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.