Interhemispheric competition during sleep.

Our understanding of the functions and mechanisms of sleep remains incomplete, reflecting their increasingly evident complexity1-3. Likewise, studies of interhemispheric coordination during sleep4-6 are often hard to connect precisely to known sleep circuits and mechanisms. Here, by recording from the claustra of sleeping bearded dragons (Pogona vitticeps), we show that, although the onsets and offsets of Pogona rapid-eye-movement (REMP) and slow-wave sleep are coordinated bilaterally, these two sleep states differ markedly in their inter-claustral coordination. During slow-wave sleep, the claustra produce sharp-wave ripples independently of one another, showing no coordination. By contrast, during REMP sleep, the potentials produced by the two claustra are precisely coordinated in amplitude and time. These signals, however, are not synchronous: one side leads the other by about 20 ms, with the leading side switching typically once per REMP episode or in between successive episodes. The leading claustrum expresses the stronger activity, suggesting bilateral competition. This competition does not occur directly between the two claustra or telencephalic hemispheres. Rather, it occurs in the midbrain and depends on the integrity of a GABAergic (γ-aminobutyric-acid-producing) nucleus of the isthmic complex, which exists in all vertebrates and is known in birds to underlie bottom-up attention and gaze control. These results reveal that a winner-take-all-type competition exists between the two sides of the brain of Pogona, which originates in the midbrain and has precise consequences for claustrum activity and coordination during REMP sleep.

A claustrum in reptiles and its role in slow-wave sleep.

The mammalian claustrum, owing to its widespread connectivity with other forebrain structures, has been hypothesized to mediate functions that range from decision-making to consciousness1. Here we report that a homologue of the claustrum, identified by single-cell transcriptomics and viral tracing of connectivity, also exists in a reptile-the Australian bearded dragon Pogona vitticeps. In Pogona, the claustrum underlies the generation of sharp waves during slow-wave sleep. The sharp waves, together with superimposed high-frequency ripples2, propagate to the entire neighbouring pallial dorsal ventricular ridge (DVR). Unilateral or bilateral lesions of the claustrum suppress the production of sharp-wave ripples during slow-wave sleep in a unilateral or bilateral manner, respectively, but do not affect the regular and rapidly alternating sleep rhythm that is characteristic of sleep in this species3. The claustrum is thus not involved in the generation of the sleep rhythm itself. Tract tracing revealed that the reptilian claustrum projects widely to a variety of forebrain areas, including the cortex, and that it receives converging inputs from, among others, areas of the mid- and hindbrain that are known to be involved in wake-sleep control in mammals4-6. Periodically modulating the concentration of serotonin in the claustrum, for example, caused a matching modulation of sharp-wave production there and in the neighbouring DVR. Using transcriptomic approaches, we also identified a claustrum in the turtle Trachemys scripta, a distant reptilian relative of lizards. The claustrum is therefore an ancient structure that was probably already present in the brain of the common vertebrate ancestor of reptiles and mammals. It may have an important role in the control of brain states owing to the ascending input it receives from the mid- and hindbrain, its widespread projections to the forebrain and its role in sharp-wave generation during slow-wave sleep.

ROS and cGMP signaling modulate persistent escape from hypoxia in Caenorhabditis elegans.

The ability to detect and respond to acute oxygen (O2) shortages is indispensable to aerobic life. The molecular mechanisms and circuits underlying this capacity are poorly understood. Here, we characterize the behavioral responses of feeding Caenorhabditis elegans to approximately 1% O2. Acute hypoxia triggers a bout of turning maneuvers followed by a persistent switch to rapid forward movement as animals seek to avoid and escape hypoxia. While the behavioral responses to 1% O2 closely resemble those evoked by 21% O2, they have distinct molecular and circuit underpinnings. Disrupting phosphodiesterases (PDEs), specific G proteins, or BBSome function inhibits escape from 1% O2 due to increased cGMP signaling. A primary source of cGMP is GCY-28, the ortholog of the atrial natriuretic peptide (ANP) receptor. cGMP activates the protein kinase G EGL-4 and enhances neuroendocrine secretion to inhibit acute responses to 1% O2. Triggering a rise in cGMP optogenetically in multiple neurons, including AIA interneurons, rapidly and reversibly inhibits escape from 1% O2. Ca2+ imaging reveals that a 7% to 1% O2 stimulus evokes a Ca2+ decrease in several neurons. Defects in mitochondrial complex I (MCI) and mitochondrial complex I (MCIII), which lead to persistently high reactive oxygen species (ROS), abrogate acute hypoxia responses. In particular, repressing the expression of isp-1, which encodes the iron sulfur protein of MCIII, inhibits escape from 1% O2 without affecting responses to 21% O2. Both genetic and pharmacological up-regulation of mitochondrial ROS increase cGMP levels, which contribute to the reduced hypoxia responses. Our results implicate ROS and precise regulation of intracellular cGMP in the modulation of acute responses to hypoxia by C. elegans.

Impact of non-contrast-enhanced imaging input sequences on the generation of virtual contrast-enhanced breast MRI scans using neural network.

OBJECTIVE: To investigate how different combinations of T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted imaging (DWI) impact the performance of virtual contrast-enhanced (vCE) breast MRI. MATERIALS AND METHODS: The IRB-approved, retrospective study included 1064 multiparametric breast MRI scans (age: 52 ± 12 years) obtained from 2017 to 2020 (single site, two 3-T MRI). Eleven independent neural networks were trained to derive vCE images from varying input combinations of T1w, T2w, and multi-b-value DWI sequences (b-value = 50-1500 s/mm2). Three readers evaluated the vCE images with regard to qualitative scores of diagnostic image quality, image sharpness, satisfaction with contrast/signal-to-noise ratio, and lesion/non-mass enhancement conspicuity. Quantitative metrics (SSIM, PSNR, NRMSE, and median symmetrical accuracy) were analyzed and statistically compared between the input combinations for the full breast volume and both enhancing and non-enhancing target findings. RESULTS: The independent test set consisted of 187 cases. The quantitative metrics significantly improved in target findings when multi-b-value DWI sequences were included during vCE training (p < 0.05). Non-significant effects (p > 0.05) were observed for the quantitative metrics on the full breast volume when comparing input combinations including T1w. Using T1w and DWI acquisitions during vCE training is necessary to achieve high satisfaction with contrast/SNR and good conspicuity of the enhancing findings. The input combination of T1w, T2w, and DWI sequences with three b-values showed the best qualitative performance. CONCLUSION: vCE breast MRI performance is significantly influenced by input sequences. Quantitative metrics and visual quality of vCE images significantly benefit when multi b-value DWI is added to morphologic T1w-/T2w sequences as input for model training. KEY POINTS: Question How do different MRI sequences impact the performance of virtual contrast-enhanced (vCE) breast MRI? Findings The input combination of T1-weighted, T2-weighted, and diffusion-weighted imaging sequences with three b-values showed the best qualitative performance. Clinical relevance While in the future neural networks providing virtual contrast-enhanced images might further improve accessibility to breast MRI, the significant influence of input data needs to be considered during translational research.

Smart forecasting of artifacts in contrast-enhanced breast MRI before contrast agent administration.

OBJECTIVES: To evaluate whether artifacts on contrast-enhanced (CE) breast MRI maximum intensity projections (MIPs) might already be forecast before gadolinium-based contrast agent (GBCA) administration during an ongoing examination by analyzing the unenhanced T1-weighted images acquired before the GBCA injection. MATERIALS AND METHODS: This IRB-approved retrospective analysis consisted of n = 2884 breast CE MRI examinations after intravenous administration of GBCA, acquired with n = 4 different MRI devices at different field strengths (1.5 T/3 T) during clinical routine. CE-derived subtraction MIPs were used to conduct a multi-class multi-reader evaluation of the presence and severity of artifacts with three independent readers. An ensemble classifier (EC) of five DenseNet models was used to predict artifacts for the post-contrast subtraction MIPs, giving as the input source only the pre-contrast T1-weighted sequence. Thus, the acquisition directly preceded the GBCA injection. The area under ROC (AuROC) and diagnostics accuracy scores were used to assess the performance of the neural network in an independent holdout test set (n = 285). RESULTS: After majority voting, potentially significant artifacts were detected in 53.6% (n = 1521) of all breast MRI examinations (age 49.6 ± 12.6 years). In the holdout test set (mean age 49.7 ± 11.8 years), at a specificity level of 89%, the EC could forecast around one-third of artifacts (sensitivity 31%) before GBCA administration, with an AuROC = 0.66. CONCLUSION: This study demonstrates the capability of a neural network to forecast the occurrence of artifacts on CE subtraction data before the GBCA administration. If confirmed in larger studies, this might enable a workflow-blended approach to prevent breast MRI artifacts by implementing in-scan personalized predictive algorithms. CLINICAL RELEVANCE STATEMENT: Some artifacts in contrast-enhanced breast MRI maximum intensity projections might be predictable before gadolinium-based contrast agent injection using a neural network. KEY POINTS: • Potentially significant artifacts can be observed in a relevant proportion of breast MRI subtraction sequences after gadolinium-based contrast agent administration (GBCA). • Forecasting the occurrence of such artifacts in subtraction maximum intensity projections before GBCA administration for individual patients was feasible at 89% specificity, which allowed correctly predicting one in three future artifacts. • Further research is necessary to investigate the clinical value of such smart personalized imaging approaches.

IL-17 is a neuromodulator of Caenorhabditis elegans sensory responses.

Interleukin-17 (IL-17) is a major pro-inflammatory cytokine: it mediates responses to pathogens or tissue damage, and drives autoimmune diseases. Little is known about its role in the nervous system. Here we show that IL-17 has neuromodulator-like properties in Caenorhabditis elegans. IL-17 can act directly on neurons to alter their response properties and contribution to behaviour. Using unbiased genetic screens, we delineate an IL-17 signalling pathway and show that it acts in the RMG hub interneurons. Disrupting IL-17 signalling reduces RMG responsiveness to input from oxygen sensors, and renders sustained escape from 21% oxygen transient and contingent on additional stimuli. Over-activating IL-17 receptors abnormally heightens responses to 21% oxygen in RMG neurons and whole animals. IL-17 deficiency can be bypassed by optogenetic stimulation of RMG. Inducing IL-17 expression in adults can rescue mutant defects within 6 h. These findings reveal a non-immunological role of IL-17 modulating circuit function and behaviour.

Prevalence and influencing factors for artifact development in breast MRI-derived maximum intensity projections.

BACKGROUND: Magnetic resonance imaging (MRI) provides high diagnostic sensitivity for breast cancer. However, MRI artifacts may impede the diagnostic assessment. This is particularly important when evaluating maximum intensity projections (MIPs), such as in abbreviated MRI (AB-MRI) protocols, because high image quality is desired as a result of fewer sequences being available to compensate for problems. PURPOSE: To describe the prevalence of artifacts on dynamic contrast enhanced (DCE) MRI-derived MIPs and to investigate potentially associated attributes. MATERIAL AND METHODS: For this institutional review board approved retrospective analysis, MIPs were generated from subtraction series and cropped to represent the left and right breasts as regions of interest. These images were labeled by three independent raters regarding the presence of MRI artifacts. MRI artifact prevalence and associations with patient characteristics and technical attributes were analyzed using descriptive statistics and generalized linear models (GLMMs). RESULTS: The study included 2524 examinations from 1794 patients (median age 50 years), performed on 1.5 and 3.0 Tesla MRI systems. Overall inter-rater agreement was kappa = 0.54. Prevalence of significant unilateral artifacts was 29.2% (736/2524), whereas bilateral artifacts were present in 37.8% (953/2524) of all examinations. According to the GLMM, artifacts were significantly positive associated with age (odds ratio [OR] = 1.52) and magnetic field strength (OR = 1.55), whereas a negative effect could be shown for body mass index (OR = 0.95). CONCLUSION: MRI artifacts on DCE subtraction MIPs of the breast, as used in AB-MRI, are a relevant topic. Our results show that, besides the magnetic field strength, further associated attributes are patient age and body mass index, which can provide possible targets for artifact reduction.

Advanced neural networks for classification of MRI in psoriatic arthritis, seronegative, and seropositive rheumatoid arthritis.

OBJECTIVES: To evaluate whether neural networks can distinguish between seropositive RA, seronegative RA, and PsA based on inflammatory patterns from hand MRIs and to test how psoriasis patients with subclinical inflammation fit into such patterns. METHODS: ResNet neural networks were utilized to compare seropositive RA vs PsA, seronegative RA vs PsA, and seropositive vs seronegative RA with respect to hand MRI data. Results from T1 coronal, T2 coronal, T1 coronal and axial fat-suppressed contrast-enhanced (CE), and T2 fat-suppressed axial sequences were used. The performance of such trained networks was analysed by the area under the receiver operating characteristics curve (AUROC) with and without presentation of demographic and clinical parameters. Additionally, the trained networks were applied to psoriasis patients without clinical arthritis. RESULTS: MRI scans from 649 patients (135 seronegative RA, 190 seropositive RA, 177 PsA, 147 psoriasis) were fed into ResNet neural networks. The AUROC was 75% for seropositive RA vs PsA, 74% for seronegative RA vs PsA, and 67% for seropositive vs seronegative RA. All MRI sequences were relevant for classification, however, when deleting contrast agent-based sequences the loss of performance was only marginal. The addition of demographic and clinical data to the networks did not provide significant improvements for classification. Psoriasis patients were mostly assigned to PsA by the neural networks, suggesting that a PsA-like MRI pattern may be present early in the course of psoriatic disease. CONCLUSION: Neural networks can be successfully trained to distinguish MRI inflammation related to seropositive RA, seronegative RA, and PsA.

Shift of radiotherapy use during the first wave of the COVID-19 pandemic? An analysis of German inpatient data.

OBJECTIVE: To assess the change in inpatient radiotherapy related to COVID-19 lockdown measures during the first wave of the pandemic in 2020. METHODS: We included cases hospitalized between January 1 and August 31, 2018-2020, with a primary ICD-10 diagnosis of C00-C13, C32 (head and neck cancer, HNC) and C53 (cervical cancer, CC). Data collection was conducted within the Medical Informatics Initiative. Outcomes were fractions and admissions. Controlling for decreasing hospital admissions during holidays, calendar weeks of 2018/2019 were aligned to Easter 2020. A lockdown period (LP; 16/03/2020-02/08/2020) and a return-to-normal period (RNP; 04/05/2020-02/08/2020) were defined. The study sample comprised a control (admission 2018/19) and study cohort (admission 2020). We computed weekly incidence and IR ratios from generalized linear mixed models. RESULTS: We included 9365 (CC: 2040, HNC: 7325) inpatient hospital admissions from 14 German university hospitals. For CC, fractions decreased by 19.97% in 2020 compared to 2018/19 in the LP. In the RNP the reduction was 28.57% (p < 0.001 for both periods). LP fractions for HNC increased by 10.38% (RNP: 9.27%; p < 0.001 for both periods). Admissions for CC decreased in both periods (LP: 10.2%, RNP: 22.14%), whereas for HNC, admissions increased (LP: 2.25%, RNP: 1.96%) in 2020. Within LP, for CC, radiotherapy admissions without brachytherapy were reduced by 23.92%, whereas surgery-related admissions increased by 20.48%. For HNC, admissions with radiotherapy increased by 13.84%, while surgery-related admissions decreased by 11.28% in the same period. CONCLUSION: Related to the COVID-19 lockdown in an inpatient setting, radiotherapy for HNC treatment became a more frequently applied modality, while admissions of CC cases decreased.

Automated artifact detection in abbreviated dynamic contrast-enhanced (DCE) MRI-derived maximum intensity projections (MIPs) of the breast.

OBJECTIVES: To automatically detect MRI artifacts on dynamic contrast-enhanced (DCE) maximum intensity projections (MIPs) of the breast using deep learning. METHODS: Women who underwent clinically indicated breast MRI between October 2015 and December 2019 were included in this IRB-approved retrospective study. We employed two convolutional neural network architectures (ResNet and DenseNet) to detect the presence of artifacts on DCE MIPs of the left and right breasts. Networks were trained on images acquired up to and including the year 2018 using a 5-fold cross-validation (CV). Ensemble classifiers were built with the resulting CV models and applied to an independent holdout test dataset, which was formed by images acquired in 2019. RESULTS: Our study sample contained 2265 examinations from 1794 patients (median age at first acquisition: 50 years [IQR: 17 years]), corresponding to 1827 examinations of 1378 individuals in the training dataset and 438 examinations of 416 individuals in the holdout test dataset with a prevalence of image-level artifacts of 53% (1951/3654 images) and 43% (381/876 images), respectively. On the holdout test dataset, the ResNet and DenseNet ensembles demonstrated an area under the ROC curve of 0.92 and 0.94, respectively. CONCLUSION: Neural networks are able to reliably detect artifacts that may impede the diagnostic assessment of MIPs derived from DCE subtraction series in breast MRI. Future studies need to further explore the potential of such neural networks to complement quality assurance and improve the application of DCE MIPs in a clinical setting, such as abbreviated protocols. KEY POINTS: • Deep learning classifiers are able to reliably detect MRI artifacts in dynamic contrast-enhanced protocol-derived maximum intensity projections of the breast. • Automated quality assurance of maximum intensity projections of the breast may be of special relevance for abbreviated breast MRI, e.g., in high-throughput settings, such as cancer screening programs.

DQAgui: a graphical user interface for the MIRACUM data quality assessment tool.

BACKGROUND: With the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the number of data elements to be analyzed, DQ reports of data stored within research networks can grow very large. They might be cumbersome to read and important information could be overseen quickly. To address this issue, a DQ assessment (DQA) tool with a graphical user interface (GUI) was developed and provided as a web application. METHODS: The aim was to provide an easy-to-use interface for users without prior programming knowledge to carry out DQ checks and to present the results in a clearly structured way. This interface serves as a starting point for a more detailed investigation of possible DQ irregularities. A user-centered development process ensured the practical feasibility of the interactive GUI. The interface was implemented in the R programming language and aligned to Kahn et al.'s DQ categories conformance, completeness and plausibility. RESULTS: With DQAgui, an R package with a web-app frontend for DQ assessment was developed. The GUI allows users to perform DQ analyses of tabular data sets and to systematically evaluate the results. During the development of the GUI, additional features were implemented, such as analyzing a subset of the data by defining time periods and restricting the analyses to certain data elements. CONCLUSIONS: As part of the MIRACUM project, DQAgui is now being used at ten German university hospitals for DQ assessment and to provide a central overview of the availability of important data elements in a datamap over 2 years. Future development efforts should focus on design optimization and include a usability evaluation.

[Singing Voice Handicap Index-12 : Development and validation of a German version]. / Der Singing Voice Handicap Index-12 : Entwicklung und Validierung einer deutschen Fassung.

BACKGROUND: The aim of this study was to develop a shortened German version of the Singing Voice Handicap Index (SVHI). The SVHI is a one-dimensional instrument for self-assessment of a voice disorder in singers. The questionnaire developed in the USA comprises 36 items and has been available in a validated German version since 2013. METHODS: Bicentric data from a total of 200 patients formed the basis for item analysis and selection. Using corrected item-total correlations, 12 items were selected for the abridged version. The internal consistency was calculated. The SVHI-12 was subsequently validated in 97 vocal patients and 105 vocally healthy singers (control group) using the test-retest procedure. RESULTS: The SVHI-12 achieved a good internal consistency (Cronbach's alpha = 0.93) and a good test-retest reliability (intra-class correlation r = 0.88 ; p < 0.001). The patients had significantly higher overall scores (18 ± 13 vs. 7 ± 6) compared to the healthy control group. The SVHI-12 overall score correlated significantly positively with the severity of the voice disorder as reported by the patient (r = 0.68; p < 0.001). As a threshold value above which a voice can be described as disturbed, a total score > 7 points was calculated using receiver operating curve analysis. As an indication of a voice disorder, a sensitivity of 81% and a specificity of 71% is thus achieved (Youden index 0.523, area under the curve 0.827, 95% confidence interval 0.769-0.885). CONCLUSION: The shortened SVHI has similarly good psychometric characteristics to the original SVHI. With the SVHI-12, a valid and effective instrument for the detection of singing voice disorders is available for German-speaking countries.

[Possibility of determining «Paradox¼ and «Lancaster¼ barrel boring type by human body gunshot wounds morphology and clothing defects]. / O vozmozhnosti sudebno-meditsinskoi diagnostiki tipa sverlovki kanala stvola «Paradox¼ i «Lancaster¼ po morfologii ognestrel'nykh ranenii tela cheloveka i povrezhdenii odezhdy.

In the specialized forensic medical literature there is no data that allow to reliably and objectively confirm application «Paradox¼ or «Lancaster¼ boring firearms to cause injury. This study analyzes the literature in order to determine the possibility of diagnosing these types of weapon's barrel boring by the morphology of injury. The results of the analysis demonstrate a high probability of barrel boring type distinctive features existing. In addition, has been found the opportunity to determine the type of bullet in the cartridge used to damage. Concluded that it is necessary to do an additional experimental research of the specified conditions for causing firearm injuries.

BiasCorrector: Fast and accurate correction of all types of experimental biases in quantitative DNA methylation data derived by different technologies.

Quantification of DNA methylation in neoplastic cells is crucial both from mechanistic and diagnostic perspectives. However, such measurements are prone to different experimental biases. Polymerase chain reaction (PCR) bias results in an unequal recovery of methylated and unmethylated alleles at the sample preparation step. Post-PCR biases get introduced additionally by the readout processes. Correcting the biases is more practicable than optimising experimental conditions, as demonstrated previously. However, utilisation of our earlier developed algorithm strongly necessitates automation. Here, we present two R packages: rBiasCorrection, the core algorithms to correct biases; and BiasCorrector, its web-based graphical user interface frontend. The software detects and analyses experimental biases in calibration DNA samples at a single base resolution by using cubic polynomial and hyperbolic regression. The correction coefficients from the best regression type are employed to compensate for the bias. Three common technologies-bisulphite pyrosequencing, next-generation sequencing and oligonucleotide microarrays-were used to comprehensively test BiasCorrector. We demonstrate the accuracy of BiasCorrector's performance and reveal technology-specific PCR- and post-PCR biases. BiasCorrector effectively eliminates biases regardless of their nature, locus, the number of interrogated methylation sites and the detection method, thus representing a user-friendly tool for producing accurate epigenetic results.

Hemolysis in patients with Extracorporeal Membrane Oxygenation therapy for severe Acute Respiratory Distress Syndrome - a systematic review of the literature.

The Acute Respiratory Distress Syndrome (ARDS) is common in patients on the Intensive Care Unit and associated with significant mortality rates. In situations of severe respiratory insufficiency and failure of all possible conservative therapeutic approaches, veno-venous extracorporeal membrane oxygenation (VV ECMO) is used as a final option for temporary replacement of pulmonary function. ARDS as well as sepsis and VV ECMO treatment are all associated with intravascular hemolysis. The extent and relevance of intravascular hemolysis in the context of ARDS therapy is unclear. This systematic review aims to summarize the current evidence on the incidence and associated complications of intravascular hemolysis in adult patients with ARDS and treatment with VV ECMO. The databases MEDLINE, EMBASE and Web of Science were systematically searched and 19 publications fulfilled inclusion criteria. The incidence of hemolysis in patients with ARDS and treatment with VV ECMO ranged from 0 to 41% with survivors showing lower incidences and less severe hemolysis. A pump head thrombosis and high blood flows (≥3 l/min) as well as use of dual-lumen cannulas but not different pump models were associated with increased hemolysis. In conclusion, intravascular hemolysis in patients with ARDS and treatment with VV ECMO is a common and relevant complication that appears associated with increased mortality. Apart from ECMO hardware-settings, no additional possible causes for increased red cell breakdown such as disease severity, duration of ECMO therapy, or number and quality of red blood cell transfusions were investigated. Further research is needed to determine the origin and relevance of intravascular hemolysis in patients with ARDS and treatment with VV ECMO.

A multi-organ-chip co-culture of liver and testis equivalents: a first step toward a systemic male reprotoxicity model.

STUDY QUESTION: Is it possible to co-culture and functionally link human liver and testis equivalents in the combined medium circuit of a multi-organ chip? SUMMARY ANSWER: Multi-organ-chip co-cultures of human liver and testis equivalents were maintained at a steady-state for at least 1 week and the co-cultures reproduced specific natural and drug-induced liver-testis systemic interactions. WHAT IS KNOWN ALREADY: Current benchtop reprotoxicity models typically do not include hepatic metabolism and interactions of the liver-testis axis. However, these are important to study the biotransformation of substances. STUDY DESIGN, SIZE, DURATION: Testicular organoids derived from primary adult testicular cells and liver spheroids consisting of cultured HepaRG cells and hepatic stellate cells were loaded into separate culture compartments of each multi-organ-chip circuit for co-culture in liver spheroid-specific medium, testicular organoid-specific medium or a combined medium over a week. Additional multi-organ-chips (single) and well plates (static) were loaded only with testicular organoids or liver spheroids for comparison. Subsequently, the selected type of medium was supplemented with cyclophosphamide, an alkylating anti-neoplastic prodrug that has demonstrated germ cell toxicity after its bioactivation in the liver, and added to chip-based co-cultures to replicate a human liver-testis systemic interaction in vitro. Single chip-based testicular organoids were used as a control. Experiments were performed with three biological replicates unless otherwise stated. PARTICIPANTS/MATERIALS, SETTING, METHODS: The metabolic activity was determined as glucose consumption and lactate production. The cell viability was measured as lactate dehydrogenase activity in the medium. Additionally, immunohistochemical and real-time quantitative PCR end-point analyses were performed for apoptosis, proliferation and cell-specific phenotypical and functional markers. The functionality of Sertoli and Leydig cells in testicular spheroids was specifically evaluated by measuring daily inhibin B and testosterone release, respectively. MAIN RESULTS AND THE ROLE OF CHANCE: Co-culture in multi-organ chips with liver spheroid-specific medium better supported the metabolic activity of the cultured tissues compared to other media tested. The liver spheroids did not show significantly different behaviour during co-culture compared to that in single culture on multi-organ-chips. The testicular organoids also developed accordingly and produced higher inhibin B but lower testosterone levels than the static culture in plates with testicular organoid-specific medium. By comparison, testosterone secretion by testicular organoids cultured individually on multi-organ-chips reached a similar level as the static culture at Day 7. This suggests that the liver spheroids have metabolised the steroids in the co-cultures, a naturally occurring phenomenon. The addition of cyclophosphamide led to upregulation of specific cytochromes in liver spheroids and loss of germ cells in testicular organoids in the multi-organ-chip co-cultures but not in single-testis culture. LARGE-SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: The number of biological replicates included in this study was relatively small due to the limited availability of individual donor testes and the labour-intensive nature of multi-organ-chip co-cultures. Moreover, testicular organoids and liver spheroids are miniaturised organ equivalents that capture key features, but are still simplified versions of the native tissues. Also, it should be noted that only the prodrug cyclophosphamide was administered. The final concentration of the active metabolite was not measured. WIDER IMPLICATIONS OF THE FINDINGS: This co-culture model responds to the request of setting up a specific tool that enables the testing of candidate reprotoxic substances with the possibility of human biotransformation. It further allows the inclusion of other human tissue equivalents for chemical risk assessment on the systemic level. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by research grants from the Scientific Research Foundation Flanders (FWO), Universitair Ziekenhuis Brussel (scientific fund Willy Gepts) and the Vrije Universiteit Brussel. Y.B. is a postdoctoral fellow of the FWO. U.M. is founder, shareholder and CEO of TissUse GmbH, Berlin, Germany, a company commercializing the Multi-Organ-Chip platform systems used in the study. The other authors have no conflict of interest to declare.

Memory of recent oxygen experience switches pheromone valence in Caenorhabditis elegans.

Animals adjust their behavioral priorities according to momentary needs and prior experience. We show that Caenorhabditis elegans changes how it processes sensory information according to the oxygen environment it experienced recently. C. elegans acclimated to 7% O2 are aroused by CO2 and repelled by pheromones that attract animals acclimated to 21% O2 This behavioral plasticity arises from prolonged activity differences in a circuit that continuously signals O2 levels. A sustained change in the activity of O2-sensing neurons reprograms the properties of their postsynaptic partners, the RMG hub interneurons. RMG is gap-junctionally coupled to the ASK and ADL pheromone sensors that respectively drive pheromone attraction and repulsion. Prior O2 experience has opposite effects on the pheromone responsiveness of these neurons. These circuit changes provide a physiological correlate of altered pheromone valence. Our results suggest C. elegans stores a memory of recent O2 experience in the RMG circuit and illustrate how a circuit is flexibly sculpted to guide behavioral decisions in a context-dependent manner.

Integrative Bioinformatic Analyses of Global Transcriptome Data Decipher Novel Molecular Insights into Cardiac Anti-Fibrotic Therapies.

Integrative bioinformatics is an emerging field in the big data era, offering a steadily increasing number of algorithms and analysis tools. However, for researchers in experimental life sciences it is often difficult to follow and properly apply the bioinformatical methods in order to unravel the complexity and systemic effects of omics data. Here, we present an integrative bioinformatics pipeline to decipher crucial biological insights from global transcriptome profiling data to validate innovative therapeutics. It is available as a web application for an interactive and simplified analysis without the need for programming skills or deep bioinformatics background. The approach was applied to an ex vivo cardiac model treated with natural anti-fibrotic compounds and we obtained new mechanistic insights into their anti-fibrotic action and molecular interplay with miRNAs in cardiac fibrosis. Several gene pathways associated with proliferation, extracellular matrix processes and wound healing were altered, and we could identify micro (mi) RNA-21-5p and miRNA-223-3p as key molecular components related to the anti-fibrotic treatment. Importantly, our pipeline is not restricted to a specific cell type or disease and can be broadly applied to better understand the unprecedented level of complexity in big data research.

A method for the graphical modeling of relative temporal constraints.

Searching for patient cohorts in electronic patient data often requires the definition of temporal constraints between the selection criteria. However, beyond a certain degree of temporal complexity, the non-graphical, form-based approaches implemented in current translational research platforms may be limited when modeling such constraints. In our opinion, there is a need for an easily accessible and implementable, fully graphical method for creating temporal queries. We aim to respond to this challenge with a new graphical notation. Based on Allen's time interval algebra, it allows for modeling temporal queries by arranging simple horizontal bars depicting symbolic time intervals. To make our approach applicable to complex temporal patterns, we apply two extensions: with duration intervals, we enable the inference about relative temporal distances between patient events, and with time interval modifiers, we support counting and excluding patient events, as well as constraining numeric values. We describe how to generate database queries from this notation. We provide a prototypical implementation, consisting of a temporal query modeling frontend and an experimental backend that connects to an i2b2 system. We evaluate our modeling approach on the MIMIC-III database to demonstrate that it can be used for modeling typical temporal phenotyping queries.

Environmental CO2 inhibits Caenorhabditis elegans egg-laying by modulating olfactory neurons and evokes widespread changes in neural activity.

Carbon dioxide (CO2) gradients are ubiquitous and provide animals with information about their environment, such as the potential presence of prey or predators. The nematode Caenorhabditis elegans avoids elevated CO2, and previous work identified three neuron pairs called "BAG," "AFD," and "ASE" that respond to CO2 stimuli. Using in vivo Ca(2+) imaging and behavioral analysis, we show that C. elegans can detect CO2 independently of these sensory pathways. Many of the C. elegans sensory neurons we examined, including the AWC olfactory neurons, the ASJ and ASK gustatory neurons, and the ASH and ADL nociceptors, respond to a rise in CO2 with a rise in Ca(2+). In contrast, glial sheath cells harboring the sensory endings of C. elegans' major chemosensory neurons exhibit strong and sustained decreases in Ca(2+) in response to high CO2. Some of these CO2 responses appear to be cell intrinsic. Worms therefore may couple detection of CO2 to that of other cues at the earliest stages of sensory processing. We show that C. elegans persistently suppresses oviposition at high CO2. Hermaphrodite-specific neurons (HSNs), the executive neurons driving egg-laying, are tonically inhibited when CO2 is elevated. CO2 modulates the egg-laying system partly through the AWC olfactory neurons: High CO2 tonically activates AWC by a cGMP-dependent mechanism, and AWC output inhibits the HSNs. Our work shows that CO2 is a more complex sensory cue for C. elegans than previously thought, both in terms of behavior and neural circuitry.