Search

In recent years, the field of neuroscience has gone through rapid experimental advances and extensive use of quantitative and computational methods. This accelerating growth has created a need for methodological analysis of the role of theory and the modeling approaches currently used in this field. Toward that end, we start from the general view that the primary role of science is to solve empirical problems, and that it does so by developing theories that can account for phenomena within their domain of application. We propose a commonly-used set of terms - descriptive, mechanistic, and normative - as methodological designations that refer to the kind of problem a theory is intended to solve. Further, we find that models of each kind play distinct roles in defining and bridging the multiple levels of abstraction necessary to account for any neuroscientific phenomenon. We then discuss how models play an important role to connect theory and experiment, and note the importance of well-defined translation functions between them. Furthermore, we describe how models themselves can be used as a form of experiment to test and develop theories. This report is the summary of a discussion initiated at the conference Present and Future Theoretical Frameworks in Neuroscience, which we hope will contribute to a much-needed discussion in the neuroscientific community., deposited on: https://arxiv.org/abs/2003.13825

Recent progress in mass spectrometry (MS) lipidomics has led to a rapid proliferation of studies across biology and biomedicine and facilitating important discoveries. These generate extremely large raw datasets requiring sophisticated tailored solutions to support automated data processing. To address this, numerous software tools have been developed, tailored for specific tasks in the data analysis pipeline. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time-consuming. Here, we first review the data processing pipeline, summarizing the number and scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing including (1) lipid-oriented databases, (2) MS data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification, and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Summary Precision nutrition based on metabolic phenotype may increase the effectiveness of interventions. In this proof-of-concept study, we investigated the effect of modulating dietary macronutrient composition according to muscle insulin-resistant (MIR) or liver insulin-resistant (LIR) phenotypes on cardiometabolic health. Women and men with MIR or LIR (n = 242, body mass index [BMI] 25–40 kg/m2, 40–75 years) were randomized to phenotype diet (PhenoDiet) group A or B and followed a 12-week high-monounsaturated fatty acid (HMUFA) diet or low-fat, high-protein, and high-fiber diet (LFHP) (PhenoDiet group A, MIR/HMUFA and LIR/LFHP; PhenoDiet group B, MIR/LFHP and LIR/HMUFA). PhenoDiet group B showed no significant improvements in the primary outcome disposition index, but greater improvements in insulin sensitivity, glucose homeostasis, serum triacylglycerol, and C-reactive protein compared with PhenoDiet group A were observed. We demonstrate that modulating macronutrient composition within the dietary guidelines based on tissue-specific insulin resistance (IR) phenotype enhances cardiometabolic health improvements. Clinicaltrials.gov registration: NCT03708419, CCMO registration NL63768.068.17.

Transit amplification (TA), a state of combined, rapid proliferative expansion and differentiation of stem cell-descendants, remains poorly defined at the molecular level. The Polycomb Repressive Complex 1 (PRC1) protein BMI1 has been localized to TA compartments, yet its exact role in TA is unclear. PRC1 proteins control gene expression, cell proliferation and DNA-damage repair. Coordination of such DNA-templated activities during TA is predicted to be crucial to support DNA replication and differentiation-associated transcriptional programming. We here examined whether chondrogenesis provides a relevant biological context for synchronized coordination of these chromatin-based tasks by BMI1. Taking advantage of a prominently featuring TA-phase during chondrogenesis in vitro and in vivo, we here report that TA is completely dependent on intact PRC1 function. BMI1-depleted chondrogenic progenitors rapidly accumulate double strand DNA breaks during DNA replication, present massive non-H3K27me3-directed transcriptional deregulation and fail to undergo chondrogenic TA. Genome-wide accumulation of Topoisomerase 2α and Geminin suggests a model in which PRC1 synchronizes replication and transcription during rapid chondrogenic progenitor expansion. Our combined data reveals for the first time a vital cell-autonomous role for PRC1 during chondrogenesis. We provide evidence that chondrocyte hyper-replication and hypertrophy represent a unique example of programmed senescence in vivo. These findings provide new perspectives on PRC1 function in development and disease., The authors received financial support from the European Molecular Biology Organization (Germany; www.embl.de) ASTF5-2009 (F.S.) and the René Vogels foundation (F.S.); grant BFU2010-18146 (MINECO, MV) and Oncocycle program S2010/BMD2470 (Comunidad de Madrid, MV); the Dutch Science Organization (ZonMW-NWO; www.NWO.nl) VIDI grant 864.12.007 (H.M.); VIDI grant 016.046.362 (J.W.V.); Netherlands Reuma foundation (The Netherlands; www.ruemafonds.nl) grant LLP14 (J.W.V., L. van Rhijn, Maastricht, The Netherlands) and a transnational University of Limburg grant (J.W.V., B.W.G.).

Background Intestinal microbiota might interact with capecitabine and vice versa. Patients and methods 33 mCRC patients collected faecal samples before, during, and after three cycles capecitabine. Results Intestinal microbiota were not affected by capecitabine and not different between responders and non-responders. Conclusions Our study provides insights into challenges and points of attention for the design of upcoming clinical microbiota studies. Background Previous pre-clinical research has indicated that the intestinal microbiota can potentiate anti-tumour efficacy of capecitabine and that capecitabine treatment impacts intestinal microbiota composition and diversity. Using a longitudinal design, this study explores the associations between the intestinal microbiota and treatment response in patients with metastatic colorectal cancer (mCRC) during capecitabine treatment. Patients and methods Patients with mCRC treated with capecitabine were prospectively enrolled in a multicentre cohort study. Patients collected a faecal sample and completed a questionnaire before, during, and after three cycles of capecitabine. Several clinical characteristics, including tumour response, toxicity and antibiotic use were recorded. Intestinal microbiota were analysed by amplicon sequencing of the 16S rRNA V4 gene-region. Results 33 patients were included. After three cycles of capecitabine, six patients (18%) achieved a partial response, 25 (76%) showed stable disease, and one (3%) experienced progressive disease. 90 faecal samples were collected. Microbial diversity (α-diversity), community structure (β-diversity), and bacterial abundance on phylum and genus level were not significantly different between responders and non-responders and were not significantly affected by three cycles of capecitabine. Conclusions This is the first clinical study with longitudinal intestinal microbiota sampling in mCRC patients that explores the role of the intestinal microbiota during treatment with capecitabine. Intestinal microbiota composition and diversity before, during, and after three cycles of capecitabine were not associated with response in this study population. Capecitabine did not induce significant changes in the microbiota composition and diversity during the treatment period. Individual effects of antibiotics during capecitabine treatment were observed.

Antibiotic exposure disturbs the developing infant gut microbiota. The capacity of the gut microbiota to recover from this disturbance (resilience) depends on the type of antibiotic. In this study, infant gut microbiota was exposed to a combination of amoxicillin and clavulanate (amoxicillin/clavulanate) in an in vitro colon model (TIM-2) with fecal-derived microbiota from 1-month-old (1-M; a mixed-taxa community type) as well as 3-month-old (3-M; Bifidobacterium dominated community type) breastfed infants. We investigated the effect of two common infant prebiotics, 2′-fucosyllactose (2’-FL) or galacto-oligosaccharides (GOS), on the resilience of infant gut microbiota to amoxicillin/clavulanate-induced changes in microbiota composition and activity. Amoxicillin/clavulanate treatment decreased alpha diversity and induced a temporary shift of microbiota to a community dominated by enterobacteria. Moreover, antibiotic treatment increased succinate and lactate in both 1- and 3-M colon models, while decreasing the production of short-chain (SCFA) and branched-chain fatty acids (BFCA). The prebiotic effect on the microbiota recovery depended on the fermenting capacity of antibiotic-exposed microbiota. In the 1-M colon model, the supplementation of 2’-FL supported the recovery of microbiota and restored the production of propionate and butyrate. In the 3-M colon model, GOS supplementation supported the recovery of microbiota and increased the production of acetate and butyrate.

The regenerative capacity of corneal endothelial cells (CECs) differs between species; in bigger mammals, CECs are arrested in a non-proliferative state. Damage to these cells can compromise their function causing corneal opacity. Corneal transplantation is the current treatment for the recovery of clear eyesight, but the donor tissue demand is higher than the availability and there is a need to develop novel treatments. Interestingly, rabbit CECs retain a high proliferative profile and can repopulate the endothelium. There is a lack of fundamental knowledge to explain these differences. Gaining information on their transcriptomic variances could allow the identification of CEC proliferation drivers. In this study, human, sheep, and rabbit CECs are analyzed at the transcriptomic level. To understand the differences across each species, a pipeline for the analysis of pathways with different activities is generated. The results reveal that 52 pathways have different activity when comparing species with non-proliferative CECs (human and sheep) to species with proliferative CECs (rabbit). The results show that Notch and TGF-beta pathways have increased activity in species with non-proliferative CECs, which might be associated with their low proliferation. Overall, this study illustrates transcriptomic pathway-level differences that can provide leads to develop novel therapies to regenerate the corneal endothelium.

Carnosine (β-alanyl-L-histidine) is a naturally occurring endogenous peptide widely distributed in excitable tissues such as the brain. This dipeptide possesses well-demonstrated antioxidant, anti-inflammatory, and anti-aggregation properties, and it may be useful for treatment of pathologies characterized by oxidative stress and energy unbalance such as depression and Alzheimer’s disease (AD). Microglia, the brain-resident macrophages, are involved in different physiological brain activities such synaptic plasticity and neurogenesis, but their dysregulation has been linked to the pathogenesis of numerous diseases. In AD brain, the activation of microglia towards a pro-oxidant and pro-inflammatory phenotype has found in an early phase of cognitive decline, reason why new pharmacological targets related to microglia activation are of great importance to develop innovative therapeutic strategies. In particular, microglia represent a common model of lipopolysaccharides (LPS)-induced activation to identify novel pharmacological targets for depression and AD and numerous studies have linked the impairment of energy metabolism, including ATP dyshomeostasis, to the onset of depressive episodes. In the present study, we first investigated the toxic potential of LPS + ATP in the absence or presence of carnosine. Our studies were carried out on human microglia (HMC3 cell line) in which LPS + ATP combination has shown the ability to promote cell death, oxidative stress, and inflammation. Additionally, to shed more light on the molecular mechanisms underlying the protective effect of carnosine, its ability to modulate reactive oxygen species production and the variation of parameters representative of cellular energy metabolism was evaluated by microchip electrophoresis coupled to laser-induced fluorescence and high performance liquid chromatography, respectively. In our experimental conditions, carnosine prevented LPS + ATP-induced cell death and oxidative stress, also completely restoring basal energy metabolism in human HMC3 microglia. Our results suggest a therapeutic potential of carnosine as a new pharmacological tool in the context of multifactorial disorders characterize by neuroinflammatory phenomena including depression and AD.

The metabolic axis linking the gut microbiome and heart is increasingly being researched in the context of cardiovascular health. The gut microbiota-derived trimethylamine/trimethylamine N-oxide (TMA/TMAO) pathway is responsible along this axis for the bioconversion of dietary precursors into TMA/TMAO and has been implicated in the progression of heart failure and dysbiosis through a positive-feedback interaction. Systems biology approaches in the context of researching this interaction offer an additional dimension for deepening the understanding of metabolism along the gut-heart axis. For instance, genome-scale metabolic models allow to study the functional role of pathways of interest in the context of an entire cellular or even whole-body metabolic network. In this mini review, we provide an overview of the latest findings on the TMA/TMAO super pathway and summarize the current state of knowledge in a curated pathway map on the community platform WikiPathways. The pathway map can serve both as a starting point for continual curation by the community as well as a resource for systems biology modeling studies. This has many applications, including addressing remaining gaps in our understanding of the gut-heart axis. We discuss how the curated pathway can inform a further curation and implementation of the pathway in existing whole-body metabolic models, which will allow researchers to computationally simulate this pathway to further understand its role in cardiovascular metabolism.

INTRODUCTION: Recent advances in wearable technology allow for the development of wirelessly connected sensors to continuously measure vital parameters in the general ward or even at home. The present study assesses the accuracy of a wearable patch (Healthdot) for continuous monitoring of heartrate (HR) and respiration rate (RR).MATERIALS AND METHODS: The Healthdot measures HR and RR by means of chest accelerometry. The study population consisted of patients following major abdominal oncological surgery. The analysis focused on the agreement between HR and RR measured by the Healthdot and the gold standard patient monitor in the intensive and post-anesthesia care unit.RESULTS: For HR, a total of 112 h of measurements was collected in 26 patients. For RR, a total of 102 h of measurements was collected in 21 patients. On second to second analysis, 97% of the HR and 87% of the RR measurements were within 5 bpm and 3 rpm of the reference monitor. Assessment of 5-min averaged data resulted in 96% of the HR and 95% of the RR measurements within 5 bpm and 3 rpm of the reference monitor. A Clarke error grid analysis showed that 100% of the HR and 99.4% of the 5-min averaged data was clinically acceptable.CONCLUSION: The Healthdot accurately measured HR and RR in a cohort of patients recovering from major abdominal surgery, provided that good quality data was obtained. These results push the Healthdot forward as a clinically acceptable tool in low acuity settings for unobtrusive, automatic, wireless and continuous monitoring.

Although lipids are crucial molecules for cell structure, metabolism, and signaling in most organs, they have additional specific functions in the skin. Lipids are required for the maintenance and regulation of the epidermal barrier, physical properties of the skin, and defense against microbes. Analysis of the lipidomeethe totality of lipidseis of similar complexity to those of proteomics or other omics, with lipid structures ranging from simple, linear, to highly complex structures. In addition, the ordering and chemical modifications of lipids have consequences on their biological function, especially in the skin. Recent advances in analytic capability (usually with mass spectrometry), bioinformatic processing, and integration with other dermatological big data have allowed researchers to increasingly understand the roles of specific lipid species in skin biology. In this paper, we review the techniques used to analyze skin lipidomics and epilipidomics.

The human brain effortlessly solves the complex computational task of sound localization using a mixture of spatial cues. How the brain performs this task in naturalistic listening environments (e.g. with reverberation) is not well understood. In the present paper, we build on the success of deep neural net-works at solving complex and high-dimensional problems [1] to develop goal-driven, neurobiological-inspired convolutional neural network (CNN) models of human spatial hearing. After training, we visual-ize and quantify feature representations in intermediate layers to gain insights into the representational mechanisms underlying sound location encoding in CNNs. Our results show that neurobiological-inspired CNN models trained on real-life sounds spatialized with human binaural hearing characteristics can accu-rately predict sound location in the horizontal plane. CNN localization acuity across the azimuth resem-bles human sound localization acuity, but CNN models outperform human sound localization in the back. Training models with different objective functions -that is, minimizing either Euclidean or angular dis-tance -modulates localization acuity in particular ways. Moreover, different implementations of binaural integration result in unique patterns of localization errors that resemble behavioral observations in humans. Finally, feature representations reveal a gradient of spatial selectivity across network layers, starting with broad spatial representations in early layers and progressing to sparse, highly selective spa-tial representations in deeper layers. In sum, our results show that neurobiological-inspired CNNs are a valid approach to modeling human spatial hearing. This work paves the way for future studies combining neural network models with empirical measurements of neural activity to unravel the complex compu-tational mechanisms underlying neural sound location encoding in the human auditory pathway. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Understanding the biological-electrical transduction mechanisms is essential for reliable neural signal recording and feature extraction. As an alternative to state-of-the-art lumped-element circuit models, here we adopt a multiscale-multiphysics finite-element modeling framework. The model couples ion transport with the Hodgkin-Huxley model and the readout circuit, and is used to investigate a few relevant case studies. This approach is amenable to explore ion transport in the extracellular medium otherwise invisible to circuit model analysis.

The underlying biological mechanisms causing persistent fatigue complaints after colorectal cancer treatment need further investigation. We investigated longitudinal associations of circulating concentrations of 138 metabolites with total fatigue and subdomains of fatigue between 6 weeks and 2 years after colorectal cancer treatment. Among stage I-III colorectal cancer survivors (n = 252), blood samples were obtained at 6 weeks, and 6, 12 and 24 months posttreatment. Total fatigue and fatigue subdomains were measured using a validated questionnaire. Tandem mass spectrometry was applied to measure metabolite concentrations (BIOCRATES AbsoluteIDQp180 kit). Confounder-adjusted longitudinal associations were analyzed using linear mixed models, with false discovery rate (FDR) correction. We assessed interindividual (between-participant differences) and intraindividual longitudinal associations (within-participant changes over time). In the overall longitudinal analysis, statistically significant associations were observed for 12, 32, 17 and three metabolites with total fatigue and the subscales "fatigue severity," "reduced motivation" and "reduced activity," respectively. Specifically, higher concentrations of several amino acids, lysophosphatidylcholines, diacylphosphatidylcholines, acyl-alkylphosphatidylcholines and sphingomyelins were associated with less fatigue, while higher concentrations of acylcarnitines were associated with more fatigue. For "fatigue severity," associations appeared mainly driven by intraindividual associations, while for "reduced motivation" stronger interindividual associations were found. We observed longitudinal associations of several metabolites with total fatigue and fatigue subscales, and that intraindividual changes in metabolites over time were associated with fatigue severity. These findings point toward inflammation and an impaired energy metabolism due to mitochondrial dysfunction as underlying mechanisms. Mechanistic studies are necessary to determine whether these metabolites could be targets for intervention.

Current computational models of whole-body glucose homeostasis describe physiological processes by which insulin regulates circulating glucose concentrations. While these models perform well in response to oral glucose challenges, interaction with other nutrients that impact postprandial glucose metabolism, such as amino acids (AAs), is not considered. Here, we developed a computational model of the human glucose-insulin system, which incorporates the effects of AAs on insulin secretion and hepatic glucose production. This model was applied to postprandial glucose and insulin time-series data following different AA challenges (with and without co-ingestion of glucose), dried milk protein ingredients, and dairy products. Our findings demonstrate that this model allows accurate description of postprandial glucose and insulin dynamics and provides insight into the physiological processes underlying meal responses. This model may facilitate the development of computational models that describe glucose homeostasis following the intake of multiple macronutrients, while capturing relevant features of an individual's metabolic health.

The infant gut microbiota affects childhood health. This pioneer microbiota may be vulnerable to antibiotic exposures, but could be supported by prebiotic oligosaccharides found in breast milk and some infant formulas. We sought to characterize the effects of several exposures on the neonatal gut microbiota, including human milk oligosaccharides (HMOs), galacto-oligosaccharides (GOS), and infant/maternal antimicrobial exposures. We profiled the stool microbiota of 1023 one-month-old infants from the KOALA Birth Cohort using 16S rRNA gene amplicon sequencing. We quantified 15 HMOs in breast milk from the mothers of 220 infants, using high-performance liquid chromatography-mass spectrometry. Both breastfeeding and antibiotic exposure decreased gut microbial diversity, but each was associated with contrasting shifts in microbiota composition. Other factors associated with microbiota composition included C-section, homebirth, siblings, and exposure to animals. Neither infant exposure to oral antifungals nor maternal exposure to antibiotics during pregnancy were associated with infant microbiota composition. Four distinct groups of breast milk HMO compositions were evident, corresponding to maternal Secretor status and Lewis group combinations defined by the presence/absence of certain fucosylated HMOs. However, we found the strongest evidence for microbiota associations between two non-fucosylated HMOs: 6'-sialyllactose (6'-SL) and lacto-N-hexaose (LNH), which were associated with lower and higher relative abundances of Bifidobacterium, respectively. Among 111 exclusively formula-fed infants, the GOS-supplemented formula was associated with a lower relative abundance of Clostridium perfringens. In conclusion, the gut microbiota is sensitive to some prebiotic and antibiotic exposures during early infancy and understanding their effects could inform future strategies for safeguarding a health-promoting infant gut microbiota.

In a Dutch non-consanguineous patient having mitochondrial encephalomyopathy with complex I and complex IV deficiency, whole exome sequencing revealed two compound heterozygous variants in SLIRP. SLIRP gene encodes a stem-loop RNA-binding protein that regulates mitochondrial RNA expression and oxidative phosphorylation (OXPHOS). A frameshift and a deep-intronic splicing variant reduced the amount of functional wild-type SLIRP RNA to 5%. Consequently, in patient fibroblasts, MT-ND1, MT-ND6, and MT-CO1 expression was reduced. Lentiviral transduction of wild-type SLIRP cDNA in patient fibroblasts increased MT-ND1, MT-ND6, and MT-CO1 expression (2.5–7.2-fold), whereas mutant cDNAs did not. A fourfold decrease of citrate synthase versus total protein ratio in patient fibroblasts indicated that the resulting reduced mitochondrial mass caused the OXPHOS deficiency. Transduction with wild-type SLIRP cDNA led to a 2.4-fold increase of this ratio and partly restored OXPHOS activity. This confirmed causality of the SLIRP variants. In conclusion, we report SLIRP variants as a novel cause of mitochondrial encephalomyopathy with OXPHOS deficiency.

Whole exome sequencing (WES), analyzed with GENESIS and WeGET, revealed a homozygous deletion in the C1QBP gene in a patient with progressive external ophthalmoplegia (PEO) and multiple mtDNA deletions. The gene encodes the mitochondria-located complementary 1 Q subcomponent-binding protein, involved in mitochondrial homeostasis. Biallelic mutations in C1QBP cause mitochondrial cardiomyopathy and/or PEO with variable age of onset. Our patient showed only late-onset PEO-plus syndrome without overt cardiac involvement. Available data suggest that early-onset cardiomyopathy variants localize in important structural domains and PEO-plus variants in the coiled-coil region. Our patient demonstrates that C1QBP mutations should be considered in individuals with PEO with or without cardiomyopathy. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Selective attention enables the preferential processing of relevant stimulus aspects. Invasive animal studies have shown that attending a sound feature rapidly modifies neuronal tuning throughout the auditory cortex. Human neuroimaging studies have reported enhanced auditory cortical responses with selective attention. To date, it remains unclear how the results obtained with functional magnetic resonance imaging (fMRI) in humans relate to the electrophysiological findings in animal models. Here we aim to narrow the gap between animal and human research by combining a selective attention task similar in design to those used in animal electrophysiology with high spatial resolution ultra-high field fMRI at 7 Tesla. Specifically, human participants perform a detection task, whereas the probability of target occurrence varies with sound frequency. Contrary to previous fMRI studies, we show that selective attention resulted in population receptive field sharpening, and consequently reduced responses, at the attended sound frequencies. The difference between our results to those of previous fMRI studies supports the notion that the influence of selective attention on auditory cortex is diverse and may depend on context, stimulus, and task.

The ACE2 receptors essential for SARS-CoV-2 infections are expressed not only in the lung but also in many other tissues in the human body. To better understand the disease mechanisms and progression, it is essential to understand how the virus affects and alters molecular pathways in the different affected tissues. In this study, we mapped the proteomics data obtained from Nie X. et al. (2021) to the pathway models of the COVID-19 Disease Map project and WikiPathways. The differences in pathway activities between COVID-19 and non-COVID-19 patients were calculated using the Wilcoxon test. As a result, 46% (5,235) of the detected proteins were found to be present in at least one pathway. Only a few pathways were altered in multiple tissues. As an example, the Kinin-Kallikrein pathway, an important inflammation regulatory pathway, was found to be less active in the lung, spleen, testis, and thyroid. We can confirm previously reported changes in COVID-19 patients such as the change in cholesterol, linolenic acid, and arachidonic acid metabolism, complement, and coagulation pathways in most tissues. Of all the tissues, we found the thyroid to be the organ with the most changed pathways. In this tissue, lipid pathways, energy pathways, and many COVID-19 specific pathways such as RAS and bradykinin pathways, thrombosis, and anticoagulation have altered activities in COVID-19 patients. Concluding, our results highlight the systemic nature of COVID-19 and the effect on other tissues besides the lung.

Hepatology communications 5(8), 1400-1411 (2021). doi:10.1002/hep4.1728, Published by Wiley, Hoboken, NJ

The variety of available mitochondrial quantification tools makes it difficult to select the most reliable and accurate quantification tool. Here, we performed elaborate analyses on five open source ImageJ tools. Excessive clustering of mitochondrial structures was observed in four tools, caused by the global thresholding applied by these tools. The Mitochondrial Analyzer, which uses adaptive thresholding, outperformed the other examined tools, with accurate structural segregation and identification. Additionally, we showed that the Mitochondrial Analyzer successfully identifies mitochondrial morphology differences. Based on the observed performance, we consider the Mitochondrial Analyzer the best open source tool for mitochondrial network morphology quantification.

A solid-phase extraction procedure was optimized to extract 3-fucosyllactose and other human milk oligosaccharides (HMOs) from human milk samples separately, followed by absolute quantitation using high-performance anion-exchange chromatography-pulsed amperometric detection and porous graphitized carbon-liquid chromatography-mass spectrometry, respectively. The approach developed was applied on a pilot sample set of 20 human milk samples and paired infant feces collected at around 1 month postpartum. One-dimensional 1H nuclear magnetic resonance spectroscopy was employed on the same samples to determine the relative levels of fucosylated epitopes and sialylated (Neu5Ac) structural elements. Based on different HMO consumption patterns in the gastrointestinal tract, the infants were assigned to three clusters as follows: complete consumption; specific consumption of non-fucosylated HMOs; and, considerable levels of HMOs still present with consumption showing no specific preference. The consumption of HMOs by infant microbiota also showed structure specificity, with HMO core structures and Neu5Ac(α2-3)-decorated HMOs being most prone to degradation. The degree and position of fucosylation impacted HMO metabolization differently.

Analysis of the genes retained in the minimized Mycoplasma JCVI-Syn3A genome established that systems that repair or preempt metabolite damage are essential to life. Several genes known to have such functions were identified and experimentally validated, including 5-formyltetrahydrofolate cycloligase, coenzyme A (CoA) disulfide reductase, and certain hydrolases. Furthermore, we discovered that an enigmatic YqeK hydrolase domain fused to NadD has a novel proofreading function in NAD synthesis and could double as a MutT-like sanitizing enzyme for the nucleotide pool. Finally, we combined metabolomics and cheminformatics approaches to extend the core metabolic map of JCVI-Syn3A to include promiscuous enzymatic reactions and spontaneous side reactions. This extension revealed that several key metabolite damage control systems remain to be identified in JCVI-Syn3A, such as that for methylglyoxal. IMPORTANCE Metabolite damage and repair mechanisms are being increasingly recognized. We present here compelling genetic and biochemical evidence for the universal importance of these mechanisms by demonstrating that stripping a genome down to its barest essentials leaves metabolite damage control systems in place. Furthermore, our metabolomic and cheminformatic results point to the existence of a network of metabolite damage and damage control reactions that extends far beyond the corners of it that have been characterized so far. In sum, there can be little room left to doubt that metabolite damage and the systems that counter it are mainstream metabolic processes that cannot be separated from life itself.Metabolite damage and repair mechanisms are being increasingly recognized. We present here compelling genetic and biochemical evidence for the universal importance of these mechanisms by demonstrating that stripping a genome down to its barest essentials leaves metabolite damage control systems in place.

Scientific reports 12(1), 20189 (2022). doi:10.1038/s41598-022-24488-9, Published by Macmillan Publishers Limited, part of Springer Nature, [London]

Tinnitus is a clinical condition where a sound is perceived without an external sound source. Homeostatic plasticity (HSP), serving to increase neural activity as compensation for the reduced input to the auditory pathway after hearing loss, has been proposed as a mechanism underlying tinnitus. In support, animal models of tinnitus show evidence of increased neural activity after hearing loss, including increased spontaneous and sound-driven firing rate, as well as increased neural noise throughout the auditory processing pathway. Bridging these findings to human tinnitus, however, has proven to be challenging. Here we implement hearing loss-induced HSP in a Wilson-Cowan Cortical Model of the auditory cortex to predict how homeostatic principles operating at the microscale translate to the meso- to macroscale accessible through human neuroimaging. We observed HSP-induced response changes in the model that were previously proposed as neural signatures of tinnitus, but that have also been reported as correlates of hearing loss and hyperacusis. As expected, HSP increased spontaneous and sound-driven responsiveness in hearing-loss affected frequency channels of the model. We furthermore observed evidence of increased neural noise and the appearance of spatiotemporal modulations in neural activity, which we discuss in light of recent human neuroimaging findings. Our computational model makes quantitative predictions that require experimental validation, and may thereby serve as the basis of future human studies of hearing loss, tinnitus, and hyperacusis.

Aims The dilated cardiomyopathy (DCM) phenotype is the result of combined genetic and acquired triggers. Until now, clinical decision-making in DCM has mainly been based on ejection fraction (EF) and NYHA classification, not considering the DCM heterogenicity. The present study aimed to identify patient subgroups by phenotypic clustering integrating aetiologies, comorbidities, and cardiac function along cardiac transcript levels, to unveil pathophysiological differences between DCM subgroups. Methods and results We included 795 consecutive DCM patients from the Maastricht Cardiomyopathy Registry who underwent in-depth phenotyping, comprising extensive clinical data on aetiology and comorbodities, imaging and endomyocardial biopsies. Four mutually exclusive and clinically distinct phenogroups (PG) were identified based upon unsupervised hierarchical clustering of principal components: [PG1] mild systolic dysfunction, [PG2] auto-immune, [PG3] genetic and arrhythmias, and [PG4] severe systolic dysfunction. RNA-sequencing of cardiac samples (n = 91) revealed a distinct underlying molecular profile per PG: pro-inflammatory (PG2, auto-immune), pro-fibrotic (PG3; arrhythmia), and metabolic (PG4, low EF) gene expression. Furthermore, event-free survival differed among the four phenogroups, also when corrected for well-known clinical predictors. Decision tree modelling identified four clinical parameters (auto-immune disease, EF, atrial fibrillation, and kidney function) by which every DCM patient from two independent DCM cohorts could be placed in one of the four phenogroups with corresponding outcome (n = 789; Spain, n = 352 and Italy, n = 437), showing a feasible applicability of the phenogrouping. Conclusion The present study identified four different DCM phenogroups associated with significant differences in clinical presentation, underlying molecular profiles and outcome, paving the way for a more personalized treatment approach., Graphical Abstract

BackgroundPandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a “commons.” Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases. However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modeled with entity schemas represented by Shape Expressions.ResultsAs a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable is demonstrated by integrating data from NCBI (National Center for Biotechnology Information) Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates.ConclusionsAlthough this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, human coronavirus NL63, human coronavirus 229E, human coronavirus HKU1, human coronavirus OC4).

INTRODUCTION: The shift toward remote patient monitoring methods to detect clinical deterioration requires testing of wearable devices in real-life clinical settings. This study aimed to develop a remote early warning scoring (REWS) system based on continuous measurements using a wearable device, and compare its diagnostic performance for the detection of deterioration to the diagnostic performance of the conventional modified early warning score (MEWS).MATERIALS AND METHODS: The study population of this prospective, single center trial consisted of patients who underwent major abdominal cancer surgery and were monitored using routine in-hospital spotcheck measurements of the vital parameters. Heart and respiratory rates were measured continuously using a wireless accelerometer patch (HealthDot). The prediction by MEWS of deterioration toward a complication graded Clavien-Dindo of 2 or higher was compared to the REWS derived from continuous measurements by the wearable patch.MAIN RESULTS: A total of 103 patients and 1909 spot-check measurements were included in the analysis. Postoperative deterioration was observed in 29 patients. For both EWS systems, the sensitivity (MEWS: 0.20 95% CI: [0.13-0.29], REWS: 0.20 95% CI: [0.13-0.29]) and specificity (MEWS: 0.96 95% CI: [0.95-0.97], REWS: 0.96 95% CI: [0.95-0.97]) were assessed.CONCLUSIONS: The diagnostic value of the REWS method, based on continuous measurements of the heart and respiratory rates, is comparable to that of the MEWS in patients following major abdominal cancer surgery. The wearable patch could detect the same amount of deteriorations, without requiring manual spot check measurements.

Chronic inflammation, marked by C-reactive protein, has been associated with changes in methylation, but the causal relationship is unclear. Here, the authors perform a Epigenome-wide association meta-analysis for C-reactive protein levels and find that these methylation changes are likely the consequence of inflammation and could contribute to disease.We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

PURPOSE: The trabecular meshwork (TM) is situated in the most frontal part of the eye and is thought to play an important role in the regulation of the eye pressure. However, this tissue is rather difficult to harvest for research. The purpose of this study is therefore to integrate the existing gene expression data of the healthy TM to increase sample size and identify its signature genes and pathways. This provides a robust reference for the study of molecular disease processes and supports the selection of candidate target genes for new treatments.METHODS: A systematic search identified microarray data of healthy TM tissue. After quality control, datasets of low quality and deviating samples were excluded. Remaining individuals were jointly normalized and integrated into one database. The average gene expression of each tested gene over all individuals was calculated. The 25% genes with the highest average expression were identified as the most active genes in the healthy TM and used as input for pathway and network analysis. Additionally, ubiquitous pathways and genes were identified and excluded from the results. Lastly, we identified genes which are likely to be TM-specific.RESULTS: The gene expression data of 44 individuals, obtained from 18 datasets, were jointly normalized. Ubiquitous genes (n = 688) and ubiquitous pathways (n = 73) were identified and excluded. Following, 1882 genes and 211 pathways were identified as the signature genes and pathways of the healthy TM. Pathway analysis revealed multiple molecular processes of which some were already known to be active in the TM, for example extracellular matrix and elastic fiber formation. Forty-six candidate TM-specific genes were identified. These consist mainly of pseudogenes or novel transcripts of which the function is unknown.CONCLUSIONS: In this comprehensive meta-analysis we identified non-ubiquitous genes and pathways that form the signature of the functioning of the healthy TM. Additionally, 46 candidate TM-specific genes were identified. This method can also be used for other tissues that are difficult to obtain for study.

BackgroundProspective research in the field of cochlear implants is hampered by methodological issues and small sample sizes. The ELEPHANT study presents an alternative clinical trial design with a daily randomized approach evaluating individualized tonotopical fitting of a cochlear implant (CI).MethodsA single-blinded, daily-randomized clinical trial will be implemented to evaluate a new imaging-based CI mapping strategy. A minimum of 20 participants will be included from the start of the rehabilitation process with a 1-year follow-up period. Based on a post-operative cone beam CT scan (CBCT), mapping of electrical input will be aligned to natural place-pitch arrangement in the individual cochlea. The CI’s frequency allocation table will be adjusted to match the electrical stimulation of frequencies as closely as possible to corresponding acoustic locations in the cochlea. A randomization scheme will be implemented whereby the participant, blinded to the intervention allocation, crosses over between the experimental and standard fitting program on a daily basis, and thus effectively acts as his own control, followed by a period of free choice between both maps to incorporate patient preference. With this new approach the occurrence of a first-order carryover effect and a limited sample size is addressed.DiscussionThe experimental fitting strategy is thought to give rise to a steeper learning curve, result in better performance in challenging listening situations, improve sound quality, better complement residual acoustic hearing in the contralateral ear and be preferred by recipients of a CI. Concurrently, the suitability of the novel trial design will be considered in investigating these hypotheses.Trial registrationClinicalTrials.gov:NCT03892941. Registered 27 March 2019.

Purpose Performing bioinformatics analyses using trabecular meshwork (TM) gene expression data in order to further elucidate the molecular pathogenesis of primary open-angle glaucoma (POAG), and to identify candidate target genes. Methods A systematic search in Gene Expression Omnibus and ArrayExpress was conducted, and quality control and preprocessing of the data was performed with ArrayAnalysis.org. Molecular pathway overrepresentation analysis was performed with PathVisio using pathway content from three pathway databases: WikiPathways, KEGG and Reactome. In addition, Gene Ontology (GO) analysis was performed on the gene expression data. The significantly changed pathways were clustered into functional categories which were combined into a network of connected genes. Results Ninety-two significantly changed pathways were clustered into five functional categories: extracellular matrix (ECM), inflammation, complement activation, senescence and Rho GTPase signalling. ECM included pathways involved in collagen, actin and cell-matrix interactions. Inflammation included pathways entailing NF-kappa B and arachidonic acid. The network analysis showed that several genes overlap between the inflammation cluster on the one hand, and the ECM, complement activation and senescence clusters on the other hand. GO analysis, identified additional clusters, related to development and corticosteroids. Conclusion This study provides an overview of the processes involved in the molecular pathogenesis of POAG in the TM. The results show good face validity and confirm findings from histological, biochemical, genome-wide association and transcriptomics studies. The identification of known points of action for drugs, such as Rho GTPase, arachidonic acid, NF-kappa B, prostaglandins and corticosteroid clusters, supports the value of this approach to identify potential drug targets.

Contains fulltext : 219192.pdf (Publisher’s version ) (Closed access) Auditory spatial tasks induce functional activation in the occipital - visual - cortex of early blind humans. Less is known about the effects of blindness on auditory spatial processing in the temporal - auditory - cortex. Here, we investigated spatial (azimuth) processing in congenitally and early blind humans with a phase-encoding functional magnetic resonance imaging (fMRI) paradigm. Our results show that functional activation in response to sounds in general- independent of sound location - was stronger in the occipital cortex but reduced in the medial temporal cortex of blind participants in comparison with sighted participants. Additionally, activation patterns for binaural spatial processing were different for sighted and blind participants in planum temporale. Finally, fMRI responses in the auditory cortex of blind individuals carried less information on sound azimuth position than those in sighted individuals, as assessed with a 2-channel, opponent coding model for the cortical representation of sound azimuth. These results indicate that early visual deprivation results in reorganization of binaural spatial processing in the auditory cortex and that blind individuals may rely on alternative mechanisms for processing azimuth position. 14 p.

Background Inherited Metabolic Disorders (IMDs) are rare diseases where one impaired protein leads to a cascade of changes in the adjacent chemical conversions. IMDs often present with non-specific symptoms, a lack of a clear genotype–phenotype correlation, and de novo mutations, complicating diagnosis. Furthermore, products of one metabolic conversion can be the substrate of another pathway obscuring biomarker identification and causing overlapping biomarkers for different disorders. Visualization of the connections between metabolic biomarkers and the enzymes involved might aid in the diagnostic process. The goal of this study was to provide a proof-of-concept framework for integrating knowledge of metabolic interactions with real-life patient data before scaling up this approach. This framework was tested on two groups of well-studied and related metabolic pathways (the urea cycle and pyrimidine de-novo synthesis). The lessons learned from our approach will help to scale up the framework and support the diagnosis of other less-understood IMDs. Methods Our framework integrates literature and expert knowledge into machine-readable pathway models, including relevant urine biomarkers and their interactions. The clinical data of 16 previously diagnosed patients with various pyrimidine and urea cycle disorders were visualized on the top 3 relevant pathways. Two expert laboratory scientists evaluated the resulting visualizations to derive a diagnosis. Results The proof-of-concept platform resulted in varying numbers of relevant biomarkers (five to 48), pathways, and pathway interactions for each patient. The two experts reached the same conclusions for all samples with our proposed framework as with the current metabolic diagnostic pipeline. For nine patient samples, the diagnosis was made without knowledge about clinical symptoms or sex. For the remaining seven cases, four interpretations pointed in the direction of a subset of disorders, while three cases were found to be undiagnosable with the available data. Diagnosing these patients would require additional testing besides biochemical analysis. Conclusion The presented framework shows how metabolic interaction knowledge can be integrated with clinical data in one visualization, which can be relevant for future analysis of difficult patient cases and untargeted metabolomics data. Several challenges were identified during the development of this framework, which should be resolved before this approach can be scaled up and implemented to support the diagnosis of other (less understood) IMDs. The framework could be extended with other OMICS data (e.g. genomics, transcriptomics), and phenotypic data, as well as linked to other knowledge captured as Linked Open Data.

Significance A wealth of existing findings show that financially constrained individuals are myopic decision-makers who are particularly concerned about the present. We propose that the use of existing intertemporal choice tasks may have skewed our understanding of the decision-making of financially constrained individuals. Specifically, we observe that—as long as an immediate payout is guaranteed—financially constrained individuals are no more myopic than their more affluent counterparts., A large stream of literature found that individuals who experience financial strain are particularly concerned about their present needs—that is, they are more likely to choose smaller immediate payoffs over larger future payoffs. In contrast, some recent findings suggest that financially constrained individuals may be more concerned about future needs instead (e.g., they are relatively more likely to invest in long-lived durables than in short-lived experiences). We propose that the use of traditional intertemporal choice tasks has made prior studies overly sensitive to the myopia-inducing effects of financial constraint. These tasks typically offer a choice between receiving a smaller payoff in the present versus a larger payoff in the future. Across three studies, we observe that, as long as some immediate payout is guaranteed, financially constrained individuals are as likely as nonconstrained individuals to accept a delay for a larger payoff. These findings qualify prior demonstrations of the myopic effects of financial constraint and suggest that the traditionally used choice paradigm might not accurately capture time preferences, particularly for financially constrained individuals. Furthermore, they provide possible interventions for those interested in reducing the myopia of financially constrained individuals who are facing all now versus all later decisions.

SummaryThroughout the chapters in this book, pathways are used to visualize how genetically inheritable metabolic disorders are related. These pathways provide common conceptual models which explain groups of chemical reactions within their biological context. Visual representations of the reactions in biological pathway diagrams provide intuitive ways to study the complex metabolic processes. In order to link (clinical) data to these pathways, they have to be understood by computers. Understanding how to move from a regular pathway drawing to its machine-readable counterpart is pertinent for creating proper models. This chapter outlines the various aspects of the digital counterparts of the pathway diagrams in this book, connecting them to databases and using them in data integration and analysis. This is followed by three examples of bioinformatics applications including a pathway enrichment analysis, a biological network extension, and a final example that integrates pathways with clinical biomarker data.

Scope: Persistent DNA methylation changes may mediate the effects of early-life exposures on later-life health. However, because the length of the human lifespan is challenging for prospective studies, there are few relevant data from human longitudinal studies. Projecting data from mouse models of early-life exposure to existing human studies offers a potential tool to address this research challenge. Methods and Results: C57BL/6J mice were fed low or normal folate diets before and during pregnancy and lactation. Genome-wide promoter methylation was measured in male offspring livers at 17.5 days gestation and 28 weeks. Eight gene promoters were concurrently hypermethylated by folate depletion in fetuses and adults (>1.10 fold-change; pConclusion: Some persistent folate-induced methylation changes observed in mice were mirrored in humans. This demonstrates utility of mouse data in identifying human loci for interrogation as biomarkers of later-life health.

The global need to expand the design of energy-storage devices led to the investigation of alkali metal - Ionic Liquid (IL) mixtures as a possible class of electrolytes. In this study, 1D and 2D Nuclear Magnetic Resonance (NMR) and Electrochemical Impedance Spectroscopy (EIS) as well as Molecular Dynamics (MD) simulations were used to study the intermolecular interactions in imidazolium-based IL - water - alkali halide ternary mixtures. The 1H and 23Na 1D and 1H DOSY NMR spectra revealed that the presence of small quantities of NaCl does not influence the aggregation of water molecules in the IL nano-domains. The order of adding ionic compounds to water, as well as the certain water and NaCl molecular ratios, lead to the formation of isolated water clusters. Two ternary solutions representing different orders of compounds mixing (H2O+ IL + NaCl or H2O+ NaCl + IL) showed a strong dependence of the initial solvation shell of Na+ and the self-clustering of water. Furthermore, the behaviour of water was found to be independent from the conditions applied during the solution preparation, such as temperature and/or duration of stirring and aging. These findings could be confirmed by large differences in the amount of ionic species, observed in the ternary solutions and depending on the order of mixing/solute preparation.

Obesity-related insulin resistance (IR) may develop in multiple organs, representing various etiologies for cardiometabolic diseases. We identified abdominal subcutaneous adipose tissue (ScAT) transcriptome profiles in liver or muscle IR by means of RNA sequencing in overweight or obese participants of the Diet, Obesity, and Genes (DiOGenes) (NCT00390637, ClinicalTrials.gov) cohort (n = 368). Tissue-specific IR phenotypes were derived from a 5-point oral glucose tolerance test. Hepatic and muscle IR were characterized by distinct abdominal ScAT transcriptome profiles. Genes related to extracellular remodeling were upregulated in individuals with primarily hepatic IR, while genes related to inflammation were upregulated in individuals with primarily muscle IR. In line with this, in two independent cohorts, the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) (n = 325) and the Maastricht Study (n = 685), an increased systemic low-grade inflammation profile was specifically related to muscle IR but not to liver IR. We propose that increased ScAT inflammatory gene expression may translate into an increased systemic inflammatory profile, linking ScAT inflammation to the muscle IR phenotype. These distinct IR phenotypes may provide leads for more personalized prevention of cardiometabolic diseases.

Recent functional MRI (fMRI) studies have highlighted differences in responses to natural sounds along the rostral-caudal axis of the human superior temporal gyrus. However, due to the indirect nature of the fMRI signal, it has been challenging to relate these fMRI observations to actual neuronal response properties. To bridge this gap, we present a forward model of the fMRI responses to natural sounds combining a neuronal model of the auditory cortex with physiological modeling of the hemodynamic BOLD response. Neuronal responses are modeled with a dynamic recurrent firing rate model, reflecting the tonotopic, hierarchical processing in the auditory cortex along with the spectro-temporal tradeoff in the rostral-caudal axis of its belt areas. To link modeled neuronal response properties with human fMRI data in the auditory belt regions, we generated a space of neuronal models, which differed parametrically in spectral and temporal specificity of neuronal responses. Then, we obtained predictions of fMRI responses through a biophysical model of the hemodynamic BOLD response (P-DCM). Using Bayesian model comparison, our results showed that the hemodynamic BOLD responses of the caudal belt regions in the human auditory cortex were best explained by modeling faster temporal dynamics and broader spectral tuning of neuronal populations, while rostral belt regions were best explained through fine spectral tuning combined with slower temporal dynamics. These results support the hypotheses of complementary neural information processing along the rostral-caudal axis of the human superior temporal gyrus.

Mitochondria change their shape, size and number, in response to cellular demand, through mitochondrial dynamics. The interaction between mitochondria and the ER, through ER-mitochondrial contact sites, is crucial in mitochondrial dynamics. Several protein complexes tethering mitochondria to the ER include proteins involved in fission or fusion but also proteins involved in calcium homeostasis, which is known to affect mitochondrial dynamics. The formation of these contact sites are especially important for mitochondrial fission as these contact sites induce both outer and inner membrane constriction, prior to recruitment of Drp1. While the exact molecular mechanisms behind these constrictions remain uncertain, several hypotheses have been proposed. In this review, we discuss the involvement of tethering complexes in mitochondrial dynamics and provide an overview of the current knowledge and hypotheses on the constriction of the outer and inner mitochondrial membrane at ER-mitochondrial contact sites.

Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.

Genome-scale metabolic models (GEMs) are comprehensive knowledge bases of cellular metabolism and serve as mathematical tools for studying biological phenotypes and metabolic states or conditions in various organisms and cell types. Given the sheer size and complexity of human metabolism, selecting parameters for existing analysis methods such as metabolic objective functions and model constraints is not straightforward in human GEMs. In particular, comparing several conditions in large GEMs to identify condition- or disease-specific metabolic features is challenging. In this study, we showcase a scalable, model-driven approach for an in-depth investigation and comparison of metabolic states in large GEMs which enables identifying the underlying functional differences. Using a combination of flux space sampling and network analysis, our approach enables extraction and visualisation of metabolically distinct network modules. Importantly, it does not rely on known or assumed objective functions. We apply this novel approach to extract the biochemical differences in adipocytes arising due to unlimited vs blocked uptake of branched-chain amino acids (BCAAs, considered as biomarkers in obesity) using a human adipocyte GEM (iAdipocytes1809). The biological significance of our approach is corroborated by literature reports confirming our identified metabolic processes (TCA cycle and Fatty acid metabolism) to be functionally related to BCAA metabolism. Additionally, our analysis predicts a specific altered uptake and secretion profile indicating a compensation for the unavailability of BCAAs. Taken together, our approach facilitates determining functional differences between any metabolic conditions of interest by offering a versatile platform for analysing and comparing flux spaces of large metabolic networks., Author summary Cellular metabolism is a highly complex and interconnected system. As many lifestyle diseases in humans have a strong metabolic component, it is important to understand metabolic differences between healthy and diseased states. In systems biology, metabolic behaviours are investigated using genome-scale metabolic models. In addition to the sheer size and complexity of the genome-scale metabolic models of human systems, using existing analysis methods is challenging and the parameter selection is not straightforward. Therefore, novel methodological frameworks are necessary for analysing metabolic conditions despite the challenges posed by human models. Particularly, an ongoing challenge has been that of comparing several phenotypes for identifying condition- or disease-specific metabolic signatures. We address this significant challenge by developing a scalable and model-driven approach, ComMet (Comparison of Metabolic states). ComMet enables an in-depth investigation and comparison of metabolic phenotypes in large models while also identifying the underlying functional differences. Novel hypotheses can be generated using ComMet for not only understanding known metabolic phenotypes better but also for guiding the design of new experiments to validate the processes predicted by ComMet.

BackgroundWhereas several engineered nanomaterials are able to incite toxicological effects, the underlying molecular processes are understudied. And the varied physicochemical properties complicate toxicological predictions. Gene expression data allow us to study the cell-specific responses of individual genes, whereas their role in biological processes is harder to interpret. An overrepresentation analysis allows us to identify enriched biological processes and link the experimental data to these, but still prompt broad results which complicates the analysis of detailed toxicological processes. We demonstrated a targeted filtering approach to compare the cell-specific effects of two concentrations of the widely used nanomaterial titanium dioxide (TiO2) -nanobelts.MethodsWe compared public gene expression data generated by Tilton et al. from colon endothelium cells (Caco2), lung endothelium cells (SAE), and monocytic like cells (THP1) after 24-hour exposure to low (10 μg/ml) and high (100 μg/ml) concentrations of TiO2 -nanobelts. We used pathway enrichment analysis of the WikiPathways collection to identify cell and concentration-specific affected pathways. Gene sets from selected Gene Ontology terms (apoptosis, inflammation, DNA damage response and oxidative stress) highlighted pathways with a clear toxicity focus. Finally, pathway-gene networks were created to show the genetic overlap between the altered toxicity-related pathways.ResultsAll cell lines showed more differentially expressed genes after exposure to higher concentration, but our analysis found clear differences in affected molecular processes between the cell lines. Approximately half of the affected pathways are categorized with one of the selected toxicity-related processes. Caco2 cells show resilience to low and high concentrations. SAE cells display some cytotoxic response to the high concentration, while THP1 cells are already strongly affected at a low concentration. The networks show for up- and downregulation for the THP1 cells the most pathways. Additionally, the networks show gene overlap between almost all pathways for all conditions.ConclusionsThe approach allowed us to focus the analysis on affected cytotoxic processes and highlight cell-specific effects. The results showed that Caco2 cells are more resilient to TiO2 -nanobelts exposure compared to SAE cells, while THP1 cells were affected the most. The automated workflow can be easily adapted using other Gene Ontology terms focusing on other biological processes.