Sorting Experiments Research Articles

Up-regulated GRB7 protein in gastric cancer cells correlates with clinical properties and increases proliferation and stem cell properties.

It has been reported that GRB7 is closely related to a variety of human solid tumors, but its role in gastric cancer has not been reported yet. The purpose of this study was to investigate the expression level and intracellular effects of GRB7 in human gastric cancer. Real-time fluorescent quantitative PCR and Western blot were used to detect the expression of GRB7 in gastric cancer cell lines. The immunohistochemical staining and SPSS analysis verified the GRB7 protein expression. Stable gastric cancer cell lines, MTT experiments, clone formation experiments, cell cycle flow cytometry experiments, sphere formation experiments and lateral subpopulation cell sorting experiments were conducted to investigate the role of GRB7 in gastric cancer cells. We found that the expression of GRB7 in gastric cancer cell lines was higher than that of the corresponding normal gastric epithelial cells, and correspondingly higher in gastric cancer tissues than its paired adjacent tissues. GRB7 protein was expressed more highly in cancer tissues than in adjacent tissues. GRB7 protein expression levels were positively correlated with the clinical stage of gastric cancer patients, and negatively correlated with the survival prognosis of patients. GSEA analysis of GRB7 mRNA levels in gastric cancer tissues and normal gastric epithelial tissues from public databases showed that GRB7 may affect cell proliferation and related processes of intracellular stem cells. GRB7 can promote the proliferation of gastric cancer cells and is positively related to the self-renewal ability of gastric cancer stem cells. This study shows that GRB7 molecules highly expressed in gastric cancer tissues can promote the proliferation of gastric cancer cells and increase the proportion of gastric cancer stem cells, so it is expected to become a diagnostic molecule or potential therapeutic target for gastric cancer.

Liver-resident CD44hiCD27− γδT Cells Help to Protect Against Listeria monocytogenes Infection

Gamma delta (γδ) T cells are heterogeneous and functionally committed to producing interferon (IFN)-γ and interleukin (IL)-17. γδT cells are defined as tissue-resident lymphocytes in barrier tissues. Among them, IL-17-producing γδT cells are relatively abundant in the liver. However, a systematic and comprehensive understanding of the residency characteristics and function of hepatic IL-17A+ γδT cells is lacking. We undertook a single-cell analysis of γδT17 cells derived from murine livers. A parabiosis model was used to assess tissue residency. Fluorescence-activated cell sorting and adoptive transfer experiments were used to investigate the response and protective role of liver-resident CD44hiCD27- γδT cells in Listeria monocytogenes infection. Transwell assay was used to assess the role of macrophages in the chemotaxis of liver-resident CD44hiCD27- γδT cells. We identified hepatic IL-17A-producing γδT cells as CD44hiCD27- γδT cells. They had tissue-resident characteristics and resided principally within the liver. Vγ6+ T cells also exhibited liver-resident features. Liver-resident CD44hiCD27- γδT cells had significantly increased proliferation capacity, and their proportion rapidly increased after infection. Some CD44hiCD27- γδT cells could produce IL-17A and IFN-γ simultaneously in response to Lm infection. Adoptive transfer of hepatic CD44hiCD27- γδT cells into Lm-infected TCRδ-/- mice led to markedly lower bacterial numbers in the liver. Hepatic macrophages promoted the migration and accumulation of liver-resident CD44hiCD27- γδT cells into infection sites. Liver-resident CD44hiCD27- γδT cells protect against Lm infection. Hepatic macrophages coordinate with liver-resident CD44hiCD27- γδT cells and contribute to the clearance of Lm at the early stage of infection corporately.

Particle size distribution: An experimental study using southern African reduction methods and raw materials.

We experimentally created a particle size dataset that is based on reduction sequences and raw materials typical of the Middle and Later Stone Age in southern Africa. The reason for creating this new dataset is that current particle size frameworks are based, almost exclusively, on flint and western European knapping methods. We produced the dataset using knapping methods and raw materials frequently encountered in the southern African archaeological record because we wanted to test whether it has the same distribution as particle size datasets experimentally created in Europe, and to initialise the production of a database for use in the analysis of lithic assemblages from southern African Late Pleistocene deposits. We reduced 117 cores of quartz, quartzite, jasper, chalcedony, hornfels, and rhyolite. The knapping methods selected were unidirectional, discoidal, Levallois recurrent and bipolar flaking. In this article we compare this new particle size distribution dataset with the results obtained from previous experiments. We found that the southern African dataset shows a wider size range distribution, which seems to be explained by differences in knapping methods and raw materials. Our results show that there is overlap between the distribution of the southern African experimental knapping dataset and the sorting experiment conducted by Lenoble on flint artefacts in a runoff context. This article shows that a particle size analysis is not sufficient on its own to assess the perturbation of an archaeological assemblage and must be coupled with other analytical tools.

Sorting of heterogeneous colloids by AC-dielectrophoretic forces in a microfluidic chip with asymmetric orifices

HypothesisThe synthesis of compositionally heterogeneous particles is central to the development of complex colloidal units for self-assembly and self-propulsion. Yet, as the complexity of particles grows, synthesis becomes more prone to “errors”. We hypothesize that alternating-current dielectrophoretic forces can efficiently sort Janus particles, as a function of patch size and material, and colloidal dumbbells by size. ExperimentsWe prepared Janus particles with different patch size and material by physical vapor deposition and colloidal dumbbells via capillarity-assisted particle assembly. We then performed sorting experiments in a microfluidic chip comprising electrodes with asymmetric orifices, specifically exploiting the dielectric contrast between different portions of the particles or their size difference to steer them towards different outlets. FindingsWe calculated that the DEP force for Janus particles may switch from positive to negative as a function of composition at a critical AC frequency, thus enabling sorting different particles crossing the electrodes’ region. The predictions are confirmed by optical microscopy experiments. We also show that intact and “broken” dumbbells can be simply separated as they experience different DEP forces. The integration of multiple asymmetric orifices leads a larger zone with high field gradient to increase separation efficiency and makes it a promising tool to select precise particle populations, isolating fractions with narrowly distributed characteristics.

Exploratory compositional analysis of street bin litter: Empirical study in a regional city in Belgium

Street bin litter (SBL) is an overlooked waste stream and its composition has barely been studied. In a first characterization attempt, five sorting experiments were performed on SBL collected in Leuven, Belgium. The waste was sampled and sorted into 8 main and 39 subfractions. The largest main fractions found were illegally dumped waste (33 ± 3%), organics (17 ± 4%) and paper and cardboard (16 ± 2%). On a functional level, the street bins were estimated to contain about 35% packaging, of which beverage and food packaging constituted 46% and 38–44%, respectively. SBL is in relative terms too small a waste stream for economically viable material recovery. However, in order to make a full transition to a circular economy and due to its high visibility, SBL cannot be neglected. Preventive measures and the full application of Extended Producer Responsibility schemes can help to achieve SBL reduction.

Design Principle of RF Stealth Anti-Sorting Signal Based on Multi-Dimensional Compound Modulation with Pseudo-Center Width Agility

Anti-sorting signal design is an important direction of radio frequency (RF) stealth signal design. The RF stealth signal design is based on the anti-sorting signal design principle, which is essentially the failure principle of the radar signal sorting algorithm. Cluster pre-sorting, the key to radar signal sorting, has the advantages of fast sorting, simultaneous sorting of multiple sources, and greatly reduced computational pressure of the main sorting. However, a unified and widely applicable cluster-sorting failure principle guiding the anti-sorting signal design has not been formally reported in RF stealth anti-sorting signal design. In this paper, the principles of the data field-based K-means clustering algorithm and the fuzzy C-means clustering algorithm are first studied. Aiming at the key step of data similarity measurement in the clustering algorithm, the failure principle of cluster sorting based on pseudo-center wide-agile multi-dimensional compound modulation is proposed. This principle can correctly guide the design of the anti-clustering sorting signal, so it is also called the design principle of the RF stealth anti-sorting signal based on pseudo-center wide-agile multi-dimensional compound modulation. The correctness of the principle is proved by formula derivation, signal simulation, and a sorting experiment. Through a signal comparison simulation with random interference pulse anti-sorting signals, it is strongly proved that the anti-sorting performance of signals designed under the guidance of the anti-clustering signal design principle proposed in this paper is stronger than that of random interference pulse signals. This study provides theoretical support for designing RF stealth anti-sorting signals. Using the signal design principle proposed in this paper, the anti-sorting performance of the RF stealth signal is improved by 10%. The principle of signal design helps to improve design efficiency.

STEM-19. LIVE DETECTION OF NEURAL STEM AND GLIOBLASTOMA CELLS BY A LUMINESCENT CONJUGATED OLIGOTHIOPHENE DERIVATIVE

Abstract Glioblastoma (GBM) is an aggressive nervous system tumor with a mean survival time of 12-14 months. Cells with neural stem cell-like properties can be derived from GBM tumors. These cells seem to escape conventional irradiation treatment, chemotherapy, and surgery, and may play a crucial role for relapse. It is therefore urgent to develop novel approaches for reliable detection of neural stem cell-like cells in GBM. Here we report a luminescent conjugated oligothiophene (LCO), named GlioStem (p-HTMI), for non-invasive and non-amplified real-time detection of live human patient-derived GBM cells and embryonic neural stem/progenitor cells (NSPCs). Within a maximum of 10 minutes after administration of the molecule in vitro, in the existing media, fluorescence emission was observed without any modulation of the cells or additional vehicle, resulting in efficient detection of cytoplasmic luminescent signal in NSPCs or GBM cells from rodents and humans, detectable at Alexa488/GFP wavelength. GlioStem is functionalized with a methylated imidazole moiety resembling the side chain of histidine/histamine, and non-methylated analogues were not functional. In vitro, GlioStem was shown to identify fetal cortical NSPCs from rat (FGF2-expanded), embryonic stem cell-derived NSPCs from mouse (FGF2/EGF-expanded), and FGF2-exposed C6 glioma cell cultures from rat, but not any other cell types investigated. Cell sorting experiments of patient-derived, FGF2/EGF-expanded GBM cells demonstrated that GlioStem in addition to NSPC-markers like Nestin and Sox2 labeled the same population (overlap > 90%) of cells as CD271, a proposed marker for stem cell-like cells and rapidly migrating cells in glioblastoma. Our results suggest that the LCO GlioStem is a versatile tool for immediate and selective detection of subpopulations of neural stem and glioma cells.

Low-latency label-free image-activated cell sorting using fast deep learning and AI inferencing

Classification and sorting of cells using image-activated cell sorting (IACS) systems can bring significant insight to biomedical sciences. Incorporating deep learning algorithms into IACS enables cell classification and isolation based on complex and human-vision uninterpretable morphological features within a heterogeneous cell population. However, the limited capabilities and complicated implementation of deep learning–assisted IACS systems reported to date hinder the adoption of the systems for a wide range of biomedical research. Here, we present image-activated cell sorting by applying fast deep learning algorithms to conduct cell sorting without labeling. The overall sorting latency, including signal processing and AI inferencing, is less than 3 ms, and the training time for the deep learning model is less than 30 min with a training dataset of 20,000 images. Both values set the record for IACS with sorting by AI inference. . We demonstrated our system performance through a 2-part polystyrene beads sorting experiment with 96.6% sorting purity, and a 3-part human leukocytes sorting experiment with 89.05% sorting purity for monocytes, 92.00% sorting purity for lymphocytes, and 98.24% sorting purity for granulocytes. The above performance was achieved with simple hardware containing only 1 FPGA, 1 PC and GPU, as a result of an optimized custom CNN UNet and efficient use of computing power. The system provides a compact, sterile, low-cost, label-free, and low-latency cell sorting solution based on real-time AI inferencing and fast training of the deep learning model.

Influence of Transforming Growth Factors beta 1 and beta 3 in the Scar Formation Process.

Transforming growth factor-beta (TGF-β) plays an instrumental role in forming scars and keloids. TGF-β isoforms exhibit differential expression, indicating distinct wound healing and scar formation functions. However, the role of TGF-β1 and TGF-β3 in wound healing and scar formation remains unclear. This study aimed to compare the specific roles of TGF-β1 and TGF-β3 in wound healing and scar formation by biomolecular analysis. The study was conducted by cell isolation and culture cells from a total of 20 human samples. Normal human fibroblasts (NHF) were isolated from normal human samples and myofibroblasts from the different scar types, namely hypertrophic (HT) and keloid (K) scars. NHF and cells from the HT, and K scar, each of which were divided into 3 sample groups: the untreated control, TGF-β1 (10µg/mL)-treated group, and TGF-β3 (10µg/mL)-treated group. The results of confocal microscopy and fluorescence-activated cell sorting experiments were compared. Both the HT and K groups had higher α-smooth muscle actin (α-SMA) expression than the NHF group in the untreated control group. In comparison with the untreated group, NHFs showed a significant increase in α-SMA expression in the TGF-β1-treated group. HT showed a high α-SMA level, which was statistically significant compared with the normal fibroblasts. In the TGF-β3-treated group, α-SMA expression was slightly increased in NHF as compared with the untreated group. TGF-β3 treated HT exhibited a greater reduction in α-SMA expression than in the TGF-β1 treated HT. K, on the other hand, had only a minimal effect on the treatment of TGF-β1 and TGF-β3. The findings suggest that TGF-β3 may play a regulatory role in the wound repair process, which could be useful in the development of scar-reducing therapies for patients with scar-related cosmetic concerns.

Research on Cognition and Inference Model of Interface Color Imagery Based on EEG Technology

The mobile phone interface has become important access to daily information and social entertainment. And the color design of digital interfaces has a direct impact on improving the user experience. In order to explore the user's perceptual cognition of the interface color imagery, the objective relationship between EEG (Electroencephalography) signal and interface color imagery cognition is analyzed and an inference model of interface color imagery based on EEG is established. Imagery words were selected by a card sorting experiment. EEG data is generated in the users' cognition process of matching app interface color and imagery words. Experimental results show that the N400 component appears in the experiment of imagery word as the target stimulus, and the P300 component appears in the experiment of interface picture as the target stimulus. The inference model of interface color imagery is established by Extreme Learning Machine (ELM) based on the average amplitude data of N400 or P300. Results of the verification experiment indicate that the inference model can accurately predict the imagery match tendency of interface color and imagery words.

Single-cell glycomics analysis by CyTOF-Lec reveals glycan features defining cells differentially susceptible to HIV.

High-parameter single-cell phenotyping has enabled in-depth classification and interrogation of immune cells, but to date has not allowed for glycan characterization. Here, we develop CyTOF-Lec as an approach to simultaneously characterize many protein and glycan features of human immune cells at the single-cell level. We implemented CyTOF-Lec to compare glycan features between different immune subsets from blood and multiple tissue compartments, and to characterize HIV-infected cell cultures. Using bioinformatics approaches to distinguish preferential infection of cellular subsets from viral-induced remodeling, we demonstrate that HIV upregulates the levels of cell-surface fucose and sialic acid in a cell-intrinsic manner, and that memory CD4+ T cells co-expressing high levels of fucose and sialic acid are highly susceptible to HIV infection. Sialic acid levels were found to distinguish memory CD4+ T cell subsets expressing different amounts of viral entry receptors, pro-survival factors, homing receptors, and activation markers, and to play a direct role in memory CD4+ T cells' susceptibility to HIV infection. The ability of sialic acid to distinguish memory CD4+ T cells with different susceptibilities to HIV infection was experimentally validated through sorting experiments. Together, these results suggest that HIV remodels not only cellular proteins but also glycans, and that glycan expression can differentiate memory CD4+ T cells with vastly different susceptibility to HIV infection.

P-Cadherin Is Expressed by Epithelial Progenitor Cells and Melanocytes in the Human Corneal Limbus.

Interactions between limbal epithelial progenitor cells (LEPC) and surrounding niche cells, which include limbal mesenchymal stromal cells (LMSC) and melanocytes (LM), are essential for the maintenance of the limbal stem cell niche required for a transparent corneal surface. P-cadherin (P-cad) is a critical stem cell niche adhesion molecule at various epithelial stem cell niches; however, conflicting observations were reported on the presence of P-cad in the limbal region. To explore this issue, we assessed the location and phenotype of P-cad+ cells by confocal microscopy of human corneoscleral tissue. In subsequent fluorescence-activated cell sorting (FACS) experiments, we used antibodies against P-cad along with CD90 and CD117 for the enrichment of LEPC, LMSC and LM, respectively. The sorted cells were characterized by immunophenotyping and the repopulation of decellularized limbal scaffolds was evaluated. Our findings demonstrate that P-cad is expressed by epithelial progenitor cells as well as melanocytes in the human limbal epithelial stem cell niche. The modified flow sorting addressing P-cad as well as CD90 and CD117 yielded enriched LEPC (CD90−CD117−P-cad+) and pure populations of LMSC (CD90+CD117−P-cad−) and LM (CD90−CD117+P-cad+). The enriched LEPC showed the expression of epithelial progenitor markers and better colony-forming ability than their P-cad− counterparts. The cultured LEPC and LM exhibited P-cad expression at intercellular junctions and successfully repopulated decellularized limbal scaffolds. These data suggest that P-cad is a critical cell–cell adhesion molecule, connecting LEPC and LM, which may play an important role in the long-term maintenance of LEPC at the limbal stem cell niche; moreover, these findings led to further improvement of cell enrichment protocols to enhance the yield of LEPC.

A GFP-based ratiometric sensor for cellular methionine oxidation.

Methionine oxidation is a reversible post-translational protein modification, affecting protein function, and implicated in aging and degenerative diseases. The detection of accumulating methionine oxidation in living cells or organisms, however, has not been achieved. Here we introduce a genetically encoded probe for methionine oxidation (GEPMO), based on the super-folder green fluorescent protein (sfGFP), as a specific, versatile, and integrating sensor for methionine oxidation. Placed at amino-acid position 147 in an otherwise methionine-less sfGFP, the oxidation of this specific methionine to methionine sulfoxide results in a ratiometric fluorescence change when excited with ∼400 and ∼470nm light. The strength and homogeneity of the sensor expression is suited for live-cell imaging as well as fluorescence-activated cell sorting (FACS) experiments using standard laser wavelengths (405/488nm). Expressed in mammalian cells and also in S. cerevisiae, the sensor protein faithfully reports on the status of methionine oxidation in an integrating manner. Variants targeted to membranes and the mitochondria provide subcellular resolution of methionine oxidation, e.g. reporting on site-specific oxidation by illumination of endogenous protoporphyrin IX.

Seed or soil: Tracing the immune subsets in metastatic tumors.

Mapping the tumor-infiltrating immune subsets to an origin of malignancy or tissue niche is important for designing effective immunotherapies, yet it remains a challenging task. In this issue of Cancer Cell, Liu etal. pieced together this puzzle through a comprehensive single-cell analysis of colorectal cancer patients with liver metastases.

Visual Sorting Method Based on Multi-Modal Information Fusion

Visual sorting of stacked parcels is a key issue in intelligent logistics sorting systems. In order to improve the sorting success rate of express parcels and effectively obtain the sorting order of express parcels, a visual sorting method based on multi-modal information fusion (VS-MF) is proposed in this paper. Firstly, an object detection network based on multi-modal information fusion (OD-MF) is proposed. The global gradient feature is extracted from depth information as a self-attention module. More spatial features are learned by the network, and the detection accuracy is improved significantly. Secondly, a multi-modal segmentation network based on Swin Transformer (MS-ST) is proposed to detect the optimal sorting positions and poses of parcels. More fine-grained information of the sorting parcels and the relationships between them are gained by adding Swin Transformer models. Frequency domain information and depth information are used as supervision signals to obtain the pickable areas and infer the occlusion degrees of parcels. A strategy for the optimal sorting order is also proposed to ensure the stability of the system. Finally, a sorting system with a 6-DOF robot is constructed to complete the sorting task of stacked parcels. The accuracy and stability the system are verified by sorting experiments.

Quantity- and quality-oriented scenario optimizations for the material recycling of plastic packaging in Japan

In Japan, the material recycling (MR) of plastic packaging waste faces several problems. Almost half of the collected waste plastics become residue, and the quality of recycled resins is not high because the mixture of various types of plastics makes sorting by resin type difficult. Therefore, an appropriate combination of source separation targets and sorting processes based on plastic type needs to be explored to increase the quantity of waste plastics recycled and enhance the quality of recovered plastics. Furthermore, the acceptability of recovered plastics as raw materials for use in plastic products needs to be assessed by matching the quantity and quality of recovered plastics with the demand and quality requirements of resin users. In this study, we evaluated the purity and quantity of plastics recovered by resin type for 80 combinations of source-separation targets and sorting processes based on the results of a sorting experiment using an actual optical sorter. Then, we developed recycling scenarios that optimized the quantity and/or quality of plastics recovered for MR by allocating waste plastics to the 80 source-separation/sorting schemes using linear programming with the upper limit of the acceptable amounts of recovered plastics and quality constraints. We found that the recycling target established by the Japanese government could be reached, if resin users proactively accepted recycled resin. On the other hand, the current rate of MR could be maintained solely with high-quality recovered plastics, if the collection rate for recycling and the acceptable amounts of the high-quality recovered plastics were significantly boosted.

Simulation and Experimental Study of Potato Conveyor Trajectory for Optimization Design of Belt-Fed Potato Sorter

HighlightsPotatoes of different mass had significantly different moving times and trajectories during unloading.Moving time and trajectory length increased with the increase in mass level of potatoes at different initial speeds.The belt-fed potato sorter developed by investigating potato moving trajectories had high accuracy and low damage.Abstract. Belt conveyors are one of the main transport methods in potato sorting equipment. Generally, potatoes are detected and sorted while being discharged from the end of the loading conveyor. Therefore, the moving time and trajectory of potatoes are critical to determining the detection and sorting positions. In this study, the detection and sorting locations were optimized by investigating the influence of different mass levels of potatoes on their moving time and trajectories at different initial speeds by using a high-speed camera. In addition, a dynamic simulation model of potato movement was established using ADAMS software for further comparison. It was found that the potato trajectories and moving times were significantly influenced by the potato mass levels in a practical experiment. At the same initial speed, the moving time and trajectory length increased with the increase in mass level. Calculation methods for the optimal size and position of the rod ejectors and the unloading conveyor are proposed. When the initial speed was 1 m s-1, the length of the rod ejectors was 218.77 mm with a falling height of 250 mm, and the vertical and horizontal distances between the loading and unloading conveyors were 450 and 216.7 mm, respectively. Finally, a sorting experiment was performed to verify the design, and a classification accuracy of 98.95% and damage rate of 1.26% were obtained. This study provides a theoretical reference for the optimization design of belt-fed potato sorters. Keywords: Optimization design, Potato, Simulation, Trajectory tracking.

Tableware tidying-up robot for self-service restaurant – robot system design

This study developed an automated tableware tidying-up robot mechanism to tidy up the tableware in a self-service restaurant with a large number of tableware. This study focused on the process of sorting and collecting tableware that were placed on trays by the guest and flowed to robot with belts conveyor. The separated tableware was placed in a washing machine. Garbage and leftover food were also treated with this robot mechanism. The parallel arm and robot hand mechanism were designed to realise the advantages of low cost, high processing speed, and space saving. It was proved that the prototype robot can move and grab tableware smoothly with the high-speed position control. The finger and hand rotation mechanism can throw away leftover food by the leftover food throwing experiment. Additionally, the system can sort the tableware by multiple robots was verified using the tableware sorting experiment.

Optimal categorisation

The debate as to whether language influences cognition has been long standing but has yielded conflicting findings across domains such as colour and kinship categories. Fewer studies have investigated systems such as nominal classification (gender, classifiers) across different languages to examine the effects of linguistic categorisation on cognition. Effective categorisation needs to be informative to maximise communicative efficiency but also simple to minimise cognitive load. It therefore seems plausible to suggest that different systems of nominal classification have implications for the way speakers conceptualise relevant entities. A suite of seven experiments was designed to test this; here we focus on our card sorting experiment, which contains two sub-tasks — a free sort and a structured sort. Participants were 119 adults across six Oceanic languages from Vanuatu and New Caledonia, with classifier inventories ranging from two to 23. The results of the card sorting experiment reveal that classifiers appear to provide structure for cognition in tasks where they are explicit and salient. The free sort task did not incite categorisation through classifiers, arguably as it required subjective judgement, rather than explicit instruction. This was evident from our quantitative and qualitative analyses. Furthermore, the languages employing more extreme categorisation systems displayed smaller variation in comparison to more moderate systems. Thus, systems that are more informative or more rigid appear to be more efficient. The study implies that the influence of language on cognition may vary across languages, and that not all nominal classification systems employ this optimal trade-off between simplicity and informativeness. These novel data provide a new perspective on the origin and nature of nominal classification.

Hybrid Animism: The Sensing Surfaces Of Planetary Computation

This article proposes to examine animism through the perspective provided by a notion of immanent matter drawn on process philosophy (Spinoza, Deleuze and Guattari), and quantum physics (Bohm, Rovelli). It then deploys this perspective to illuminate how planetary computation - the impact of digital media technologies on a planetary scale - is rewiring the cognitive, affective, perceptual capacities of the human. The article puts forward the notion of hybrid animism, as a speculative and imaginative philosophical fiction ('philoso-fiction') to grasp planetary computation as a sensorial pan-affective event, and to account for the hybrid techno-digital ecologies humans already inhabit, characterised by ongoing modulation, sensorial intensification and pervasive distribution of computational matter across a plethora of screens, surfaces and surroundings. The value of this proposition, the article explains, is to eschew dominant techno-deterministic narratives: not only techno-euphoria and techno-dystopia, but also the notion of technology as enchantment, with its in-built mystification. By deploying the philoso-fiction of hybrid animism and the un-mediated intuitive sensorial grasp it fosters, planetary computation can begin to be immediately perceived as the expression of new modes of co-habitation and co-evolution of the human and the nonhuman. Finally, the article brings together the nonhuman mutating surfaces of digital matter with cephalopods' skins to vividly and speculatively illustrate hybrid animism as a thought experiment of sorts.