follow this tendency. CONCLUSIONS: We quantified the missed lesion rate in different densities of breast tissue using a novel breast phantom, which is imperative for advancing individualized screening mammography.

Early manifestations and differential gene expression associated with photoreceptor degeneration in Prom1-deficient retina.

Retinitis pigmentosa (RP) and macular dystrophy (MD) are characterized by gradual photoreceptor death in the retina and are often associated with genetic mutations, including those in the prominin-1 (Prom1) gene. Prom1-knockout (KO) mice recapitulate key features of these diseases including light-dependent retinal degeneration and constriction of retinal blood vessels. The mechanisms underlying such degeneration have remained unclear, however. We here analysed early events associated with retinal degeneration in Prom1-KO mice. We found that photoreceptor cell death and glial cell activation occur between 2 and 3 weeks after birth. Whereas gene expression was not affected at 2 weeks, the expression of several genes was altered at 3 weeks in the Prom1-KO retina, with the expression of that for endothelin-2 (Edn2) being markedly upregulated. Expression of Edn2 was also induced by light stimulation in Prom1-KO mice reared in the dark. Treatment with endothelin receptor antagonists attenuated photoreceptor cell death, gliosis and retinal vessel stenosis in Prom1-KO mice. Our findings thus reveal early manifestations of retinal degeneration in a model of RP/MD and suggest potential therapeutic agents for these diseases. This article has an associated First Person interview with the first author of the paper.

Photocatalytic CO2 reduction using metal complexes in various ionic liquids.

Aiming to diversify photocatalytic systems for CO2 reduction using metal complexes, this study investigated the use of various ionic liquids as reaction solvents. The photophysical properties of an Ir(iii) complex, functioning as a photosensitiser, and the photocatalytic ability of mixed systems consisting of the Ir(iii) photosensitiser and a Re(i) catalyst in twelve kinds of ionic liquids were systematically investigated by comparison with those in N,N-dimethylacetamide (DMA), which is a standard solvent for photocatalytic CO2 reduction. Even though the photophysical properties of the Ir(iii) complex in ionic-liquid solutions were quite similar to those in DMA, both the photosensitising ability of the Ir complex and the photocatalytic abilities of the systems strongly depended on the structures of the ionic liquids. Several ionic liquids were successfully used as new solvents for the photocatalytic systems showing durability similar to or higher than DMA solutions. The results demonstrated that even a small modification of the molecular structures of ionic liquids can control the efficiencies of both the photosensitising cycles and the catalytic cycles for CO2 reduction.

Attention Networks in ADHD Adults after Working Memory Training with a Dual n-Back Task.

Patients affected by Attention-Deficit/Hyperactivity Disorder (ADHD) are characterized by impaired executive functioning and/or attention deficits. Our study aim is to determine whether the outcomes measured by the Attention Network Task (ANT), i.e., the reaction times (RTs) to specific target and cue conditions and alerting, orienting, and conflict (or executive control) effects are affected by cognitive training with a Dual n-back task. We considered three groups of young adult participants: ADHD patients without medication (ADHD), ADHD with medication (MADHD), and age/education-matched controls. Working memory training consisted of a daily practice of 20 blocks of Dual n-back task (approximately 30 min per day) for 20 days within one month. Participants of each group were randomly assigned into two subgroups, the first one with an adaptive mode of difficulty (adaptive training), while the second was blocked at the level 1 during the whole training phase (1-back task, baseline training). Alerting and orienting effects were not modified by working memory training. The dimensional analysis showed that after baseline training, the lesser the severity of the hyperactive-impulsive symptoms, the larger the improvement of reaction times on trials with high executive control/conflict demand (i.e., what is called Conflict Effect), irrespective of the participants' group. In the categorical analysis, we observed the improvement in such Conflict Effect after the adaptive training in adult ADHD patients irrespective of their medication, but not in controls. The ex-Gaussian analysis of RT and RT variability showed that the improvement in the Conflict Effect correlated with a decrease in the proportion of extreme slow responses. The Dual n-back task in the adaptive mode offers as a promising candidate for a cognitive remediation of adult ADHD patients without pharmaceutical medication.

An Integrated Genomic Approach Identifies HOXC8 as an Upstream Regulator in Ovarian Endometrioma.

PURPOSE: To identify the upstream regulators (URs) involved in the onset and pathogenesis of ovarian endometrioma. METHODS: Recently, a method called Significance-based Modules Integrating the Transcriptome and Epigenome (SMITE) that uses transcriptome data in combination with publicly available data for identifying URs of cellular processes has been developed. Here, we used SMITE with transcriptome data from ovarian endometrioma stromal cells (ovESCs) and eutopic endometrium stromal cells (euESCs) in combination with publicly available gene regulatory network data. To confirm the URs identified by SMITE, we developed a Boolean network simulation to see if correcting aberrant expressions of the identified genes could restore the entire gene expression profile of ovESCs to a profile similar to that of euESCs. We then established euESCs overexpressing the identified gene and characterized them by cell function assays and transcriptome analysis. RESULTS: SMITE identified 12 potential URs in ovarian endometrioma that were confirmed by the Boolean simulation. One of the URs, HOXC8, was confirmed to be overexpressed in ovESCs. HOXC8 overexpression significantly enhanced cell proliferation, migration, adhesion, and fibrotic activities, and altered expression statuses of the genes involved in transforming growth factor (TGF)-ß signaling. HOXC8 overexpression also increased the expression levels of phosphorylated SMAD2/SMAD3. The increased adhesion and fibrosis activities by HOXC8 were significantly inhibited by E-616452, a selective inhibitor of TGF-ß receptor type I kinases. MAIN CONCLUSIONS: Integrated genomic approaches identified HOXC8 as an UR in ovarian endometrioma. The pathological features of ovarian endometrioma including cell proliferation, adhesion, and fibrosis were induced by HOXC8 and its subsequent activation of TGF-ß signaling.

Prediction of glandularity and breast radiation dose from mammography results in Japanese women.

Glandularity has a marked impact on the incidence of breast cancer and the missed lesion rate of mammography. The aim of this study was to develop a novel model for predicting glandularity and patient radiation dose using physical factors that are easily determined prior to mammography. Data regarding glandularity and mean glandular dose were obtained from 331 mammograms. A stepwise multiple regression analysis model was developed to predict glandularity using age, compressed breast thickness and body mass index (BMI), while a model to predict mean glandular dose was created using quantified glandularity, age, compressed breast thickness, height and body weight. The most significant factor for predicting glandularity was age, the influence of which was 1.8 times that of BMI. The most significant factor for predicting mean glandular dose was compressed breast thickness, the influence of which was 1.4 times that of glandularity, 3.5 times that of age and 6.1 times that of height. Both models were statistically significant (both p < 0.0001). Easily determined physical factors were able to explain 42.8% of the total variance in glandularity and 62.4% of the variance in mean glandular dose. Graphical abstract Validation results of the above prediction model made using physical factors in Japanese women. The plotted points of actual vs. prediction glandularity shown in a are distributed in the vicinity of the diagonal line, and the residual plot for predicted glandularity shows an almost random distribution as shown in b. These distributions indicate the appropriateness of the prediction model.