Interesting Link Research Articles

Bioinformatics analysis and prediction of Alzheimer's disease and alcohol dependence based on Ferroptosis-related genes.

Alzheimer's disease (AD) is a neurodegenerative disease whose origins have not been universally accepted. Numerous studies have demonstrated the relationship between AD and alcohol dependence; however, few studies have combined the origins of AD, alcohol dependence, and programmed cell death (PCD) to analyze the mechanistic relationship between the development of this pair of diseases. We demonstrated in previous studies the relationship between psychiatric disorders and PCD, and in the same concerning neurodegeneration-related AD, we found an interesting link with the Ferroptosis pathway. In the present study, we explored the bioinformatic interactions between AD, alcohol dependence, and Ferroptosis and tried to elucidate and predict the development of AD from this aspect. We selected the Alzheimer's disease dataset GSE118553 and alcohol dependence dataset GSE44456 from the Gene Expression Omnibus (GEO) database. Ferroptosis-related genes were gathered through Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and relevant literature, resulting in a total of 88 related genes. For the AD and alcohol dependence datasets, we conducted Limma analysis to identify differentially expressed genes (DEGs) and performed functional enrichment analysis on the intersection set. Furthermore, we used ferroptosis-related genes and the DEGs to perform machine learning crossover analysis, employing Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify candidate immune-related central genes. This analysis was also used to construct protein-protein interaction networks (PPI) and artificial neural networks (ANN), as well as to plot receiver operating characteristic (ROC) curves for diagnosing AD and alcohol dependence. We analyzed immune cell infiltration to explore the role of immune cell dysregulation in AD. Subsequently, we conducted consensus clustering analysis of AD using three relevant candidate gene models and examined the immune microenvironment and functional pathways between different subgroups. Finally, we generated a network of gene-gene interactions and miRNA-gene interactions using Networkanalyst. The crossover of AD and alcohol dependence DEG contains 278 genes, and functional enrichment analysis showed that both AD and alcohol dependence were strongly correlated with Ferroptosis, and then crossed them with Ferroptosis-related genes to obtain seven genes. Three candidate genes were finally identified by machine learning to build a diagnostic prediction model. After validation by ANN and PPI analysis, ROC curves were plotted to assess the diagnostic value of AD and alcohol dependence. The results showed a high diagnostic value of the predictive model. In the immune infiltration analysis, functional metabolism and immune microenvironment of AD patients were significantly associated with Ferroptosis. Finally, analysis of target genes and miRNA-gene interaction networks showed that hsa-mir-34a-5p and has-mir-106b-5p could simultaneously regulate the expression of both CYBB and ACSL4. We obtained a diagnostic prediction model with good effect by comprehensive analysis, and validation of ROC in AD and alcohol dependence data sets showed good diagnostic, predictive value for both AD (AUC 0. 75, CI 0.91-0.60), and alcohol dependence (AUC 0.81, CI 0.95-0.68). In the consensus clustering grouping, we identified variability in the metabolic and immune microenvironment between subgroups as a likely cause of the different prognosis, which was all related to Ferroptosis function. Finally, we discovered that hsa-mir-34a-5p and has-mir-106b-5p could simultaneously regulate the expression of both CYBB and ACSL4.

Macroecological links between the Linnean, Wallacean, and Darwinian shortfalls

Species are the currency of most biodiversity studies. However, many shortfalls and biases remain in our biodiversity estimates, preventing a comprehensive understanding of the eco-evolutionary processes that have shaped the biodiversity currently available on Earth. Biased biodiversity estimates also jeopardize the effective implementation of data-driven conservation strategies, ultimately leading to biodiversity loss. Here, we delve into the concept of the Latitudinal Taxonomy Gradient (LTG) and show how this new idea provides an interesting conceptual link between the Linnean (i.e., our ignorance of how many species there are on Earth), Darwinian (i.e., our ignorance of species evolutionary relationships), and Wallacean (i.e., our ignorance on species distribution) shortfalls. More specifically, we contribute to an improved understanding of LTGs and establish the basis for the development of new methods that allow us to: (i) better account for the integration between different shortfalls and, (ii) estimate how these interactions may affect our understanding about the evolutionary components of richness gradients at macroecological scales.

Insights into the Structural Conformations of the Tau Protein in Different Aggregation Status.

Tau is a protein characterized by large structural portions displaying extended conformational changes. Unfortunately, the accumulation of this protein into toxic aggregates in neuronal cells leads to a number of severe pathologies, collectively named tauopathies. In the last decade, significant research advancements were achieved, including a better understanding of Tau structures and their implication in different tauopathies. Interestingly, Tau is characterized by a high structural variability depending on the type of disease, the crystallization conditions, and the formation of pathologic aggregates obtained from in vitro versus ex vivo samples. In this review, we reported an up-to-date and comprehensive overview of Tau structures reported in the Protein Data Bank, with a special focus on discussing the connections between structural features, different tauopathies, different crystallization conditions, and the use of in vitro or ex vivo samples. The information reported in this article highlights very interesting links between all these aspects, which we believe may be of particular relevance for a more informed structure-based design of compounds able to modulate Tau aggregation.

The obesity-induced expression of T-bet in B cells promotes metabolic dysfunction and alters antibody responses

Abstract Obesity is a leading risk factor for premature mortality and poor medical outcomes due to its increasing global prevalence and its profound impact on the human body. Obesity also has a significant immune component as the establishment of a chronic inflammation in obese individuals is a significant driver of metabolic dysfunction. Additionally, obesity alters anti-tumor immunity, and it impairs protective antibody responses during infection or vaccination. The outcome can be extremely catastrophic, as highlighted in the COVID-19 pandemic with obese patients being particular susceptible to the disease. This relationship warrants more investigation into the obesity-associated changes occurring in B cells, central players in both the obesity-associated chronic inflammation and in the production of antibodies. Our lab has identified a subset of B cells which is expanded in both humans and mice during obesity and is characterized by the expression of the transcription factor T-bet. In vivostudies using obese mice fed a high fat diet revealed that these Tbet+ B cells promote inflammation and metabolic dysfunction through the production of proinflammatory antibodies. Additionally, blocking the expression of T-bet in the B cells of obese mice resulted in significant changes in antibody responses, with a greater expansion of germinal center B cells and an increased ability to generate antigen-specific B cells following immunization. Based on our findings, T-bet+ B cells represent an interesting link between obesity, inflammation, and antibody responses. Identifying the mechanisms regulating their function will provide new potential ways to reduce inflammation and enhance protection against infectious diseases in obese patients.

Automatic Exercise Generation for Exploring Connections between Mathematics and Music

Abstract Mathematics and Music are closely connected and their multifaceted relationship has been explored since ancient times. Pythagoras was one of the first who discovered and formalized one of those connections by studying the arithmetic of musical intervals, expressing them by numerical ratios and relating ratios to consonance/dissonance notions, being the Pythagorean tuning and scale based on arithmetic principles. Another interesting link between Mathematics and Music is the geometric approach to musical composition. Geometric patterns are present in different musical style compositions and some composing techniques, such as the 12-tone technique, use geometric transformations, involving also applications of modular arithmetic and set theory to Music. The aim of this work is to present existing relations between Mathematics and Music and to propose automatic exercise generation for exploring and studying those relations. The exercises are generated using the system MVGEN and the LaTeX package MusiXTeX. The generation process and the automatically generated exercises can be used for creating learning and assessment materials for education in Mathematics and Music, linking Science and Art.

NRF2 signaling pathway: A comprehensive prognostic and gene expression profile analysis in breast cancer.

Breast cancer is the most frequently diagnosed malignant tumor in women and a major public health concern. NRF2 axis is a cellular protector signaling pathway protecting both normal and cancer cells from oxidative damage. NRF2 is a transcription factor that binds to the gene promoters containing antioxidant response element-like sequences. In this report, differential expression of NRF2 signaling pathway elements, as well as the correlation of NRF2 pathway mRNAs with various clinicopathologic characteristics, including molecular subtypes, tumor grade, tumor stage, and methylation status, has been investigated in breast cancer using METABRIC and TCGA datasets. In the current report, our findings revealed the deregulation of several NRF2 signaling elements in breast cancer patients. Moreover, there were negative correlations between the methylation of NRF2 genes and mRNA expression. The expression of NRF2 genes significantly varied between different breast cancer subtypes. In conclusion, substantial deregulation of NRF2 signaling components suggests an important role of these genes in breast cancer. Because of the clear associations between mRNA expression and methylation status, DNA methylation could be one of the mechanisms that regulate the NRF2 pathway in breast cancer. Differential expression of Hippo genes among various breast cancer molecular subtypes suggests that NRF2 signaling may function differently in different subtypes of breast cancer. Our data also highlights an interesting link between NRF2 components' transcription and tumor grade/stage in breast cancer.

The sleeping brain’s connectivity and family environment: characterizing sleep EEG coherence in an infant cohort

Brain connectivity closely reflects brain function and behavior. Sleep EEG coherence, a measure of brain’s connectivity during sleep, undergoes pronounced changes across development under the influence of environmental factors. Yet, the determinants of the developing brain’s sleep EEG coherence from the child’s family environment remain unknown. After characterizing high-density sleep EEG coherence in 31 healthy 6-month-old infants by detecting strongly synchronized clusters through a data-driven approach, we examined the association of sleep EEG coherence from these clusters with factors from the infant’s family environment. Clusters with greatest coherence were observed over the frontal lobe. Higher delta coherence over the left frontal cortex was found in infants sleeping in their parents’ room, while infants sleeping in a room shared with their sibling(s) showed greater delta coherence over the central parts of the frontal cortex, suggesting a link between local brain connectivity and co-sleeping. Finally, lower occipital delta coherence was associated with maternal anxiety regarding their infant’s sleep. These interesting links between sleep EEG coherence and family factors have the potential to serve in early health interventions as a new set of targets from the child’s immediate environment.

Associated long-term effects of decabromodiphenyl ethane on the gut microbial profiles and metabolic homeostasis in Sprague-Dawley rat offspring

Decabromodiphenyl ethane (DBDPE) as a widely used brominated flame retardant is harmful to human health due to its toxicity, including cardiovascular toxicity, reproductive toxicity, and hepatotoxicity. However, the knowledge of the long-term effects and structural and metabolic function influence on gut microbiota from DBDPE exposure remains limited. This study was mainly aimed at the gut microbiome and fecal metabolome of female rats and their offspring exposed to DBDPE in early life. 16S rRNA gene sequencing demonstrated that maternal DBDPE exposure could increase the α-diversity of gut microbiota in immature offspring while decreasing the abundance of Bifidobacterium, Clostridium, Muribaculum, Escherichia, and Lactobacillus in adult offspring. The nonmetric multidimensional scaling showed a consistency in the alternation of β-diversity between pregnant rats and their adult offspring. Furthermore, the short-chain fatty acids produced by gut microbiota dramatically increased in adult offspring after maternal DBDPE exposure, revealing that DBDPE treatment disrupted the gut microbial compositions and altered the gut community's metabolic functions. Untargeted metabolomics identified 41 differential metabolites and seven metabolic pathways between adult offspring from various groups. Targeted metabolomic showed that maternal high dose DBDPE exposure obviously decreased the level of glutathione, taurine, and l-carnitine in their adult offspring, which verified the correlation between weight loss and amino acid metabolites. An interesting link between some gut bacteria (especially the Firmicutes) and fecal metabolites demonstrated the shifts in gut microbiota may drive the metabolic process of fecal metabolites. The current findings provide new insight into long-term effects on human health.

Gas Helicity Yields New Insights into Gas–Liquid Reactor Design: Enhanced Oxygen Transfer Rate of Coaxial Mixers at Low-Speed Ratio

The gas helicity isosurface plots (i.e., the projection of the gas velocity onto the gas vorticity) were used to visualize the degree of gas entrainment in the impeller vortices. We discovered an interesting link between the gas helicity and the volumetric mass transfer coefficient. The gas helicity can be negatively or positively depending upon the alignment of the entrained gas motion with the impeller rotation. The 1 wt % CMC and xanthan gum solutions obey the power-law and Herschel-Bulkley rheological models, respectively. The dissolved oxygen concentration profile was investigated both experimentally and numerically using coaxial mixers consisting of a central impeller and a wall-scraping anchor. The local gas helicity near the impeller blades revealed that the 1 wt % CMC and xanthan gum solutions experienced a different mass transfer capacity at the critical anchor impeller speed of 30 rpm. This study provides insights into how new energy-efficient impellers can be designed.

Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the applicability of DNNs in scenarios where annotated images are scarce. Mixed supervision is an appealing alternative for mitigating this obstacle. In this setting, only a small fraction of the data contains complete pixel-wise annotations and other images have a weaker form of supervision, e.g., only a handful of pixels are labeled. In this work, we propose a dual-branch architecture, where the upper branch (teacher) receives strong annotations, while the bottom one (student) is driven by limited supervision and guided by the upper branch. Combined with a standard cross-entropy loss over the labeled pixels, our novel formulation integrates two important terms: (i) a Shannon entropy loss defined over the less-supervised images, which encourages confident student predictions in the bottom branch; and (ii) a Kullback-Leibler (KL) divergence term, which transfers the knowledge (i.e., predictions) of the strongly supervised branch to the less-supervised branch and guides the entropy (student-confidence) term to avoid trivial solutions. We show that the synergy between the entropy and KL divergence yields substantial improvements in performance. We also discuss an interesting link between Shannon-entropy minimization and standard pseudo-mask generation, and argue that the former should be preferred over the latter for leveraging information from unlabeled pixels. We evaluate the effectiveness of the proposed formulation through a series of quantitative and qualitative experiments using two publicly available datasets. Results demonstrate that our method significantly outperforms other strategies for semantic segmentation within a mixed-supervision framework, as well as recent semi-supervised approaches. Moreover, in line with recent observations in classification, we show that the branch trained with reduced supervision and guided by the top branch largely outperforms the latter. Our code is publicly available: https://github.com/by-liu/ConfKD.

Black hole chemistry, the cosmological constant and the embedding tensor

We study black-hole thermodynamics in theories that contain dimensionful constants such as the cosmological constant or coupling constants in Wald’s formalism. The most natural way to deal with these constants is to promote them to scalar fields introducing a (d − 1)-form Lagrange multiplier that forces them to be constant on-shell. These (d − 1)-form potentials provide a dual description of them and, in the context of superstring/supergravity theories, a higher-dimensional origin/explanation. In the context of gauged supergravity theories, all these constants can be collected in the embedding tensor. We show in an explicit 4-dimensional example that the embedding tensor can also be understood as a thermodynamical variable that occurs in the Smarr formula in a duality-invariant fashion. This establishes an interesting link between black-hole thermodynamics, gaugings and compactifications in the context of superstring/supergravity theories.

THE ROLE OF ANNA (ASJA) LĀCIS IN THE GENESIS OF WALTER BENJAMIN’S PHILOSOPHICAL THOUGHT

Walter Benjamin’s collection of articles, Passagenwerk (The Arcades Project), is regarded as the quintessence of his philosophical thought and aesthetical beliefs. A forerunner of this monumental work is the travel description entitled “Napoli”, written in co-authorship with Anna Lācis, where the keyword is porosity, which is a metaphor for the specific way of thinking for Walter Benjamin. The collection of literary sketches “One Way Street” and “Moscow Diary”, created in cooperation with Anna Lācis, are also important records of the 20th century aesthetical perceptions and ideological considerations. There exists an interesting intertextual link between the images of cities in various Benjamin’s works – Naples, Rīga, Moscow. The article is an attempt to discover the “unclear” influence of Asja Lācis on the philosophical thought of Walter Benjamin and is based on Beata Paškevica’s monograph “In der Stadt der Parolen. Asja Lacis, Walter Benjamin und Bertolt Brecht” published in Germany in 2006. The conclusion is that Asja Lācis has not had a great influence on Benjamin’s political views but on his aesthetical views. This has been metaphorically formulated by Benjamin himself in the dedication text of his book “One Way Street”.

Source-free domain adaptation for image segmentation.

Domain adaptation (DA) has drawn high interest for its capacity to adapt a model trained on labeled source data to perform well on unlabeled or weakly labeled target data from a different domain. Most common DA techniques require concurrent access to the input images of both the source and target domains. However, in practice, privacy concerns often impede the availability of source images in the adaptation phase. This is a very frequent DA scenario in medical imaging, where, for instance, the source and target images could come from different clinical sites. We introduce a source-free domain adaptation for image segmentation. Our formulation is based on minimizing a label-free entropy loss defined over target-domain data, which we further guide with weak labels of the target samples and a domain-invariant prior on the segmentation regions. Many priors can be derived from anatomical information. Here, a class-ratio prior is estimated from anatomical knowledge and integrated in the form of a Kullback-Leibler (KL) divergence in our overall loss function. Furthermore, we motivate our overall loss with an interesting link to maximizing the mutual information between the target images and their label predictions. We show the effectiveness of our prior-aware entropy minimization in a variety of domain-adaptation scenarios, with different modalities and applications, including spine, prostate and cardiac segmentation. Our method yields comparable results to several state-of-the-art adaptation techniques, despite having access to much less information, as the source images are entirely absent in our adaptation phase. Our straightforward adaptation strategy uses only one network, contrary to popular adversarial techniques, which are not applicable to a source-free DA setting. Our framework can be readily used in a breadth of segmentation problems, and our code is publicly available: https://github.com/mathilde-b/SFDA.

A Short Scale to Measure Self-Reported Aversive Personality in Political Elites

In order to explain the behavior of political elites, research increasingly considers personality traits. Within this line of research, a recent focus is on socially aversive – yet non-pathological – personality traits (e.g., Machiavellianism, narcissism, psychopathy), with the idea to better understand behavior violating generally accepted ethical, moral, and social norms. Assessments of politicians’ aversive personality traits have so far been almost exclusively based on observer reports of experts and voters. Herein, by contrast, we introduce the Political Elites Aversive Personality Scale (“PEAPS”) particularly tailored to measure self-reported aversive personality among politicians. More precisely, based on two studies with German politicians, we develop a 6-item short scale comprising aspects of different socially aversive personality traits (Machiavellianism, narcissism, psychopathy, and spitefulness). The scale shows an acceptable model fit, an acceptable internal consistency, an acceptable measurement equivalence, and meaningful correlations with other (self-reported) psychological traits and campaign behavior. Moreover, the scale significantly contributes to the explanation of candidates’ negative campaigning, going beyond the explanatory power of models capturing broad, basic personality traits. Overall, the suggested scale provides interesting links to research in (political) psychology and can help to explain attitudes, behavior, and performance of political elites.

Improving the Functional and Sensory Properties of Cookies by Ultrasonic Treatment of Whey Proteins

The profiles of food products are one interesting link that adds a new functional component. Cookies became one of the remarkable foods as a result of their simple preparation, a protracted period, and a sensible acceptance by the population. The effects of sonication on physical and sensory characteristics of cookies to be enhanced were studied. The results showed that cookies prepared with 5 and 10% replacement of sonicated whey protein had significant differences in sensory evaluation especially crumb, but there were no significant differences in the physical characteristics, so we can conclude that sonication will improve sensory properties of cookies. Also, we can conclude that biscuit samples supplemented with 5 or 10% WPC were nutrient-rich. The results of the sensory evaluation showed that the cookie samples supplemented with 5% WPC performed better in most of the characteristics but decreased with an increase in the WPC level. The texture properties of the cookie samples indicated that the control cookies with WPC-supplemented cookies showed no significant differences in most studied properties. It can be concluded that the addition of sonicated whey protein enhanced the physiochemical and sensory properties of cookies.

Probing the Carrier Dynamics of Polymer Composites with Single and Hybrid Carbon Nanotube Fillers for Improved Thermoelectric Performance

The incorporation of carbon nanotubes (CNTs) within polymer hosts offers a great platform for the development of advanced thermoelectric (TE) composite materials. Over the years, several CNT/polymer composite formulations have been investigated on an effort to maximize the TE performance. Meanwhile, several studies focused on the decay dynamics of the charged excitons within CNTs itself and therefrom derived structures, aiming to investigate the lifetimes and the corresponding recombination processes of free charge carriers. The latter physical phenomena play a crucial role in the performance of various types of energy converting and scavenging materials. Nevertheless, up to this date, there is no systematic study on the combination of TE parameters and the critical charge carrier dynamics within CNT containing TE polymer composites. Herein, a variety of composites with single and hybrid CNT fillers based on polycarbonate (PC) and polyether ether ketone (PEEK) polymer matrices were prepared by melt-mixing in small scale. At the same loading, the addition of single fillers in PC results in higher Seebeck coefficients and similar conductivities when compared to the use of hybrid filler systems. In contrast, with hybrid filler systems in PEEK composites, higher power factors could be reached than in single filler composites. Moreover, the PC-based composites are studied using ultrafast laser time-resolved transient absorption spectroscopy (TAS), for the investigation of the exciton lifetimes and the physical origins of free charge carrier transport within the TE films. The findings of this study reveal interesting links between the TE parameters and the obtained charge carrier dynamics.

FAAH rs324420 Polymorphism Is Associated with Performance in Elite Rink-Hockey Players.

Simple SummaryGenetic factors play a key role in athletes’ success; therefore, the interest for the study of the genetic profile contributing the most to extraordinary results in sport has been increasing. The aim of this study was to evaluate the impact of genetic determinants in the athletic performance of the world’s top best rink-hockey players. According to our results, elite rink-hockey players carrying the Fatty Acid Amide Hydrolase (FAAH) rs324420 A allele (AA or AC genotype) are three times more likely to be super athletes, which could be attributed to a higher pain tolerance and better stress coping, which may be useful for training and competition strategies. Despite the promising results, as this is a pioneer study, additional studies are needed for further validation of our results in rink-hockey and other sport modalities.Genetic factors are among the major contributors to athletic performance. Although more than 150 genetic variants have been correlated with elite athlete status, genetic foundations of competition-facilitating behavior influencing elite performances are still scarce. This is the first study designed to examine the distribution of genetic determinants in the athletic performance of elite rink-hockey players. A total of 116 of the world’s top best rink-hockey players (28.2 ± 8.7 years old; more than 50% are cumulatively from the best four world teams and the best five Portuguese teams), who participated at the elite level in the National Rink-Hockey Championship in Portugal, were evaluated in anthropometric indicators/measurements, training conditions, sport experience and sport injuries history. Seven genetic polymorphisms were analyzed. Polymorphism genotyping was performed using the TaqMan® Allelic Discrimination Methodology. Rink-hockey players demonstrated significantly different characteristics according to sex, namely anthropometrics, training habits, sports injuries and genetic variants, such as Vitamin D Receptor (VDR) rs731236 (p < 0.05). The Fatty Acid Amide Hydrolase (FAAH) rs324420 A allele was significantly associated with improved athletic performance (AA/AC vs. CC, OR = 2.80; 95% Cl, 1.23–6.35; p = 0.014; p = 0.008 after Bootstrap) and confirmed as an independent predictor among elite rink-hockey players (adjusted OR = 2.88; 95% Cl, 1.06–7.80; p = 0.038). Our results open an interesting link from FAAH-related biology to athletic performance.

Characterizing Creative Thinking and Creative Achievements in Relation to Symptoms of Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder.

Previous research on ADHD and ASD has mainly focused on the deficits associated with these conditions, but there is also evidence for strengths. Unfortunately, our understanding of potential strengths in neurodevelopmental conditions is limited. One particular strength, creativity, has been associated with both ADHD and ASD. However, the distinct presentations of both conditions beg the question whether ADHD and ASD associate with the same or different aspects of creativity. Therefore, the current study investigated the links between ADHD and ASD symptoms, creative thinking abilities, and creative achievements. To investigate the spectrum of ADHD and ASD symptoms, self-reported ADHD and ASD symptoms, convergent (Remote Associations Test) and divergent thinking (Alternative Uses Task) and creative achievements (Creative Achievement Questionnaire) were assessed in a self-reportedly healthy sample of adults (n = 470). We performed correlation analysis to investigate the relation between ADHD/ASD symptoms and creativity measures. In a second phase of analysis, data from an adult ADHD case-control study (n = 151) were added to investigate the association between ADHD symptoms and divergent thinking in individuals with and without a diagnosis of ADHD.Our analysis revealed that having more ADHD symptoms in the general population was associated with higher scores on all the outcome measures for divergent thinking (fluency, flexibility, and originality), but not for convergent thinking. Individuals with an ADHD diagnosis in the case-control sample also scored higher on measures of divergent thinking. Combining data of the population based and case-control studies showed that ADHD symptoms predict divergent thinking up to a certain level of symptoms. No significant associations were found between the total number of ASD symptoms and any of the creativity measures. However, explorative analyses showed interesting links between the ASD subdomains of problems with imagination and symptoms that relate to social difficulties. Our findings showed a link between ADHD symptoms and divergent thinking abilities that plateaus in the clinical spectrum of symptoms. For ASD symptoms, no relation was found with creativity measures. Increasing the knowledge about positive phenotypes associated with neurodevelopmental conditions and their symptom dimensions might aid psychoeducation, decrease stigmatization and improve quality of life of individuals living with such conditions.

The Drama of History: Ibsen, Hegel, Nietzsche

The Drama of History: Ibsen, Hegel, Nietzsche

Hepatocyte-derived MANF mitigates ethanol-induced liver steatosis in mice via enhancing ASS1 activity and activating AMPK pathway.

Hepatic steatosis plays a detrimental role in the onset and progression of alcohol-associated liver disease (ALD). Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an evolutionarily conserved protein related to the unfolded protein response. Recent studies have demonstrated that MANF plays an important role in liver diseases. In this study, we investigated the role of MANF in ethanol-induced steatosis and the underlying mechanisms. We showed that the hepatic MANF expression was markedly upregulated in mouse model of ALD by chronic-plus-single-binge ethanol feeding. Moreover, after chronic-plus-binge ethanol feeding, hepatocyte-specific MANF knockout (HKO) mice displayed more severe hepatic steatosis and liver injury than wild-type (WT) control mice. Immunoprecipitation-coupled MS proteomic analysis revealed that arginosuccinate synthase 1 (ASS1), a rate-limiting enzyme in the urea cycle, resided in the same immunoprecipitated complex with MANF. Hepatocyte-specific MANF knockout led to decreased ASS1 activity, whereas overexpression of MANF contributed to enhanced ASS1 activity in vitro. In addition, HKO mice displayed unique urea cycle metabolite patterns in the liver with elevated ammonia accumulation after ethanol feeding. ASS1 is known to activate AMPK by generating an intracellular pool of AMP from the urea cycle. We also found that MANF supplementation significantly ameliorated ethanol-induced steatosis in vivo and in vitro by activating the AMPK signaling pathway, which was partly ASS1 dependent. This study demonstrates a new mechanism in which MANF acts as a key molecule in maintaining hepatic lipid homeostasis by enhancing ASS1 activity and uncovers an interesting link between lipid metabolism and the hepatic urea cycle under excessive alcohol exposure.