Publications

Upon the initiation of collective cell migration, the cells at the free edge are specified as leader cells; however, the mechanism underlying the leader cell specification remains elusive. Here, we show that lamellipodial extension after the release from mechanical confinement causes sustained extracellular signal-regulated kinase (ERK) activation and underlies the leader cell specification. Live-imaging of Madin-Darby canine kidney (MDCK) cells and mouse epidermis through the use of Förster resonance energy transfer (FRET)-based biosensors showed that leader cells exhibit sustained ERK activation in a hepatocyte growth factor (HGF)-dependent manner. Meanwhile, follower cells exhibit oscillatory ERK activation waves in an epidermal growth factor (EGF) signaling-dependent manner. Lamellipodial extension at the free edge increases the cellular sensitivity to HGF. The HGF-dependent ERK activation, in turn, promotes lamellipodial extension, thereby forming a positive feedback loop between cell extension and ERK activation and specifying the cells at the free edge as the leader cells. Our findings show that the integration of physical and biochemical cues underlies the leader cell specification during collective cell migration.Copyright © 2022 Elsevier Inc. All rights reserved.

JTD Keywords: activation, c-met, contact inhibition, focal adhesions, heparan-sulfate, mechanical forces, morphogenesis, rho, stress fibers, Collective cell migration, Erk, Feedback regulation, Fret, Growth-factor receptor, Hgf, Lamellipodia, Leader cell specification, Signal transduction, Traction force, Wound healing

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. In this work, we used a network-based mathematical model to identify sensitivity regulators and drug combinations for the PI3Ka inhibitor alpelisib in estrogen receptor positive (ER) PIK3CAmutant breast cancer. The model-predicted efficacious combination of alpelisib and BH3 mimetics, for example, MCL1 inhibitors, was experimentally validated in ER breast cancer cell lines. Consistent with the model, FOXO3 downregulation reduced sensitivity to alpelisib, revealing a novel potential resistance mechanism. Cell line-specific sensitivity to combinations of alpelisib and BH3 mimetics depended on which BCL2 family members were highly expressed. On the basis of these results, newly developed cell line-specific network models were able to recapitulate the observed differential response to alpelisib and BH3 mimetics. This approach illustrates how network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.

JTD Keywords: activation, akt, feedback, foxo, leads, p27(kip1), phosphorylation, reveals, transcription factors, Dependent kinase inhibitor

The extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase (MAPK) pathway involves a three-step cascade of kinases that transduce signals and promote processes such as cell growth, development, and apoptosis. An aberrant response of this pathway is related to the proliferation of cell diseases and tumors. By using simulation modeling, we document that the protein arginine methyltransferase 5 (PRMT5) modulates the MAPK pathway and thus avoids an aberrant behavior. PRMT5 methylates the Raf kinase, reducing its catalytic activity and thereby, reducing the activation of ERK in time and amplitude. Two minimal computational models of the epidermal growth factor (EGF)-Ras-ERK MAPK pathway influenced by PRMT5 were proposed: a first model in which PRMT5 is activated by EGF and a second one in which PRMT5 is stimulated by the cascade response. The reported results show that PRMT5 reduces the time duration and the expression of the activated ERK in both cases, but only in the first model PRMT5 limits the EGF range that generates an ERK activation. Based on our data, we propose the protein PRMT5 as a regulatory factor to develop strategies to fight against an excessive activity of the MAPK pathway, which could be of use in chronic diseases and cancer.

JTD Keywords: cancer, cell response modulation, computational model, egf-ras-erk signaling route, mapk pathway, methylation, Arginine methyltransferase 5, Cancer, Cell response modulation, Colorectal-cancer, Computational model, Egf-ras-erk signaling route, Epidermal-growth-factor, Factor receptor, Histone h3, Kinase cascade, Mapk pathway, Methylation, Negative-feedback, Pc12 cells, Prmt5, Protein, Signal-transduction

During collective migration of epithelial cells, the migration direction is aligned over a tissue-scale expanse. Although the collective cell migration is known to be directed by mechanical forces transmitted via cell-cell junctions, it remains elusive how the intercellular force transmission is coordinated with intracellular biochemical signaling to achieve collective movements. Here, we show that intercellular coupling of extracellular signal-regulated kinase (ERK)-mediated mechanochemical feedback yields long-distance transmission of guidance cues. Mechanical stretch activates ERK through epidermal growth factor receptor (EGFR) activation, and ERK activation triggers cell contraction. The contraction of the activated cell pulls neighboring cells, evoking another round of ERK activation and contraction in the neighbors. Furthermore, anisotropic contraction based on front-rear polarization guarantees unidirectional propagation of ERK activation, and in turn, the ERK activation waves direct multicellular alignment of the polarity, leading to long-range ordered migration. Our findings reveal that mechanical forces mediate intercellular signaling underlying sustained transmission of guidance cues for collective cell migration.

JTD Keywords: Collective cell migration, EGFR, ERK/MAPK, FRET, Front-rear polarity, Intercellular signal transfer, Mathematical model, Mechanochemical feedback, Mechanotransduction, wave propagation

Whispering gallery mode resonator lasers hold the promise of an ultralow intrinsic limit of detection. However, the widespread use of these devices for biosensing applications has been hindered by the complexity and lack of robustness of the proposed configurations. In this work, we demonstrate biosensing with an integrated microdisk laser. Al2O3doped with Yb3+ was utilized because of its low optical losses as well as its emission in the range 1020–1050 nm, outside the absorption band of water. Single-mode laser emission was obtained at a wavelength of 1024 nm with a linewidth of 250 kHz while the microdisk cavity was submerged in water. A limit of detection of 300 pM (3.6 ng/ml) of the protein rhS100A4 in urine was experimentally demonstrated, showing the potential of the proposed devices for biosensing.

JTD Keywords: Distributed feedback lasers, Fiber lasers, Laser modes, Microdisk lasers, Single mode lasers, Tunable lasers

Concentrations down to 3 nM of the rhS100A4 protein, associated with human tumor development, have been detected in undiluted urine using an integrated sensor based on microring resonators in the emerging Al2O3 photonic platform. The fabricated microrings were designed for operation in the C-band (λ = 1565 nm) and exhibited a high-quality factor in air of 3.2 × 105. The bulk refractive index sensitivity of the devices was ~100 nm/RIU (for TM polarization) with a limit of detection of ~10−6 RIU. A surface functionalization protocol was developed to allow for the selective binding of the monoclonal antibodies designed to capture the target biomarker to the surface of the Al2O3 microrings. The detection of rhS100A4 proteins at clinically relevant concentrations in urine is a big milestone towards the use of biosensors for the screening and early diagnosis of different cancers. Biosensors based on this microring technology can lead to portable, multiplexed and easy-to-use point of care devices.

JTD Keywords: Distributed feedback lasers, Effective refractive index, Laser coupling, Polarization maintaining fibers, Refractive index, Scanning electron microscopy

This chapter discusses basic concepts from control theory and machine learning to facilitate a formal understanding of animal learning and motor control. It first distinguishes between feedback and feed-forward control strategies, and later introduces the classification of machine learning applications into supervised, unsupervised, and reinforcement learning problems. Next, it links these concepts with their counterparts in the domain of the psychology of animal learning, highlighting the analogies between supervised learning and classical conditioning, reinforcement learning and operant conditioning, and between unsupervised and perceptual learning. Additionally, it interprets innate and acquired actions from the standpoint of feedback vs anticipatory and adaptive control. Finally, it argues how this framework of translating knowledge between formal and biological disciplines can serve us to not only structure and advance our understanding of brain function but also enrich engineering solutions at the level of robot learning and control with insights coming from biology.

JTD Keywords: Feedback control, Feed-forward control, Supervised learning, Unsupervised learning, Reinforcement, Learning, Classical conditioning, Operant conditioning, Reflex, Anticipatory reflex

Endowing current surgical robotic systems with haptic feedback to perform minimally invasive surgery (MIS), such as laparoscopy, is still a challenge. Haptic is a feature lost in surgical teleoperated systems limiting surgeons capabilities and ability. The availability of haptics would provide important advantages to the surgeon: Improved tissue manipulation, reducing the breaking of sutures and increase the feeling of telepresence, among others. To design and develop a haptic system, the measurement of forces can be implemented based on two approaches: Direct and indirect force sensing. MIS performed with surgical robots, imposes many technical constraints to measure forces, such as: Miniaturization, need of sterilization or materials compatibility, making it necessary to rely on indirect force sensing. Based on mathematical models of the components involved in an intervention and indirect force sensing techniques, a global perspective on how to address the problem of measurement of tool-tissue interaction forces is presented.

JTD Keywords: Surgical robotics, Haptic feedback, Indirect force sensing, Machine learning, Data fusion, Mathematical models