Construction of high-performance and sustainable polylactic acid composites for 3D printing applications with plasticizer.

Polylactic acid (PLA) attains much attention because of its biodegradability, biocompatibility, and high strength, but its further application was remarkably hindered by its brittleness. In order to improve the toughness of PLA, a biodegradable composite was prepared by blending ductile polycaprolactone (PCL), stiff microcrystalline cellulose (MCC), and green plasticizer tributyl citrate (TBC) with PLA by melting extrusion. The physicochemical properties and microstructure of PLA composites were thoroughly investigated using FTIR, TGA, DSC, XRD, melting rheology, optical transmittance, 3d printing, tensile tests, and SEM. The tensile tests results show that introduction of TBC exhibited a remarkable improvement effect in the elongation at break of PLA/PCL/MCC (PPM) composite, increasing from 2.9 % of PPM to up to 30 % of PPM/6TBC and PPM/8TBC. Noticeably, the strength of PPM/TBC composites (at least 33.1 MPa) was enhanced compared with that of PPM (28.2 MPa). The plasticization of TBC, enhancing the compatibility of composites, and reinforcing effect of MCC were identified as pivotal factors in toughening and reinforcing PLA. Furthermore, it is observed that the incorporation of TBC contributed to enhanced thermal stability, crystallinity, and rheology property of composites. This research supplies a novel approach to bolstering the toughness of PLA and broaden its potential applications.

METTL16 promotes liver cancer stem cell self-renewal via controlling ribosome biogenesis and mRNA translation.

BACKGROUND: While liver cancer stem cells (CSCs) play a crucial role in hepatocellular carcinoma (HCC) initiation, progression, recurrence, and treatment resistance, the mechanism underlying liver CSC self-renewal remains elusive. We aim to characterize the role of Methyltransferase 16 (METTL16), a recently identified RNA N6-methyladenosine (m6A) methyltransferase, in HCC development/maintenance, CSC stemness, as well as normal hepatogenesis. METHODS: Liver-specific Mettl16 conditional KO (cKO) mice were generated to assess its role in HCC pathogenesis and normal hepatogenesis. Hydrodynamic tail-vein injection (HDTVi)-induced de novo hepatocarcinogenesis and xenograft models were utilized to determine the role of METTL16 in HCC initiation and progression. A limiting dilution assay was utilized to evaluate CSC frequency. Functionally essential targets were revealed via integrative analysis of multi-omics data, including RNA-seq, RNA immunoprecipitation (RIP)-seq, and ribosome profiling. RESULTS: METTL16 is highly expressed in liver CSCs and its depletion dramatically decreased CSC frequency in vitro and in vivo. Mettl16 KO significantly attenuated HCC initiation and progression, yet only slightly influenced normal hepatogenesis. Mechanistic studies, including high-throughput sequencing, unveiled METTL16 as a key regulator of ribosomal RNA (rRNA) maturation and mRNA translation and identified eukaryotic translation initiation factor 3 subunit a (eIF3a) transcript as a bona-fide target of METTL16 in HCC. In addition, the functionally essential regions of METTL16 were revealed by CRISPR gene tiling scan, which will pave the way for the development of potential inhibitor(s). CONCLUSIONS: Our findings highlight the crucial oncogenic role of METTL16 in promoting HCC pathogenesis and enhancing liver CSC self-renewal through augmenting mRNA translation efficiency.

Effect of Stabilizers and Thermoplastic Polyurethane on the Properties of Three-Dimensional Printed Photochromic Wood Flour/Polylactic Acid Composites.

This study was aimed at investigating the photofatigue resistance and mechanical properties of photochromic wood-plastic composites using a stabilizer complex-AH (antioxidant 1010 and hindered amine light stabilizer HALS 770)-with different contents of thermoplastic polyurethane (TPU), which was prepared by the melt-blending extrusion process and three-dimensional (3D) printing. Photofatigue resistance, mechanical property, microtopography, and thermal analyses of 3D printed samples were performed. The results showed that the difference in surface color of composites improved by 26.7% with addition of AH after 10 days of accelerated aging, whereas the mechanical strength decreased. Upon adding TPU, composites' impact strength significantly increased by 25.48% and 87.87% with 10% and 20% addition, respectively. Meanwhile, the interface compatibilities between the components were enhanced. The differential scanning calorimetry and thermogravimetric analysis results indicated that 10% TPU could improve the thermal stability of composites.

Macrocyclization of linear molecules by deep learning to facilitate macrocyclic drug candidates discovery.

Interest in macrocycles as potential therapeutic agents has increased rapidly. Macrocyclization of bioactive acyclic molecules provides a potential avenue to yield novel chemical scaffolds, which can contribute to the improvement of the biological activity and physicochemical properties of these molecules. In this study, we propose a computational macrocyclization method based on Transformer architecture (which we name Macformer). Leveraging deep learning, Macformer explores the vast chemical space of macrocyclic analogues of a given acyclic molecule by adding diverse linkers compatible with the acyclic molecule. Macformer can efficiently learn the implicit relationships between acyclic and macrocyclic structures represented as SMILES strings and generate plenty of macrocycles with chemical diversity and structural novelty. In data augmentation scenarios using both internal ChEMBL and external ZINC test datasets, Macformer display excellent performance and generalisability. We showcase the utility of Macformer when combined with molecular docking simulations and wet lab based experimental validation, by applying it to the prospective design of macrocyclic JAK2 inhibitors.

The innovative model based on artificial intelligence algorithms to predict recurrence risk of patients with postoperative breast cancer.

Purpose: This study aimed to develop a machine learning model to retrospectively study and predict the recurrence risk of breast cancer patients after surgery by extracting the clinicopathological features of tumors from unstructured clinical electronic health record (EHR) data. Methods: This retrospective cohort included 1,841 breast cancer patients who underwent surgical treatment. To extract the principal features associated with recurrence risk, the clinical notes and histopathology reports of patients were collected and feature engineering was used. Predictive models were next conducted based on this important information. All algorithms were implemented using Python software. The accuracy of prediction models was further verified in the test cohort. The area under the curve (AUC), precision, recall, and F1 score were adopted to evaluate the performance of each model. Results: A training cohort with 1,289 patients and a test cohort with 552 patients were recruited. From 2011 to 2019, a total of 1,841 textual reports were included. For the prediction of recurrence risk, both LSTM, XGBoost, and SVM had favorable accuracies of 0.89, 0.86, and 0.78. The AUC values of the micro-average ROC curve corresponding to LSTM, XGBoost, and SVM were 0.98 ± 0.01, 0.97 ± 0.03, and 0.92 ± 0.06. Especially the LSTM model achieved superior execution than other models. The accuracy, F1 score, macro-avg F1 score (0.87), and weighted-avg F1 score (0.89) of the LSTM model produced higher values. All P values were statistically significant. Patients in the high-risk group predicted by our model performed more resistant to DNA damage and microtubule targeting drugs than those in the intermediate-risk group. The predicted low-risk patients were not statistically significant compared with intermediate- or high-risk patients due to the small sample size (188 low-risk patients were predicted via our model, and only two of them were administered chemotherapy alone after surgery). The prognosis of patients predicted by our model was consistent with the actual follow-up records. Conclusions: The constructed model accurately predicted the recurrence risk of breast cancer patients from EHR data and certainly evaluated the chemoresistance and prognosis of patients. Therefore, our model can help clinicians to formulate the individualized management of breast cancer patients.

Amplitude-mediated chimera states in nonlocally coupled Stuart-Landau oscillators.

Chimera states achieve the coexistence of coherent and incoherent subgroups through symmetry breaking and emerge in physical, chemical, and biological systems. We show the presence of amplitude-mediated multicluster chimera states in nonlocally coupled Stuart-Landau oscillators. We clarify the prerequisites for having different types of chimera states by analytically and numerically studying how phase transitions occur between these states. Our results demonstrate how the oscillation amplitudes interact with the phase degrees of freedom in chimera states and significantly advance our understanding of the generation mechanisms of such states in coupled oscillator systems.

3D printing with high content of lignin enabled by introducing polyurethane.

The efficient utilization of lignin in 3D printing had attracted increasing attention using this abundant and eco-friendly material. However, the large-scale utilization of lignin in 3D printing remains a great challenge due to its inherent brittleness and non-thermoplasticity. In this study, thermoplastic polyurethane (TPU) was introduced to regulate the rheological properties of lignin for 3D printing. The Lignin/TPU composite of 3D printing exhibited a smooth surface, non-plastic, warm wood touch, and natural color at 50 wt% lignin loading. To further improve the mechanical properties of the composite, carbon fiber (CF) was added to the Lignin/TPU composite. The resulting CF/Lignin/TPU composites possessed 1.7 times higher tensile strength and 2.4 times higher elongation at break compared to Lignin/TPU composite. Meanwhile, the smooth surface of filament and dense interlayer bonds of printed specimens are also achieved. This work provides new insights to realize the high-value utilization of lignin and expands the practical application of lignin in 3D printing.

Elevated expression of the rhythm gene NFIL3 promotes the progression of TNBC by activating NF-κB signaling through suppression of NFKBIA transcription.

BACKGROUND: Epidemiological studies have confirmed that abnormal circadian rhythms are associated with tumorigenesis in breast cancer. However, few studies have investigated the pathological roles of rhythm genes in breast cancer progression. In this study, we aimed to evaluate the aberrant expression of 32 rhythm genes in breast cancer and detect the pathological roles and molecular mechanisms of the altered rhythm gene in regulating the progression of triple negative breast cancer (TNBC). METHODS: The aberrant expression of rhythm genes in breast cancer was screened by searching the GEPIA database and validated by using qRT-PCR and immunohistochemistry staining. Bioinformatics analysis combined with luciferase reporter experiment and chromatinimmunopercitation (ChIP) were used to investigate the molecular mechanism about aberrant expression of identified rhythm gene in breast cancer. The pathological roles of identified rhythm gene in TNBC progression was evaluated by colony formation assay, wound healing experiment, transwell assay, subcutaneous tumor formation and the mouse tail vein injection model through gain-of-function and loss-of-function strategies respectively. mRNA array, bioinformatics analysis, luciferase reporter experiment, ChIP and immunoflurescence assay were employed to investigate the key molecules and signaling pathways by which the identified rhythm gene regulating TNBC progression. RESULTS: We identified that nuclear factor interleukin 3 regulated (NFIL3) expression is significantly altered in TNBC compared with both normal breast tissues and other subtypes of breast cancer. We found that NFIL3 inhibits its own transcription, and thus, downregulated NFIL3 mRNA indicates high expression of NFIL3 protein in breast cancer. We demonstrated that NFIL3 promotes the proliferation and metastasis of TNBC cells in vitro and in vivo, and higher expression of NFIL3 is associated with poor prognosis of patients with TNBC. We further demonstrated that NFIL3 enhances the activity of NF-κB signaling. Mechanistically, we revealed that NFIL3 directly suppresses the transcription of NFKBIA, which blocks the activation of NF-κB and inhibits the progression of TNBC cells in vitro and in vivo. Moreover, we showed that enhancing NF-κB activity by repressing NFKBIA largely mimics the oncogenic effect of NFIL3 in TNBC, and anti-inflammatory strategies targeting NF-κB activity block the oncogenic roles of NFIL3 in TNBC. CONCLUSION: NFIL3 promotes the progression of TNBC by suppressing NFKBIA transcription and then enhancing NF-κB signaling-mediated cancer-associated inflammation. This study may provide a new target for TNBC prevention and therapy.

Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks.

Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain.

3D Modeling of Epithelial Tumors-The Synergy between Materials Engineering, 3D Bioprinting, High-Content Imaging, and Nanotechnology.

The current statistics on cancer show that 90% of all human cancers originate from epithelial cells. Breast and prostate cancer are examples of common tumors of epithelial origin that would benefit from improved drug treatment strategies. About 90% of preclinically approved drugs fail in clinical trials, partially due to the use of too simplified in vitro models and a lack of mimicking the tumor microenvironment in drug efficacy testing. This review focuses on the origin and mechanism of epithelial cancers, followed by experimental models designed to recapitulate the epithelial cancer structure and microenvironment, such as 2D and 3D cell culture models and animal models. A specific focus is put on novel technologies for cell culture of spheroids, organoids, and 3D-printed tissue-like models utilizing biomaterials of natural or synthetic origins. Further emphasis is laid on high-content imaging technologies that are used in the field to visualize in vitro models and their morphology. The associated technological advancements and challenges are also discussed. Finally, the review gives an insight into the potential of exploiting nanotechnological approaches in epithelial cancer research both as tools in tumor modeling and how they can be utilized for the development of nanotherapeutics.

Effect of amorphous cellulose on the deformation behavior of cellulose composites: molecular dynamics simulation.

This study was aimed at predicting and enhancing the properties of the blend, as well as exploring the mechanism, of a polylactic acid (PLA)/amorphous cellulose composite system through molecular characterization. The static properties of the amorphous cellulose/PLA blend model and the mechanical response of the material under uniaxial tension were studied by molecular dynamics simulation to establish the structure-property relationship. PLA and cellulose showed poor miscibility, the change in the compatibility of the mixture can be attributed to the hydrogen bond interaction between the cellulose and PLA functional groups. The radius of gyration, interaction and free volume of the molecular chain in the blend were analyzed. The conformational changes under tensile deformation indicated that the load-bearing role of cellulose in the system was the main reason for increasing the strength of the material. The yield process was considered to be the infiltration of free volume caused by deformation.

Theta-Nested Gamma Oscillations in Next Generation Neural Mass Models.

Theta-nested gamma oscillations have been reported in many areas of the brain and are believed to represent a fundamental mechanism to transfer information across spatial and temporal scales. In a series of recent experiments in vitro it has been possible to replicate with an optogenetic theta frequency stimulation several features of cross-frequency coupling (CFC) among theta and gamma rhythms observed in behaving animals. In order to reproduce the main findings of these experiments we have considered a new class of neural mass models able to reproduce exactly the macroscopic dynamics of spiking neural networks. In this framework, we have examined two set-ups able to support collective gamma oscillations: namely, the pyramidal interneuronal network gamma (PING) and the interneuronal network gamma (ING). In both set-ups we observe the emergence of theta-nested gamma oscillations by driving the system with a sinusoidal theta-forcing in proximity of a Hopf bifurcation. These mixed rhythms always display phase amplitude coupling. However, two different types of nested oscillations can be identified: one characterized by a perfect phase locking between theta and gamma rhythms, corresponding to an overall periodic behavior; another one where the locking is imperfect and the dynamics is quasi-periodic or even chaotic. From our analysis it emerges that the locked states are more frequent in the ING set-up. In agreement with the experiments, we find theta-nested gamma oscillations for forcing frequencies in the range [1:10] Hz, whose amplitudes grow proportionally to the forcing intensity and which are clearly modulated by the theta phase. Furthermore, analogously to the experiments, the gamma power and the frequency of the gamma-power peak increase with the forcing amplitude. At variance with experimental findings, the gamma-power peak does not shift to higher frequencies by increasing the theta frequency. This effect can be obtained, in our model, only by incrementing, at the same time, also the stimulation power. An effect achieved by increasing the amplitude either of the noise or of the forcing term proportionally to the theta frequency. On the basis of our analysis both the PING and the ING mechanism give rise to theta-nested gamma oscillations with almost identical features.

Lightweight, Anisotropic, Compressible, and Thermally-Insulating Wood Aerogels with Aligned Cellulose Fibers.

The growing demand for lightweight, renewable, and excellent thermal insulation materials has fueled a search for high performance biomass materials with good mechanical compressibility and ultralow thermal conductivity. We propose a fabrication method for making a lightweight, anisotropic, and compressible wood aerogel with aligned cellulose fibers by a simple chemical treatment. The wood aerogel was mainly composed of highly aligned cellulose fibers with a relative crystallinity of 77.1%. The aerogel exhibits a low density of 32.18 mg/cm3 and a high specific surface area of 31.68 m2/g due to the removal of lignin and hemicellulose from the wood. Moreover, the multilayer structure of the aerogel was formed under the restriction of wood rays. Combined with a nanoscale pore, the aerogel presents good compressibility and an ultralow thermal conductivity of 0.033 W/mK. These results show that the wood aerogel is a high quality biomass material with a potential function of thermal insulation through optimizing structures.

Three-Dimensional-Printed Shape Memory Biomass Composites for Thermal-Responsive Devices.

In this study, unique three-dimensional (3D)-printed shape memory biomass composites were prepared by the melt blending and extrusion of polyurethane, polycaprolactone (PCL), and wood flour (WF) with adjustable contents. The addition content of PCL was used to adjust the shape memory transition temperature and improve the shape fixing rate of composites. The crystallization, thermal, mechanical, and shape memory properties of different composites were investigated. The results of X-ray diffraction and differential scanning calorimetry tests showed that the crystallization peak and melting temperature of different composites were not obviously changed. As the PCL content increased, the tensile strength of the composites decreased first and then increased, and the elongation at break gradually decreased. Thermal response shape memory test results showed that, when the PCL content was 30 wt.%, the composites had high shape recovery rate and fixed rate (both ∼100%). In addition, carbon black (CB) was added as a photothermal conversion material to the composite with a preferred ratio to achieve the photothermal response shape memory performance. With the addition of CB, the thermal conductivity of composites was improved. Under the same conditions, the thicker the 3D-printed specimens, the longer the specimen shape recovery time; the greater the light intensity, the shorter the specimen shape recovery time. Compared with the composite without CB, the flower model printed with the composites containing CB had a better photothermal response shape memory performance.

Interfacial Adhesion of Polylactic Acid on Cellulose Surface: A Molecular Dynamics Study.

Interfacial bonding and adhesion mechanisms are important in determining the final properties of the polymer composite. Molecular dynamics (MD) simulations have been used to characterize the interfacial structure and adhesion behavior of crystalline cellulose planes in contact with polylactic acid. The structure of the PLA at the interface exhibits a shape that can accommodate the structure of the cellulose surface. The adhesion between the PLA and the cellulose surface is affected by the polarity of the functional groups and the surface roughness. The improved adhesion is primarily due to hydrogen bonds formed between the cellulose and PLA molecular chains. Cellulose planes with higher molecular protrusions and greater surface roughness produce stronger adhesion to PLA due to enhanced hydrogen bonding. This study provides a basic insight into the interfacial mechanisms of PLA and cellulose surfaces at the molecular level.

Preparation and Characterization of 3D Printed PLA-Based Conductive Composites Using Carbonaceous Fillers by Masterbatch Melting Method.

This study was aimed at improving the conductivity of polylactic acid (PLA)-based composites by incorporating carbonaceous fillers. The composites with the addition of graphene nanoplatelets (rGO) or multi-walled carbon nanotubes (MWCNTs) were fabricated by the masterbatch melting method in order to improve the dispersion of the two kinds of nano-fillers. The results showed that, with the addition of 9 wt % rGO, the volume electrical resistivity of the composite reached the minimum electrical resistance of 103 Ω·m, at which point the conductive network in the composites was completely formed. The interfacial compatibility, apparent viscosity, and the thermal stability of the composite were also good. The rGO functionalized by sodium dodecylbenzene sulfonate (SDBS) was an efficient method to further improve the electrical conductivity of the composite, compared with tannic acid and MWCNTs. The resistivity was reduced by an order in magnitude. Patterns printed onto different baseplates by fused deposition modeling illustrated that the functionalized composite had certain flexibility and it is suitable for printing complex shapes.

Electrical and Thermal Conductivity of Polylactic Acid (PLA)-Based Biocomposites by Incorporation of Nano-Graphite Fabricated with Fused Deposition Modeling.

The aim of the study was to improve the electrical and thermal conductivity of the polylactic acid/wood flour/thermoplastic polyurethane composites by Fused Deposition Modeling (FDM). The results showed that, when the addition amount of nano-graphite reached 25 pbw, the volume resistivity of the composites decreased to 108 Ω·m, which was a significant reduction, indicating that the conductive network was already formed. It also had good thermal conductivity, mechanical properties, and thermal stability. The adding of the redox graphene (rGO) combined with graphite into the composites, compared to the tannic acid-functionalized graphite or the multi-walled carbon nanotubes, can be an effective method to improve the performance of the biocomposites, because the resistivity reduced by one order magnitude and the thermal conductivity increased by 25.71%. Models printed by FDM illustrated that the composite filaments have a certain flexibility and can be printed onto paper or flexible baseplates.

Mechanical, Thermal, and Shape Memory Properties of Three-Dimensional Printing Biomass Composites.

In this study, a series of heat-induced shape memory composites was prepared by the hot-melt extrusion and three-dimensional (3D) printing of thermoplastic polyurethane (TPU) using wood flour (WF) with different contents of EPDM-g-MAH. The mechanical properties, microtopography, thermal property analysis, and heat-induced shape memory properties of the composites were examined. The results showed that, when the EPDM-g-MAH content was 4%, the tensile elongation and tensile strength of the composites reached the maximum value. The scanning electron microscopy and dynamic mechanical analysis results revealed a good interface bonding between TPU and WF when the EPDM-g-MAH content was 4%. The thermogravimetric analysis indicated that the thermal stability of TPU/WF composites was enhanced by the addition of 4% EPDM-g-MAH. Heat-induced shape memory test results showed that the shape memory performance of composites with 4% EPDM-g-MAH was better than that of unmodified-composites. The composites' shape recovery performance at a temperature of 60 °C was higher than that of the composites at ambient temperature. It was also found that, when the filling angle of the specimen was 45°, the recovery angle of the composites was larger.

Asymmetric couplings enhance the transition from chimera state to synchronization.

Chimera state has been well studied recently, but little attention has been paid to its transition to synchronization. We study this topic here by considering two groups of adaptively coupled Kuramoto oscillators. By searching the final states of different initial conditions, we find that the system can easily show a chimera state with robustness to initial conditions, in contrast to the sensitive dependence of chimera state on initial conditions in previous studies. Further, we show that, in the case of symmetric couplings, the behaviors of the two groups are always complementary to each other, i.e., robustness of chimera state, except a small basin of synchronization. Interestingly, we reveal that the basin of synchronization will be significantly increased when either the coupling of inner groups or that of intergroups are asymmetric. This transition from the attractor of chimera state to the attractor of synchronization is closely related to both the phase delay and the asymmetric degree of coupling strengths, resulting in a diversity of attractor's patterns. A theory based on the Ott-Antonsen ansatz is given to explain the numerical simulations. This finding may be meaningful for the control of competition between two attractors in biological systems, such as the cardiac rhythm and ventricular fibrillation, etc.

Coexistence of Quantized, Time Dependent, Clusters in Globally Coupled Oscillators.

We report on a novel collective state, occurring in globally coupled nonidentical oscillators in the proximity of the point where the transition from the system's incoherent to coherent phase converts from explosive to continuous. In such a state, the oscillators form quantized clusters, where neither their phases nor their instantaneous frequencies are locked. The oscillators' instantaneous speeds are different within the clusters, but they form a characteristic cusped pattern and, more importantly, they behave periodically in time so that their average values are the same. Given its intrinsic specular nature with respect to the recently introduced Chimera states, the phase is termed the Bellerophon state. We provide an analytical and numerical description of Bellerophon states, and furnish practical hints on how to seek them in a variety of experimental and natural systems.