Molecular Domains Research Articles

Power Efficiency Enhancement of Organic Light-Emitting Diodes Due to the Favorable Horizontal Orientation of a Naphthyridine-Based Thermally Activated Delayed Fluorescence Luminophore.

Four emitters based on the naphthyridine acceptor moiety and various donor units exhibiting thermally activated delayed fluorescence (TADF) were designed and synthesized. The emitters exhibited excellent TADF properties with a small ΔE ST and a high photoluminescence quantum yield. A green TADF organic light-emitting diode based on 10-(4-(1,8-naphthyridin-2-yl)phenyl)-10H-phenothiazine exhibited a maximum external quantum efficiency of 16.4% with Commission Internationale de L'éclairage coordinates of (0.368, 0.569) as well as a high current and power efficiency of 58.6 cd/A and 57.1 lm/W, respectively. The supreme power efficiency is a record-high value among the reported values of devices with naphthyridine-based emitters. This results from its high photoluminescence quantum yield, efficient TADF, and horizontal molecular orientation. The molecular orientations of the films of the host and the host doped with the naphthyridine emitter were explored by angle-dependent photoluminescence and grazing-incidence small-angle X-ray scattering (GIWAXS). The orientation order parameters (ΘADPL) were found to be 0.37, 0.45, 0.62, and 0.74 for the naphthyridine dopants with dimethylacridan, carbazole, phenoxazine, and phenothiazine donor moieties, respectively. These results were also proven by GIWAXS measurement. The derivative of naphthyridine and phenothiazine was shown to be more flexible to align with the host and to show the favorable horizontal molecular orientation and crystalline domain size, benefiting the outcoupling efficiency and contributing to the device efficiency.

Engineering Multi-Scale Organization for Biotic and Organic Abiotic Electroactive Systems.

Multi-scale organization of molecular and living components is one of the most critical parameters that regulate charge transport in electroactive systems-whether abiotic, biotic, or hybrid interfaces. In this article, an overview of the current state-of-the-art for controlling molecular order, nanoscale assembly, microstructure domains, and macroscale architectures of electroactive organic interfaces used for biomedical applications is provided. Discussed herein are the leading strategies and challenges to date for engineering the multi-scale organization of electroactive organic materials, including biomolecule-based materials, synthetic conjugated molecules, polymers, and their biohybrid analogs. Importantly, this review provides a unique discussion on how the dependence of conduction phenomena on structural organization is observed for electroactive organic materials, as well as for their living counterparts in electrogenic tissues and biotic-abiotic interfaces. Expansion of fabrication capabilities that enable higher resolution and throughput for the engineering of ordered, patterned, and architecture electroactive systems will significantly impact the future of bioelectronic technologies for medical devices, bioinspired harvesting platforms, and in vitro models of electroactive tissues. In summary, this article presents how ordering at multiple scales is important for modulating transport in both the electroactive organic, abiotic, and living components of bioelectronic systems.

Cooperative Calcium Phosphate Deposition on Collagen-Inspired Short Peptide Nanofibers for Application in Bone Tissue Engineering.

In recent years, immense attention has been devoted over the production of osteoinductive materials. To this direction, collagen has a dominant role in developing hard tissues and plays a crucial role in the biomineralization of these tissues. Here, we demonstrated for the first time the potential of the shortest molecular pentapeptide domain inspired from collagen toward mineralizing hydroxyapatite on peptide fibers to develop bone-filling material. Our simplistic approach adapted the easy and facile route of introducing the metal ions onto the peptide nanofibers, displaying adsorbed glutamate onto the surface. This negatively charged surface further induces the nucleation of the crystalline growth of hydroxyapatite. Interestingly, nucleation and growth of the hydroxyapatite crystals lead to the formation of a self-supporting hydrogel to construct a suitable interface for cellular interactions. Furthermore, microscopic and spectroscopic investigations revealed the crystalline growth of the hydroxyapatite onto peptide fibers. The physical properties were also influenced by this crystalline deposition, as evident from the hierarchical organization leading to hydrogels with enhanced mechanical stiffness and improved thermal stability of the scaffold. Furthermore, the mineralized peptide fibers were highly compatible with osteoblast cells and showed increased cellular biomarkers production, which further reinforced the potential application toward effectively fabricating the grafts for bone tissue engineering.

Data-driven approach to integrating genomic and behavioral preclinical traumatic brain injury research.

Understanding recovery from TBI is complex, involving multiple systems and modalities. The current study applied modern data science tools to manage this complexity and harmonize large-scale data to understand relationships between gene expression and behavioral outcomes in a preclinical model of chronic TBI (cTBI). Data collected by the Moody Project for Translational TBI Research included rats with no injury (naïve animals with similar amounts of anesthetic exposure to TBI and sham-injured animals), sham injury, or lateral fluid percussion TBI, followed by recovery periods up to 12 months. Behavioral measures included locomotor coordination (beam balance neuroscore) and memory and cognition assessments (Morris water maze: MWM) at multiple timepoints. Gene arrays were performed using hippocampal and cortical samples to probe 45,610 genes. To reduce the high dimensionality of molecular and behavioral domains and uncover gene-behavior associations, we performed non-linear principal components analyses (NL-PCA), which de-noised the data. Genomic NL-PCA unveiled three interpretable eigengene components (PC2, PC3, and PC4). Ingenuity pathway analysis (IPA) identified the PCs as an integrated stress response (PC2; EIF2-mTOR, corticotropin signaling, etc.), inflammatory factor translation (PC3; PI3K-p70S6K signaling), and neurite growth inhibition (PC4; Rho pathways). Behavioral PCA revealed three principal components reflecting the contribution of MWM overall speed and distance, neuroscore/beam walk, and MWM platform measures. Integrating the genomic and behavioral domains, we then performed a 'meta-PCA' on individual PC scores for each rat from genomic and behavioral PCAs. This meta-PCA uncovered three unique multimodal PCs, characterized by robust associations between inflammatory/stress response and neuroscore/beam walk performance (meta-PC1), stress response and MWM performance (meta-PC2), and stress response and neuroscore/beam walk performance (meta-PC3). Multivariate analysis of variance (MANOVA) on genomic-behavioral meta-PC scores tested separately on cortex and hippocampal samples revealed the main effects of TBI and recovery time. These findings are a proof of concept for the integration of disparate data domains for translational knowledge discovery, harnessing the full syndromic space of TBI.

Wave function analyses of scandium-doped aluminium clusters, AlnSc (n = 1-24), and their CO2 fixation abilities.

Nanoclusters represent a connection between (i) solid state systems and (ii) species in the atomic and molecular domains. Additionally, nanoclusters can also have very interesting electronic, optical and magnetic properties. For example, some aluminium clusters behave as superatoms and the doping of these clusters might strengthen their adsorption capabilities. Thus, we address herein the structural, energetic and electronic characterisation of scandium-doped aluminium clusters (AlnSc (n = 1-24)) by means of density functional theory calculations and quantum chemical topology wave function analyses. We studied the effect of Sc-doping on the structure and charge distribution by considering pure Al clusters as well. The quantum theory of atoms in molecules (QTAIM) reveals that interior Al atoms have large negative atomic charges (≈2a.u.) and hence the atoms surrounding them are considerably electron deficient. The Interacting Quantum Atoms (IQA) energy partition allowed us to establish the nature of the interaction between the Al13 superatom and the Al12Sc cluster with Al to form the complexes Al14 and Al13Sc, respectively. We also used the IQA approach to examine (i) the influence of Sc on the geometry of the AlnSc complexes along with (ii) the cooperative effects in the binding of AlnSc and Aln+1 clusters. We also exploited the QTAIM and IQA approaches to study the interaction of the electrophilic surface of the examined systems with CO2. Overall, we observe that the investigated Sc-doped Al complexes with a marked stability towards disproportionation reactions exhibit strong adsorption energies with CO2. Concomitantly, the carbon dioxide molecule is considerably distorted and destabilised, conditions which might prepare it for further chemical reactions. Altogether, this paper gives valuable insights on the tuning of the properties of metallic clusters for their design and exploitation in custom-made materials.

Thermal behavior of astrophysical amorphous molecular ices.

Ice is a major component of astrophysical environments - from interstellar molecular clouds through protoplanetary disks to evolved solar systems. Ice and complex organic matter coexist in these environments as well, and it is thought primordial ice brought the molecules of life to Earth four billion years ago, which could have kickstarted the origin of life on Earth. To understand the journey of ice and organics from their origins to becoming a part of evolved planetary systems, it is important to complement high spatial and spectral resolution telescopes such as JWST with laboratory experimental studies that provide deeper insight into the processes that occur in these astrophysical environments. Our laboratory studies are aimed at providing this knowledge. In this article we present simultaneous mass spectrometric and infrared spectroscopic investigation on how molecular ice mixtures behave at different temperatures and how this information is critical to interpret observational data from protoplanetary disks as well as comets. We find that amorphous to crystalline water ice transformation is the most critical phenomenon that differentiates between outgassing of trapped volatiles such as CO2vs. outgassing of pure molecular ice domains of the same in a mixed molecular ice. Crystalline water ice is found to trap only a small fraction of other volatiles (<5%), indicating ice grain composition in astrophysical and planetary environments must be different depending on whether the ice is in amorphous phase or transformed into crystalline phase, even if the crystalline ice undergoes radiation-induced amorphization subsequently. Crystallization of water ice is a key differentiator for many ices in astronomical environments as well as in our Solar System.

Self-assembled multilayers direct a buffer interphase for long-life aqueous zinc-ion batteries

A self-assembled multilayer was used to homogenize ion flux and accelerate charge transfer through area-induced deposition effects and strong dipole moments. The molecular domains act as a buffer interphase to achieve long-term stability.

αβ T-cell receptor recognition of self-phosphatidylinositol presented by CD1b

CD1 glycoproteins present lipid-based antigens to T-cell receptors (TCRs). A role for CD1b in T-cell-mediated autoreactivity was proposed when it was established that CD1b can present self-phospholipids with short alkyl chains (∼C34) to T cells; however, the structural characteristics of this presentation and recognition are unclear. Here, we report the 1.9 Å resolution binary crystal structure of CD1b presenting a self-phosphatidylinositol-C34:1 and an endogenous scaffold lipid. Moreover, we also determined the 2.4Å structure of CD1b-phosphatidylinositol complexed to an autoreactive αβ TCR, BC8B. We show that the TCR docks above CD1b and directly contacts the presented antigen, selecting for both the phosphoinositol headgroup and glycerol neck region via antigen remodeling within CD1b and allowing lateral escape of the inositol moiety through a channel formed by the TCR α-chain. Furthermore, through alanine scanning mutagenesis and surface plasmon resonance, we identified key CD1b residues mediating this interaction, with Glu-80 abolishing TCR binding. We in addition define a role for both CD1b α1 and CD1b α2 molecular domains in modulating this interaction. These findings suggest that the BC8B TCR contacts both the presented phospholipid and the endogenous scaffold lipid via a dual mechanism of corecognition. Taken together, these data expand our understanding into the molecular mechanisms of CD1b-mediated T-cell autoreactivity.

Advanced carbon molecular sieve membranes derived from molecularly engineered cross-linkable copolyimide for gas separations.

Carbon molecular sieve (CMS) membranes with precise molecular discrimination ability and facile scalability are attractive next-generation membranes for large-scale, energy-efficient gas separations. Here, structurally engineered CMS membranes derived from a tailor-made cross-linkable copolyimide with kinked structure are reported. We demonstrate that combining two features, kinked backbones and cross-linkable backbones, to engineer polyimide precursors while controlling pyrolysis conditions allows the creation of CMS membranes with improved gas separation performance. Our results indicate that the CMS membranes provide a versatile platform for a broad spectrum of challenging gas separations. The gas transport properties of the resulting CMS membranes are interpreted in terms of a model reflecting both molecular sieving Langmuir domains and a disordered continuous phase, thereby providing insight into structure evolution from the cross-linkable polyimide precursor to a final CMS membrane. With this understanding of CMS membrane structure and separation performance, these systems are promising for environmentally friendly gas separations.

Entropy of Weighted Graph by Edge Weights by Using Sombor Reduced Index

This paper delves into the exploration of entropy in weighted graphs, where edge weights are determined by the Sombor Reduced Index. The primary aim is to establish and substantiate results by examining various graph types, including Connected Graphs, Star Graphs, Unicyclic Graphs, Regular Graphs, Complete Graphs, Complete Bipartite Graphs, Chemical Graphs, and Tree Graphs. Through rigorous analysis, we unveil the implications of these weighted structures on information content and structural complexities. Additionally, we extend our study to compute weighted entropies for molecular graphs representing specific dendrimer structures. This research contributes to a nuanced understanding of the informational intricacies embedded in diverse graph configurations, particularly emphasizing their significance in the molecular domain.

Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms

Anaplastic lymphoma kinase (ALK) and ROS oncogene 1 (ROS1) gene fusions are well-established key players in non-small cell lung cancer (NSCLC). Although their frequency is relatively low, their detection is important for patient care and guides therapeutic decisions. The accepted methods used for their detection are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) assay, as well as DNA and RNA-based sequencing methodologies. These assays are expensive, time-consuming, and require technical expertise and specialized equipment as well as biological specimens that are not always available. Here we present an alternative detection method using a computer vision deep learning approach. An advanced convolutional neural network (CNN) was used to generate classifier models to detect ALK and ROS1-fusions directly from scanned hematoxylin and eosin (H&E) whole slide images prepared from NSCLC tumors of patients. A two-step training approach was applied, with an initial unsupervised training step performed on a pan-cancer sample cohort followed by a semi-supervised fine-tuning step, which supported the development of a classifier with performances equal to those accepted for diagnostic tests. Validation of the ALK/ROS1 classifier on a cohort of 72 lung cancer cases who underwent ALK and ROS1-fusion testing at the pathology department at Sheba Medical Center displayed sensitivities of 100% for both genes (six ALK-positive and two ROS1-positive cases) and specificities of 100% and 98.6% respectively for ALK and ROS1, with only one false-positive result for ROS1-alteration. These results demonstrate the potential advantages that machine learning solutions may have in the molecular pathology domain, by allowing fast, standardized, accurate, and robust biomarker detection overcoming many limitations encountered when using current techniques. The integration of such novel solutions into the routine pathology workflow can support and improve the current clinical pipeline.

Unsaturation pattern of phosphatidylglycerols modulating the interaction of lysicamine with cells membrane models at the air-water interface

Lysicamine, an alkaloid with tumorigenic activity, was incorporated in cell membrane models made of lipid Langmuir monolayers. Dipalmitoylphosphocholine (DPPC), dioleoylphosphocholine (DOPC), and palmitoyloleoylcholine (POPC) represented non-tumorigenic cell membranes, and dipalmitoylphosphoserine (DPPS), dioleoylphosphoserine (DOPS), and palmitoyloleoylserine (POPS), tumorigenic ones. The monolayers were characterized by tensiometry, infrared spectroscopy, and Brewster Angle Microscopy (BAM). No significant shifts of the isotherms were observed for the saturated lipids (DPPC and DPPS), while for the others (DOPC, POPS, DOPS, and POPS), more significant changes were observed not only in the compression isotherms but also in the surface pressure-time curve for pre-compressed monolayers. The molecular organization, as well as the morphology of the drug-lipid monolayers, could be inferred with infrared spectroscopy and BAM. While the first revealed that the alkyl chain ordering changed upon lysicamine incorporation, the second showed how the drug could distinctly change the state of aggregation of molecular domains at the air-water interface. In conclusion, lysicamine could interact distinctly with each lipid at the air-water interface, showing the dependence not only on the lipid polar groups but also on the level of unsaturation of the alkyl chains.

Key astroglial markers in human liver cirrhosis of different degree: immunohistochemical study

The aim of the study – determining the immunohistochemical levels of the GFAP, GS and AQP4 in different regions of the human brain in the conditions of liver cirrhosis of different degree. Materials and methods. The study was performed on sectional material of 90 patients who suffered during lifetime from liver non-alcoholic cirrhosis of classes A (n = 30, group “A”), B (n = 30, group “B”) and C (n = 30, group “C”) according to Child–Pugh classification, including 59 (65.55 %) cases with clinical symptoms of I–IV grade hepatic encephalopathy. Cortex, white matter, hippocampus, thalamus, striopallidum, cerebellum, were examined using immunohistochemical method for evaluation of GFAP, GS and AQP4 levels. Results. GFAP expression gradually decreased from classes A to C of cirrhosis. The most expressed GFAP decline was found in class C in the cortex and thalamus (6.74- and 6.23-fold decrease). Contrary to GFAP, GS expression gradually increased along with aggravation of cirrhosis. The most prominent augmentation of GS was related in the cortex and thalamus in “C” group, respectively 4.34- and 4.26-fold increase. AQP4 levels also showed growing mode correlated with cirrhosis aggravation. The highest increase was found in the cortex and thalamus in “C” group (4.25- and 4.34-fold increase, respectively). Starting from class B, altered GFAP, GS, and AQP4 levels showed region-dependent relationships. GS and AQP4 were positively correlated in all 6 studied regions, while the inverse relationships were found between GFAP vs. GS and GFAP vs. AQP4 proteins. Conclusions. As early as in class A of cirrhosis, dynamic molecular alterations are occurred in the brain astrocytes, indicating the progressive development of astroglial remodeling with a violation of its cytoskeleton and redistribution of molecular domains within cells. This phenomenon is region- and time-specific; its signs get stronger with time from class to class, becoming most pronounced in class C. Among studied brain regions, cortex and thalamus are characterized by the most pronounced protein changes. Starting from class B, the remarkable relationship is seen between molecular changes of both direct and inverse type. Simultaneously emerging links might indicate synergistic involvement of these molecules in astroglial remodeling in chronic hepatic encephalopathy. Alterations in the mentioned astroglial molecular complex can serve both as a diagnostic marker of reactive astrogliosis during liver cirrhosis and represent a target for novel therapeutic approaches regarding encephalopathy in cirrhotic patients.

Identification of PHB2 as a Potential Biomarker of Luminal A Breast Cancer Cells Using a Cell-Specific Aptamer.

Precise diagnosis of breast cancer molecular subtypes remains a great challenge in clinics. The present molecular biomarkers are not specific enough to classify breast cancer subtypes precisely, which requests for more accurate and specific molecular biomarkers to be discovered. Aptamers evolved by the cell-systematic evolution of ligands by exponential enrichment (SELEX) method show great potential in the discovery and identification of cell membrane targets via aptamer-based cell membrane protein pull-down, which has been regarded as a novel and powerful weapon for the discovery and identification of new molecular biomarkers. Herein, a cell membrane protein PHB2 was identified as a potential molecular biomarker specifically expressed in the cell membranes of MCF-7 breast cancer cells using a DNA aptamer MF3Ec. Further experiments demonstrated that the PHB2 protein is differentially expressed in the cell membranes of MCF-7, SK-BR-3, and MDA-MB-231 breast cancer cells and MCF-10A cells, and the binding molecular domains of aptamer MF3Ec and anti-PHB2 antibodies to the PHB2 protein are different due to there being no obvious competitions between aptamer MF3Ec and anti-PHB2 antibodies in the binding to the cell membranes of target MCF-7 cells. Due to those four cells belonging to luminal A, HER2-positive, and triple-negative breast cancer cell subtypes and human normal mammary epithelial cells, respectively, the PHB2 protein in the cell membrane may be a potential biomarker for precise diagnosis of the luminal A breast cancer cell subtype, which is endowed with the ability to differentiate the luminal A breast cancer cell subtype from HER2-positive and triple-negative breast cancer cell subtypes and human normal mammary epithelial cells, providing a new molecular biomarker and therapeutic target for the accurate and precise classification and diagnostics and personalized therapy of breast cancer.

Nanoscale Chemical Imaging of Human Cell Membranes Using Tip‐Enhanced Raman Spectroscopy

AbstractLack of appropriate tools for visualizing cell membrane molecules at the nanoscale in a non‐invasive and label‐free fashion limits our understanding of many vital cellular processes. Here, we use tip‐enhanced Raman spectroscopy (TERS) to visualize the molecular distribution in pancreatic cancer cell (BxPC‐3) membranes in ambient conditions without labelling, with a spatial resolution down to ca. 2.5 nm. TERS imaging reveals segregation of phenylalanine‐, histidine‐, phosphatidylcholine‐, protein‐, and cholesterol‐rich BxPC‐3 cell membrane domains at the nm length‐scale. TERS imaging also showed a cell membrane region where cholesterol is mixed with protein. Interestingly, the higher resolution TERS imaging revealed that the molecular domains observed on the BxPC‐3 cell membrane are not chemically “pure” but also contain other biomolecules. These results demonstrate the potential of TERS for non‐destructive and label‐free imaging of cell membranes with nanoscale resolution.

Nanoscale Chemical Imaging of Human Cell Membranes Using Tip-Enhanced Raman Spectroscopy.

Lack of appropriate tools for visualizing cell membrane molecules at the nanoscale in a non-invasive and label-free fashion limits our understanding of many vital cellular processes. Here, we use tip-enhanced Raman spectroscopy (TERS) to visualize the molecular distribution in pancreatic cancer cell (BxPC-3) membranes in ambient conditions without labelling, with a spatial resolution down to ca. 2.5 nm. TERS imaging reveals segregation of phenylalanine-, histidine-, phosphatidylcholine-, protein-, and cholesterol-rich BxPC-3 cell membrane domains at the nm length-scale. TERS imaging also showed a cell membrane region where cholesterol is mixed with protein. Interestingly, the higher resolution TERS imaging revealed that the molecular domains observed on the BxPC-3 cell membrane are not chemically "pure" but also contain other biomolecules. These results demonstrate the potential of TERS for non-destructive and label-free imaging of cell membranes with nanoscale resolution.

Monitoring cell membrane recycling dynamics of proteins using whole-cell fluorescence recovery after photobleaching of pH-sensitive genetic tags.

Population behavior of signaling molecules on the cell surface is key to their adaptive function. Live imaging of proteins tagged with fluorescent molecules has been an essential tool in understanding this behavior. Typically, genetic or chemical tags are used to target molecules present throughout the cell, whereas antibody-based tags label the externally exposed molecular domains only. Both approaches could potentially overlook the intricate process of in-out membrane recycling in which target molecules appear or disappear on the cell surface. This limitation is overcome by using a pH-sensitive fluorescent tag, such as Super-Ecliptic pHluorin (SEP), because its emission depends on whether it resides inside or outside the cell. Here we focus on the main glial glutamate transporter GLT1 and describe a genetic design that equips GLT1 molecules with SEP without interfering with the transporter's main function. Expressing GLT1-SEP in astroglia in cultures or in hippocampal slices enables monitoring of the real-time dynamics of the cell-surface and cytosolic fractions of the transporter in living cells. Whole-cell fluorescence recovery after photobleaching and quantitative image-kinetic analysis of the resulting time-lapse images enables assessment of the rate of GLT1-SEP recycling on the cell surface, a fundamental trafficking parameter unattainable previously. The present protocol takes 15-20 d to set up cell preparations, and 2-3 d to carry out live cell experiments and data analyses. The protocol can be adapted to study different membrane molecules of interest, particularly those proteins whose lifetime on the cell surface is critical to their adaptive function.

β-PIX cooperates with GIT1 to regulate endothelial nitric oxide synthase in sinusoidal endothelial cells.

Previous studies have demonstrated that G protein-coupled receptor kinase interacting-1 protein (GIT1) associates with endothelial nitric oxide synthase (eNOS) to regulate nitric oxide production in sinusoidal endothelial cells (SECs). Here, we hypothesized that GIT1's tightly associated binding partner, β-PIX (p21-activated kinase-interacting exchange factor β, ARHGEF7) is specifically important in the regulation of eNOS activity. We examined β-PIX expression in normal rat liver by immunohistochemistry and explored β-PIX protein-protein interactions using immunoprecipitation and immunoblotting. The role of β-PIX in regulating eNOS enzymatic activity was studied in GIT1-deficient SECs. Finally, structural analysis of interaction sites in GIT1 and β-PIX required to regulate eNOS activity were mapped. β-PIX was expressed primarily in SECs in normal liver and was either absent or expressed at extremely low levels in other liver cells (stellate cells, Kupffer cells, and hepatocytes). β-PIX interacted with GIT1 and eNOS to form a trimolecular signaling module in normal SECs and was important in stimulating eNOS activity. Of note, GIT1-β-PIX interaction led to synergistic enhancement of eNOS activity, and β-PIX-driven increase in eNOS activity was GIT1 dependent. Disruption of β-PIX or GIT1 in normal SECs using β-PIX siRNA or GIT1-deficient SECs led to reduced eNOS activity. Finally, specific GIT1 domains [Spa2 homology domain (SHD) and synaptic localization domain (SLD), aa 331-596] and the β-PIX COOH terminal (aa 496-555) appeared to be critical in the regulation eNOS activity. The data indicate that β-PIX regulates eNOS phosphorylation and function in normal SECs and highlight the importance of the GIT1/β-PIX/eNOS trimolecular complex in normal liver SEC function.NEW & NOTEWORTHY β-PIX is a multidomain protein known to be a GIT1 binding partner. We report here that in the normal liver, the distribution and cellular localization of β-PIX are restricted largely to sinusoidal endothelial cells. Furthermore, β-PIX interacts with eNOS and GIT1 promotes eNOS activity and NO production and therefore exerts a novel posttranslational regulatory function on eNOS activity in sinusoidal endothelial cells. We also have identified specific molecular domains important in GIT1 and β-PIX's interaction with eNOS, which may represent novel therapeutic targets in the control of sinusoidal blood flow and intrahepatic resistance.

Deep inside molecules — digital twins at the nanoscale

BackgroundDigital twins offer rich potential for exploration in virtual reality (VR). Using interactive molecular simulation approaches, they enable a human operator to access the physical properties of molecular objects and to build, manipulate, and study their assemblies. Integrative modeling and drug design are important applications of this technology. MethodsIn this study, head-mounted virtual reality displays connected to molecular simulation engines were used to create interactive and immersive digital twins. They were used to perform tasks relevant to specific use cases. ResultsThree areas were investigated, including model building, rational design, and tangible models. Here, we report several membrane-embedded systems of ion channels, viral components, and artificial water channels. We were able to improve and create molecular designs based on digital twins. ConclusionsThe molecular application domain offers great opportunities, and most of the technical and technological aspects have been solved. Wider adoption is expected once the onboarding of VR is simplified and the technology gains wider acceptance.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR.

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.