Cell proliferation and Notch signaling coordinate the formation of epithelial folds in the Drosophila leg.

The formation of complex three-dimensional organs during development requires precise coordination between patterning networks and mechanical forces. In particular, tissue folding is a crucial process that relies on a combination of local and tissue-wide mechanical forces. Here, we investigate the contribution of cell proliferation to epithelial morphogenesis using the Drosophila leg tarsal folds as a model. We reveal that tissue-wide compression forces generated by cell proliferation, in coordination with the Notch signaling pathway, are essential for the formation of epithelial folds in precise locations along the proximo-distal axis of the leg. As cell numbers increase, compressive stresses arise, promoting the folding of the epithelium and reinforcing the apical constriction of invaginating cells. Additionally, the Notch target dysfusion plays a key function specifying the location of the folds, through the apical accumulation of F-actin and the apico-basal shortening of invaginating cells. These findings provide new insights into the intricate mechanisms involved in epithelial morphogenesis, highlighting the crucial role of tissue-wide forces in shaping a three-dimensional organ in a reproducible manner.

Mechanical stress combines with planar polarised patterning during metaphase to orient embryonic epithelial cell divisions.

The planar orientation of cell division (OCD) is important for epithelial morphogenesis and homeostasis. Here, we ask how mechanics and antero-posterior (AP) patterning combine to influence the first divisions after gastrulation in the Drosophila embryonic epithelium. We analyse hundreds of cell divisions and show that stress anisotropy, notably from compressive forces, can reorient division directly in metaphase. Stress anisotropy influences the OCD by imposing metaphase cell elongation, despite mitotic rounding, and overrides interphase cell elongation. In strongly elongated cells, the mitotic spindle adapts its length to, and hence its orientation is constrained by, the cell long axis. Alongside mechanical cues, we find a tissue-wide bias of the mitotic spindle orientation towards AP-patterned planar polarised Myosin-II. This spindle bias is lost in an AP-patterning mutant. Thus, a patterning-induced mitotic spindle orientation bias overrides mechanical cues in mildly elongated cells, whereas in strongly elongated cells the spindle is constrained close to the high stress axis.

High-level cognition is supported by information-rich but compressible brain activity patterns.

To efficiently yet reliably represent and process information, our brains need to produce information-rich signals that differentiate between moments or cognitive states, while also being robust to noise or corruption. For many, though not all, natural systems, these two properties are often inversely related: More information-rich signals are less robust, and vice versa. Here, we examined how these properties change with ongoing cognitive demands. To this end, we applied dimensionality reduction algorithms and pattern classifiers to functional neuroimaging data collected as participants listened to a story, temporally scrambled versions of the story, or underwent a resting state scanning session. We considered two primary aspects of the neural data recorded in these different experimental conditions. First, we treated the maximum achievable decoding accuracy across participants as an indicator of the "informativeness" of the recorded patterns. Second, we treated the number of features (components) required to achieve a threshold decoding accuracy as a proxy for the "compressibility" of the neural patterns (where fewer components indicate greater compression). Overall, we found that the peak decoding accuracy (achievable without restricting the numbers of features) was highest in the intact (unscrambled) story listening condition. However, the number of features required to achieve comparable classification accuracy was also lowest in the intact story listening condition. Taken together, our work suggests that our brain networks flexibly reconfigure according to ongoing task demands and that the activity patterns associated with higher-order cognition and high engagement are both more informative and more compressible than the activity patterns associated with lower-order tasks and lower engagement.

Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function.

Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning-based methods demand huge training data and are difficult to generalize. Here, we propose to conduct Biomedical data compRession with Implicit nEural Function (BRIEF) by representing the target data with compact neural networks, which are data specific and thus have no generalization issues. Benefiting from the strong representation capability of implicit neural function, BRIEF achieves 2[Formula: see text]3 orders of magnitude compression on diverse biomedical data at significantly higher fidelity than existing techniques. Besides, BRIEF is of consistent performance across the whole data volume, and supports customized spatially varying fidelity. BRIEF's multifold advantageous features also serve reliable downstream tasks at low bandwidth. Our approach will facilitate low-bandwidth data sharing and promote collaboration and progress in the biomedical field.

A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics.

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

Compression drives diverse transcriptomic and phenotypic adaptations in melanoma.

Physical forces are prominent during tumor progression. However, it is still unclear how they impact and drive the diverse phenotypes found in cancer. Here, we apply an integrative approach to investigate the impact of compression on melanoma cells. We apply bioinformatics to screen for the most significant compression-induced transcriptomic changes and investigate phenotypic responses. We show that compression-induced transcriptomic changes are associated with both improvement and worsening of patient prognoses. Phenotypically, volumetric compression inhibits cell proliferation and cell migration. It also induces organelle stress and intracellular oxidative stress and increases pigmentation in malignant melanoma cells and normal human melanocytes. Finally, cells that have undergone compression become more resistant to cisplatin treatment. Our findings indicate that volumetric compression is a double-edged sword for melanoma progression and drives tumor evolution.

Colloidal tubular microrobots for cargo transport and compression.

Microrobot swarms have seen increased interest in recent years due to their potentials for in vivo delivery and imaging with cooperative propulsion modes and enhanced imaging signals. Yet most swarms developed so far are limited to dense particle aggregates, far simpler than complicated three-dimensional assemblies of anisotropic particles. Here, we show via assembly path design that complex hollow tubular structures can be assembled from simple isotropic colloidal spheres and those complicated, metastable, microtubes can be formed from simple, energetically favorable colloidal membranes. The assembled microtubes can remain intact and roll under a precessing magnetic field, with propulsion directions and velocities precisely controlled by field components. The hollow spaces inside enable these tubular microrobots to grab, transport, and release cargos on command. We also demonstrate unique compressing and uncompressing capabilities with our tubular microrobots, making them effective microtweezers. Our work shows that complicated microrobots can be transformed from simple assemblies, providing an insight on building micromachines.

PI3K functions as a hub in mechanotransduction.

Mammalian cells integrate different types of stimuli that govern their fate. These stimuli encompass biochemical as well as biomechanical cues (shear, tensile, and compressive stresses) that are usually studied separately. The phosphatidylinositol 3-kinase (PI3K) enzymes, producing signaling phosphoinositides at plasma and intracellular membranes, are key in intracellular signaling and vesicular trafficking pathways. Recent evidence in cancer research demonstrates that these enzymes are essential in mechanotransduction. Despite this, the importance of the integration of biomechanical cues and PI3K-driven biochemical signals is underestimated. In this opinion article, we make the hypothesis that modeling of biomechanical cues is critical to understand PI3K oncogenicity. We also identify known/missing knowledge in terms of isoform specificity and molecular pathways of activation, knowledge that is needed for clinical applications.

Confinement plus myosin-II suppression maximizes heritable loss of chromosomes, as revealed by live-cell ChReporters.

The mechanical environment of a cell can have many effects, but whether it impacts the DNA sequence of a cell has remained unexamined. To investigate this, we developed a live-cell method to measure changes in chromosome numbers. We edited constitutive genes with GFP or RFP tags on single alleles and discovered that cells that lose Chromosome reporters (ChReporters) become non-fluorescent. We applied our new tools to confined mitosis and to inhibition of the putative tumor suppressor myosin-II. We quantified compression of mitotic chromatin in vivo and demonstrated that similar compression in vitro resulted in cell death, but also rare and heritable ChReptorter loss. Myosin-II suppression rescued lethal multipolar divisions and maximized ChReporter loss during three-dimensional (3D) compression and two-dimensional (2D) lateral confinement, but not in standard 2D culture. ChReporter loss was associated with chromosome mis-segregation, rather than just the number of divisions, and loss in vitro and in mice was selected against in subsequent 2D cultures. Inhibition of the spindle assembly checkpoint (SAC) caused ChReporter loss in 2D culture, as expected, but not during 3D compression, suggesting a SAC perturbation. Thus, ChReporters enable diverse studies of viable genetic changes, and show that confinement and myosin-II affect DNA sequence and mechano-evolution.

A survey of BWT variants for string collections.

MOTIVATION: In recent years, the focus of bioinformatics research has moved from individual sequences to collections of sequences. Given the fundamental role of the Burrows-Wheeler Transform (BWT) in string processing, a number of dedicated tools have been developed for computing the BWT of string collections. While the focus has been on improving efficiency, both in space and time, the exact definition of the BWT employed has not been at the center of attention. As we show in this paper, the different tools in use often compute non-equivalent BWT variants: the resulting transforms can differ from each other significantly, including the number r of runs, a central parameter of the BWT. Moreover, with many tools, the transform depends on the input order of the collection. In other words, on the same dataset, the same tool may output different transforms if the dataset is given in a different order. RESULTS: We studied 18 dedicated tools for computing the BWT of string collections and were able to identify 6 different BWT variants computed by these tools. We review the differences between these BWT variants, both from a theoretical and from a practical point of view, comparing them on 8 real-life biological datasets with different characteristics. We find that the differences can be extensive, depending on the datasets, and are largest on collections of many similar short sequences. The parameter r, the number of runs of the BWT, also shows notable variation between the different BWT variants; on our datasets, it varied by a multiplicative factor of up to 4.2. AVAILABILITY: Source code and scripts to replicate the results and download the data used in the article are available at https://github.com/davidecenzato/BWT-variants-for-string-collections. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Establishing finite element model credibility of a pedicle screw system under compression-bending: An end-to-end example of the ASME V&V 40 standard.

Computational modeling and simulation (CM&S) is a key tool in medical device design, development, and regulatory approval. For example, finite element analysis (FEA) is widely used to understand the mechanical integrity and durability of orthopaedic implants. The ASME V&V 40 standard and supporting FDA guidance provide a framework for establishing model credibility, enabling deeper reliance on CM&S throughout the total product lifecycle. Examples of how to apply the principles outlined in the ASME V&V 40 standard are important to facilitating greater adoption by the medical device community, but few published examples are available that demonstrate best practices. Therefore, this paper outlines an end-to-end (E2E) example of the ASME V&V 40 standard applied to an orthopaedic implant. The objective of this study was to illustrate how to establish the credibility of a computational model intended for use as part of regulatory evaluation. In particular, this study focused on whether a design change to a spinal pedicle screw construct (specifically, the addition of a cannulation to an existing non-cannulated pedicle screw) would compromise the rod-screw construct mechanical performance. This question of interest (?OI) was addressed by establishing model credibility requirements according to the ASME V&V 40 standard. Experimental testing to support model validation was performed using spinal rods and non-cannulated pedicle screw constructs made with medical grade titanium (Ti-6Al-4V ELI). FEA replicating the experimental tests was performed by three independent modelers and validated through comparisons of common mechanical properties such as stiffness and yield force. The validated model was then used to simulate F1717 compression-bending testing on the new cannulated pedicle screw design to answer the ?OI, without performing any additional experimental testing. This E2E example provides a realistic scenario for the application of the ASME V&V 40 standard to orthopedic medical device applications.

HiCMC: High-Efficiency Contact Matrix Compressor.

BACKGROUND: Chromosome organization plays an important role in biological processes such as replication, regulation, and transcription. One way to study the relationship between chromosome structure and its biological functions is through Hi-C studies, a genome-wide method for capturing chromosome conformation. Such studies generate vast amounts of data. The problem is exacerbated by the fact that chromosome organization is dynamic, requiring snapshots at different points in time, further increasing the amount of data to be stored. We present a novel approach called the High-Efficiency Contact Matrix Compressor (HiCMC) for efficient compression of Hi-C data. RESULTS: By modeling the underlying structures found in the contact matrix, such as compartments and domains, HiCMC outperforms the state-of-the-art method CMC by approximately 8% and the other state-of-the-art methods cooler, LZMA, and bzip2 by over 50% across multiple cell lines and contact matrix resolutions. In addition, HiCMC integrates domain-specific information into the compressed bitstreams that it generates, and this information can be used to speed up downstream analyses. CONCLUSION: HiCMC is a novel compression approach that utilizes intrinsic properties of contact matrix, such as compartments and domains. It allows for a better compression in comparison to the state-of-the-art methods. HiCMC is available at https://github.com/sXperfect/hicmc .

scCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene-gene interactions.

BACKGROUND: Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to highly-stochastic transcriptomics data, accurate detection of cell types is still challenged, especially for RNA-sequencing data from human beings. In this case, deep neural networks have been increasingly employed to mine cell type specific patterns and have outperformed statistic approaches in cell clustering. RESULTS: Using cross-correlation to capture gene-gene interactions, this study proposes the scCompressSA method to integrate topological patterns from scRNA-seq data, with support of self-attention (SA) based coefficient compression (CC) block. This SA-based CC block is able to extract and employ static gene-gene interactions from scRNA-seq data. This proposed scCompressSA method has enhanced clustering accuracy in multiple benchmark scRNA-seq datasets by integrating topological and temporal features. CONCLUSION: Static gene-gene interactions have been extracted as temporal features to boost clustering performance in single-cell clustering For the scCompressSA method, dual-channel SA based CC block is able to integrate topological features and has exhibited extraordinary detection accuracy compared with previous clustering approaches that only employ temporal patterns.

Compression of time in double-step saccades.

Temporal intervals appear compressed at the time of saccades. Here, I asked if saccadic compression of time is related to motor planning or to saccade execution. To dissociate saccade motor planning from its execution, I used the double-step paradigm, in which subjects have to perform two horizontal saccades successively. At various times around the saccade sequence, I presented two large horizontal bars, which marked an interval lasting 100 ms. After 700 ms, a second temporal interval was presented, varying in duration across trials. Subjects were required to judge which interval appeared shorter. I found that during the first saccades in the double-step paradigm, temporal intervals were compressed. Maximum temporal compression coincided with saccade onset. Around the time of the second saccade, I found temporal compression as well, however, the time of maximum compression preceded saccade onset by about 70 ms. I compared the magnitude and time of temporal compression between double-step saccades and amplitude-matched single saccades, which I measured separately. Although I found no difference in time compression magnitude, the time when maximum compression occurred differed significantly. I conclude that the temporal shift of time compression in double-step saccades demonstrates the influence of saccade motor planning on time perception.NEW & NOTEWORTHY Visually defined temporal intervals appear compressed at the time of saccades. Here, I tested time perception during double-step saccades dissociating saccade planning from execution. Although around the time of the first saccade, peak compression was found at saccade onset, compression around the time of the second saccade peaked 70 ms before saccade onset. The results suggest that saccade motor planning influences time perception.

Boron neutron capture therapy delays the decline in neurological function in a mouse model of metastatic spinal tumors.

Metastatic spinal tumors are increasingly prevalent due to advancements in cancer treatment, leading to prolonged survival rates. This rising prevalence highlights the need for developing more effective therapeutic approaches to address this malignancy. Boron neutron capture therapy (BNCT) offers a promising solution by delivering targeted doses to tumors while minimizing damage to normal tissue. In this study, we evaluated the efficacy and safety of BNCT as a potential therapeutic option for spine metastases in mouse models induced by A549 human lung adenocarcinoma cells. The animal models were randomly allocated into three groups: untreated (n = 10), neutron irradiation only (n = 9), and BNCT (n = 10). Each mouse was administered 4-borono-L-phenylalanine (250 mg/kg) intravenously, followed by measurement of boron concentrations 2.5 h later. Overall survival, neurological function of the hindlimb, and any adverse events were assessed post irradiation. The tumor-to-normal spinal cord and blood boron concentration ratios were 3.6 and 2.9, respectively, with no significant difference observed between the normal and compressed spinal cord tissues. The BNCT group exhibited significantly prolonged survival rates compared with the other groups (vs. untreated, p = 0.0015; vs. neutron-only, p = 0.0104, log-rank test). Furthermore, the BNCT group demonstrated preserved neurological function relative to the other groups (vs. untreated, p = 0.0004; vs. neutron-only, p = 0.0051, multivariate analysis of variance). No adverse events were observed post irradiation. These findings indicate that BNCT holds promise as a novel treatment modality for metastatic spinal tumors.

Compressed cerebro-cerebellar functional gradients in children and adolescents with attention-deficit/hyperactivity disorder.

Both cortical and cerebellar developmental differences have been implicated in attention-deficit/hyperactivity disorder (ADHD). Recently accumulating neuroimaging studies have highlighted hierarchies as a fundamental principle of brain organization, suggesting the importance of assessing hierarchy abnormalities in ADHD. A novel gradient-based resting-state functional connectivity analysis was applied to investigate the cerebro-cerebellar disturbed hierarchy in children and adolescents with ADHD. We found that the interaction of functional gradient between diagnosis and age was concentrated in default mode network (DMN) and visual network (VN). At the same time, we also found that the opposite gradient changes of DMN and VN caused the compression of the cortical main gradient in ADHD patients, implicating the co-occurrence of both low- (visual processing) and high-order (self-related thought) cognitive dysfunction manifesting in abnormal cerebro-cerebellar organizational hierarchy in ADHD. Our study provides a neurobiological framework to better understand the co-occurrence and interaction of both low-level and high-level functional abnormalities in the cortex and cerebellum in ADHD.

Randomized adaptive selection trial of cryotherapy, compression therapy, and placebo to prevent taxane-induced peripheral neuropathy in patients with breast cancer.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a common and debilitating adverse effect of taxane therapy. Small non-randomized studies in patients with early-stage breast cancer (ESBC) suggest both cryotherapy and compression therapy may prevent CIPN. It is unknown which is more effective. METHODS: We conducted a randomized phase IIB adaptive sequential selection trial of cryotherapy vs. compression therapy vs. placebo ("loose" gloves/socks) during taxane chemotherapy. Participants were randomized in triplets. Garments were worn for 90-120 min, beginning 15 min prior and continuing for 15 min following the infusion. The primary goal was to select the best intervention based on a Levin-Robbins-Leu sequential selection procedure. The primary endpoint was a < 5-point decrease in the Functional Assessment of Cancer Therapy Neurotoxicity (FACT-NTX) at 12 weeks. An arm was eliminated if it had four or more fewer successes than the currently leading arm. Secondary endpoints included intervention adherence and patient-reported comfort/satisfaction. RESULTS: Between April 2019 and April 2021, 63 patients were randomized (cryotherapy (20); compression (22); placebo (21)). Most patients (60.3%) were treated with docetaxel. The stopping criterion was met after the 17th triplet (n = 51) was evaluated; success at 12 weeks occurred in 11 (64.7%) on compression therapy, 7 (41.1%) on cryotherapy, and 7 (41.1%) on placebo. Adherence to the intervention was lowest with cryotherapy (35.0%) compared to compression (72.7%) and placebo (76.2%). CONCLUSION: Compression therapy was the most effective intervention in this phase IIB selection trial to prevent CIPN and was well tolerated. Compression therapy for the prevention of CIPN should be evaluated in a phase III study. CLINICAL TRIAL REGISTRATION: ClinicaTrials.gov Identifier: NCT03873272.

Self-Assembled Molecular Fibers Aligned by Compression in Water.

Molecular self-assembly has attracted much attention as a potential approach for fabricating nanostructured functional materials. To date, energy-efficient fabrication of nano-objects such as nanofibers, nanorings, and nanotubes is achieved using well-designed self-assembling molecules. However, the application of molecular self-assembly to industrial manufacturing processes remains challenging because regulating the positions and directions of self-assembled products is difficult. Non-covalent molecular assemblies are also too fragile to allow mechanical handling. The present work demonstrates the macroscopic alignment of self-assembled molecular fibers using compression. Specifically, the macroscopic bundling of self-assembled nanofibers is achieved following dispersion in water. These fiber bundles can also be chemically crosslinked without drastic changes in morphology via trialkoxysilyl groups. Subsequently, vertically oriented porous membranes can be produced rapidly by slicing the bundles. This technique is expected to be applicable to various functional self-assembled fibers and can lead to the development of innovative methods of producing anisotropic nanostructured materials.

High-Sensitive Spatiotemporal Distribution Imaging of Compression Stresses Based on Time-Evolutional Responsiveness.

Mechanoresponsive materials have been studied to visualize and measure stresses in various fields. However, the high-sensitive and spatiotemporal imaging remain a challenging issue. In particular, the time evolutional responsiveness is not easily integrated in mechanoresponsive materials. In the present study, high-sensitive spatiotemporal imaging of weak compression stresses is achieved by time-evolutional controlled diffusion processes using conjugated polymer, capsule, and sponge. Stimuli-responsive polydiacetylene (PDA) is coated inside a sponge. A mechanoresponsive capsule is set on the top face of the sponge. When compression stresses in the range of 6.67-533 kPa are applied to the device, the blue color of PDA is changed to red by the diffusion of the interior liquid containing a guest polymer flowed out of the disrupted capsule. The applied strength (F/N), time (t/s), and impulse (F·t/N s) are visualized and quantified by the red-color intensity. When a guest metal ion is intercalated in the layered structure of PDA to tune the responsivity, the device visualizes the elapsed time (τ/min) after unloading the stresses. PDA, capsule, and sponge play the important roles to achieve the time evolutional responsiveness for the high-sensitive spatiotemporal distribution imaging through the controlled diffusion processes.

A Chemo-Mechanically Coupled DNA Origami Clamp Capable of Generating Robust Compression Forces.

DNA nanostructures have been utilized to study biological mechanical processes and construct artificial nanosystems. Many application scenarios necessitate nanodevices able to robustly generate large single molecular forces. However, most existing dynamic DNA nanostructures are triggered by probabilistic hybridization reactions between spatially separated DNA strands, which only non-deterministically generate relatively small compression forces (≈0.4 piconewtons (pN)). Here, an intercalator-triggered dynamic DNA origami nanostructure is developed, where large amounts of local binding reactions between intercalators and the nanostructure collectively lead to the robust generation of relatively large compression forces (≈11.2 pN). Biomolecular loads with different stiffnesses, 3, 4, and 6-helix DNA bundles are efficiently bent by the compression forces. This work provides a robust and powerful force-generation tool for building highly chemo-mechanically coupled molecular machines in synthetic nanosystems.