Molecular Interconnections Research Articles

Ultra-broad sensing range, high sensitivity textile pressure sensors with heterogeneous fibre architecture and molecular interconnection strategy

Textile-based pressure sensors have garnered extensive attentions owing to their potentials in health monitoring, human–machine interactions, wearable human–machine interfaces (HMIs) and soft robotics. High sensitivity over a broad sensing range are highly desired yet challenging for textile pressure sensors due to the incompressibility of matrix materials and the stiffening of microstructures. Herein, we developed a high performance pressure sensor based on the silk/3-Aminopropyltriethoxy-silane/titanium carbide (Silk/APTES/MXene) film. The silk is designed with heterogeneous fiber architecture, which enables rich and multi-level contact pattern and could compensate for the effect of structural stiffening. Furthermore, APTES molecules are used to enhance the interface bonding between MXene and silk, promoting the mechanical stability of the sensor. Benefiting from these advantages, the Silk/APTES/MXene sensor device is achieved with high sensitivity of 17.1 KPa−1 over an ultra-broad sensing range up to 3.3 MPa (R2 = 0.997), ultra-low detection limit (0.25 Pa), and low fatigue toughness after 5000 cycles loading and unloading. With these merits, we have demonstrated its capability for a series of human motion detection (such as foot movement detection, arm/wrist/finger bending, etc) and an overall accuracy of 95 % is obtained with the help of CNN-based convolution neural architecture. More significantly, we have built an entire intelligent human–machine dialogue system and a patient-audience dialogue system, from lip/sign language recognition to real-time screen display and final voice output.

Meta-analysis and transcriptomic analysis reveal that NKRF and ZBTB17 regulate the NF-κB signaling pathway, contributing to the shared molecular mechanisms of Alzheimer's disease and atherosclerosis.

Alzheimer's disease (AD) and atherosclerosis (AS) are widespread diseases predominantly observed in the elderly population. Despite their prevalence, the underlying molecular interconnections between these two conditions are not well understood. Utilizing meta-analysis, bioinformatics methodologies, and the GEO database, we systematically analyzed transcriptome data to pinpoint key genes concurrently differentially expressed in AD and AS. Our experimental validations in mouse models highlighted the prominence of two genes, NKRF (NF-κB-repressing factor) and ZBTB17 (MYC-interacting zinc-finger protein 1). These genes appear to influence the progression of both AD and AS by modulating the NF-κB signaling pathway, as confirmed through subsequent invitro and invivo studies. This research uncovers a novel shared molecular pathway between AD and AS, underscoring the significant roles of NKRF and ZBTB17 in the pathogenesis of these disorders.

Glucometabolic-Related Genes as Diagnostic Biomarkers and Therapeutic Targets for Alzheimer's Disease and Type 2 Diabetes Mellitus: A Bioinformatics Analysis.

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two widespread chronic disorders characterized by shared risk factors and molecular pathways. Glucose metabolism, pivotal for cellular homeostasis and energy supply, plays a critical role in these diseases. Its disturbance has been linked to the pathogenesis of both AD and T2DM. However, a comprehensive investigation into the specific roles of glucometabolic genes in the onset and progression of AD and T2DM has yet to be conducted. By analyzing microarray datasets from the Gene Expression Omnibus (GEO) repository, we identified differentially expressed glucometabolic genes (DEGs) in AD and T2DM cohorts. A range of bioinformatics tools were employed for functional annotation, pathway enrichment, protein interaction network construction, module analysis, ROC curve assessment, correlation matrix construction, gene set enrichment analysis, and gene-drug interaction mapping of these DEGs. Key genes were further validated using quantitative real-time polymerase chain reaction (qRT-PCR) in AD and T2DM murine models. Our investigation identified 41 glucometabolic-related DEGs, with six prominent genes (G6PD, PKM, ENO3, PFKL, PGD, and TALDO1) being common in both AD and T2DM cohorts. These genes play crucial roles in metabolic pathways including glycolysis, pentose phosphate pathway, and amino sugar metabolism. Their diagnostic potential was highlighted by area under curve (AUC) values exceeding 0.6 for AD and 0.8 for T2DM. Further analysis explored the interactions, pathway enrichments, regulatory mechanisms, and potential drug interactions of these key genes. In the AD murine model, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed significant upregulation of G6pd, Eno3, and Taldo1. Similarly, in the T2DM murine model, elevated expression levels of G6pd, Pfkl, Eno3, and Pgd were observed. Our rigorous research sheds light on the molecular interconnections between AD and T2DM from a glucometabolic perspective, revealing new opportunities for pharmacological innovation and therapeutic approaches. This study appears to be the first to extensively investigate glucometabolic-associated DEGs and key genes in both AD and T2DM, utilizing multiple datasets. These insights are set to enhance our understanding of the complex pathophysiology underlying these widespread chronic diseases.

Therapeutic Targeting of Glutaminolysis as a Novel Strategy to Combat Cancer Stem Cells

Rare subpopulations of cancer stem cells (CSCs) have the ability to self-renew and are the primary driving force behind cancer metastatic dissemination and the preeminent hurdle to cancer treatment. As opposed to differentiated, non-malignant tumor offspring, CSCs have sophisticated metabolic patterns that, depending on the kind of cancer, rely mostly on the oxidation of major fuel substrates such as glucose, glutamine, and fatty acids for survival. Glutaminolysis is a series of metabolic reactions that convert glutamine to glutamate and, eventually, α-ketoglutarate, an intermediate in the tricarboxylic acid (TCA) cycle that provides biosynthetic building blocks. These building blocks are mostly utilized in the synthesis of macromolecules and antioxidants for redox homeostasis. A recent study revealed the cellular and molecular interconnections between glutamine and cancer stemness in the cell. Researchers have increasingly focused on glutamine catabolism in their attempt to discover an effective therapy for cancer stem cells. Targeting catalytic enzymes in glutaminolysis, such as glutaminase (GLS), is achievable with small molecule inhibitors, some of which are in early-phase clinical trials and have promising safety profiles. This review summarizes the current findings in glutaminolysis of CSCs and focuses on novel cancer therapies that target glutaminolysis in CSCs.

Accelerated parametrization of catalyst performance in organic electrosynthesis

The increasing availability of renewable electrical energy from wind and solar power is becoming an enabler for the next phase in the global energy transition, namely the coupling of different energy sectors. Besides electrochemical energy conversion for daily and seasonal energy storage, the synthesis of organic fine chemicals or commodities by direct utilization of electricity has enormous potential to contribute to the reduction of greenhouse gas emissions. Electrical energy has already proven to be a perfect replacement for reducing and oxidizing chemical reagents in various reactions, sometimes even succeeding with superb selectivity or even unique molecular interconnectivity. Non-aqueous electrochemical processes in organic media have received much attention over the last decades as a methodology to achieve high electrode potentials and stability of generated active species, inaccessible in an aqueous medium. Because of the exceptional flexibility of the approach and the many influential parameters, however, the discovery and development of novel electrochemical processes commonly comprise extensive experimentation based on batch cell preparation accompanied by post-mortem analysis. The state-of-the-art approaches are cumbersome and time-consuming and often lack the information depth that could be obtained with direct analysis of intermediates and products. This perspective aims to overview current advances in the development of intensive methods for organic electrosynthetic catalyst search protocols and optimization. Novel high-throughput experimentation strategies for fast probing of large numbers of materials and solution compositions, combined with time-resolved product analysis and automated data analysis as well as artificial intelligence, will in the future accelerate the implementation of renewable energy in chemical industry processes.

Interaction of Transformer Oil Parameters on Each Other and on Transformer Health Index Using Curve Estimation Regression Method

Power transformers are one of the most significant and expensive equipment in power systems that are exposed to electrical, thermal, and chemical tensions. The transformer health index is a measure that uses test data and field inspections to assess the condition and determine the remaining life of the transformer. The purpose of this article as a new idea is to determine the relationships between electrical, physical, and chemical parameters of transformer oil, dissolved gases, and the transformer health index. One of the advantages of using the regression method in analyzing transformer data compared to the other methods to evaluate the transformer health index is determining the influence of the parameters that have the most impact on each other. Some achievements of this article are as follows: (1) introducing moisture content as the parameter that plays an effective role in reducing dielectric oil breakdown voltage and improving the transformer health index; (2) determining the inverse relationship between acidity and furfural components; (3) determining furfural as a parameter with the greatest role in reducing the Interfacial tension (IFT) of oil (molecular interconnection); (4) determining CO gas as the parameter with the most role in the production of furfural component; (5) determining C2H2 gas as the parameter with the most role in producing the acid component. For example, with a 1 ppm increase in the moisture component, the oil breakdown voltage decreases by 0.583 kV in the compound, growth, exponential, and logistic regressions, or with a 1 ppm increase in the furfural component, the oil interfacial tension decreases by 0.644 mN/m in power regression. In this article, the curve estimation regression method is used and the results are plotted by SPSS statistical software to analyze the interaction between different transformer parameters. To perform the simulations, test data related to 120 transformers have been considered.

Transcriptomic Changes Highly Similar to Alzheimer's Disease Are Observed in a Subpopulation of Individuals During Normal Brain Aging.

Aging is a major risk factor for late-onset Alzheimer’s disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic datasets from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45–70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic datasets from another cohort of older individuals (>70 years), we found that samples from cognitively normal older individuals clustered with the “healthy aging” subgroup while AD samples mainly clustered with the “AD similar” subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the “normal brain aging” to identify the very early molecular events that may lead to LOAD development.

Hypothetical molecular interconnection between type 2 diabetes and dyslexia

BackgroundDyslexia is one of the most common learning disabilities, especially among children. Type 2 diabetes is a metabolic disorder that affects a large population globally, with metabolic disorders. There have been several genes that are identified as causes of Dyslexia, and in recent studies, it has been found out that some of those genes are also involved in several metabolic pathways. For several years, it has been known that type 2 diabetes causes several neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease. Furthermore, in several studies, it was suggested that type 2 diabetes also has some associations with learning disabilities. This raises the question of whether “Is there a connection between type 2 diabetes and dyslexia?”. In this study, this question is elaborated by linking their developmental processes via bioinformatics analysis about these two diseases individually and collectively.ResultThe literature review for dyslexia and type two diabetes was completed. As the result of this literature review, the genes that are associated to type 2 diabetes and dyslexia were identified. The biological pathways of dyslexia, and dyslexia associated genes, type 2 diabetes, and type 2 diabetes associated genes were identified. The association of these genes, regarding to their association with pathways were analysed, and using STRING database the gene associations were analysed and identified.ConclusionThe findings of this research included the interaction analysis via gene association, co-expression and protein–protein interaction. These findings clarified the interconnection between dyslexia and type 2 diabetes in molecular level and it will be the beginning of an answer regarding to the relationship between T2D and dyslexia. Finally, by improving the understanding this paper aims to open the way for the possible future approach to examine this hypothesis.

Regulatory network of miRNAs, lncRNAs and target genes associated with immune response in bovine mastitis

Abstract Bovine mastitis is mainly caused by Escherichia coli and Streptococcus uberis. It is associated with complex multifactorial phenotypes, requiring an integrative approach to elucidate the molecular networks underlying variable disease outcome. The association of lncRNAs, miRNAs and their target as key players in immunity regulation has not been studied in bovine mastitis. We hypothesize that non-coding genes could mediate immune response in bovine mastitis and have potential as disease markers or drug targets. Through bioinformatic analyses, we investigated the networks of lncRNAs, miRNAs and mRNAs, and identified key regulatory elements driving immune response in bovine mastitis. Our analyses reveal 16 highly significant immune response genes including MYD88, IL-10, IL-4, ICAM1, CXCL8, IL-18 and CSF2. Notably, of the 2904 miRNAs reported, six - bta-miR-24-3p, bta-miR-149-5p, bta-miR-223, bta-miR-185, bta-miR-328, and bta-miR-874, were predicted to bind multiple regions of target genes. Likewise, eight out of 22 lncRNAs including NONBTAT001181.2, XR_003030515.1 and XR_003030515.1 bind 13 mRNA targets. Of interest, some of these are conserved in 15 different species, including Homo sapiens. Our functional analyses show that these lncRNAs and miRNAs may regulate pathogenesis of bovine mastitis through lipopolysaccharide-mediated signaling pathway, regulation of chemokine (C-X-C motif) ligand 2 production, regulation of IL-23 production, positive regulation of chemokine production and pattern recognition receptor activity. This interactome lays a foundation for molecular interconnectivity of regulatory elements in bovine mastitis, deserving further elucidation for potential vaccine and therapeutics.

Solvent Annealing Enables 15.39% Efficiency All‐Small‐Molecule Solar Cells through Improved Molecule Interconnection and Reduced Non‐Radiative Loss

AbstractPost‐treatment is of great importance to form nanoscale phase‐separated morphology for all‐small‐molecule organic solar cells (ASM‐OSCs), while the reasons for the difference between thermal annealing (TA) and solvent annealing (SVA) remain unclear. In this work, the influences of TA and SVA (with three common solvents of THF, CS2, and CF) are systematically investigated based on BT‐2F:N3 through characterization of photovoltaic performance, molecular stacking, charge transfer, etc. The results indicate that: i) solvents with good solubility induce stronger molecular interaction than that of TA treatment, and thus endowing molecules with better mobility to migrate for crystallization and phase separation, which leads to better J‐aggregation and molecular interconnection. ii) Donor‐selectively dissolved CS2 is better for optimizing the donor domain for its suitable domain size, improved molecular interaction and interconnection, and reduced trap states. iii) CS2 imposes a small impact on N3 acceptors and thus alleviates the increment of non‐radiative recombination. As a result, CS2 SVA with unique multifunctions enables a PCE of 15.39% with simultaneously improved voltage (0.845 V) and fill factor (75.02%), which is much higher than 14.66% of TA treatment. Moreover, 15.39% efficiency is also the highest value in binary ASM‐OSCs.

MiR-146a regulates insulin sensitivity via NPR3

The pathogenesis of obesity-related metabolic diseases has been linked to the inflammation of white adipose tissue (WAT), but the molecular interconnections are still not fully understood. MiR-146a controls inflammatory processes by suppressing pro-inflammatory signaling pathways. The aim of this study was to characterize the role of miR-146a in obesity and insulin resistance. MiR-146a−/− mice were subjected to a high-fat diet followed by metabolic tests and WAT transcriptomics. Gain- and loss-of-function studies were performed using human Simpson–Golabi–Behmel syndrome (SGBS) adipocytes. Compared to controls, miR-146a−/− mice gained significantly more body weight on a high-fat diet with increased fat mass and adipocyte hypertrophy. This was accompanied by exacerbated liver steatosis, insulin resistance, and glucose intolerance. Likewise, adipocytes transfected with an inhibitor of miR-146a displayed a decrease in insulin-stimulated glucose uptake, while transfecting miR-146a mimics caused the opposite effect. Natriuretic peptide receptor 3 (NPR3) was identified as a direct target gene of miR-146a in adipocytes and CRISPR/Cas9-mediated knockout of NPR3 increased insulin-stimulated glucose uptake and enhanced de novo lipogenesis. In summary, miR-146a regulates systemic and adipocyte insulin sensitivity via downregulation of NPR3.

Peroxisome Proliferator-Activated Receptors as Molecular Links between Caloric Restriction and Circadian Rhythm.

The circadian rhythm plays a chief role in the adaptation of all bodily processes to internal and environmental changes on the daily basis. Next to light/dark phases, feeding patterns constitute the most essential element entraining daily oscillations, and therefore, timely and appropriate restrictive diets have a great capacity to restore the circadian rhythm. One of the restrictive nutritional approaches, caloric restriction (CR) achieves stunning results in extending health span and life span via coordinated changes in multiple biological functions from the molecular, cellular, to the whole–body levels. The main molecular pathways affected by CR include mTOR, insulin signaling, AMPK, and sirtuins. Members of the family of nuclear receptors, the three peroxisome proliferator–activated receptors (PPARs), PPARα, PPARβ/δ, and PPARγ take part in the modulation of these pathways. In this non-systematic review, we describe the molecular interconnection between circadian rhythm, CR–associated pathways, and PPARs. Further, we identify a link between circadian rhythm and the outcomes of CR on the whole–body level including oxidative stress, inflammation, and aging. Since PPARs contribute to many changes triggered by CR, we discuss the potential involvement of PPARs in bridging CR and circadian rhythm.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes.

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein–protein interaction modules based on “hub genes”, called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Physiological State Dictates the Proteasomal-Mediated Purging of Misfolded Protein Fragments.

A pivotal feature that underlies the development of neurodegeneration is the accumulation of protein aggregates. In response, eukaryotic cells have evolved sophisticated quality control mechanisms to identify, repair and/or eliminate the misfolded abnormal proteins. Chaperones identify any otherwise abnormal conformations in proteins and often help them to regain their correct conformation. However, if repair is not an option, the abnormal protein is selectively degraded to prevent its oligomerization into toxic multimeric complexes. Autophagiclysosomal system and the ubiquitin-proteasome system mediate the targeted degradation of the aberrant protein fragments. Despite the increasing understanding of the molecular counteracting responses toward the accumulation of dysfunctional misfolded proteins, the molecular links between the upstream physiological inputs and the clearance of abnormal misfolded proteins is relatively poorly understood. Recent work has demonstrated that certain physiological states such as vigorous exercise and fasting may enhance the ability of mammalian cells to clear misfolded, toxic and aberrant protein fragments. These findings unveil a novel mechanism that activates the cells' protein-disposal machinery, facilitating the adaptation process of cellular proteome to fluctuations in cellular demands and alterations of environmental cues. Herein, we briefly discuss the molecular interconnection between certain physiological cues and proteasomal degradation pathway in the context of these interesting findings and highlight some of the future prospects.

Strengths and Opportunities of Network Medicine in Cardiovascular Diseases

Network medicine can advance current medical practice by arising as response to the limitations of a reductionist approach focusing on cardiovascular (CV) diseases as a direct consequence of a single defect. This molecular-bioinformatic approach integrates heterogeneous "omics" data and artificial intelligence to identify a chain of perturbations involving key components of multiple molecular networks that are closely related in the human interactome. The clinical view of the network-based approach is greatly supported by the general law of molecular interconnection governing all biological complex systems. Recent advances in bioinformatics have culminated in numerous quantitative platforms able to identify CV disease modules underlying perturbations of the interactome. This might provide novel insights in CV disease mechanisms as well as putative biomarkers and drug targets. We describe the network-based principles and discuss their application to classifying and treating common CV diseases. We compare the strengths and weaknesses of molecular networks in comparison with the classical current reductionist approach, and remark on the necessity for a two-way approach connecting network medicine with large clinical trials to concretely translate novel insights from bench to bedside.

P.119Analysis of the structural and metabolic consequences of McArdle disease using the murine model

McArdle disease is an autosomal recessive disorder caused by the absence of the muscle glycogen phosphorylase, which leads to impairment of glycogen breakdown. The McArdle mouse, a model heavily affected by glycogen accumulation and exercise intolerance, was used to characterize disease progression at three different ages. The molecular and histopathological consequences of the disease were analyzed in five different hind-limb muscles (soleus, extensor digitorum longus, tibialis anterior, gastrocnemius and quadriceps) of young (8-week-old), adult (35-week-old) and old (70-week-old) mice. We observed progressive muscle degeneration, fibrosis and inflammation process that was not associated with an increase in muscle glycogen content during aging. Additionally, this progressive degeneration varied among muscle and fiber types. The lack of glycogen content increase was associated with the inactivation of glycogen synthase and not with compensatory expression of the Pygl and/or Pygb genes in mature muscle. Furthermore, the molecular interconnection between skeletal muscle-liver and adipose tissue was assessed in these mice in order to determine whether there was an upregulation of the oxidative metabolism during disease progression as McArdle mice presented a clear reduction in abdominal fat and liver glycogen content. In this regard, mitochondrial content and activity were assessed in both oxidative and glycolytic muscles as oxidative fibers (specially IIa fibers) presented more structural damage caused by higher glycogen accumulation than glycolytic fibers (IIx and IIx/IIb fibers). Lower levels of mitochondrial content and activity were found in the skeletal muscle of McA mice with respect to their wild-type counterparts.

Alternative Splicing of ALS Genes: Misregulation and Potential Therapies.

Neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA), Parkinson's, Alzheimer's, and Huntington's disease affect a rapidly increasing population worldwide. Although common pathogenic mechanisms have been identified (e.g., protein aggregation or dysfunction, immune response alteration and axonal degeneration), the molecular events underlying timing, dosage, expression, and location of RNA molecules are still not fully elucidated. In particular, the alternative splicing (AS) mechanism is a crucial player in RNA processing and represents a fundamental determinant for brain development, as well as for the physiological functions of neuronal circuits. Although in recent years our knowledge of AS events has increased substantially, deciphering the molecular interconnections between splicing and ALS remains a complex task and still requires considerable efforts. In the present review, we will summarize the current scientific evidence outlining the involvement of AS in the pathogenic processes of ALS. We will also focus on recent insights concerning the tuning of splicing mechanisms by epigenomic and epi-transcriptomic regulation, providing an overview of the available genomic technologies to investigate AS drivers on a genome-wide scale, even at a single-cell level resolution. In the future, gene therapy strategies and RNA-based technologies may be utilized to intercept or modulate the splicing mechanism and produce beneficial effects against ALS.

Immunoregulatory Interplay Between Arginine and Tryptophan Metabolism in Health and Disease.

Over evolution, some amino-acid catabolic pathways have become critical checkpoints in immunity (1–3). The associated immunoregulatory effects rely on the depletion of specific amino acids in the microenvironment and/or generation of biologically active metabolites (4). Consumption of l-arginine (Arg) by arginase 1 (ARG1) represents a well-known immunoregulatory mechanism exploited by M2 macrophages (5) and myeloid-derived suppressor cells (MDSCs) (6–8) in tumor settings. ARG1 is also expressed by human neutrophils (9). Indoleamine 2,3-dioxygenase 1 (IDO1)—a powerful immunosuppressive enzyme catalyzing the first, rate limiting step in l-tryptophan (Trp) catabolism—depletes Trp and produces immunoregulatory molecules collectively known as kynurenines (10–13). High IDO1 expression and catalytic activity occur in dendritic cells (DCs)—professional antigen presenting cells—in response to interferon-γ (IFN-γ) (8, 10, 11). Unlike ARG1, IDO1 is also endowed with non-enzymatic signaling activity in DCs that, in the presence of transforming growth factor-β (TGF-β) in microenvironments, leads to durable immunoregulatory effects (14, 15). In conventional DCs (cDCs), a relay pathway—marked by the sequential activation of ARG1 and IDO1—promotes a potent immunoregulatory phenotype (8, 16, 17). In this setting, spermidine, i.e., a polyamine produced downstream of the ARG1-dependent pathway (18), is capable of triggering IDO1 phosphorylation and signaling, and thus may represent the critical molecular interconnection between the two enzymes (8, 16). Here, we discuss the possible protective vs. pathogenetic roles of the interplay between IDO1 and ARG1 in reprogramming immune cell functions in neoplasia and autoimmune diseases.

A comprehensive map of human elastin cross-linking during elastogenesis.

Elastin is an essential structural protein in the extracellular matrix of vertebrates. It is the core component of elastic fibers, which enable connective tissues such as those of the skin, lungs or blood vessels to stretch and recoil. This function is provided by elastin's exceptional properties, which mainly derive from a unique covalent cross-linking between hydrophilic lysine-rich motifs of units of the monomeric precursor tropoelastin. To date, elastin's cross-linking is poorly investigated. Here, we purified elastin from human tissue and cleaved it into soluble peptides using proteases with different specificities. We then analyzed elastin's molecular structure by identifying unmodified residues, post-translational modifications and cross-linked peptides by high-resolution mass spectrometry and amino acid analysis. The data revealed the presence of multiple isoforms in parallel and a complex and heterogeneous molecular interconnection. We discovered that the same lysine residues in different monomers were simultaneously involved in various cross-link types or remained unmodified. Furthermore, both types of cross-linking domains, Lys-Pro and Lys-Ala domains, participate not only in bifunctional inter- but also in intra-domain cross-links. We elucidated the sequences of several desmosine-containing peptides and the contribution of distinct domains such as 6, 14 and 25. In contrast to earlier assumptions proposing that desmosine cross-links are formed solely between two domains, we elucidated the structure of a peptide that proves a desmosine formation with participation of three Lys-Ala domains. In summary, these results provide new and detailed insights into the cross-linking process, which takes place within and between human tropoelastin units in a stochastic manner.

Recoverable and self-healing electromagnetic wave absorbing nanocomposites

Recent advancements in electronics engineering require materials with the resiliency and sustainability to extend their life time. With this regard, we presented a sustainable multi-functional nanocomposites strategy by introducing dynamic imine bonds based polyazomethine (PAM) as molecular interconnects and Fe3O4-loaded multiwalled carbon nanotubes as electromagnetic (EM) wave absorbing units. Driven by the reversible dynamic imine bonds, our materials show robust spontaneous self-healing with excellent healing efficiencies of 95% for PAM and 90% for nanocomposite, and an accelerated recovery under a moderate mechanical stimulus. By adding Fe3O4-loaded multiwalled carbon nanotubes, the hybrids show excellent EM wave absorbing properties with 50% increment on minimum reflection coefficient (−40.6 dB) than the reported value. We demonstrate a full degradability by decomposing a nanocomposite sheet of 100 mg in an acidic solution within 90 min at room temperature. The nanofillers and monomers after degradation can be re-used to synthesis nanocomposites. The testing results for recoverable nanocomposites show a good retention on mechanical property. This novel strategy may shed a light on the downstream applications in EM wave absorbing devices and smart structures with great potential to accelerate circular economy.