A Platform Approach to Cleavable Macrocycles for the Controlled Disassembly of Mechanically Caged Molecules

Inspired by interlocked oligonucleotides, peptides and knotted proteins, synthetic systems where a macrocycle cages a bioactive species that is "switched on" by breaking the mechanical bond have been reported. However, to date, each example uses a bespoke chemical design. Here we present a platform approach to mechanically caged structures wherein a single macrocycle precursor is diversified at a late stage to include a range of trigger units that control ring opening in response to enzymatic, chemical, or photochemical stimuli. We also demonstrate that our approach is applicable to other classes of macrocycles suitable for rotaxane and catenane formation.

Effect of Interlayer Bonding on Superlubric Sliding of Graphene Contacts: A Machine-Learning Potential Study

Surface defects and their mutual interactions are anticipated to affect the superlubric sliding of incommensurate layered material interfaces. Atomistic understanding of this phenomenon is limited due to the high computational cost of ab initio simulations and the absence of reliable classical force-fields for molecular dynamics simulations of defected systems. To address this, we present a machine-learning potential (MLP) for bilayer defected graphene, utilizing state-of-the-art graph neural networks trained against many-body dispersion corrected density functional theory calculations under iterative configuration space exploration. The developed MLP is utilized to study the impact of interlayer bonding on the friction of bilayer defected graphene interfaces. While a mild effect on the sliding dynamics of aligned graphene interfaces is observed, the friction coefficients of incommensurate graphene interfaces are found to significantly increase due to interlayer bonding, nearly pushing the system out of the superlubric regime. The methodology utilized herein is of general nature and can be adapted to describe other homogeneous and heterogeneous defected layered material interfaces.

Room Temperature Relaxometry of Single Nitrogen Vacancy Centers in Proximity to α-RuCl3 Nanoflakes

Nitrogen vacancy (NV) center-based magnetometry has been proven to be a versatile sensor for various classes of magnetic materials in broad temperature and frequency ranges. Here, we use the longitudinal relaxation time T1 of single NV centers to investigate the spin dynamics of nanometer-thin flakes of α-RuCl3 at room temperature. We observe a significant reduction in the T1 in the presence of α-RuCl3 in the proximity of NVs, which we attribute to paramagnetic spin noise confined in the 2D hexagonal planes. Furthermore, the T1 time exhibits a monotonic increase with an applied magnetic field. We associate this trend with the alteration of the spin and charge noise in α-RuCl3 under an external magnetic field. These findings suggest that the influence of the spin dynamics of α-RuCl3 on the T1 of the NV center can be used to gain information about the material itself and the technique to be used on other 2D materials.

Facial Selectivity in Mechanical Bond Formation: Axially Chiral Enantiomers and Geometric Isomers from a Simple Prochiral Macrocycle

In 1971, Schill recognized that a prochiral macrocycle encircling an oriented axle led to geometric isomerism in rotaxanes. More recently, we identified an overlooked chiral stereogenic unit in rotaxanes that arises when a prochiral macrocycle encircles a prochiral axle. Here, we show that both stereogenic units can be accessed using equivalent strategies, with a single weak stereodifferentiating interaction sufficient for moderate to excellent stereoselectivity. Using this understanding, we demonstrated the first direct enantioselective (70% ee) synthesis of a mechanically axially chiral rotaxane.

The Final Stereogenic Unit of [2]Rotaxanes: Type 2 Geometric Isomers

Mechanical stereochemistry arises when the interlocking of stereochemically trivial covalent subcomponents results in a stereochemically complex object. Although this general concept was identified in 1961, the stereochemical description of these molecules is still under development to the extent that new forms of mechanical stereochemistry are still being identified. Here, we present a simple analysis of rotaxane and catenane stereochemistry that allowed us to identify the final missing simple mechanical stereogenic unit, an overlooked form of rotaxane geometric isomerism, and demonstrate its stereoselective synthesis.

Study of PEG-b-PLA/Eudragit S100 Blends on the Nanoencapsulation of Indigo Carmine Dye and Application in Controlled Release

A nanocapsule shell of poly(ethylene glycol)-block-poly(d,l-lactic acid) (PEG-b-PLA) mixed with anionic Eudragit S100 (90/10% w/w) was previously used to entrap and define the self-assembly of indigo carmine (IC) within the hydrophilic cavity core. In the present work, binary blends were prepared by solution mixing at different PEG-b-PLA/Eudragit S100 ratios (namely, 100/0, 90/10, 75/25, and 50/50% w/w) to elucidate the role of the capsule shell in tuning the encapsulation of the anionic dye (i.e., IC). The results showed that the higher content of Eudragit S100 in the blend decreases the miscibility of the two polymers due to weak intermolecular interactions between PEG-b-PLA and Eudragit S100. Moreover, with an increase in the amount of Eudragit S100, a higher thermal stability was observed related to the mobility restriction of PEG-b-PLA chains imposed by Eudragit S100. Formulations containing 10 and 25% Eudragit S100 exhibited an optimal interplay of properties between the negative surface charge and the miscibility of the polymer blend. Therefore, the anionic character of the encapsulating agent provides sufficient accumulation of IC molecules in the nanocapsule core, leading to dye aggregates following the self-assembly. At the same time, the blending of the two polymers tunes the IC release properties in the initial stage, achieving slow and controlled release. These findings give important insights into the rational design of polymeric nanosystems containing organic dyes for biomedical applications.

Neuroanatomy in virtual reality: Development and pedagogical evaluation of photogrammetry-based 3D brain models

Anatomy studies are an essential part of medical training. The study of neuroanatomy in particular presents students with a unique challenge of three-dimensional spatial understanding. Virtual Reality (VR) has been suggested to address this challenge, yet the majority of previous reports have implemented computer-generated or imaging-based models rather than models of real brain specimens. Using photogrammetry of real human bodies and advanced editing software, we developed 3D models of a real human brain at different stages of dissection. Models were placed in a custom-built virtual laboratory, where students can walk around freely, explore, and manipulate (i.e., lift the models, rotate them for different viewpoints, etc.). Sixty participants were randomly assigned to one of three learning groups: VR, 3D printed models or read-only, and given 1 h to study the white matter tracts of the cerebrum, followed by theoretical and practical exams and a learning experience questionnaire. We show that following self-guided learning in virtual reality, students demonstrate a gain in spatial understanding and an increased satisfaction with the learning experience, compared with traditional learning approaches. We conclude that the models and virtual lab described in this work may enhance learning experience and improve learning outcomes.

Parafoveal vision reveals qualitative differences between fusiform face area and parahippocampal place area

The center-periphery visual field axis guides early visual system organization with enhanced resources devoted to central vision leading to reduced peripheral performance relative to that of central vision (i.e., behavioral eccentricity effect) for many visual functions. The center-periphery organization extends to high-order visual cortex where, for example, the well-studied face-sensitive fusiform face area (FFA) shows sensitivity to central vision and the place-sensitive parahippocampal place area (PPA) shows sensitivity to peripheral vision. As we have recently found that face perception is more sensitive to eccentricity than place perception, here we examined whether these behavioral findings reflect differences in FFA's and PPA's sensitivities to eccentricity. We assumed FFA would show higher sensitivity to eccentricity than PPA would, but that both regions' modulation by eccentricity would be invariant to the viewed category. We parametrically investigated (fMRI, n = 32) how FFA's and PPA's activations are modulated by eccentricity (≤8°) and category (upright/inverted faces/houses) while keeping stimulus size constant. As expected, FFA showed an overall higher sensitivity to eccentricity than PPA. However, both regions' activation modulations by eccentricity were dependent on the viewed category. In FFA, a reduction of activation with growing eccentricity ("BOLD eccentricity effect") was found (with different amplitudes) for all categories. In PPA however, qualitatively different BOLD eccentricity effect modulations were found (e.g., at 8° mild BOLD eccentricity effect for houses but a reverse BOLD eccentricity effect for faces and no modulation for inverted faces). Our results emphasize that peripheral vision investigations are critical to further our understanding of visual processing.

Urban Air-Quality Estimation Using Visual Cues and a Deep Convolutional Neural Network in Bengaluru (Bangalore), India

Mobile monitoring provides robust measurements of air pollution. However, resource constraints often limit the number of measurements so that assessments cannot be obtained in all locations of interest. In response, surrogate measurement methodologies, such as videos and images, have been suggested. Previous studies of air pollution and images have used static images (e.g., satellite images or Google Street View images). The current study was designed to develop deep learning methodologies to infer on-road pollutant concentrations from videos acquired with dashboard cameras. Fifty hours of on-road measurements of four pollutants (black carbon, particle number concentration, PM2.5 mass concentration, carbon dioxide) in Bengaluru, India, were analyzed. The analysis of each video frame involved identifying objects and determining motion (by segmentation and optical flow). Based on these visual cues, a regression convolutional neural network (CNN) was used to deduce pollution concentrations. The findings showed that the CNN approach outperformed several other machine learning (ML) techniques and more conventional analyses (e.g., linear regression). The CO2 prediction model achieved a normalized root-mean-square error of 10-13.7% for the different train-validation division methods. The results here thus contribute to the literature by using video and the relative motion of on-screen objects rather than static images and by implementing a rapid-analysis approach enabling analysis of the video in real time. These methods can be applied to other mobile-monitoring campaigns since the only additional equipment they require is an inexpensive dashboard camera.

Bactericidal and non-cytotoxic activity of bacteriocin produced by Lacticaseibacillus paracasei F9-02 and evaluation of its tolerance to various physico-chemical conditions

This study aims to explore novel lactic acid bacteria (LAB) from breast-fed infants' faeces towards characterizing their antimicrobial compound, bacteriocin. The LAB, Lacticaseibacillus paracasei F9-02 showed strong antimicrobial activity against clinical pathogens. Their proteinaceous nature was confirmed as the activity was completely abolished when treated with proteinaceous enzymes and retained during neutral pH and catalase treatment. The purified bacteriocin showed antimicrobial activity at the minimum inhibitory concentration (MIC) value of 7.56 μg/ml against vancomycin-resistant Enterococcus sp. [vancomycin-resistant enterococcal (VRE)], and methicillin-resistant Staphylococcus aureus (MRSA), 15.13 μg/ml against Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella enterica subsp. enterica serotype typhi and 30.25 μg/ml against Shigella flexneri. Present study also proved the bactericidal, non-cytotoxic and non-hemolytic nature of bacteriocin. Additionally, bacteriocin retained their stability under various physico-chemical conditions, broad range of pH (2-10), temperature (40-121°C), enzymes (amylase, lipase and lysozyme), surfactants [Tween-20, 80, 100 and sodium dodecyl sulfate (SDS)], metal ions (CaCl2 , FeSO4 , ZnSO4 , MgSO4 , MnSO4 , CuCl2 ) and NaCl (2%-8%). The molecular weight of bacteriocin (~28 kDa) was determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), functional and active groups were assessed by Fourier Transform-Infrared (FT-IR). To our knowledge, this is the first study reporting L. paracasei from breast-fed infants' faeces and assessing their antimicrobial compound, bacteriocin. The study results furnish the essential features to confirm the therapeutic potential of L. paracasei F9-02 bacteriocin.

The interplay between autophagy and chloroplast vesiculation pathways under dark-induced senescence

In cellular circumstances where carbohydrates are scarce, plants can use alternative substrates for cellular energetic maintenance. In plants, the main protein reserve is present in the chloroplast, which contains most of the total leaf proteins and represents a rich source of nitrogen and amino acids. Autophagy plays a key role in chloroplast breakdown, a well-recognised symptom of both natural and stress-induced plant senescence. Remarkably, an autophagic-independent route of chloroplast degradation associated with chloroplast vesiculation (CV) gene was previously demonstrated. During extended darkness, CV is highly induced in the absence of autophagy, contributing to the early senescence phenotype of atg mutants. To further investigate the role of CV under dark-induced senescence conditions, mutants with low expression of CV (amircv) and double mutants amircv1xatg5 were characterised. Following darkness treatment, no aberrant phenotypes were observed in amircv single mutants; however, amircv1xatg5 double mutants displayed early senescence and altered dismantling of chloroplast and membrane structures under these conditions. Metabolic characterisation revealed that the functional lack of both CV and autophagy leads to higher impairment of amino acid release and differential organic acid accumulation during starvation conditions. The data obtained are discussed in the context of the role of CV and autophagy, both in terms of cellular metabolism and the regulation of chloroplast degradation.

Delocalization quantitatively mapped for prototypic organic nitroanions as well as azidoform anions

Delocalization of occupied orbitals impacts the chemical bonding in the simplest known pernitroanions [(NO2)3C]- (1) and [(NO2)2N]- (2) as well as other functionalized organic anions. By quantitatively mapping it onto molecular backbones of 1, 2, [CH2NO2]- (3), [CH3NNO2]- (4) and [C(N3)]- (6) anions (all modeled by QM calculations), the Weinhold's NBO analysis refines their chemical structure, enabling to explain and even predict their essential chemical behaviour. In detail, the HOMO of 1 and 2 is associated with the central atom to the degree of 70.7% and 80.4%, respectively, while the HOMO localization on O atoms for 3 and 4 is 85.3% and 81.1%, respectively. Predomination of C-alkylation for 1 and that of O-alkylation for 3 in non-coordinating solvents thus becomes clear. The important news is that the easiness of homolytically disrupting the N-N bond in 2, a constituent of inexpensive powerful explosives, is because of the occupancy of the related σ*orbital increases with stretching this bond. The same is true for electrocyclic extrusion of NO3- from this molecule. This antibonding effect may be assumed to be the common cause of the proneness of aliphatic nitro compounds to decompose. Pyramidal anion 6 is a highly localized carbanion. Its isomer of molecular symmetry CS has a unique chemical structure of its azido substituents: each of them is represented by one high-weight resonance structure, e.g., N-N[triple bond, length as m-dash]N. The prediction is that the dinitrogen-eliminating decomposition of this isomer is more facile than of the isomer of C3 symmetry. In summary, this study affords three novel particular insights into the chemical structure and reactivity of these anions: chemically telling delocalization-augmented molecular structures, a reasonable hypothesis of the common cause of thermally triggered instability of aliphatic nitro compounds, and discovered one-resonance structure azido groups.

Adjustable Fluorescence Emission of J-Aggregated Tricarbocyanine in the Near-Infrared-II Region

Near-infrared (NIR) J-aggregates attract increasing attention in many areas, especially in biomedical applications, as they combine the advantages of NIR spectroscopy with the unique J-aggregation properties of organic dyes. They enhance light absorption and have been used as effective biological imaging and therapeutic agents to achieve high-resolution imaging or effective phototherapy in vivo. In this work, we present novel J-aggregates composed of the well-known cyanine molecules. Cyanines are one of the few types of molecules whose absorption and emission can be shifted over a broad spectral range, from the ultraviolet (UV) to the NIR regime. They can easily transform into J-aggregates with narrow absorption and emission peaks, which is accompanied by a red shift in their spectra. In this work, we show, for the first time, that the tricarbocyanine dye (IR 820) has two sharp fluorescence emission bands in the NIR-II region with high photostability. These emission bands can be tuned to a desired wavelength in the range of 1150-1560 and 1675 nm, with a linear dependence on the excitation wavelength. Cryogenic transmission electron microscopy (cryo-TEM) images are presented, and combined with molecular modeling analysis, they confirm IR 820 π-stacked self-assembled fibrous structures.

Electrocatalytic Reduction of Dinitrogen to Ammonia with Water as Proton and Electron Donor Catalyzed by a Combination of a Tri-ironoxotungstate and an Alkali Metal Cation

The electrification of ammonia synthesis is a key target for its decentralization and lowering impact on atmospheric CO2 concentrations. The lithium metal electrochemical reduction of nitrogen to ammonia using alcohols as proton/electron donors is an important advance, but requires rather negative potentials, and anhydrous conditions. Organometallic electrocatalysts using redox mediators have also been reported. Water as a proton and electron donor has not been demonstrated in these reactions. Here a N2 to NH3 electrocatalytic reduction using an inorganic molecular catalyst, a tri-iron substituted polyoxotungstate, {SiFe3W9}, is presented. The catalyst requires the presence of Li+ or Na+ cations as promoters through their binding to {SiFe3W9}. Experimental NMR, CV and UV-vis measurements, and MD simulations and DFT calculations show that the alkali metal cation enables the decrease of the redox potential of {SiFe3W9} allowing the activation of N2. Controlled potential electrolysis with highly purified 14N2 and 15N2 ruled out formation of NH3 from contaminants. Importantly, using Na+ cations and polyethylene glycol as solvent, the anodic oxidation of water can be used as a proton and electron donor for the formation of NH3. In an undivided cell electrolyzer under 1 bar N2, rates of NH3 formation of 1.15 nmol sec-1 cm-2, faradaic efficiencies of ∼25%, 5.1 equiv of NH3 per equivalent of {SiFe3W9} in 10 h, and a TOF of 64 s-1 were obtained. The future development of suitable high surface area cathodes and well solubilized N2 and the use of H2O as the reducing agent are important keys to the future deployment of an electrocatalytic ammonia synthesis.

Enabling Peptide Ligation at Aromatic Junction Mimics via Native Chemical Ligation and Palladium-Mediated S-Arylation

Synthetic strategies to assemble peptide fragments are in high demand to access homogeneous proteins for various applications. Here, we combined native chemical ligation (NCL) and Pd-mediated Cys arylation to enable practical peptide ligation at aromatic junctions. The utility of one-pot NCL and S-arylation at the Phe and Tyr junctions was demonstrated and employed for the rapid chemical synthesis of the DNA-binding domains of the transcription factors Myc and Max. Organometallic palladium reagents coupled with NCL enabled a practical strategy to assemble peptides at aromatic junctions.

On-Demand, Reversible, Ultrasensitive Polymer Membrane Based on Molecular Imprinting Polymer

The development of in vivo, longitudinal, real-time monitoring devices is an essential step toward continuous, precision health monitoring. Molecularly imprinted polymers (MIPs) are popular sensor capture agents that are more robust than antibodies and have been used for sensors, drug delivery, affinity separations, assays, and solid-phase extraction. However, MIP sensors are typically limited to one-time use due to their high binding affinity (>10⁷ M^-1) and slow-release kinetics (<10^-4 μM/sec). To overcome this challenge, current research has focused on stimuli-responsive MIPs (SR-MIPs), which undergo a conformational change induced by external stimuli to reverse molecular binding, requiring additional chemicals or outside stimuli. Here, we demonstrate fully reversible MIP sensors based on electrostatic repulsion. Once the target analyte is bound within a thin film MIP on an electrode, a small electrical potential successfully releases the bound molecules, enabling repeated, accurate measurements. We demonstrate an electrostatically refreshed dopamine sensor with a 760 pM limit of detection, linear response profile, and accuracy even after 30 sensing-release cycles. These sensors could repeatedly detect <1 nM dopamine released from PC-12 cells in vitro, demonstrating they can longitudinally measure low concentrations in complex biological environments without clogging. Our work provides a simple and effective strategy for enhancing the use of MIPs-based biosensors for all charged molecules in continuous, real-time health monitoring and other sensing applications.

Actin-capping protein regulates actomyosin contractility to maintain germline architecture in C. elegans

Actin dynamics play an important role in tissue morphogenesis, yet the control of actin filament growth takes place at the molecular level. A challenge in the field is to link the molecular function of actin regulators with their physiological function. Here, we report an in vivo role of the actin-capping protein CAP-1 in the Caenorhabditis elegans germline. We show that CAP-1 is associated with actomyosin structures in the cortex and rachis, and its depletion or overexpression led to severe structural defects in the syncytial germline and oocytes. A 60% reduction in the level of CAP-1 caused a twofold increase in F-actin and non-muscle myosin II activity, and laser incision experiments revealed an increase in rachis contractility. Cytosim simulations pointed to increased myosin as the main driver of increased contractility following loss of actin-capping protein. Double depletion of CAP-1 and myosin or Rho kinase demonstrated that the rachis architecture defects associated with CAP-1 depletion require contractility of the rachis actomyosin corset. Thus, we uncovered a physiological role for actin-capping protein in regulating actomyosin contractility to maintain reproductive tissue architecture.

G4mismatch: Deep neural networks to predict G-quadruplex propensity based on G4-seq data

G-quadruplexes are non-B-DNA structures that form in the genome facilitated by Hoogsteen bonds between guanines in single or multiple strands of DNA. The functions of G-quadruplexes are linked to various molecular and disease phenotypes, and thus researchers are interested in measuring G-quadruplex formation genome-wide. Experimentally measuring G-quadruplexes is a long and laborious process. Computational prediction of G-quadruplex propensity from a given DNA sequence is thus a long-standing challenge. Unfortunately, despite the availability of high-throughput datasets measuring G-quadruplex propensity in the form of mismatch scores, extant methods to predict G-quadruplex formation either rely on small datasets or are based on domain-knowledge rules. We developed G4mismatch, a novel algorithm to accurately and efficiently predict G-quadruplex propensity for any genomic sequence. G4mismatch is based on a convolutional neural network trained on almost 400 millions human genomic loci measured in a single G4-seq experiment. When tested on sequences from a held-out chromosome, G4mismatch, the first method to predict mismatch scores genome-wide, achieved a Pearson correlation of over 0.8. When benchmarked on independent datasets derived from various animal species, G4mismatch trained on human data predicted G-quadruplex propensity genome-wide with high accuracy (Pearson correlations greater than 0.7). Moreover, when tested in detecting G-quadruplexes genome-wide using the predicted mismatch scores, G4mismatch achieved superior performance compared to extant methods. Last, we demonstrate the ability to deduce the mechanism behind G-quadruplex formation by unique visualization of the principles learned by the model.

Charge Dynamics Electron Microscopy: Nanoscale Imaging of Femtosecond Plasma Dynamics

Understanding and actively controlling the spatiotemporal dynamics of nonequilibrium electron clouds is fundamental for the design of light and electron sources, high-power electronic devices, and plasma-based applications. However, electron clouds evolve in a complex collective fashion on the nanometer and femtosecond scales, producing electromagnetic screening that renders them inaccessible to existing optical probes. Here, we solve the long-standing challenge of characterizing the evolution of electron clouds generated upon irradiation of metallic structures using an ultrafast transmission electron microscope to record the charged plasma dynamics. Our approach to charge dynamics electron microscopy (CDEM) is based on the simultaneous detection of electron-beam acceleration and broadening with nanometer/femtosecond resolution. By combining experimental results with comprehensive microscopic theory, we provide a deep understanding of this highly out-of-equilibrium regime, including previously inaccessible intricate microscopic mechanisms of electron emission, screening by the metal, and collective cloud dynamics. Beyond the present specific demonstration, the here-introduced CDEM technique grants us access to a wide range of nonequilibrium electrodynamic phenomena involving the ultrafast evolution of bound and free charges on the nanoscale.

DC Signature of Snap-through Bistability in Carbon Nanotube Mechanical Resonators

Bistable arched beams exhibiting Euler-Bernoulli snap-through buckling are widely investigated as promising candidates for various potential applications, such as memory devices, energy harvesters, sensors, and actuators. Recently, we reported the realization of a buckled suspended carbon nanotube (CNT) based bistable resonator, which exhibits a unique three-dimensional snap-through transition and an extremely large change in frequency as a result. In this article, we address a unique characteristic of these devices in which a significant change in the DC conductance is also observed at the mechanical snap-through transition. Through the analysis of this phenomenon, we arrive at several important conclusions: we find that the common approach to determining CNT vibrational resonance amplitude is inaccurate; we find evidence that latching phenomena should be easily realizable, relevant for RF switches and nonvolatile memory devices. Finally, we present evidence for possible inner shell sliding, which is relevant for understanding interlayer coupling and moiré pattern research.

Structural Insights into Cellulose-Coated Oil in Water Emulsions

Cellulose is a renewable biopolymer, abundant on Earth, with a multi-level supramolecular structure. There has been significant interest and advancement in utilizing natural cellulose to stabilize emulsions. In our research, we develop and examine oil in water emulsions surrounded by unmodified cellulose as microreactors for the process of transformation of cellulose into valuable chemicals such as biodiesel. This study presents morphological characterization of cellulose-coated emulsions that can be used for such purposes. Cryogenic-scanning electron microscopy imaging along with light microscopy and light scattering reveals a multi-layer inner structure: an oil core surrounded by a porous cellulose hydrogel shell, coated by an outer shell of regenerated cellulose. Measurements of small-angle X-ray scattering provide quantification of the nano-scale structure within the porous cellulose hydrogel inner shell of the emulsion particle. These characteristics are relevant to utilization of cellulose-coated emulsions in various applications such as controlled release and as hosts for enzymatic biotechnological reactions.

Acetic Acid Enables Precise Tailoring of the Mechanical Behavior of Protein-Based Hydrogels

Engineering viscoelastic and biocompatible materials with tailored mechanical and microstructure properties capable of mimicking the biological stiffness (<17 kPa) or serving as bioimplants will bring protein-based hydrogels to the forefront in the biomaterials field. Here, we introduce a method that uses different concentrations of acetic acid (AA) to control the covalent tyrosine-tyrosine cross-linking interactions at the nanoscale level during protein-based hydrogel synthesis and manipulates their mechanical and microstructure properties without affecting protein concentration and (un)folding nanomechanics. We demonstrated this approach by adding AA as a precursor to the preparation buffer of a photoactivated protein-based hydrogel mixture. This strategy allowed us to synthesize hydrogels made from bovine serum albumin (BSA) and eight repeats protein L structure, with a fine-tailored wide range of stiffness (2-35 kPa). Together with protein engineering technologies, this method will open new routes in developing and investigating tunable protein-based hydrogels and extend their application toward new horizons.

Design and Use of a Gold Nanoparticle-Carbon Dot Hybrid for a FLIM-Based IMPLICATION Nano Logic Gate

The interest in nanomaterials resides in the fact that they can be used to create smaller, faster, and more portable systems. Nanotechnology is already transforming health care. Nanoparticles are being used by scientists to target malignancies, improve drug delivery systems, and improve medical imaging. Integration of biomolecular logic gates with nanostructures has opened new paths in illness detection and therapy that need precise control of complicated components. Most studies have used fluorescence intensity techniques to implement the logic function. Its drawbacks, mainly when working with nanoparticles in intracellular media, include fluctuations in excitation power, fluorophore concentration dependence, and interference from cell autofluorescence. We suggest using fluorescence lifetime imaging microscopy (FLIM) in order to circumvent these constraints. Designing a nanohybrid composed of gold nanoparticles (AuNPs) and red-emitting carbon dots (CDs) can be used to develop a FLIM-based logic gate that can respond to multiple input parameters. Our findings indicate a nanohybrid that can serve as a nano-computer to receive and integrate chemical and biochemical stimuli and produce a definitive output measured by FLIM. This can open a new research avenue for enhanced diagnostics and therapy that require complicated factor handling and precise control. The AuNPs are conjugated to CDs' surfaces through a strong covalent linkage. The AuNP-CD nanohybrid shows fluorescence lifetime (FLT) quenching of pristine CDs after conjugation to AuNPs. The FLT was reduced from 3.61 ± 0.037 to 2.48 ± 0.040 ns. This quenched FLT can be recovered back by using trypsin as a recovering agent, giving us a reversible logic output. The FLT was recovered to 3.01 ± 0.01 ns after trypsin addition. This "on-off-on" response can be used to construct the IMPLICATION logic gate.

Ion Pathways in Biomineralization: Perspectives on Uptake, Transport, and Deposition of Calcium, Carbonate, and Phosphate

Minerals are formed by organisms in all of the kingdoms of life. Mineral formation pathways all involve uptake of ions from the environment, transport of ions by cells, sometimes temporary storage, and ultimately deposition in or outside of the cells. Even though the details of how all this is achieved vary enormously, all pathways need to respect both the chemical limitations of ion manipulation, as well as the many "housekeeping" roles of ions in cell functioning. Here we provide a chemical perspective on the biological pathways of biomineralization. Our approach is to compare and contrast the ion pathways involving calcium, phosphate, and carbonate in three very different organisms: the enormously abundant unicellular marine coccolithophores, the well investigated sea urchin larval model for single crystal formation, and the complex pathways used by vertebrates to form their bones. The comparison highlights both common and unique processes. Significantly, phosphate is involved in regulating calcium carbonate deposition and carbonate is involved in regulating calcium phosphate deposition. One often overlooked commonality is that, from uptake to deposition, the solutions involved are usually supersaturated. This therefore requires not only avoiding mineral deposition where it is not needed but also exploiting this saturated state to produce unstable mineral precursors that can be conveniently stored, redissolved, and manipulated into diverse shapes and upon deposition transformed into more ordered and hence often functional final deposits.

Extensive Redox Non-Innocence in Iron Bipyridine-Diimine Complexes: a Combined Spectroscopic and Computational Study

Metal-ligand cooperation is an important aspect in earth-abundant metal catalysis. Utilizing ligands as electron reservoirs to supplement the redox chemistry of the metal has resulted in many new exciting discoveries. Here, we demonstrate that iron bipyridine-diimine (BDI) complexes exhibit an extensive electron-transfer series that spans a total of five oxidation states, ranging from the trication [Fe(BDI)]3+ to the monoanion [Fe(BDI]-1. Structural characterization by X-ray crystallography revealed the multifaceted redox noninnocence of the BDI ligand, while spectroscopic (e.g., 57Fe Mössbauer and EPR spectroscopy) and computational studies were employed to elucidate the electronic structure of the isolated complexes, which are further discussed in this report.

Bifunctional Oxygen Electrocatalysis on Mixed Metal Phthalocyanine-Modified Carbon Nanotubes Prepared via Pyrolysis

Non-precious-metal catalysts are promising alternatives for Pt-based cathode materials in low-temperature fuel cells, which is of great environmental importance. Here, we have investigated the bifunctional electrocatalytic activity toward the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) of mixed metal (FeNi; FeMn; FeCo) phthalocyanine-modified multiwalled carbon nanotubes (MWCNTs) prepared by a simple pyrolysis method. Among the bimetallic catalysts containing nitrogen derived from corresponding metal phthalocyanines, we report the excellent ORR activity of FeCoN-MWCNT and FeMnN-MWCNT catalysts with the ORR onset potential of 0.93 V and FeNiN-MWCNT catalyst for the OER having EOER = 1.58 V at 10 mA cm-2. The surface morphology, structure, and elemental composition of the prepared catalysts were examined with scanning electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The FeCoN-MWCNT and FeMnN-MWCNT catalysts were prepared as cathodes and tested in anion-exchange membrane fuel cells (AEMFCs). Both catalysts displayed remarkable AEMFC performance with a peak power density as high as 692 mW cm-2 for FeCoN-MWCNT.

Computational analysis of sense-antisense chimeric transcripts reveals their potential regulatory features and the landscape of expression in human cells

Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA-RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

Thin Layer Buckling in Perovskite CsPbBr3 Nanobelts

Flexible semiconductor materials, where structural fluctuations and transformation are tolerable and have low impact on electronic properties, focus interest for future applications. Two-dimensional thin layer lead halide perovskites are hailed for their unconventional optoelectronic features. We report structural deformations via thin layer buckling in colloidal CsPbBr₃ nanobelts adsorbed on carbon substrates. The microstructure of buckled nanobelts is determined using transmission electron microscopy and atomic force microscopy. We measured significant decrease in emission from the buckled nanobelt using cathodoluminescence, marking the influence of such mechanical deformations on electronic properties. By employing plate buckling theory, we approximate adhesion forces between the buckled nanobelt and the substrate to be F_adhesion ∼ 0.12 μN, marking a limit to sustain such deformation. This work highlights detrimental effects of mechanical buckling on electronic properties in halide perovskite nanostructures and points toward the capillary action that should be minimized in fabrication of future devices and heterostructures based on nanoperovskites.

Effect of the Synthetic Method on the Properties of Ni-Based Hydrogen Oxidation Catalysts

The latest progress in alkaline anion-exchange membranes has led to the expectation that less costly catalysts than those of the platinum-group metals may be used in anion-exchange membrane fuel cell devices. In this work, we compare structural properties and the catalytic activity for the hydrogen-oxidation reaction (HOR) for carbon-supported nanoparticles of Ni, Ni₃Co, Ni₃Cu, and Ni₃Fe, synthesized by chemical and solvothermal reduction of metal precursors. The catalysts are well dispersed on the carbon support, with particle diameter in the order of 10 nm, and covered by a layer of oxides and hydroxides. The activity for the HOR was assessed by voltammetry in hydrogen-saturated aqueous solutions of 0.1 mol dm^-1 KOH. A substantial activation by potential cycling of the pristine catalysts synthesized by solvothermal reduction is necessary before these become active for the HOR; in situ Raman spectroscopy shows that after activation the surface of the Ni/C, Ni₃Fe, and Ni₃Co catalysts is fully reduced at 0 V, whereas the surface of the Ni₃Cu catalyst is not. The activation procedure had a smaller but negative impact on the catalysts synthesized by chemical reduction. After activation, the exchange-current densities normalized with respect to the ECSA (electrochemically active surface area) were approximately independent of composition but relatively high compared to catalysts of larger particle diameter.

Autophagy is required for lipid homeostasis during dark-induced senescence

Autophagy is an evolutionarily conserved mechanism that mediates the degradation of cytoplasmic components in eukaryotic cells. In plants, autophagy has been extensively associated with the recycling of proteins during carbon-starvation conditions. Even though lipids constitute a significant energy reserve, our understanding of the function of autophagy in the management of cell lipid reserves and components remains fragmented. To further investigate the significance of autophagy in lipid metabolism, we performed an extensive lipidomic characterization of Arabidopsis (Arabidopsis thaliana) autophagy mutants (atg) subjected to dark-induced senescence conditions. Our results revealed an altered lipid profile in atg mutants, suggesting that autophagy affects the homeostasis of multiple lipid components under dark-induced senescence. The acute degradation of chloroplast lipids coupled with the differential accumulation of triacylglycerols (TAGs) and plastoglobuli indicates an alternative metabolic reprogramming toward lipid storage in atg mutants. The imbalance of lipid metabolism compromises the production of cytosolic lipid droplets and the regulation of peroxisomal lipid oxidation pathways in atg mutants.

Data science in cell imaging

Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Computation, traditionally used to quantitatively test specific hypotheses, must now also enable iterative hypothesis generation and testing by deciphering hidden biologically meaningful patterns in complex, dynamic or high-dimensional cell image data. Data science is uniquely positioned to aid in this process. In this Perspective, we survey the rapidly expanding new field of data science in cell imaging. Specifically, we highlight how data science tools are used within current image analysis pipelines, propose a computation-first approach to derive new hypotheses from cell image data, identify challenges and describe the next frontiers where we believe data science will make an impact. We also outline steps to ensure broad access to these powerful tools - democratizing infrastructure availability, developing sensitive, robust and usable tools, and promoting interdisciplinary training to both familiarize biologists with data science and expose data scientists to cell imaging.

Transition-Metal- and Nitrogen-Doped Carbide-Derived Carbon/Carbon Nanotube Composites as Cathode Catalysts for Anion-Exchange Membrane Fuel Cells

Transition-metal- and nitrogen-codoped carbide-derived carbon/carbon nanotube composites (M-N-CDC/CNT) have been prepared, characterized, and used as cathode catalysts in anion-exchange membrane fuel cells (AEMFCs). As transition metals, cobalt, iron, and a combination of both have been investigated. Metal and nitrogen are doped through a simple high-temperature pyrolysis technique with 1,10-phenanthroline as the N precursor. The physicochemical characterization shows the success of metal and nitrogen doping as well as very similar morphologies and textural properties of all three composite materials. The initial assessment of the oxygen reduction reaction (ORR) activity, employing the rotating ring-disk electrode method, indicates that the M-N-CDC/CNT catalysts exhibit a very good electrocatalytic performance in alkaline media. We find that the formation of HO2 - species in the ORR catalysts depends on the specific metal composition (Co, Fe, or CoFe). All three materials show excellent stability with a negligible decline in their performance after 10000 consecutive potential cycles. The very good performance of the M-N-CDC/CNT catalyst materials is attributed to the presence of M-N x and pyridinic-N moieties as well as both micro- and mesoporous structures. Finally, the catalysts exhibit excellent performance in in situ tests in H2/O2 AEMFCs, with the CoFe-N-CDC/CNT reaching a current density close to 500 mA cm-2 at 0.75 V and a peak power density (P max) exceeding 1 W cm-2. Additional tests show that P max reaches 0.8 W cm-2 in an H2/CO2-free air system and that the CoFe-N-CDC/CNT material exhibits good stability under both AEMFC operating conditions.

The roles of online and offline replay in planning

Animals and humans replay neural patterns encoding trajectories through their environment, both whilst they solve decision-making tasks and during rest. Both on-task and off-task replay are believed to contribute to flexible decision making, though how their relative contributions differ remains unclear. We investigated this question by using magnetoencephalography (MEG) to study human subjects while they performed a decision-making task that was designed to reveal the decision algorithms employed. We characterised subjects in terms of how flexibly each adjusted their choices to changes in temporal, spatial and reward structure. The more flexible a subject, the more they replayed trajectories during task performance, and this replay was coupled with re-planning of the encoded trajectories. The less flexible a subject, the more they replayed previously preferred trajectories during rest periods between task epochs. The data suggest that online and offline replay both participate in planning but support distinct decision strategies.

Prevalence and determinants of serological evidence of atrophic gastritis among Arab and Jewish residents of Jerusalem: a cross-sectional study

OBJECTIVE

Understanding the correlates of premalignant gastric lesions is essential for gastric cancer prevention. We examined the prevalence and correlates of serological evidence of atrophic gastritis, a premalignant gastric condition, using serum pepsinogens (PGs) in two populations with differing trends in gastric cancer incidence.

METHODS

In a cross-sectional study, using ELISA we measured serum PGI and PGII concentrations (Biohit, Finland), Helicobacter pylori serum IgG and cytotoxin-associated gene A (CagA) antigen IgG antibodies in archived sera of 692 Jews and 952 Arabs aged 25-78 years, randomly selected from Israel's population registry in age-sex and population strata. Multivariable logistic regression analyses were performed.

RESULTS

Using cut-offs of PGI <30µg/L  or PGI:PGII <3.0, the prevalence of atrophic gastritis was higher among Arab than Jewish participants: 8.8% (95% CIs 7.2% to 10.8%) vs 5.9% (95% CI 4.4% to 7.9%), increasing with age in both groups (p<0.001 for trend). Among Jewish participants, infection with H. pylori CagA phenotype was positively related to atrophic gastritis: adjusted OR (aOR) 2.16 (95% CI 0.94 to 4.97), but not to non-CagA infections aOR 1.17 (95% CI 0.53 to 2.55). The opposite was found among Arabs: aOR 0.09 (95% CI 0.03 to 0.24) for CagA positive and aOR 0.15 (95% CI 0.06 to 0.41) for Cag A negative phenotypes (p<0.001 for interaction). Women had a higher atrophic gastritis prevalence than men. Obesity and smoking were not significantly related to atrophic gastritis; physical activity tended to be inversely associated in Arabs (p=0.08 for interaction).

CONCLUSIONS

The prevalence of atrophic gastritis was higher among Arabs than Jews and was differently associated with the CagA phenotype.

Associations of Helicobacter pylori infection and peptic disease with diabetic mellitus: Results from a large population-based study

BACKGROUND

Evidence is conflicting regarding the association between Helicobacter pylori infection and diabetes mellitus. The study objective was to examine associations of H. pylori infection, gastric ulcers and duodenal ulcers, with diabetes mellitus.

METHODS

This cross-sectional study was undertaken using coded data from the computerized database of Maccabi Health Services in Israel, on 147,936 individuals aged 25-95 years who underwent the urea breath test during 2002-2012. Multiple logistic regression models were conducted, while adjusting for known risk factors for diabetes mellitus.

RESULTS

A H. pylori positive test was recorded for 76,992 (52.0%) individuals and diabetes for 12,207 (8.3%). The prevalence of diabetes was similar in individuals with and without H. pylori infection, but this association was modified (P for heterogeneity 0.049) by body mass index (BMI): adjusted odds ratio (aOR) 1.16 (95% confidence intervals (CI) 1.04-1.29) in persons with BMI<25 kg/m2 versus aOR 1.03 (95% CI 0.98-1.08) in persons with BMI≥25 kg/m2. Diabetes mellitus prevalence was higher in persons with gastric (aOR 1.20 (95% CI 1.06-1.34)) and duodenal ulcers (aOR 1.20 (95% CI 1.12-1.28)) compared to persons without these diagnoses.

CONCLUSIONS

In this large population-based study, we demonstrated significant positive associations, albeit of small magnitude, of H. pylori infection and peptic disease with diabetes. The long-term gastric inflammation and associated-damage to the gastric mucosa might play a role in such associations.