Pedicled abdominal flap using deep inferior epigastric artery perforators for forearm reconstruction: A case report.

BACKGROUND: Pedicled abdominal flaps are a widely used surgical technique for forearm reconstruction in patients with soft tissue defects. However, some drawbacks include restricted flap size, partial flap loss, and donor-site morbidity. To address these concerns, we present a case of a pedicled abdominal flap using the deep inferior epigastric artery perforators (DIEP) for forearm reconstruction in a patient with a large soft tissue defect. CASE SUMMARY: A 46-year-old male patient was admitted to our hospital with forearm injury caused by a pressing machine. A 15 cm × 10 cm soft tissue defect with complete rupture of the ulnar side structures of the forearm was found. One week after orthopedic management of the neurovascular injury and fractures using the first stage of Masquelet technique, the patient was referred to the plastic and reconstructive surgery department for wound coverage. Surgical debridement and negative-pressure wound therapy revealed a 20 cm × 15 cm soft tissue defect. A pedicle abdominal flap with the DIEP was used to cover the defect. Three weeks later, the flap was detached from the abdomen, and the abdominal defect was directly closed. Subsequently, the second stage of Masquelet technique was performed at the fracture site at week 10. Finally, all donor and recipient sites healed without complications, such as flap dehiscence, infection, hematoma, or necrosis. Fracture site osteosynthesis was achieved without complications. CONCLUSION: Pedicled abdominal flap using the DIEP provides a reliable option for forearm reconstruction in patients with large soft tissue defects.

Statistical modeling of mRNP transport in dendrites: A comparative analysis of ß-actin and Arc mRNP dynamics.

Localization of messenger RNA (mRNA) in dendrites is crucial for regulating gene expression during long-term memory formation. mRNA binds to RNA-binding proteins (RBPs) to form messenger ribonucleoprotein (mRNP) complexes that are transported by motor proteins along microtubules to their target synapses. However, the dynamics by which mRNPs find their target locations in the dendrite have not been well understood. Here, we investigated the motion of endogenous ß-actin and Arc mRNPs in dissociated mouse hippocampal neurons using the MS2 and PP7 stem-loop systems, respectively. By evaluating the statistical properties of mRNP movement, we found that the aging Lévy walk model effectively describes both ß-actin and Arc mRNP transport in proximal dendrites. A critical difference between ß-actin and Arc mRNPs was the aging time, the time lag between transport initiation and measurement initiation. The longer mean aging time of ß-actin mRNP (~100 s) compared with that of Arc mRNP (~30 s) reflects the longer half-life of constitutively expressed ß-actin mRNP. Furthermore, our model also permitted us to estimate the ratio of newly generated and pre-existing ß-actin mRNPs in the dendrites. This study offers a robust theoretical framework for mRNP transport, which provides insight into how mRNPs locate their targets in neurons.

Nonequilibrium diffusion of active particles bound to a semiflexible polymer network: Simulations and fractional Langevin equation.

In a viscoelastic environment, the diffusion of a particle becomes non-Markovian due to the memory effect. An open question concerns quantitatively explaining how self-propulsion particles with directional memory diffuse in such a medium. Based on simulations and analytic theory, we address this issue with active viscoelastic systems where an active particle is connected with multiple semiflexible filaments. Our Langevin dynamics simulations show that the active cross-linker displays superdiffusive and subdiffusive athermal motion with a time-dependent anomalous exponent α. In such viscoelastic feedback, the active particle always exhibits superdiffusion with α = 3/2 at times shorter than the self-propulsion time (τA). At times greater than τA, the subdiffusive motion emerges with α bounded between 1/2 and 3/4. Remarkably, active subdiffusion is reinforced as the active propulsion (Pe) is more vigorous. In the high Pe limit, athermal fluctuation in the stiff filament eventually leads to α = 1/2, which can be misinterpreted with the thermal Rouse motion in a flexible chain. We demonstrate that the motion of active particles cross-linking a network of semiflexible filaments can be governed by a fractional Langevin equation combined with fractional Gaussian noise and an Ornstein-Uhlenbeck noise. We analytically derive the velocity autocorrelation function and mean-squared displacement of the model, explaining their scaling relations as well as the prefactors. We find that there exist the threshold Pe (Pe∗) and crossover times (τ∗ and τ†) above which active viscoelastic dynamics emerge on timescales of τ∗≲ t ≲ τ†. Our study may provide theoretical insight into various nonequilibrium active dynamics in intracellular viscoelastic environments.

A machine learning approach to discover migration modes and transition dynamics of heterogeneous dendritic cells.

Dendritic cell (DC) migration is crucial for mounting immune responses. Immature DCs (imDCs) reportedly sense infections, while mature DCs (mDCs) move quickly to lymph nodes to deliver antigens to T cells. However, their highly heterogeneous and complex innate motility remains elusive. Here, we used an unsupervised machine learning (ML) approach to analyze long-term, two-dimensional migration trajectories of Granulocyte-macrophage colony-stimulating factor (GMCSF)-derived bone marrow-derived DCs (BMDCs). We discovered three migratory modes independent of the cell state: slow-diffusive (SD), slow-persistent (SP), and fast-persistent (FP). Remarkably, imDCs more frequently changed their modes, predominantly following a unicyclic SD→FP→SP→SD transition, whereas mDCs showed no transition directionality. We report that DC migration exhibits a history-dependent mode transition and maturation-dependent motility changes are emergent properties of the dynamic switching of the three migratory modes. Our ML-based investigation provides new insights into studying complex cellular migratory behavior.

Formation of cellular close-ended tunneling nanotubes through mechanical deformation.

Membrane nanotubes or tunneling nanotubes (TNTs) that connect cells have been recognized as a previously unidentified pathway for intercellular transport between distant cells. However, it is unknown how this delicate structure, which extends over tens of micrometers and remains robust for hours, is formed. Here, we found that a TNT develops from a double filopodial bridge (DFB) created by the physical contact of two filopodia through helical deformation of the DFB. The transition of a DFB to a close-ended TNT is most likely triggered by disruption of the adhesion of two filopodia by mechanical energy accumulated in a twisted DFB when one of the DFB ends is firmly attached through intercellular cadherin-cadherin interactions. These studies pinpoint the mechanistic questions about TNTs and elucidate a formation mechanism.

Fractal and Knot-Free Chromosomes Facilitate Nucleoplasmic Transport.

Chromosomes in the nucleus assemble into hierarchies of 3D domains that, during interphase, share essential features with a knot-free condensed polymer known as the fractal globule (FG). The FG-like chromosome likely affects macromolecular transport, yet its characteristics remain poorly understood. Using computer simulations and scaling analysis, we show that the 3D folding and macromolecular size of the chromosomes determine their transport characteristics. Large-scale subdiffusion occurs at a critical particle size where the network of accessible volumes is critically connected. Condensed chromosomes have connectivity networks akin to simple Bernoulli bond percolation clusters, regardless of the polymer models. However, even if the network structures are similar, the tracer's walk dimension varies. It turns out that the walk dimension depends on the network topology of the accessible volume and dynamic heterogeneity of the tracer's hopping rate. We find that the FG structure has a smaller walk dimension than other random geometries, suggesting that the FG-like chromosome structure accelerates macromolecular diffusion and target-search.

Stochastic chromatin packing of 3D mitotic chromosomes revealed by coherent X-rays.

DNA molecules are atomic-scale information storage molecules that promote reliable information transfer via fault-free repetitions of replications and transcriptions. Remarkable accuracy of compacting a few-meters-long DNA into a micrometer-scale object, and the reverse, makes the chromosome one of the most intriguing structures from both physical and biological viewpoints. However, its three-dimensional (3D) structure remains elusive with challenges in observing native structures of specimens at tens-of-nanometers resolution. Here, using cryogenic coherent X-ray diffraction imaging, we succeeded in obtaining nanoscale 3D structures of metaphase chromosomes that exhibited a random distribution of electron density without characteristics of high-order folding structures. Scaling analysis of the chromosomes, compared with a model structure having the same density profile as the experimental results, has discovered the fractal nature of density distributions. Quantitative 3D density maps, corroborated by molecular dynamics simulations, reveal that internal structures of chromosomes conform to diffusion-limited aggregation behavior, which indicates that 3D chromatin packing occurs via stochastic processes.

Objective comparison of methods to decode anomalous diffusion.

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers.

Cleavage of HSP90ß induced by histone deacetylase inhibitor and proteasome inhibitor modulates cell growth and apoptosis.

HSP90, one of the molecular chaperones, contributes to protein stability in most living organisms. Previously, we found cleavage of HSP90 by caspase 10 in response to treatment with histone deacetylase inhibitor or proteasome inhibitor in leukemic cell lines. In this study, we investigated this phenomenon in various cell lines and found that HSP90 was cleaved by treatment with SAHA or MG132 in 6 out of 16 solid tumor cell lines. To further investigate the effects of HSP90 cleavage on cells, we introduced mutations to the potential cleavage sites of HSP90ß and found that the 294th aspartic acid residue of the protein was mainly cleaved. In the K562 and Mia-PaCa-2 cell lines expressing HSP90ß D294A, the cleavage of HSP90 by the treatment with SAHA or MG132 was reduced compared with the K562 and Mia-PaCa-2 cell lines expressing HSP90ß WT. Accordingly, cell growth and survival were enhanced by HSP90ß D294A expression. Therefore, we suggest that HSP90 cleavage widely occurs in several cell lines, and cleavage of HSP90 may have a potential for one of the mechanisms involved in the anti-tumor effects of known drugs and novel anti-tumor drug candidates.

Anomalous diffusion of active Brownian particles cross-linked to a networked polymer: Langevin dynamics simulation and theory.

Quantitatively understanding the dynamics of an active Brownian particle (ABP) interacting with a viscoelastic polymer environment is a scientific challenge. It is intimately related to several interdisciplinary topics such as the microrheology of active colloids in a polymer matrix and the athermal dynamics of the in vivo chromosomes or cytoskeletal networks. Based on Langevin dynamics simulation and analytic theory, here we explore such a viscoelastic active system in depth using a star polymer of functionality f with the center cross-linker particle being ABP. We observe that the ABP cross-linker, despite its self-propelled movement, attains an active subdiffusion with the scaling ΔR2(t) ∼ tα with α ≤ 1/2, through the viscoelastic feedback from the polymer. Counter-intuitively, the apparent anomaly exponent α becomes smaller as the ABP is driven by a larger propulsion velocity, but is independent of functionality f or the boundary conditions of the polymer. We set forth an exact theory and show that the motion of the active cross-linker is a Gaussian non-Markovian process characterized by two distinct power-law displacement correlations. At a moderate Péclet number, it seemingly behaves as fractional Brownian motion with a Hurst exponent H = α/2, whereas, at a high Péclet number, the self-propelled noise in the polymer environment leads to a logarithmic growth of the mean squared displacement (∼ln t) and a velocity autocorrelation decaying as -t-2. We demonstrate that the anomalous diffusion of the active cross-linker is precisely described by a fractional Langevin equation with two distinct random noises.

Correction: Immature dendritic cells navigate microscopic mazes to find tumor cells.

Correction for 'Immature dendritic cells navigate microscopic mazes to find tumor cells' by Eujin Um et al., Lab Chip, 2019, 19, 1665-1675.

Mapping the spectrum of 3D communities in human chromosome conformation capture data.

Several experiments show that the three dimensional (3D) organization of chromosomes affects genetic processes such as transcription and gene regulation. To better understand this connection, researchers developed the Hi-C method that is able to detect the pairwise physical contacts of all chromosomal loci. The Hi-C data show that chromosomes are composed of 3D compartments that range over a variety of scales. However, it is challenging to systematically detect these cross-scale structures. Most studies have therefore designed methods for specific scales to study foremost topologically associated domains (TADs) and A/B compartments. To go beyond this limitation, we tailor a network community detection method that finds communities in compact fractal globule polymer systems. Our method allows us to continuously scan through all scales with a single resolution parameter. We found: (i) polymer segments belonging to the same 3D community do not have to be in consecutive order along the polymer chain. In other words, several TADs may belong to the same 3D community. (ii) CTCF proteins-a loop-stabilizing protein that is ascribed a big role in TAD formation-are well correlated with community borders only at one level of organization. (iii) TADs and A/B compartments are traditionally treated as two weakly related 3D structures and detected with different algorithms. With our method, we detect both by simply adjusting the resolution parameter. We therefore argue that they represent two specific levels of a continuous spectrum 3D communities, rather than seeing them as different structural entities.

Traditional and Novel Mechanisms of Heat Shock Protein 90 (HSP90) Inhibition in Cancer Chemotherapy Including HSP90 Cleavage.

HSP90 is a molecular chaperone that increases the stability of client proteins. Cancer cells show higher HSP90 expression than normal cells because many client proteins play an important role in the growth and survival of cancer cells. HSP90 inhibitors mainly bind to the ATP binding site of HSP90 and inhibit HSP90 activity, and these inhibitors can be distinguished as ansamycin and non-ansamycin depending on the structure. In addition, the histone deacetylase inhibitors inhibit the activity of HSP90 through acetylation of HSP90. These HSP90 inhibitors have undergone or are undergoing clinical trials for the treatment of cancer. On the other hand, recent studies have reported that various reagents induce cleavage of HSP90, resulting in reduced HSP90 client proteins and growth suppression in cancer cells. Cleavage of HSP90 can be divided into enzymatic cleavage and non-enzymatic cleavage. Therefore, reagents inducing cleavage of HSP90 can be classified as another class of HSP90 inhibitors. We discuss that the cleavage of HSP90 can be another mechanism in the cancer treatment by HSP90 inhibition.

Immature dendritic cells navigate microscopic mazes to find tumor cells.

Dendritic cells (DCs) are potent antigen-presenting cells with high sentinel ability to scan their neighborhood and to initiate an adaptive immune response. Whereas chemotactic migration of mature DCs (mDCs) towards lymph nodes is relatively well documented, the migratory behavior of immature DCs (imDCs) in tumor microenvironments is still poorly understood. Here, microfluidic systems of various geometries, including mazes, are used to investigate how the physical and chemical microenvironment influences the migration pattern of imDCs. Under proper degree of confinement, the imDCs are preferentially recruited towards cancer vs. normal cells, accompanied by increased cell speed and persistence. Furthermore, a systematic screen of cytokines, reveals that Gas6 is a major chemokine responsible for the chemotactic preference. These results and the accompanying theoretical model suggest that imDC migration in complex tissue environments is tuned by a proper balance between the strength of the chemical gradients and the degree of spatial confinement.

Fluctuations of random walks in critical random environments.

Percolation networks have been widely used in the description of porous media but are now found to be relevant to understand the motion of particles in cellular membranes or the nucleus of biological cells. Random walks on the infinite cluster at criticality of a percolation network are asymptotically ergodic. On any finite size cluster of the network stationarity is reached at finite times, depending on the cluster's size. Despite of this we here demonstrate by combination of analytical calculations and simulations that at criticality the disorder and cluster size average of the ensemble of clusters leads to a non-vanishing variance of the time averaged mean squared displacement, regardless of the measurement time. Fluctuations of this relevant experimental quantity due to the disorder average of such ensembles are thus persistent and non-negligible. The relevance of our results for single particle tracking analysis in complex and biological systems is discussed.

Asymmetric polar localization dynamics of the serine chemoreceptor protein Tsr in Escherichia coli.

The spatial location of proteins in living cells can be critical for their function. For example, the E. coli chemotaxis machinery is localized to the cell poles. Here we describe the polar localization of the serine chemoreceptor Tsr using a strain synthesizing a fluorescent Tsr-Venus fusion at a low level from a single-copy chromosomal construct. Using photobleaching and imaging during recovery by new synthesis, we observed distinct asymmetry between a bright (old) pole and a dim (new) pole. The old pole was shown to be a more stable cluster and to recover after photobleaching faster, which is consistent with the hypothesis that newly synthesized Tsr proteins are inserted directly at or near the old pole. The new pole was shown to be a less stable cluster and to exchange proteins freely with highly mobile Tsr-Venus proteins diffusing in the membrane. We propose that the new pole arises from molecules escaping from the old pole and diffusing to the new pole where a more stable cluster forms over time. Our localization imaging data support a model in which a nascent new pole forms prior to stable cluster formation.

Neuronal messenger ribonucleoprotein transport follows an aging Lévy walk.

Localization of messenger ribonucleoproteins (mRNPs) plays an essential role in the regulation of gene expression for long-term memory formation and neuronal development. Knowledge concerning the nature of neuronal mRNP transport is thus crucial for understanding how mRNPs are delivered to their target synapses. Here, we report experimental and theoretical evidence that the active transport dynamics of neuronal mRNPs, which is distinct from the previously reported motor-driven transport, follows an aging Lévy walk. Such nonergodic, transient superdiffusion occurs because of two competing dynamic phases: the motor-involved ballistic run and static localization of mRNPs. Our proposed Lévy walk model reproduces the experimentally extracted key dynamic characteristics of mRNPs with quantitative accuracy. Moreover, the aging status of mRNP particles in an experiment is inferred from the model. This study provides a predictive theoretical model for neuronal mRNP transport and offers insight into the active target search mechanism of mRNP particles in vivo.

Geometry controlled anomalous diffusion in random fractal geometries: looking beyond the infinite cluster.

We investigate the ergodic properties of a random walker performing (anomalous) diffusion on a random fractal geometry. Extensive Monte Carlo simulations of the motion of tracer particles on an ensemble of realisations of percolation clusters are performed for a wide range of percolation densities. Single trajectories of the tracer motion are analysed to quantify the time averaged mean squared displacement (MSD) and to compare this with the ensemble averaged MSD of the particle motion. Other complementary physical observables associated with ergodicity are studied, as well. It turns out that the time averaged MSD of individual realisations exhibits non-vanishing fluctuations even in the limit of very long observation times as the percolation density approaches the critical value. This apparent non-ergodic behaviour concurs with the ergodic behaviour on the ensemble averaged level. We demonstrate how the non-vanishing fluctuations in single particle trajectories are analytically expressed in terms of the fractal dimension and the cluster size distribution of the random geometry, thus being of purely geometrical origin. Moreover, we reveal that the convergence scaling law to ergodicity, which is known to be inversely proportional to the observation time T for ergodic diffusion processes, follows a power-law ∼T(-h) with h < 1 due to the fractal structure of the accessible space. These results provide useful measures for differentiating the subdiffusion on random fractals from an otherwise closely related process, namely, fractional Brownian motion. Implications of our results on the analysis of single particle tracking experiments are provided.

Superdiffusion dominates intracellular particle motion in the supercrowded cytoplasm of pathogenic Acanthamoeba castellanii.

Acanthamoebae are free-living protists and human pathogens, whose cellular functions and pathogenicity strongly depend on the transport of intracellular vesicles and granules through the cytosol. Using high-speed live cell imaging in combination with single-particle tracking analysis, we show here that the motion of endogenous intracellular particles in the size range from a few hundred nanometers to several micrometers in Acanthamoeba castellanii is strongly superdiffusive and influenced by cell locomotion, cytoskeletal elements, and myosin II. We demonstrate that cell locomotion significantly contributes to intracellular particle motion, but is clearly not the only origin of superdiffusivity. By analyzing the contribution of microtubules, actin, and myosin II motors we show that myosin II is a major driving force of intracellular motion in A. castellanii. The cytoplasm of A. castellanii is supercrowded with intracellular vesicles and granules, such that significant intracellular motion can only be achieved by actively driven motion, while purely thermally driven diffusion is negligible.

Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking.

Modern microscopic techniques following the stochastic motion of labelled tracer particles have uncovered significant deviations from the laws of Brownian motion in a variety of animate and inanimate systems. Such anomalous diffusion can have different physical origins, which can be identified from careful data analysis. In particular, single particle tracking provides the entire trajectory of the traced particle, which allows one to evaluate different observables to quantify the dynamics of the system under observation. We here provide an extensive overview over different popular anomalous diffusion models and their properties. We pay special attention to their ergodic properties, highlighting the fact that in several of these models the long time averaged mean squared displacement shows a distinct disparity to the regular, ensemble averaged mean squared displacement. In these cases, data obtained from time averages cannot be interpreted by the standard theoretical results for the ensemble averages. Here we therefore provide a comparison of the main properties of the time averaged mean squared displacement and its statistical behaviour in terms of the scatter of the amplitudes between the time averages obtained from different trajectories. We especially demonstrate how anomalous dynamics may be identified for systems, which, on first sight, appear to be Brownian. Moreover, we discuss the ergodicity breaking parameters for the different anomalous stochastic processes and showcase the physical origins for the various behaviours. This Perspective is intended as a guidebook for both experimentalists and theorists working on systems, which exhibit anomalous diffusion.