Insights into the micromechanical properties of the metaphase spindle.

The microtubule-based metaphase spindle is subjected to forces that act in diverse orientations and over a wide range of timescales. Currently, we cannot explain how this dynamic structure generates and responds to forces while maintaining overall stability, as we have a poor understanding of its micromechanical properties. Here, we combine the use of force-calibrated needles, high-resolution microscopy, and biochemical perturbations to analyze the vertebrate metaphase spindle's timescale- and orientation-dependent viscoelastic properties. We find that spindle viscosity depends on microtubule crosslinking and density. Spindle elasticity can be linked to kinetochore and nonkinetochore microtubule rigidity, and also to spindle pole organization by kinesin-5 and dynein. These data suggest a quantitative model for the micromechanics of this cytoskeletal architecture and provide insight into how structural and functional stability is maintained in the face of forces, such as those that control spindle size and position, and can result from deformations associated with chromosome movement.

Geometric trade-off between contractile force and viscous drag determines the actomyosin-based motility of a cell-sized droplet.

Cell migration in confined environments is fundamental for diverse biological processes from cancer invasion to leukocyte trafficking. The cell body is propelled by the contractile force of actomyosin networks transmitted from the cell membrane to the external substrates. However, physical determinants of actomyosin-based migration capacity in confined environments are not fully understood. Here, we develop an in vitro migratory cell model, where cytoplasmic actomyosin networks are encapsulated into droplets surrounded by a lipid monolayer membrane. We find that the droplet can move when the actomyosin networks are bound to the membrane, in which the physical interaction between the contracting actomyosin networks and the membrane generates a propulsive force. The droplet moves faster when it has a larger contact area with the substrates, while narrower confinement reduces the migration speed. By combining experimental observations and active gel theory, we propose a mechanism where the balance between sliding friction force, which is a reaction force of the contractile force, and viscous drag determines the migration speed, providing a physical basis of actomyosin-based motility in confined environments.

Morphological growth dynamics, mechanical stability, and active microtubule mechanics underlying spindle self-organization.

The spindle is a dynamic intracellular structure self-organized from microtubules and microtubule-associated proteins. The spindle's bipolar morphology is essential for the faithful segregation of chromosomes during cell division, and it is robustly maintained by multifaceted mechanisms. However, abnormally shaped spindles, such as multipolar spindles, can stochastically arise in a cell population and cause chromosome segregation errors. The physical basis of how microtubules fail in bipolarization and occasionally favor nonbipolar assembly is poorly understood. Here, using live fluorescence imaging and quantitative shape analysis in Xenopus egg extracts, we find that spindles of varied shape morphologies emerge through nonrandom, bistable self-organization paths, one leading to a bipolar and the other leading to a multipolar phenotype. The bistability defines the spindle's unique morphological growth dynamics linked to each shape phenotype and can be promoted by a locally distorted microtubule flow that arises within premature structures. We also find that bipolar and multipolar spindles are stable at the steady-state in bulk but can infrequently switch between the two phenotypes. Our microneedle-based physical manipulation further demonstrates that a transient force perturbation applied near the assembled pole can trigger the phenotypic switching, revealing the mechanical plasticity of the spindle. Together with molecular perturbation of kinesin-5 and augmin, our data propose the physical and molecular bases underlying the emergence of spindle-shape variation, which influences chromosome segregation fidelity during cell division.

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its main risk factor is reportedly intraoperative procedure associated with surgeons' experience. We aimed to improve surgeons' recognition of the RLN during robot-assisted minimally invasive esophagectomy (RAMIE) by developing an artificial intelligence (AI) model. METHODS: We used 120 RAMIE videos from four institutions to develop an AI model and eight other surgical videos from another institution for AI model evaluation. AI performance was measured using the Intersection over Union (IoU). Furthermore, to verify the AI's clinical validity, we conducted the two experiments on the early identification of RLN and recognition of its location by eight trainee surgeons with or without AI. RESULTS: The IoUs for AI recognition of the right and left RLNs were 0.40 ± 0.26 and 0.34 ± 0.27, respectively. The recognition of the right RLN presence in the beginning of right RLN lymph node dissection (LND) by surgeons with AI (81.3%) was significantly more accurate (p = 0.004) than that by surgeons without AI (46.9%). The IoU of right RLN during right RLN LND recognized by surgeons with AI (0.59 ± 0.18) was significantly higher (p = 0.010) than that by surgeons without AI (0.40 ± 0.29). CONCLUSIONS: Surgeons' recognition of anatomical structures in RAMIE was improved by our AI system with high accuracy. Especially in right RLN LND, surgeons could recognize the RLN more quickly and accurately by using the AI model.

SARS-CoV-2 ORF8 is a viral cytokine regulating immune responses.

Many patients with severe COVID-19 suffer from pneumonia and the elucidation of the mechanisms underlying the development of this severe condition is important. The in vivo function of the ORF8 protein secreted by SARS-CoV-2 is not well understood. Here, we analyzed the function of ORF8 protein by generating ORF8-knockout SARS-CoV-2 and found that the lung inflammation observed in wild-type SARS-CoV-2-infected hamsters was decreased in ORF8-knockout SARS-CoV-2-infected hamsters. Administration of recombinant ORF8 protein to hamsters also induced lymphocyte infiltration into the lungs. Similar pro-inflammatory cytokine production was observed in primary human monocytes treated with recombinant ORF8 protein. Furthermore, we demonstrated that the serum ORF8 protein levels are well-correlated with clinical markers of inflammation. These results demonstrated that the ORF8 protein is a SARS-CoV-2 viral cytokine involved in the immune dysregulation observed in COVID-19 patients, and that the ORF8 protein could be a novel therapeutic target in severe COVID-19 patients.

Automated artificial intelligence-based phase-recognition system for esophageal endoscopic submucosal dissection (with video).

BACKGROUND AND AIMS: Endoscopic submucosal dissection (ESD) for superficial esophageal cancer is a multistep treatment involving several endoscopic processes. Although analyzing each phase separately is worthwhile, it is not realistic in practice owing to the need for considerable manpower. To solve this problem, we aimed to establish a state-of-the-art artificial intelligence (AI)-based system, specifically, an automated phase-recognition system that can automatically identify each endoscopic phase based on video images. METHODS: Ninety-four videos of ESD procedures for superficial esophageal cancer were evaluated in this single-center study. A deep neural network-based phase-recognition system was developed in an automated manner to recognize each of the endoscopic phases. The system was trained with the use of videos that were annotated and verified by 2 GI endoscopists. RESULTS: The overall accuracy of the AI model for automated phase recognition was 90%, and the average precision, recall, and F value rates were 91%, 90%, and 90%, respectively. Two representative ESD videos predicted by the model indicated the usability of AI in clinical practice. CONCLUSIONS: We demonstrated that an AI-based automated phase-recognition system for esophageal ESD can be established with high accuracy. To the best of our knowledge, this is the first report on automated recognition of ESD treatment phases. Because this system enabled a detailed analysis of phases, collecting large volumes of data in the future may help to identify quality indicators for treatment techniques and uncover unmet medical needs that necessitate the creation of new treatment methods and devices.

GPI glycan remodeling by PGAP5 regulates transport of GPI-anchored proteins from the ER to the Golgi.

Many eukaryotic proteins are attached to the cell surface via glycosylphosphatidylinositol (GPI) anchors. How GPI-anchored proteins (GPI-APs) are trafficked from the endoplasmic reticulum (ER) to the cell surface is poorly understood, but the GPI moiety has been postulated to function as a signal for sorting and transport. Here, we established mutant cells that were selectively defective in transport of GPI-APs from the ER to the Golgi. We identified a responsible gene, designated PGAP5 (post-GPI-attachment to proteins 5). PGAP5 belongs to a dimetal-containing phosphoesterase family and catalyzed the remodeling of the glycan moiety on GPI-APs. PGAP5 catalytic activity is a prerequisite for the efficient exit of GPI-APs from the ER. Our data demonstrate that GPI glycan acts as an ER-exit signal and suggest that glycan remodeling mediated by PGAP5 regulates GPI-AP transport in the early secretory pathway.

Edge current and pairing order transition in chiral bacterial vortices.

Bacterial suspensions show turbulence-like spatiotemporal dynamics and vortices moving irregularly inside the suspensions. Understanding these ordered vortices is an ongoing challenge in active matter physics, and their application to the control of autonomous material transport will provide significant development in microfluidics. Despite the extensive studies, one of the key aspects of bacterial propulsion has remained elusive: The motion of bacteria is chiral, i.e., it breaks mirror symmetry. Therefore, the mechanism of control of macroscopic active turbulence by microscopic chirality is still poorly understood. Here, we report the selective stabilization of chiral rotational direction of bacterial vortices in achiral circular microwells sealed by an oil/water interface. The intrinsic chirality of bacterial swimming near the top and bottom interfaces generates chiral collective motions of bacteria at the lateral boundary of the microwell that are opposite in directions. These edge currents grow stronger as bacterial density increases, and, within different top and bottom interfaces, their competition leads to a global rotation of the bacterial suspension in a favored direction, breaking the mirror symmetry of the system. We further demonstrate that chiral edge current favors corotational configurations of interacting vortices, enhancing their ordering. The intrinsic chirality of bacteria is a key feature of the pairing order transition from active turbulence, and the geometric rule of pairing order transition may shed light on the strategy for designing chiral active matter.

Hepatitis C virus modulates signal peptide peptidase to alter host protein processing.

Immunoevasins are viral proteins that prevent antigen presentation on major histocompatibility complex (MHC) class I, thus evading host immune recognition. Hepatitis C virus (HCV) evades immune surveillance to induce chronic infection; however, how HCV-infected hepatocytes affect immune cells and evade immune recognition remains unclear. Herein, we demonstrate that HCV core protein functions as an immunoevasin. Its expression interfered with the maturation of MHC class I molecules catalyzed by the signal peptide peptidase (SPP) and induced their degradation via HMG-CoA reductase degradation 1 homolog, thereby impairing antigen presentation to CD8+ T cells. The expression of MHC class I in the livers of HCV core transgenic mice and chronic hepatitis C patients was impaired but was restored in patients achieving sustained virological response. Finally, we show that the human cytomegalovirus US2 protein, possessing a transmembrane region structurally similar to the HCV core protein, targets SPP to impair MHC class I molecule expression. Thus, SPP represents a potential target for the impairment of MHC class I molecules by DNA and RNA viruses.

Improvement in Epigenetic Aging Clock Induced by BioBran Containing Rice Kefiran in Relation to Various Biomarkers: A Pilot Study.

Many lifestyle-related diseases such as cancer, dementia, myocardial infarction, and stroke are known to be caused by aging, and the WHO's ICD-11 (International Classification of Diseases, 11th edition) created the code "aging-related" in 2022. In other words, aging is irreversible but aging-related diseases are reversible, so taking measures to treat them is important for health longevity and preventing other diseases. Therefore, in this study, we used BioBran containing rice kefiran as an approach to improve aging. Rice kefiran has been reported to improve the intestinal microflora, regulate the intestines, and have anti-aging effects. BioBran has also been reported to have antioxidant effects and improve liver function, and human studies have shown that it affects the diversity of the intestinal microbiota. Quantitative measures of aging that correlate with disease risk are now available through the epigenetic clock test, which examines the entire gene sequence and determines biological age based on the methylation level. Horvath's Clock is the best known of many epigenetic clock tests and was published by Steve Horvath in 2013. In this study, we examine the effect of using Horvath's Clock to improve aging and report on the results, which show a certain effect.

Loss of the N-acetylgalactosamine side chain of the GPI-anchor impairs bone formation and brain functions and accelerates the prion disease pathology.

Glycosylphosphatidylinositol (GPI) is a posttranslational glycolipid modification of proteins that anchors proteins in lipid rafts on the cell surface. Although some GPI-anchored proteins (GPI-APs), including the prion protein PrPC, have a glycan side chain composed of N-acetylgalactosamine (GalNAc)-galactose-sialic acid on the core structure of GPI glycolipid, in vivo functions of this GPI-GalNAc side chain are largely unresolved. Here, we investigated the physiological and pathological roles of the GPI-GalNAc side chain in vivo by knocking out its initiation enzyme, PGAP4, in mice. We show that Pgap4 mRNA is highly expressed in the brain, particularly in neurons, and mass spectrometry analysis confirmed the loss of the GalNAc side chain in PrPC GPI in PGAP4-KO mouse brains. Furthermore, PGAP4-KO mice exhibited various phenotypes, including an elevated blood alkaline phosphatase level, impaired bone formation, decreased locomotor activity, and impaired memory, despite normal expression levels and lipid raft association of various GPI-APs. Thus, we conclude that the GPI-GalNAc side chain is required for in vivo functions of GPI-APs in mammals, especially in bone and the brain. Moreover, PGAP4-KO mice were more vulnerable to prion diseases and died earlier after intracerebral inoculation of the pathogenic prion strains than wildtype mice, highlighting the protective roles of the GalNAc side chain against prion diseases.

Geometric confinement guides topological defect pairings and emergent flow in nematic cell populations.

Topological defects in nematically aligned cell populations play a critical role in modulating collective motion, ranging from microbial colonies to epithelial tissues. Despite the potential of manipulating such topological defects to control diverse self-organized structures and collective dynamics, controlling the position of defects in active matter remains a challenging area of research. In this study, we investigated the geometry-guided control of defect positioning and alignment in a nematic cell population by imposing spatial constraints consisting of two or three overlapping circular boundaries. The confined cell population exhibited a paired and ordered distribution of half-integer topological defects that remained stable even when the size of the spatial constraint was altered using geometric parameters. These defects direct the inward flow of cells, induced by the curved boundary shape, towards the geometric center of the confined space. This inward flow contributes to an increase in a local cell density, and furthermore the geometry-induced nematic order provides mechanical stimulation to confined cells, as indicated by the elongated cell nucleus. Our geometry-based approach sets the foundation for controlling defect pairing and provides insights into the interplay among geometry, topology, and collective dynamics.

Evaluation of surgical complexity by automated surgical process recognition in robotic distal gastrectomy using artificial intelligence.

BACKGROUND: Although radical gastrectomy with lymph node dissection is the standard treatment for gastric cancer, the complication rate remains high. Thus, estimation of surgical complexity is required for safety. We aim to investigate the association between the surgical process and complexity, such as a risk of complications in robotic distal gastrectomy (RDG), to establish an artificial intelligence (AI)-based automated surgical phase recognition by analyzing robotic surgical videos, and to investigate the predictability of surgical complexity by AI. METHOD: This study assessed clinical data and robotic surgical videos for 56 patients who underwent RDG for gastric cancer. We investigated (1) the relationship between surgical complexity and perioperative factors (patient characteristics, surgical process); (2) AI training for automated phase recognition and model performance was assessed by comparing predictions to the surgeon-annotated reference; (3) AI model predictability for surgical complexity was calculated by the area under the curve. RESULT: Surgical complexity score comprised extended total surgical duration, bleeding, and complications and was strongly associated with the intraoperative surgical process, especially in the beginning phases (area under the curve 0.913). We established an AI model that can recognize surgical phases from video with 87% accuracy; AI can determine intraoperative surgical complexity by calculating the duration of beginning phases from phases 1-3 (area under the curve 0.859). CONCLUSION: Surgical complexity, as a surrogate of short-term outcomes, can be predicted by the surgical process, especially in the extended duration of beginning phases. Surgical complexity can also be evaluated with automation using our artificial intelligence-based model.

The relationship between the esophageal endoscopic submucosal dissection technical difficulty and its intraoperative process.

BACKGROUND: Estimating the esophageal endoscopic submucosal dissection (ESD) technical difficulty is important to reduce complications. Endoscopic duration is one of the related factors to a technical difficulty. The relationship between the esophageal ESD technical difficulty and its intraoperative process was analyzed as a first step toward automatic technical difficulty recognition using artificial intelligence. METHODS: This study enrolled 75 patients with superficial esophageal cancer who underwent esophageal ESD. The technical difficulty score was established, which consisted of three factors, including total procedure duration, en bloc resection, and complications. Additionally, technical difficulty-related factors, which were perioperative factors that included the intraoperative process, were investigated. RESULTS: Eight (11%) patients were allocated to high difficulty, whereas 67 patients (89%) were allocated to low difficulty. The intraoperative process, which was shown as the extension of each endoscopic phase, was significantly related to a technical difficulty. The area under the curve (AUC) values were higher at all the phase duration than at the clinical characteristics. Submucosal dissection phase (AUC 0.902; 95% confidence intervals (CI) 0.752-1.000), marking phase (AUC 0.827; 95% CI 0.703-0.951), and early phase which was defined as the duration from the start of marking to the end of submucosal injection (AUC 0.847; 95% CI 0.701-0.992) were significantly related to technical difficulty. CONCLUSIONS: The intraoperative process, particularly early phase, was strongly associated with esophageal ESD technical difficulty. This study demonstrated the potential for automatic evaluation of esophageal ESD technical difficulty when combined with an AI-based automatic phase evaluation system.

Influence of history of falls and physical function on obstacle-straddling behavior.

[Purpose] This study aimed to clarify the relationship between falls and lower leg motion during obstacle crossing, in which stumbling or tripping is the most common cause of falls in the elderly population. [Participants and Methods] This study included 32 older adults who performed the obstacle crossing motion. The heights of the obstacles were 20, 40, and 60 mm. To analyze the leg motion, a video analysis system was used. The hip, knee, and ankle joint angles during the crossing motion were calculated by the video analysis software, Kinovea. To evaluate the risk of falls, one leg stance time and timed up and go test were measured, and data on fall history were collected using a questionnaire. Participants were divided into two groups: high-risk and low-risk groups, according to the degree of fall risk. [Results] The high-risk group showed greater changes in hip flexion angle in the forelimb. The hip flexion angle in the hindlimb and the angle change of lower extremities among the high-risk group became larger. [Conclusion] Participants in the high-risk group should lift their legs high when performing the crossing motion to ensure foot clearance and avoid stumbling over the obstacle.

Protein Needles Designed to Self-Assemble through Needle Tip Engineering.

The dynamic process of formation of protein assemblies is essential to form highly ordered structures in biological systems. Advances in structural and synthetic biology have led to the construction of artificial protein assemblies. However, development of design strategies exploiting the anisotropic shape of building blocks of protein assemblies has not yet been achieved. Here, the 2D assembly pattern of protein needles (PNs) is controlled by regulating their tip-to-tip interactions. The PN is an anisotropic needle-shaped protein composed of ß-helix, foldon, and His-tag. Three different types of tip-modified PNs are designed by deleting the His-tag and foldon to change the protein-protein interactions. Observing their assembly by high-speed atomic force microscopy (HS-AFM) reveals that PN, His-tag deleted PN, and His-tag and foldon deleted PN form triangular lattices, the monomeric state with nematic order, and fiber assemblies, respectively, on a mica surface. Their assembly dynamics are observed by HS-AFM and analyzed by the theoretical models. Monte Carlo (MC) simulations indicate that the mica-PN interactions and the flexible and multipoint His-tag interactions cooperatively guide the formation of the triangular lattice. This work is expected to provide a new strategy for constructing supramolecular protein architectures by controlling directional interactions of anisotropic shaped proteins.

Genetic basis for the evolution of pelvic-fin brooding, a new mode of reproduction, in a Sulawesian fish.

Modes of reproduction in animals are diverse, with different modes having evolved independently in multiple lineages across a variety of taxa. However, an understanding of the genomic change driving the transition between different modes of reproduction is limited. Several ricefishes (Adrianichthyidae) on the island of Sulawesi have a unique mode of reproduction called "pelvic-fin brooding," wherein females carry externally fertilized eggs until hatching using their pelvic fins. Phylogenomic analysis demonstrated pelvic-fin brooders to have evolved at least twice in two distant clades of the Adrianichthyidae. We investigated the genetic architecture of the evolution of this unique mode of reproduction. Morphological analyses and laboratory observations revealed that females of pelvic-fin brooders have longer pelvic fins and a deeper abdominal concavity, and that they can carry an egg clutch for longer than nonbrooding adrianichthyids, suggesting that these traits play important roles in this reproductive mode. Quantitative trait locus mapping using a cross between a pelvic-fin brooder Oryzias eversi and a nonbrooding O. dopingdopingensis reveals different traits involved in pelvic-fin brooding to be controlled by different loci on different chromosomes. Genomic analyses of admixture detected no signatures of introgression between two lineages with pelvic-fin brooders, indicating that introgression is unlikely to be responsible for repeated evolution of pelvic-fin brooding. These findings suggest that multiple independent mutations may have contributed to the convergent evolution of this novel mode of reproduction.

Automated Surgical-Phase Recognition for Robot-Assisted Minimally Invasive Esophagectomy Using Artificial Intelligence.

BACKGROUND: Although a number of robot-assisted minimally invasive esophagectomy (RAMIE) procedures have been performed due to three-dimensional field of view, image stabilization, and flexible joint function, both the surgeons and surgical teams require proficiency. This study aimed to establish an artificial intelligence (AI)-based automated surgical-phase recognition system for RAMIE by analyzing robotic surgical videos. METHODS: This study enrolled 31 patients who underwent RAMIE. The videos were annotated into the following nine surgical phases: preparation, lower mediastinal dissection, upper mediastinal dissection, azygos vein division, subcarinal lymph node dissection (LND), right recurrent laryngeal nerve (RLN) LND, left RLN LND, esophageal transection, and post-dissection to completion of surgery to train the AI for automated phase recognition. An additional phase ("no step") was used to indicate video sequences upon removal of the camera from the thoracic cavity. All the patients were divided into two groups, namely, early period (20 patients) and late period (11 patients), after which the relationship between the surgical-phase duration and the surgical periods was assessed. RESULTS: Fourfold cross validation was applied to evaluate the performance of the current model. The AI had an accuracy of 84%. The preparation (p = 0.012), post-dissection to completion of surgery (p = 0.003), and "no step" (p < 0.001) phases predicted by the AI were significantly shorter in the late period than in the early period. CONCLUSIONS: A highly accurate automated surgical-phase recognition system for RAMIE was established using deep learning. Specific phase durations were significantly associated with the surgical period at the authors' institution.

Controlling Collective Motion of Kinesin-Driven Microtubules via Patterning of Topographic Landscapes.

Biomolecular motor proteins that generate forces by consuming chemical energy obtained from ATP hydrolysis play pivotal roles in organizing cytoskeletal structures in living cells. An ability to control cytoskeletal structures would benefit programmable protein patterning; however, our current knowledge is limited because of the underdevelopment of engineering approaches for controlling pattern formation. Here, we demonstrate the controlling of self-assembled patterns of microtubules (MTs) driven by kinesin motors by designing the boundary shape in fabricated microwells. By manipulating the collision angle of gliding MTs defined by the boundary shape, the self-assembly of MTs can be controlled to form protruding bundle and bridge patterns. Corroborated by the theory of self-propelled rods, we further show that the alignment of MTs determines the transition between the assembled patterns, providing a blueprint to reconstruct bridge structures in microchannels. Our findings introduce the tailoring of the self-organization of cytoskeletons and motor proteins for nanotechnological applications.

PGAP6, a GPI-specific phospholipase A2, has narrow substrate specificity against GPI-anchored proteins.

PGAP6, also known as TMEM8A, is a phospholipase A2 with specificity to glycosylphosphatidylinositol (GPI) and expressed on the surface of various cells. CRIPTO, a GPI-anchored co-receptor for a morphogenic factor Nodal, is a sensitive substrate of PGAP6. PGAP6-mediated shedding of CRIPTO plays a critical role in an early stage of embryogenesis. In contrast, CRYPTIC, a close family member of CRIPTO, is resistant to PGAP6. In this report, chimeras between CRIPTO and CRYPTIC and truncate mutants of PGAP6 were used to demonstrate that the Cripto-1/FRL1/Cryptic domain of CRIPTO is recognized by an N-terminal domain of PGAP6 for processing. We also report that among 56 human GPI-anchored proteins tested, only glypican 3, prostasin, SPACA4, and contactin-1, in addition to CRIPTO, are sensitive to PGAP6, indicating that PGAP6 has a narrow specificity toward various GPI-anchored proteins.