Bioprinting of human dermal microtissues precursors as building blocks for endogenousin vitroconnective tissue manufacturing

The advent of 3D bioprinting technologies in tissue engineering has unlocked the potential to fabricatein vitrotissue models, overcoming the constraints associated with the shape limitations of preformed scaffolds. However, achieving an accurate mimicry of complex tissue microenvironments, encompassing cellular and biochemical components, and orchestrating their supramolecular assembly to form hierarchical structures while maintaining control over tissue formation, is crucial for gaining deeper insights into tissue repair and regeneration. Building upon our expertise in developing competent three-dimensional tissue equivalents (e.g. skin, gut, cervix), we established a two-step bottom-up approach involving the dynamic assembly of microtissue precursors (μTPs) to generate macroscopic functional tissue composed of cell-secreted extracellular matrix (ECM). To enhance precision and scalability, we integrated extrusion-based bioprinting technology into our established paradigm to automate, control and guide the coherent assembly ofμTPs into predefined shapes. Compared to cell-aggregated bioink, ourμTPs represent a functional unit where cells are embedded in their specific ECM.μTPs were derived from human dermal fibroblasts dynamically seeded onto gelatin-based microbeads. After 9 days,μTPs were suspended (50% v/v) in Pluronic-F127 (30% w/v) (µTP:P30), and the obtained formulation was loaded as bioink into the syringe of the Dr.INVIVO-4D6 extrusion based bioprinter.µTP:P30 bioink showed shear-thinning behavior and temperature-dependent viscosity (gel atT> 30 °C), ensuringµTPs homogenous dispersion within the gel and optimal printability. The bioprinting involved extruding several geometries (line, circle, and square) into Pluronic-F127 (40% w/v) (P40) support bath, leveraging its shear-recovery property. P40 effectively held the bioink throughout and after the bioprinting procedure, untilµTPs fused into a continuous connective tissue.µTPs fusion dynamics was studied over 8 days of culture, while the resulting endogenous construct underwent 28 days culture. Histological, immunofluorescence analysis, and second harmonic generation reconstruction revealed an increase in endogenous collagen and fibronectin production within the bioprinted construct, closely resembling the composition of the native connective tissues.

A review on green approaches utilizing phytochemicals in the synthesis of vanadium nano particles and their applications

In the modern era, inorganic nanoparticles have received profound attention as they possess boundless applications in various fields. Among these, vanadium-based nanoparticles (VNPs) are highly remarkable due to their inherent physiological and biological properties with many therapeutic and other applications, such as drug delivery systems for diseases like cancer, environmental remediation, energy storage, energy conversion, and photocatalysis. Moreover, physically, and chemically synthesized VNPs are very versatile, however, these synthesis routes cause concern to health and the environment due to the highly savage reaction conditions, using highly toxic and harsh chemicals, which compel the researchers to develop an eco-friendly, greener, and sustainable route for synthesis. In this outlook, to avoid the innumerable limitations, a bio approach is used over chemical and physical methods. This present review emphasis on the role of various biological components in the synthesis, especially Phyto-molecules that acts as capping and reducing agent, and solvent system for the nanoparticles synthesis. Furthermore, the influence of various factors on the biogenic synthesized nanoparticles has also been discussed. Finally, potential applications of as-synthesized VNPs, principally as an antimicrobial agent and their role as a nanomedicine, energy applications as a supercapacitor, and photocatalytic agents, have been discussed.

Nano- and micro-crystalline diamond film structuring with electron beam lithography mask

Direct current plasma enhanced chemical vapor deposition (CVD) was employed to create polycrystalline diamond films from CH4/H2gaseous mixture at 98 mbar pressure and various substrate temperatures between 720 °C and 960 °C. The Si chips with patterns of periodic masked and open seeded zones were used as substrates. The mask free seeded areas evolved into polycrystalline diamond films after CVD process. The diamond crystallites of the films featured single crystal ordering individually with distinct cubic (100) or octahedral (111) facets on the film surfaces. Notably, specific growth conditions were determined for obtaining diamond films composed of the crystallites of nanometre and micrometre scale. These conditions are differing from those observed for non-pattern-prepared Si substrates. The nano-crystalline diamonds emerged within the 4.5-5 A current range, with growth conditions involving 3% CH4/H2mixture at 98 mbar. The micro-crystalline diamonds (MCDs) predominantly characterized by well-developed rectangular (100) crystal faces on the film surface were successfully grown with current settings of 5.5-6 A, under 3% CH4/H2mixture at 98 mbar. Furthermore, MCDs characterized by entirely crystalline (111) diamond faces forming CVD film surface were attained within a growth parameter range of 4.5-5.8 A, employing 3% CH4/H2mixture for certain samples, or alternatively, utilizing 5 A with a 1.5% CH4/H2mixture for others. Upon thorough evaluation, it was established that SiO2, TiO2, and Cr masks are well-suited materials for the planar patterning of both nano- and micro-crystalline diamond films, and the bottom-up approach can pave the way for the production of diamond planar structures through CVD, facilitated by electron beam lithography (EBL).

Distinctive properties of biological neural networks and recent advances in bottom-up approaches toward a better biologically plausible neural network

Although it may appear infeasible and impractical, building artificial intelligence (AI) using a bottom-up approach based on the understanding of neuroscience is straightforward. The lack of a generalized governing principle for biological neural networks (BNNs) forces us to address this problem by converting piecemeal information on the diverse features of neurons, synapses, and neural circuits into AI. In this review, we described recent attempts to build a biologically plausible neural network by following neuroscientifically similar strategies of neural network optimization or by implanting the outcome of the optimization, such as the properties of single computational units and the characteristics of the network architecture. In addition, we proposed a formalism of the relationship between the set of objectives that neural networks attempt to achieve, and neural network classes categorized by how closely their architectural features resemble those of BNN. This formalism is expected to define the potential roles of top-down and bottom-up approaches for building a biologically plausible neural network and offer a map helping the navigation of the gap between neuroscience and AI engineering.

2D Zinc Oxide - Synthesis, Methodologies, Reaction Mechanism, and Applications

Zinc oxide (ZnO) is a thermally stable n-type semiconducting material. ZnO 2D nanosheets have mainly gained substantial attention due to their unique properties, such as direct bandgap and strong excitonic binding energy at room temperature. These are widely utilized in piezotronics, energy storage, photodetectors, light-emitting diodes, solar cells, gas sensors, and photocatalysis. Notably, the chemical properties and performances of ZnO nanosheets largely depend on the nano-structuring that can be regulated and controlled through modulating synthetic strategies. Two synthetic approaches, top-down and bottom-up, are mainly employed for preparing ZnO 2D nanomaterials. However, owing to better results in producing defect-free nanostructures, homogenous chemical composition, etc., the bottom-up approach is extensively used compared to the top-down method for preparing ZnO 2D nanosheets. This review presents a comprehensive study on designing and developing 2D ZnO nanomaterials, followed by accenting its potential applications. To begin with, various synthetic strategies and attributes of ZnO 2D nanosheets are discussed, followed by focusing on methodologies and reaction mechanisms. Then, their deliberation toward batteries, supercapacitors, electronics/optoelectronics, photocatalysis, sensing, and piezoelectronic platforms are further discussed. Finally, the challenges and future opportunities are featured based on its current development.

Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38-282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure-function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

Eco-Friendly and Sustainable Pathways to Photoluminescent Carbon Quantum Dots (CQDs)

Carbon quantum dots (CQDs), a new family of photoluminescent 0D NPs, have recently received a lot of attention. They have enormous future potential due to their unique properties, which include low toxicity, high conductivity, and biocompatibility and accordingly can be used as a feasible replacement for conventional materials deployed in various optoelectronic, biomedical, and energy applications. The most recent trends and advancements in the synthesizing and setup of photoluminescent CQDs using environmentally friendly methods are thoroughly discussed in this review. The eco-friendly synthetic processes are emphasized, with a focus on biomass-derived precursors. Modification possibilities for creating newer physicochemical properties among different CQDs are also presented, along with a brief conceptual overview. The extensive amount of writings on them found in the literature explains their exceptional competence in a variety of fields, making these nanomaterials promising alternatives for real-world applications. Furthermore, the benefits, drawbacks, and opportunities for CQDs are discussed, with an emphasis on their future prospects in this emerging research field.

Material Stock and Embodied Greenhouse Gas Emissions of Global and Urban Road Pavement

Roads play a key role in movements of goods and people but require large amounts of materials emitting greenhouse gases to be produced. This study assesses the global road material stock and the emissions associated with materials' production. Our bottom-up approach combines georeferenced paved road segments with road length statistics and archetypical geometric characteristics of roads. We estimate road material stock to be of 254 Gt. If we were to build these roads anew, raw material production would emit 8.4 GtCO₂-eq. Per capita stocks range from 0.2 t/cap in Chad to 283 t/cap in Iceland, with a median of 20.6 t/cap. If the average per capita stock in Africa was to reach the current European level, 166 Gt of road materials, equivalent to the road material stock in North America and in East and South Asia, would be consumed. At the urban scale, road material stock increases with the urban area, population density, and GDP per capita, emphasizing the need for containing urban expansion. Our study highlights the challenges in estimating road material stock and serves as a basis for further research into infrastructure resource management.

Bottom-Up Evaluation of the Uncertainty of the Quantification of Microplastics Contamination in Sediment Samples

The quantification and comparison of microplastic contamination of sediments are affected by sample heterogeneity and the systematic and random effects affecting sample analysis. The quantification and combination of these components in the measurement uncertainty allows the objective interpretation of analysis results. This work presents the first detailed evaluation of the uncertainty of microplastic contamination quantification in sediments. The random and systematic effects affecting microplastic counts are modeled by the Poisson-lognormal distribution with inputs estimated from duplicate sediment analysis and the analysis of sediments spiked with microparticles. The uncertainty from particle counting was combined with the uncertainty from the determination of the dry mass of the analytical portion by the Monte Carlo method. The developed methodology was implemented in a user-friendly spreadsheet made available as the Supporting Information. The contamination of sediment samples collected in various inland Portuguese waters was determined, ranging from [0; 160] to [361; 2932] kg^-1 for a 99% confidence level, and compared by assessing if the difference between contamination levels is equivalent to zero for the same confidence level. Several samples proved to have metrologically different microplastic contamination. This work represents a contribution to the objectivity of the assessment of environmental contamination with microplastics.

Use of Social Media for Implementing Diagnoses, Consultation, Training, and Case Reporting Among Medical Professionals to Improve Patient Care: Case Study of WeChat Groups Across Health Care Settings

BACKGROUND

Health professionals in low- and middle-resource settings have limited access to up-to-date resources for diagnosing and treating illnesses, training medical staff, reviewing newly disseminated guidelines and publications, and preparing data for international disease reporting. A concomitant difficulty in high-resource settings is the need for continuing education and skills up-training in innovative procedures on unfamiliar social media platforms. These challenges can delay both patient care and epidemiological surveillance efforts. To overcome these challenges, health professionals have adapted WeChat Groups to implement timely, low-cost, and high-quality patient care.

OBJECTIVE

The primary study aim was to describe the processes taken by medical professionals across their diverse physical and virtual networks in adapting a bottom-up approach to collectively overcome resource shortages. The secondary study aim was to delineate the pathways, procedures, and resource/information sharing implemented by medical professionals using an international publicly available popular social media app (WeChat) to enhance performance of facility-based procedures and protocols for improved patient care.

METHODS

In-depth interviews, observations, and digital ethnography of WeChat Groups communications were collected from medical professionals in interconnected networks of health care facilities. Participants' WeChat Groups usage and observations of their professional functions in interconnected networks were collected from November 2018 to 2019. Qualitative analysis and thematic coding were used to develop constructs and themes in NVivo. Constructs incorporated descriptions for the implementation and uses of WeChat Groups for professional connections, health care procedures, and patient care. Themes supporting the constructs focused on the pathways and venues used by medical professionals to build trust, to establish and solidify online networks, and to identify requests and resource sharing within WeChat Groups.

RESULTS

There were 58 participants (males 36 and females 22) distributed across 24 health care settings spanning geographical networks in south China. Analysis yielded 4 constructs and 11 themes delineating the bottom-up usage of WeChat Groups among clinicians, technicians, nurses, pharmacists, and public health administrators. Participants used WeChat Groups for collectively training hospital staff in complex new procedures, processing timely diagnoses of biological specimens, staying abreast of latest trends and clinical procedures and symptoms, and contributing to case reporting for emergent illnesses and international surveillance reporting. An unexpected strength of implementing clinical, training, and research support on a popular app with international coverage is the added ability to overcome administrative and geographic barriers in resource distribution. This advantage increased a network's access to WeChat Groups members both working within China and abroad, greatly expanding the scope of shared resources.

CONCLUSIONS

The organic, bottom-up approach of repurposing extant social media apps is low cost and efficient for timely implementation to improve patient care. WeChat's international user base enables medical staff to access widespread professional networks across geographic, administrative, and economic barriers, with potential to reduce health disparities in low-resource settings.

Nanocrystals: An Approachable Delivery System for Anticancer Therapeutics

Cancer accounts for the high mortality rate and limits the life expectancy of an individual. As per the WHO report of 2020, Cancer accounts for >10 million deaths globally. Scientists are continuously pitching toward the development of novel techniques to combat this menace and enhance the efficacy of prevailing molecules. In the early phases of the drug development process, >40% of promising new therapeutic molecules are hydrophobic. Low aqueous solubility results in compromised bioavailability on administration. This limitation is a major drawback for the therapeutic use of the anticancer drug. Drug nanocrystals (NCs) have sparked a lot of interest in drug delivery. This might be due to their excellent physicochemical characteristics like tailored dissolution, high drug loading efficiency, extended circulation period, and high structural stability. These are 'n' number of the characteristics that make drug nanocrystals a promising formulation for the treatment of cancer. In the last few years, many hydrophobic or lipophilic drugs like camptothecin, paclitaxel, cyclosporin, busulfan, and thymectacin had been formulated as drug nanocrystals against anticancer therapeutics. Various formulation technologies have been developed in conjunction with nanocrystal development. This includes top-down approaches, bottom-up approaches, as well as combination technology. In this article, we will focus on the various manufacturing processes, biological fate and therapeutic applications of NCs, and future perspectives in the management of cancer.

The lived experience of psychosis: a bottom-up review co-written by experts by experience and academics

Psychosis is the most ineffable experience of mental disorder. We provide here the first co-written bottom-up review of the lived experience of psychosis, whereby experts by experience primarily selected the subjective themes, that were subsequently enriched by phenomenologically-informed perspectives. First-person accounts within and outside the medical field were screened and discussed in collaborative workshops involving numerous individuals with lived experience of psychosis as well as family members and carers, representing a global network of organizations. The material was complemented by semantic analyses and shared across all collaborators in a cloud-based system. The early phases of psychosis (i.e., premorbid and prodromal stages) were found to be characterized by core existential themes including loss of common sense, perplexity and lack of immersion in the world with compromised vital contact with reality, heightened salience and a feeling that something important is about to happen, perturbation of the sense of self, and need to hide the tumultuous inner experiences. The first episode stage was found to be denoted by some transitory relief associated with the onset of delusions, intense self-referentiality and permeated self-world boundaries, tumultuous internal noise, and dissolution of the sense of self with social withdrawal. Core lived experiences of the later stages (i.e., relapsing and chronic) involved grieving personal losses, feeling split, and struggling to accept the constant inner chaos, the new self, the diagnosis and an uncertain future. The experience of receiving psychiatric treatments, such as inpatient and outpatient care, social interventions, psychological treatments and medications, included both positive and negative aspects, and was determined by the hope of achieving recovery, understood as an enduring journey of reconstructing the sense of personhood and re-establishing the lost bonds with others towards meaningful goals. These findings can inform clinical practice, research and education. Psychosis is one of the most painful and upsetting existential experiences, so dizzyingly alien to our usual patterns of life and so unspeakably enigmatic and human.

The Six Components of Social Interactions: Actor, Partner, Relation, Activities, Context, and Evaluation

Social interactions are essential aspects of social relationships. Despite their centrality, there is a lack of a standardized approach to systematize social interactions. The present research developed (Study 1) and tested (Study 2) a taxonomy of social interactions. In Study 1 (5,676 descriptions of social interactions from N = 708 participants, age range 18–83 years), we combined a bottom-up approach based on the grounded theory with a top-down approach integrating existing empirical and theoretical literature to develop the taxonomy. The resulting taxonomy (APRACE) comprises the components Actor, Partner, Relation, Activities, Context, and Evaluation, each specified by features on three levels of abstraction. A social situation can be described by a combination of the components and their features on the respective abstraction level. Study 2 tested the APRACE using another dataset (N = 303, age range 18–88 years) with 1,899 descriptions of social interactions. The index scores of the six components, the frequencies of the features on the most abstract level, and their correlations were largely consistent across both studies, which supports the generalizability of the APRACE. The APRACE offers a generalizable tool for the comprehensive, parsimonious, and systematic description of social interactions and, thus, enables networked research on social interactions and application in a number of practical fields.

Nanomaterials: Synthesis and Applications in Theranostics

Nanomaterials are endowed with unique features and essential properties suitable for employing in the field of nanomedicine. The nanomaterials can be classified as 0D, 1D, 2D, and 3D based on their dimensions. The nanomaterials can be malleable and ductile and they can be drawn into wires and sheets. Examples of nanomaterials are quantum dots (0D), nanorods, nanowires (1D), nanosheets (2D), and nanocubes (3D). These nanomaterials can be synthesized using top-down and bottom-up approaches. The achievements of 0D and 1D nanomaterials are used to detect trace heavy metal (e.g., Pb2+) and have higher sensitivity with the order of five as compared to conventional sensors. The achievements of 2D and 3D nanomaterials are used as diagnostic and therapeutic agents with multifunctional ability in imaging systems such as PET, SPECT, etc. These imaging modalities can be used to track the drug in living tissues. This review comprises the state-of-the-art of the different dimensions of the nanomaterials employed in theranostics. The nanomaterials with different dimensions have unique physicochemical properties that can be utilized for therapy and diagnosis. The multifunctional ability of the nanomaterials can have a distinct advantage that is used in the field of theranostics. Different dimensions of the nanomaterials would have more scope in the field of nanomedicine.

In Silico/In Vitro Strategies Leading to the Discovery of New Nonribosomal Peptide and Polyketide Antibiotics Active against Human Pathogens

Antibiotics are majorly important molecules for human health. Following the golden age of antibiotic discovery, a period of decline ensued, characterised by the rediscovery of the same molecules. At the same time, new culture techniques and high-throughput sequencing enabled the discovery of new microorganisms that represent a potential source of interesting new antimicrobial substances to explore. The aim of this review is to present recently discovered nonribosomal peptide (NRP) and polyketide (PK) molecules with antimicrobial activity against human pathogens. We highlight the different in silico/in vitro strategies and approaches that led to their discovery. As a result of technological progress and a better understanding of the NRP and PK synthesis mechanisms, these new antibiotic compounds provide an additional option in human medical treatment and a potential way out of the impasse of antibiotic resistance.

Shape memory effect nanotools for nano-creation: examples of nanowire-based devices with charge density waves

Nanotweezers based on the shape memory effect have been developed and tested. In combination with a commercial nanomanipulator, they allow 3D nanoscale operation controlled in a scanning electron microscope. Here we apply the tweezers for the fabrication of nanostructures based on whiskers of NbS₃, a quasi one-dimensional compound with room-temperature charge density wave (CDW). The nanowhiskers were separated without damage from the growth batch, an entangled array, and safely transferred to a substrate with a preliminary deposited Au film. The contacts were fabricated with Pt sputtering on top of the whisker and the film. The high degree of synchronization of the sliding CDW under a RF field with a frequency up to 600 MHz confirms the high quality of the contacts and of the sample structure after the manipulations. The proposed technique paves the way to novel type micro- and nanostructures fabrication and their various applications.

Proteomic Advances in Cereal and Vegetable Crops

The importance of vegetables in human nutrition, such as cereals, which in many cases represent the main source of daily energy for humans, added to the impact that the incessant increase in demographic pressure has on the demand for these plant foods, entails the search for new technologies that can alleviate this pressure on markets while reducing the carbon footprint of related activities. Plant proteomics arises as a response to these problems, and through research and the application of new technologies, it attempts to enhance areas of food science that are fundamental for the optimization of processes. This review aims to present the different approaches and tools of proteomics in the investigation of new methods for the development of vegetable crops. In the last two decades, different studies in the control of the quality of crops have reported very interesting results that can help us to verify parameters as important as food safety, the authenticity of the products, or the increase in the yield by early detection of diseases. A strategic plan that encourages the incorporation of these new methods into the industry will be essential to promote the use of proteomics and all the advantages it offers in the optimization of processes and the solution of problems.

The Role of Mathematical Models in Immuno-Oncology: Challenges and Future Perspectives

Immuno-oncology (IO) focuses on the ability of the immune system to detect and eliminate cancer cells. Since the approval of the first immune checkpoint inhibitor, immunotherapies have become a major player in oncology treatment and, in 2021, represented the highest number of approved drugs in the field. In spite of this, there is still a fraction of patients that do not respond to these therapies and develop resistance mechanisms. In this sense, mathematical models offer an opportunity to identify predictive biomarkers, optimal dosing schedules and rational combinations to maximize clinical response. This work aims to outline the main therapeutic targets in IO and to provide a description of the different mathematical approaches (top-down, middle-out, and bottom-up) integrating the cancer immunity cycle with immunotherapeutic agents in clinical scenarios. Among the different strategies, middle-out models, which combine both theoretical and evidence-based description of tumor growth and immunological cell-type dynamics, represent an optimal framework to evaluate new IO strategies.

The Effect of Religious Dietary Cultures on Food Nitrogen and Phosphorus Footprints: A Case Study of India

The excessive consumption of nitrogen (N) and phosphorus (P), two vital nutrients for living organisms, is associated with negative environmental and health impacts. While food production contributes to a large amount of N and P loss to the environment, very little N and P is consumed as food. Food habits are affected by multiple regulations, including the dietary restrictions and dictates of various religions. In this study, religion-sensitive N-Calculator and P-Calculator approaches were used to determine the impact of religious dietary culture on the food N and P footprints of India in the major religious communities. Using 2013 data, the food N footprint of Hindus, Muslims, Christians, and Buddhists was 10.70, 11.45, 11.47, and 7.39 kg-N capita-1 year-1 (10.82 kg-N capita-1 year-1 was the national average), and the food P footprint was 1.46, 1.58, 1.04. and 1.58 kg-P capita-1 year-1 (1.48 kg-P capita-1 year-1 was the national average). The findings highlight the impact of individual choice on the N and P food footprints, and the importance of encouraging the followers of religion to follow a diet consistent with the food culture of that religion. The results of this study are a clear indication of the requirement for religion-sensitive analyses in the collecting of data pertinent to a particular country for use in making government policies designed to improve the recycling of food waste and the treatment of wastewater.

Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions

Epithelial-mesenchymal transition (EMT) is an important biological process through which epithelial cells undergo phenotypic transitions to mesenchymal cells by losing cell-cell adhesion and gaining migratory properties that cells use in embryogenesis, wound healing, and cancer metastasis. An important research topic is to identify the underlying gene regulatory networks (GRNs) governing the decision making of EMT and develop predictive models based on the GRNs. The advent of recent genomic technology, such as single-cell RNA sequencing, has opened new opportunities to improve our understanding about the dynamical controls of EMT. In this article, we review three major types of computational and mathematical approaches and methods for inferring and modeling GRNs driving EMT. We emphasize (1) the bottom-up approaches, where GRNs are constructed through literature search; (2) the top-down approaches, where GRNs are derived from genome-wide sequencing data; (3) the combined top-down and bottom-up approaches, where EMT GRNs are constructed and simulated by integrating bioinformatics and mathematical modeling. We discuss the methodologies and applications of each approach and the available resources for these studies.

VectorMOD: Method for Bottom-Up Proteomic Characterization of rAAV Capsid Post-Translational Modifications and Vector Impurities

Progress in recombinant AAV gene therapy product and process development has advanced our understanding of the basic biology of this critical delivery vector. The discovery of rAAV capsid post-translational modifications (PTMs) has spurred interest in the field for detailed rAAV-specific methods for vector lot characterization by mass spectrometry given the unique challenges presented by this viral macromolecular complex. Recent concerns regarding immunogenic responses to systemically administered rAAV at high doses has highlighted the need for investigators to catalog and track potentially immunogenic vector lot components including capsid PTMs and PTMs on host cell protein impurities. Here we present a simple step-by-step guide for academic rAAV laboratories and Chemistry, Manufacturing and Control (CMC) groups in industry to perform an in-house or outsourced bottom-up mass spectrometry workflow to characterize capsid PTMs and process impurities.

Microproteomic sample preparation

Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).

Ethical Dilemma: An Unprecedented Strike by Health care Workers in Early February 2020 in Hong Kong

Urging the government to exercise a complete border closure to inhibit the spread of the novel coronavirus from Mainland China, about 8,000 health care workers participated in a 5-day strike in early February 2020 in Hong Kong. Despite gaining 61% support from the public, dissenters criticised that the participants violated professional ethics and abandoned their accountabilities, which led to moral distress. However, the participants were guided by the four fundamental medical principles (autonomy, beneficence, non-maleficence, and justice) for public interest and health equity. Their concerns for occupational safety should not be ignored to maintain an effective health care system. In short, the strike adopted a bottom-up initiative and adhered to a public-centered perspective and community-driven ethical behaviors, through which the participants deliberated over professionalism, humanism and the imminence of public health, and the balance between them. Strikers showed care and concern for the safety of the community, sustainability of the health care system, and well-being of all people in Hong Kong.

Prediction of Oral Pharmacokinetics Using a Combination of In Silico Descriptors and In Vitro ADME Properties

Accurate prediction of oral pharmacokinetics remains challenging. This study investigated quantitative approaches for the prediction of the area under the plasma concentration-time curve after oral administration (AUC_p,oral) to rats using the in vitro-in vivo extrapolation (IVIVE), in silico model using machine learning approaches and the combination of the in silico model and in vitro data. A set of 595 structurally diverse compounds with determined AUC_p,oral at 1 mg/kg, in vitro intrinsic clearance (CL_int), an unbound fraction in plasma (f_u,p) in rats, and kinetic solubility at pH 6.8 was used for this assessment. Prediction models developed by two different types of machine learning techniques (i.e., random forest regression and Gaussian processes) were evaluated using three validation methods implementing the time and cluster-split training and test set and fivefold cross-validation. The developed machine learning models have a square of correlation coefficient (R²) in the range of 0.381-0.685 with 33-45% of the compounds being predicted within 2-fold of the observed AUC_p,oral value. The predictivity was improved by incorporating CL_int, f_u,p, and solubility as explanatory variables with R² = 0.554-0.743. In cases where extraction by the liver is the main elimination pathway and intestinal extraction is negligible, AUC_p,oral can be expressed by dose, CL_int, and f_u,p based on a well-stirred model. By using this conventional IVIVE approach, only 1.7-5.0% of compounds were predicted within the 2-fold error with R² = 0.354-0.487. Two empirical scaling factors (ESFs) determined by linear regression analysis and machine learning approaches improved the predictivity of AUC_p,oral with 33-44% predicted within twofold variability. The IVIVE using ESF predicted by random forest regression showed better predictivity of AUC_p,oral with R² = 0.471-0.618, while it still showed lower predictivity than machine learning approaches applied directly to AUC_p,oral prediction. This study demonstrated that the combination of in silico and in vitro parameters is useful to improve the predictivity of the machine learning model for rat AUC_p,oral and supports consideration for predicting AUC_p,oral for human and other non-clinical species in a similar manner.

Direct Comparison of Total Clearance Prediction: Computational Machine Learning Model versus Bottom-Up Approach Using In Vitro Assay

The in vitro-in vivo extrapolation (IVIVE) approach for predicting total plasma clearance (CL_tot) has been widely used to rank order compounds early in discovery. More recently, a computational machine learning approach utilizing physicochemical descriptors and fingerprints calculated from chemical structure information has emerged, enabling virtual predictions even earlier in discovery. Previously, this approach focused more on in vitro intrinsic clearance (CL_int) prediction. Herein, we directly compare these two approaches for predicting CL_tot in rats. A structurally diverse set of 1114 compounds with known in vivo CL_tot, in vitro CL_int, and plasma protein binding was used as the basis for this evaluation. The machine learning models were assessed by validation approaches using the time- and cluster-split training and test sets, and five-fold cross validation. Assessed by five-fold validation, the random forest regression (RF) and radial basis function (RBF) models demonstrated better prediction performance in eight attempted machine learning models. The CL_tot values predicted by the RF and RBF models were within two-fold of the observed values for 67.7 and 71.9% of cluster-split test set compounds, respectively, while the predictivity was worse in the time-split dataset. The predictivity of both models tended to be improved by incorporating in vitro parameters, unbound fraction in plasma (f_u,p), and CL_int. CL_tot prediction utilizing in vitro CL_int and the well-stirred model, correcting for the fraction unbound in blood, was substantially worse compared to machine learning approaches for the same cluster-split test set. The reason that CL_tot is underestimated by IVIVE is not fully explained by considering the calculated microsomal unbound fraction (cf_u,mic), extended clearance classification system (ECCS), and omitting high clearance compounds in excess of hepatic blood flow. The analysis suggests that in silico machine learning models may have the power to reduce reliance on or replace in vitro and in vivo studies for chemical structure optimization in early drug discovery.

In Situ Synthesis of Silicon-Carbon Composites and Application as Lithium-Ion Battery Anode Materials

Silicon can be used in a variety of applications. Particularly, silicon particles are attracting increased attention as energy storage materials for lithium-ion batteries. However, silicon has a limited cycling performance owing to its peeling from the current collector and the volume expansion that occurs during alloying with lithium in the charging process. Significant contributors to this problem are the even distribution of silicon nanoparticles within the carbon matrix and their deep placement in the internal structure. In this study, we synthesized silicon nanoparticles and carbon materials via a bottom-up approach using a new method called plasma in solution. Silicon nanoparticles and the carbon matrix were synthesized in a structure similar to carbon black. It was confirmed that the silicon particles were evenly distributed in the carbon matrix. In addition, the evaluation of the electrochemical performance of the silicon-carbon matrix (Si-C) composite material showed that it exhibited stable cycling performance with high reversible capacity.

PBPK in Preterm and Term Neonates: A Review

INTRODUCTION

The neonatal population remains one of the populations in which appropriate dosing regimens are still lacking, resulting in a large off-label or unlicensed use. Clinical research in these small infants remains a challenge, which sparks the need for modeling and simulation as an additional tool for neonatal drug research.

METHODS

The use of physiologically based pharmacokinetic modeling in preterm and term neonates is investigated.

RESULTS

Throughout the last decade, the use of this modeling technique in this vulnerable population has received increased attention, but still many knowledge gaps exist. Firstly, an overview of the top-down, bottom-up and middle-out approach is given, and then these different modeling tools regarding feasibility and appropriate use are compared. The challenges in applying PBPK to this young population are highlighted and possible solutions are presented. Examples of applications were found in literature and a preference for the combination of a pure bottom- up approach with clinical data (the "middle-out" approach) was detected.

CONCLUSION

Perspectives to further apply this powerful modeling methodology in this population are described in order to become 'the tool' for the design of First-in-Human and First-in-Neonate trials, and the individualization of dosing in these therapeutic orphans.

A One-Step Chemical Strategy for the Formation of Carbon Nanotube Junctions in Aqueous Solution: Reaction of DNA-Wrapped Carbon Nanotubes with Diazonium Salts

A single-step chemical strategy allows the formation of single-walled carbon nanotube (SWCNT) molecular junctions in aqueous solution. SWCNTs were first wrapped with DNA to be water soluble and solution processable. Diazonium salts, which have been shown to react spontaneously with carbon nanotubes in water at room temperature, were then employed to covalently link SWCNT segments. The DNA wrapping of the nanotubes acted as a protective layer that limits the functionalization predominantly to the nanotube terminal ends, therefore allowing the assembly of linear SWCNT junctions. Upon increasing the concentration of the linker, we observed first the formation of side-to-end junctions, and eventually the assembly, through side-to-side interactions, of SWCNTs into bundles. This approach demonstrates the possibility of tuning the formation of linear and branched carbon nanotube junctions that in turn is of importance for the sustainable fabrication of solution-processable CNT-based nanoscale systems and devices.

Rehabilitative devices for a top-down approach

INTRODUCTION

In recent years, neurorehabilitation has moved from a 'bottom-up' to a 'top down' approach. This change has also involved the technological devices developed for motor and cognitive rehabilitation. It implies that during a task or during therapeutic exercises, new 'top-down' approaches are being used to stimulate the brain in a more direct way to elicit plasticity-mediated motor re-learning. This is opposed to 'Bottom up' approaches, which act at the physical level and attempt to bring about changes at the level of the central neural system.

AREAS COVERED

In the present unsystematic review, we present the most promising innovative technological devices that can effectively support rehabilitation based on a top-down approach, according to the most recent neuroscientific and neurocognitive findings. In particular, we explore if and how the use of new technological devices comprising serious exergames, virtual reality, robots, brain computer interfaces, rhythmic music and biofeedback devices might provide a top-down based approach.

EXPERT COMMENTARY

Motor and cognitive systems are strongly harnessed in humans and thus cannot be separated in neurorehabilitation. Recently developed technologies in motor-cognitive rehabilitation might have a greater positive effect than conventional therapies.

Nanocrystals of a new camptothecin derivative WCN-21 enhance its solubility and efficacy

WCN-21 is a new camptothecin derivative we synthesized and has desirable anti-tumor efficacy, but its aqueous solubility is very low and hurdles the further evaluation and development. In this study, we prepared nanocrystals of WCN-21 through a bottom-up approach to enhance its solubility and obtained WCN-21 nanorods (WND) and nanospheres (WNP). We investigated the crystallization of WND and WNP in different temperature and solvents and found that both temperature and solvents affect the crystal shapes and sizes. We prepared WND at 50°C and DMSO : H2O 1: 50 and WNP at 25°C and DMSO : H2O 1: 100 and found they were dispersed evenly in water with average hydrodynamic diameters 337 and 231 nm, respectively. WND and WNP increased the solubility of WCN-21 from extreme insolubility to more than 9 and 11 mM in H2O or PBS, respectively. In vitro studies showed that WND and WNP enhanced the uptake of WCN-21 in tumor cells by 3 and 9 folds, and increased cytotoxicity of WCN-21 in comparison with free WCN-21 by 5 and 6 folds, respectively. In xenograft tumor mice, intravenous injection of WND and WNP enhanced the accumulation of WCN-21 in tumor tissues and improved the anti-tumor efficacy. In addition, WND and WNP did not increase the toxicity of WCN-21 in mice. Therefore, nanocrystal is a robust tool to improve the solubility of insoluble drugs and holds a great potential in the application of drug development.

Fabrication of Nanostructures with Bottom-up Approach and Their Utility in Diagnostics, Therapeutics, and Others

Nanofabrication has been a critical area of research in the last two decades and has found wide-ranging application in improvising material properties, sensitive clinical diagnostics, and detection, improving the efficiency of electron transport processes within materials, generating high energy densities leading to pulse power, novel therapeutic mechanisms, environmental remediation and control. The continued improvements in the various fabrication technologies have led to realization of highly sensitive nanostructure-based devices. The fabrication of nanostructures is in principle carried out primarily using top-down or bottom-up approaches. This chapter summarizes the important bottom-up nanofabrication processes for realizing nanostructures and also highlights the recent research conducted in the domain of therapeutics and diagnostics.

On the origin of biological construction, with a focus on multicellularity

Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.

Bottom-Up Electrochemical Fabrication of Conjugated Ultrathin Layers with Tailored Switchable Properties

A bottom-up electrochemical process for fabricating conjugated ultrathin layers with tailored switchable properties is developed. Ultrathin layers of covalently grafted oligo(bisthienylbenzene) (oligo(BTB)) are used as switchable organic electrodes, and 3,4-ethylenedioxythiophene (EDOT) is oxidized on this layer. Adding only a few (less than 3) nanometers of EDOT moieties (5 to 6 units ) completely changes the switching properties of the layer without changing the surface concentration of the electroactive species. A range of new materials with tunable interfacial properties is created. They consist of oligo(BTB)-oligo(EDOT) diblock oligomers of various relative lengths covalently grafted onto the underlying electrode. These films retain reversible redox on/off switching and their switching potential can be finely tuned between +0.6 and -0.3 V/SCE while the overall thickness remains below 11 nm.

A Facile Bottom-Up Approach to Construct Hybrid Flexible Cathode Scaffold for High-Performance Lithium-Sulfur Batteries

Lithium-sulfur batteries mostly suffer from the low utilization of sulfur, poor cycle life, and low rate performances. The prime factors that affect the performance are enormous volume change of the electrode, soluble intermediate product formation, poor electronic and ionic conductivity of S, and end discharge products (i.e., Li₂S₂ and Li₂S). The attractive way to mitigate these challenges underlying in the fabrication of a sulfur nanocomposite electrode consisting of different nanoparticles with distinct properties of lithium storage capability, mechanical reinforcement, and ionic as well as electronic conductivity leading to a mechanically robust and mixed conductive (ionic and electronic conductive) sulfur electrode. Herein, we report a novel bottom-up approach to synthesize a unique freestanding, flexible cathode scaffold made of porous reduced graphene oxide, nanosized sulfur, and Mn₃O₄ nanoparticles, and all are three-dimensionally interconnected to each other by hybrid polyaniline/sodium alginate (PANI-SA) matrix to serve individual purposes. A capacity of 1098 mAh g^-1 is achieved against lithium after 200 cycles at a current rate of 2 A g^-1 with 97.6% of initial capacity at a same current rate, suggesting the extreme stability and cycling performance of such electrode. Interestingly, with the higher current density of 5 A g^-1, the composite electrode exhibited an initial capacity of 1015 mA h g^-1 and retained 71% of the original capacity after 500 cycles. The in situ Raman study confirms the polysulfide absorption capability of Mn₃O₄. This work provides a new strategy to design a mechanically robust, mixed conductive nanocomposite electrode for high-performance lithium-sulfur batteries and a strategy that can be used to develop flexible large power storage devices.

The Search Conference as a Method in Planning Community Health Promotion Actions

Aims: The aim of this article is to describe and discuss how the search conference can be used as a method for planning health promotion actions in local communities.

Design and methods: The article draws on experiences with using the method for an innovative project in health promotion in three Norwegian municipalities. The method is described both in general and how it was specifically adopted for the project.

Results and conclusions: The search conference as a method was used to develop evidence-based health promotion action plans. With its use of both bottom-up and top-down approaches, this method is a relevant strategy for involving a community in the planning stages of health promotion actions in line with political expectations of participation, ownership, and evidence-based initiatives.

Fabrication of intrafibrillar and extrafibrillar mineralized collagen/apatite scaffolds with a hierarchical structure

A biomimetic collagen-apatite (Col-Ap) scaffold resembling the composition and structure of natural bone from the nanoscale to the macroscale has been successfully prepared for bone tissue engineering. We have developed a bottom-up approach to fabricate hierarchically biomimetic Col-Ap scaffolds with both intrafibrillar and extrafibrillar mineralization. To achieve intrafibrillar mineralization, polyacrylic acid (PAA) was used as a sequestrating analog of noncollagenous proteins (NCPs) to form a fluidic amorphous calcium phosphate (ACP) nanoprecursor through attraction of calcium and phosphate ions. Sodium tripolyphosphate was used as a templating analog to regulate orderly deposition of apatite within collagen fibrils. Both X-ray diffraction and Fourier transform infrared spectroscopy suggest that the mineral phase was apatite. Field emission scanning electron microscopy, transmission electron microscopy, and selected area electron diffraction confirmed that hierarchical collagen-Ap scaffolds were produced with both intrafibrillar and extrafibrillar mineralization. Biomimetic Col-Ap scaffolds with both intrafibrillar and extrafibrillar mineralization (IE-Col-Ap) were compared with Col-Ap scaffolds with extrafibrillar mineralization only (E-Col-Ap) as well as pure collagen scaffolds in vitro for cellular proliferation using MC3T3-E1 cells. Pure collagen scaffolds had the highest rate of proliferation, while there was no statistically significant difference between IE-Col-Ap and E-Col-Ap scaffolds. Thus, the bottom-up biomimetic fabrication approach has rendered a group of promising Col-Ap scaffolds, which bear high resemblance to natural bone in terms of composition and structure.

Construction of Modular Hydrogel Sheets for Micropatterned Macro-scaled 3D Cellular Architecture

Hydrogels can be patterned at the micro-scale using microfluidic or micropatterning technologies to provide an in vivo-like three-dimensional (3D) tissue geometry. The resulting 3D hydrogel-based cellular constructs have been introduced as an alternative to animal experiments for advanced biological studies, pharmacological assays and organ transplant applications. Although hydrogel-based particles and fibers can be easily fabricated, it is difficult to manipulate them for tissue reconstruction. In this video, we describe a fabrication method for micropatterned alginate hydrogel sheets, together with their assembly to form a macro-scale 3D cell culture system with a controlled cellular microenvironment. Using a mist form of the calcium gelling agent, thin hydrogel sheets are easily generated with a thickness in the range of 100 - 200 µm, and with precise micropatterns. Cells can then be cultured with the geometric guidance of the hydrogel sheets in freestanding conditions. Furthermore, the hydrogel sheets can be readily manipulated using a micropipette with an end-cut tip, and can be assembled into multi-layered structures by stacking them using a patterned polydimethylsiloxane (PDMS) frame. These modular hydrogel sheets, which can be fabricated using a facile process, have potential applications of in vitro drug assays and biological studies, including functional studies of micro- and macrostructure and tissue reconstruction.

The Economic Burden of Obesity in Germany: Results from the Population-Based KORA Studies

OBJECTIVE

To estimate the excess costs of obese compared to normal-weight persons in Germany based on self-reported resource utilisation and work absence.

METHODS

Five cross sectional surveys of cohort studies in southern Germany were pooled resulting in 9,070 observations for 6,731 individuals (31-96 years). BMI was measured in the study centre. Self-reported health care utilisation and work absence was used to estimate direct and indirect costs for the year 2011 based on unit costs. Using regression analyses, adjusted costs for different BMI groups were calculated.

RESULTS

Overweight and obese people showed significantly higher odds of health care utilisation and productivity losses compared with normal-weight people in most categories. Total direct/indirect costs were significantly higher with increasing severity of obesity (pre-obese (1.05 (0.90-1.23) / 1.38 (1.11-1.71)), obesity level I (1.18 (1.00-1.39) / 1.33 (1.02-1.73)), obesity level II (1.46 (1.14-1.87) / 1.77 (1.18-2.65)) or level III (2.04 (1.40-2.97) / 1.99 (1.20-3.30)) compared to normal-weight participants. In particular, higher obesity classes were significantly associated with increased costs for medication, general practitioner utilisation and work absence.

CONCLUSION

Our results show that overweight and obesity are associated with enormous societal direct and indirect costs in Germany. This supports the evidence from previous top-down studies, but provides important new information based on a large pooled data set and measured BMI.

Exploring the Life Expectancy Increase in Poland in the Context of CVD Mortality Fall: The Risk Assessment Bottom-Up Approach, From Health Outcome to Policies

Life expectancy at birth is considered the best mortality-based summary indicator of the health status of the population and is useful for measuring long-term health changes. The objective of this article was to present the concept of the bottom-up policy risk assessment approach, developed to identify challenges involved in analyzing risk factor reduction policies and in assessing how the related health indicators have changed over time. This article focuses on the reasons of the significant life expectancy prolongation in Poland over the past 2 decades, thus includes policy context. The methodology details a bottom-up risk assessment approach, a chain of relations between the health outcome, risk factors, and health policy, based on Risk Assessment From Policy to Impact Dimension project guidance. A decline in cardiovascular disease mortality was a key factor that followed life expectancy prolongation. Among basic factors, tobacco and alcohol consumption, diet, physical activity, and new treatment technologies were identified. Poor health outcomes of the Polish population at the beginning of 1990s highlighted the need of the implementation of various health promotion programs, legal acts, and more effective public health policies. Evidence-based public health policy needs translating scientific research into policy and practice. The bottom-up case study template can be one of the focal tools in this process. Accountability for the health impact of policies and programs and legitimization of the decisions of policy makers has become one of the key questions nowadays in European countries' decision-making process and in EU public health strategy.

Graphene-like single-layered covalent organic frameworks: synthesis strategies and application prospects

Two-dimensional (2D) nanomaterials, such as graphene and transition metal chalcogenides, show many interesting dimension-related materials properties. Inspired by the development of 2D inorganic nanomaterials, single-layered covalent organic frameworks (sCOFs), featuring atom-thick sheets and crystalline extended organic structures with covalently bonded building blocks, have attracted great attention in recent years. With their unique graphene-like topological structure and the merit of structural diversity, sCOFs promise to possess novel and designable properties. However, the synthesis of sCOFs with well-defined structures remains a great challenge. Herein, the recent development of the bottom-up synthesis methods of 2D sCOFs, such as thermodynamic equilibrium control methods, growth-kinetics control methods, and surface-assisted covalent polymerization methods, are reviewed. Finally, some of the critical properties and application prospects of these materials are outlined.

Cluster-assembled metallic glasses

A bottom-up approach to nanofabricate metallic glasses from metal clusters as building blocks is presented. Considering metallic glasses as a subclass of cluster-assembled materials, the relation between the two lively fields of metal clusters and metallic glasses is pointed out. Deposition of selected clusters or collections of them, generated by state-of-the-art cluster beam sources, could lead to the production of a well-defined amorphous material. In contrast to rapidly quenched glasses where only the composition of the glass can be controlled, in cluster-assembled glasses, one can precisely control the structural building blocks. Comparing properties of glasses with similar compositions but differing in building blocks and therefore different in structure will facilitate the study of structure-property correlation in metallic glasses. This bottom-up method provides a novel alternative path to the synthesis of glassy alloys and will contribute to improving fundamental understanding in the field of metallic glasses. It may even permit the production of glassy materials for alloys that cannot be quenched rapidly enough to circumvent crystallization. Additionally, gaining deeper insight into the parameters governing the structure-property relation in metallic glasses can have a great impact on understanding and design of other cluster-assembled materials.

Light propagation in high-spin organic microtubes self-assembled from shape persistent macrocycles carrying oxo-verdazyl biradicals

A 1D paramagnetic organic tube self-assembled from a "clicked" shape-persistent macrocycle carrying high-spin oxoverdazyl biradicals shows optical wave guiding behavior.