Biomaterials with the ability to self-heal and recover their structural integrity offer many advantages for applications in biomedicine. The past decade has witnessed the rapid emergence of a new class of self-healing biomaterials commonly termed injectable, or printable in the context of 3D printing. These self-healing injectable biomaterials, mostly hydrogels and other soft condensed matter based on reversible chemistry, are able to temporarily fluidize under shear stress and subsequently recover their original mechanical properties. Self-healing injectable hydrogels offer distinct advantages compared to traditional biomaterials. Most notably, they can be administered in a locally targeted and minimally invasive manner through a narrow syringe without the need for invasive surgery. Their moldability allows for a patient-specific intervention and shows great prospects for personalized medicine. Injected hydrogels can facilitate tissue regeneration in multiple ways owing to their viscoelastic and diffusive nature, ranging from simple mechanical support, spatiotemporally controlled delivery of cells or therapeutics, to local recruitment and modulation of host cells to promote tissue regeneration. Consequently, self-healing injectable hydrogels have been at the forefront of many cutting-edge tissue regeneration strategies. This study provides a critical review of the current state of self-healing injectable hydrogels for tissue regeneration. As key challenges toward further maturation of this exciting research field, we identify (i) the trade-off between the self-healing and injectability of hydrogels vs their physical stability, (ii) the lack of consensus on rheological characterization and quantitative benchmarks for self-healing injectable hydrogels, particularly regarding the capillary flow in syringes, and (iii) practical limitations regarding translation toward therapeutically effective formulations for regeneration of specific tissues. Hence, here we (i) review chemical and physical design strategies for self-healing injectable hydrogels, (ii) provide a practical guide for their rheological analysis, and (iii) showcase their applicability for regeneration of various tissues and 3D printing of complex tissues and organoids.

Natural evolution has provided multicellular organisms with sophisticated functionalities and repair mechanisms for surviving and preserve their functions after an injury and/or infection. In this context, biological systems have inspired material scientists over decades to design and fabricate both self-healing polymeric materials and soft actuators with remarkable performance. The latter are capable of modifying their shape in response to environmental changes, such as temperature, pH, light, electrical/magnetic field, chemical additives, etc. In this review, we focus on the fusion of both types of materials, affording new systems with the potential to revolutionize almost every aspect of our modern life, from healthcare to environmental remediation and energy. The integration of stimuli-triggered self-healing properties into polymeric soft actuators endow environmental friendliness, cost-saving, enhanced safety, and lifespan of functional materials. We discuss the details of the most remarkable examples of self-healing soft actuators that display a macroscopic movement under specific stimuli. The discussion includes key experimental data, potential limitations, and mechanistic insights. Finally, we include a general table providing at first glance information about the nature of the external stimuli, conditions for self-healing and actuation, key information about the driving forces behind both phenomena, and the most important features of the achieved movement.

Semiconductors with multiple anions currently provide a new materials platform from which improved functionality emerges, posing new challenges and opportunities in material science. This review has endeavored to emphasize the versatility of the emerging family of semiconductors consisting of mixed chalcogen and halogen anions, known as "chalcohalides". As they are multifunctional, these materials are of general interest to the wider research community, ranging from theoretical/computational scientists to experimental materials scientists. This review provides a comprehensive overview of the development of emerging Bi- and Sb-based as well as a new Cu, Sn, Pb, Ag, and hybrid organic-inorganic perovskite-based chalcohalides. We first highlight the high-throughput computational techniques to design and develop these chalcohalide materials. We then proceed to discuss their optoelectronic properties, band structures, stability, and structural chemistry employing theoretical and experimental underpinning toward high-performance devices. Next, we present an overview of recent advancements in the synthesis and their wide range of applications in energy conversion and storage devices. Finally, we conclude the review by outlining the impediments and important aspects in this field as well as offering perspectives on future research directions to further promote the development of chalcohalide materials in practical applications in the future.

Metal-organic frameworks (MOFs) have been frequently used as photocatalysts for the hydrogen evolution reaction (HER) using sacrificial agents with UV-vis or visible light irradiation. The aim of the present review is to summarize the use of MOFs as solar-driven photocatalysts targeting to overcome the current efficiency limitations in overall water splitting (OWS). Initially, the fundamentals of the photocatalytic OWS under solar irradiation are presented. Then, the different strategies that can be implemented on MOFs to adapt them for solar photocatalysis for OWS are discussed in detail. Later, the most active MOFs reported until now for the solar-driven HER and/or oxygen evolution reaction (OER) are critically commented. These studies are taken as precedents for the discussion of the existing studies on the use of MOFs as photocatalysts for the OWS under visible or sunlight irradiation. The requirements to be met to use MOFs at large scale for the solar-driven OWS are also discussed. The last section of this review provides a summary of the current state of the field and comments on future prospects that could bring MOFs closer to commercial application.

The human microbiome is composed of a collection of dynamic microbial communities that inhabit various anatomical locations in the body. Accordingly, the coevolution of the microbiome with the host has resulted in these communities playing a profound role in promoting human health. Consequently, perturbations in the human microbiome can cause or exacerbate several diseases. In this Review, we present our current understanding of the relationship between human health and disease development, focusing on the microbiomes found across the digestive, respiratory, urinary, and reproductive systems as well as the skin. We further discuss various strategies by which the composition and function of the human microbiome can be modulated to exert a therapeutic effect on the host. Finally, we examine technologies such as multiomics approaches and cellular reprogramming of microbes that can enable significant advancements in microbiome research and engineering.

The potential of operando X-ray techniques for following the structure, fate, and active site of single-atom catalysts (SACs) is highlighted with emphasis on a synergetic approach of both topics. X-ray absorption spectroscopy (XAS) and related X-ray techniques have become fascinating tools to characterize solids and they can be applied to almost all the transition metals deriving information about the symmetry, oxidation state, local coordination, and many more structural and electronic properties. SACs, a newly coined concept, recently gained much attention in the field of heterogeneous catalysis. In this way, one can achieve a minimum use of the metal, theoretically highest efficiency, and the design of only one active site-so-called single site catalysts. While single sites are not easy to characterize especially under operating conditions, XAS as local probe together with complementary methods (infrared spectroscopy, electron microscopy) is ideal in this research area to prove the structure of these sites and the dynamic changes during reaction. In this review, starting from their fundamentals, various techniques related to conventional XAS and X-ray photon in/out techniques applied to single sites are discussed with detailed mechanistic and in situ/operando studies. We systematically summarize the design strategies of SACs and outline their exploration with XAS supported by density functional theory (DFT) calculations and recent machine learning tools.

The presence of positron emission tomography (PET) centers at most major hospitals worldwide, along with the improvement of PET scanner sensitivity and the introduction of total body PET systems, has increased the interest in the PET tracer development using the short-lived radionuclides carbon-11. In the last few decades, methodological improvements and fully automated modules have allowed the development of carbon-11 tracers for clinical use. Radiolabeling natural compounds with carbon-11 by substituting one of the backbone carbons with the radionuclide has provided important information on the biochemistry of the authentic compounds and increased the understanding of their in vivo behavior in healthy and diseased states. The number of endogenous and natural compounds essential for human life is staggering, ranging from simple alcohols to vitamins and peptides. This review collates all the carbon-11 radiolabeled endogenous and natural exogenous compounds synthesised to date, including essential information on their radiochemistry methodologies and preclinical and clinical studies in healthy subjects.

Glycans, carbohydrate molecules in the realm of biology, are present as biomedically important glycoconjugates and a characteristic aspect is that their structures in many instances are branched. In determining the primary structure of a glycan, the sugar components including the absolute configuration and ring form, anomeric configuration, linkage(s), sequence, and substituents should be elucidated. Solution state NMR spectroscopy offers a unique opportunity to resolve all these aspects at atomic resolution. During the last two decades, advancement of both NMR experiments and spectrometer hardware have made it possible to unravel carbohydrate structure more efficiently. These developments applicable to glycans include, inter alia, NMR experiments that reduce spectral overlap, use selective excitations, record tilted projections of multidimensional spectra, acquire spectra by multiple receivers, utilize polarization by fast-pulsing techniques, concatenate pulse-sequence modules to acquire several spectra in a single measurement, acquire pure shift correlated spectra devoid of scalar couplings, employ stable isotope labeling to efficiently obtain homo- and/or heteronuclear correlations, as well as those that rely on dipolar cross-correlated interactions for sequential information. Refined computer programs for NMR spin simulation and chemical shift prediction aid the structural elucidation of glycans, which are notorious for their limited spectral dispersion. Hardware developments include cryogenically cold probes and dynamic nuclear polarization techniques, both resulting in enhanced sensitivity as well as ultrahigh field NMR spectrometers with a 1H NMR resonance frequency higher than 1 GHz, thus improving resolution of resonances. Taken together, the developments have made and will in the future make it possible to elucidate carbohydrate structure in great detail, thereby forming the basis for understanding of how glycans interact with other molecules.

The field of single-atom catalysis (SAC) has expanded greatly in recent years. While there has been much success developing new synthesis methods, a fundamental disconnect exists between most experiments and the theoretical computations used to model them. The real catalysts are based on powder supports, which inevitably contain a multitude of different facets, different surface sites, defects, hydroxyl groups, and other contaminants due to the environment. This makes it extremely difficult to determine the structure of the active SAC site using current techniques. To be tractable, computations aimed at modeling SAC utilize periodic boundary conditions and low-index facets of an idealized support. Thus, the reaction barriers and mechanisms determined computationally represent, at best, a plausibility argument, and there is a strong chance that some critical aspect is omitted. One way to better understand what is plausible is by experimental modeling, i.e., comparing the results of computations to experiments based on precisely defined single-crystalline supports prepared in an ultrahigh-vacuum (UHV) environment. In this review, we report the status of the surface-science literature as it pertains to SAC. We focus on experimental work on supports where the site of the metal atom are unambiguously determined from experiment, in particular, the surfaces of rutile and anatase TiO2, the iron oxides Fe2O3 and Fe3O4, as well as CeO2 and MgO. Much of this work is based on scanning probe microscopy in conjunction with spectroscopy, and we highlight the remarkably few studies in which metal atoms are stable on low-index surfaces of typical supports. In the Perspective section, we discuss the possibility for expanding such studies into other relevant supports.

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

Lateral flow assays (LFAs) are currently the most used point-of-care sensors for both diagnostic (e.g., pregnancy test, COVID-19 monitoring) and environmental (e.g., pesticides and bacterial monitoring) applications. Although the core of LFA technology was developed several decades ago, in recent years the integration of novel nanomaterials as signal transducers or receptor immobilization platforms has brought improved analytical capabilities. In this Review, we present how nanomaterial-based LFAs can address the inherent challenges of point-of-care (PoC) diagnostics such as sensitivity enhancement, lowering of detection limits, multiplexing, and quantification of analytes in complex samples. Specifically, we highlight the strategies that can synergistically solve the limitations of current LFAs and that have proven commercial feasibility. Finally, we discuss the barriers toward commercialization and the next generation of LFAs.

With the rapid development of optoelectronic fields, electrochromic (EC) materials and devices have received remarkable attention and have shown attractive potential for use in emerging wearable and portable electronics, electronic papers/billboards, see-through displays, and other new-generation displays, due to the advantages of low power consumption, easy viewing, flexibility, stretchability, etc. Despite continuous progress in related fields, determining how to make electrochromics truly meet the requirements of mature displays (e.g., ideal overall performance) has been a long-term problem. Therefore, the commercialization of relevant high-quality products is still in its infancy. In this review, we will focus on the progress in emerging EC materials and devices for potential displays, including two mainstream EC display prototypes (segmented displays and pixel displays) and their commercial applications. Among these topics, the related materials/devices, EC performance, construction approaches, and processing techniques are comprehensively disscussed and reviewed. We also outline the current barriers with possible solutions and discuss the future of this field.

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Electron crystallography has a storied history which rivals that of its more established X-ray-enabled counterpart. Recent advances in data collection and analysis have sparked a renaissance in the field, opening a new chapter for this venerable technique. Burgeoning interest in electron crystallography has spawned innovative methods described by various interchangeable labels (3D ED, MicroED, cRED, etc.). This Review covers concepts and findings relevant to the practicing crystallographer, with an emphasis on experiments aimed at using electron diffraction to elucidate the atomic structure of three-dimensional molecular crystals.

Adeno-associated virus (AAV) has a single-stranded DNA genome encapsidated in a small icosahedrally symmetric protein shell with 60 subunits. AAV is the leading delivery vector in emerging gene therapy treatments for inherited disorders, so its structure and molecular interactions with human hosts are of intense interest. A wide array of electron microscopic approaches have been used to visualize the virus and its complexes, depending on the scientific question, technology available, and amenability of the sample. Approaches range from subvolume tomographic analyses of complexes with large and flexible host proteins to detailed analysis of atomic interactions within the virus and with small ligands at resolutions as high as 1.6 Å. Analyses have led to the reclassification of glycan receptors as attachment factors, to structures with a new-found receptor protein, to identification of the epitopes of antibodies, and a new understanding of possible neutralization mechanisms. AAV is now well-enough characterized that it has also become a model system for EM methods development. Heralding a new era, cryo-EM is now also being deployed as an analytic tool in the process development and production quality control of high value pharmaceutical biologics, namely AAV vectors.

Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.

The global spread of SARS-CoV-2 has proceeded at an unprecedented rate. Remarkably, characterization of the virus using modern tools in structural biology has also progressed at exceptional speed. Advances in electron-based imaging techniques, combined with decades of foundational studies on related viruses, have enabled the research community to rapidly investigate structural aspects of the novel coronavirus from the level of individual viral proteins to imaging the whole virus in a native context. Here, we provide a detailed review of the structural biology and pathobiology of SARS-CoV-2 as it relates to all facets of the viral life cycle, including cell entry, replication, and three-dimensional (3D) packaging based on insights obtained from X-ray crystallography, cryo-electron tomography, and single-particle cryo-electron microscopy. The structural comparison between SARS-CoV-2 and the related earlier viruses SARS-CoV and MERS-CoV is a common thread throughout this review. We conclude by highlighting some of the outstanding unanswered structural questions and underscore areas that are under rapid current development such as the design of effective therapeutics that block viral infection.

Membrane proteins are highly diverse in both structure and function and can, therefore, present different challenges for structure determination. They are biologically important for cells and organisms as gatekeepers for information and molecule transfer across membranes, but each class of membrane proteins can present unique obstacles to structure determination. Historically, many membrane protein structures have been investigated using highly engineered constructs or using larger fusion proteins to improve solubility and/or increase particle size. Other strategies included the deconstruction of the full-length protein to target smaller soluble domains. These manipulations were often required for crystal formation to support X-ray crystallography or to circumvent lower resolution due to high noise and dynamic motions of protein subdomains. However, recent revolutions in membrane protein biochemistry and cryo-electron microscopy now provide an opportunity to solve high resolution structures of both large, >1 megadalton (MDa), and small, <100 kDa (kDa), drug targets in near-native conditions, routinely reaching resolutions around or below 3 Å. This review provides insights into how the recent advances in membrane biology and biochemistry, as well as technical advances in cryo-electron microscopy, help us to solve structures of a large variety of membrane protein groups, from small receptors to large transporters and more complex machineries.

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.