AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis.

While alterations in nucleus size, shape, and color are ubiquitous in cancer, comprehensive quantification of nuclear morphology across a whole-slide histologic image remains a challenge. Here, we describe the development of a pan-tissue, deep learning-based digital pathology pipeline for exhaustive nucleus detection, segmentation, and classification and the utility of this pipeline for nuclear morphologic biomarker discovery. Manually-collected nucleus annotations were used to train an object detection and segmentation model for identifying nuclei, which was deployed to segment nuclei in H&E-stained slides from the BRCA, LUAD, and PRAD TCGA cohorts. Interpretable features describing the shape, size, color, and texture of each nucleus were extracted from segmented nuclei and compared to measurements of genomic instability, gene expression, and prognosis. The nuclear segmentation and classification model trained herein performed comparably to previously reported models. Features extracted from the model revealed differences sufficient to distinguish between BRCA, LUAD, and PRAD. Furthermore, cancer cell nuclear area was associated with increased aneuploidy score and homologous recombination deficiency. In BRCA, increased fibroblast nuclear area was indicative of poor progression-free and overall survival and was associated with gene expression signatures related to extracellular matrix remodeling and anti-tumor immunity. Thus, we developed a powerful pan-tissue approach for nucleus segmentation and featurization, enabling the construction of predictive models and the identification of features linking nuclear morphology with clinically-relevant prognostic biomarkers across multiple cancer types.

Potential protein kinase inhibitors that target G-quadruplex DNA structures in the human telomeric regions.

Telomeric regions contain Guanine-rich sequences arranged in a planar manner and connected by Hoogsteen hydrogen bonds that can fold into G-quadruplex (G4) DNA structures, and can be stabilized by monovalent metal cations. The presence of G4 DNA holds significance in cancer-related processes, especially due to their regulatory potential at transcriptional and translational levels of oncogene and tumor suppressor genes. The objective of this current research is to explore the evolving realm of FDA-approved protein kinase inhibitors, with a specific emphasis on their capacity to stabilize the G4 DNA structures formed at the human telomeric regions. This involves investigating the possibility of repurposing FDA-approved protein kinase inhibitors as a novel approach for targeting multiple cancer types. In this context, we have selected 16 telomeric G4 DNA structures as targets and 71 FDA-approved small-molecule protein kinase inhibitors as ligands. To investigate their binding affinities, molecular docking of human telomeric G4 DNA with nuclear protein kinase inhibitors and their corresponding co-crystalized ligands were performed. We found that Ponatinib and Lapatinib interact with all the selected G4 targets, the binding free energy calculations, and molecular dynamic simulations confirm their binding efficacy and stability. Thus, it is hypothesized that Ponatinib and Lapatinib may stabilize human telomeric G4 DNA in addition to their ability to inhibit BCR-ABL and the other members of the EGFR family. As a result, we also hypothesize that the stabilization of G4 DNA might represent an additional underlying mechanism contributing to their efficacy in exerting anti-cancer effects.

Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.

INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision of PathR assessment. LCMC3 (NCT02927301) evaluated neoadjuvant atezolizumab in patients with resectable NSCLC and reported a 20% major PathR rate. METHODS: We determined PathR in primary tumor resection specimens using guidelines-based visual techniques and developed a convolutional neural network model using the same criteria to digitally measure the percent viable tumor on whole-slide images. Concordance was evaluated between visual determination of percent viable tumor (n = 151) performed by one of the 47 local pathologists and three central pathologists. RESULTS: For concordance among visual determination of percent viable tumor, the interclass correlation coefficient was 0.87 (95% confidence interval [CI]: 0.84-0.90). Agreement for visually assessed 10% or less viable tumor (major PathR [MPR]) in the primary tumor was 92.1% (Fleiss kappa = 0.83). Digitally assessed percent viable tumor (n = 136) correlated with visual assessment (Pearson r = 0.73; digital/visual slope = 0.28). Digitally assessed MPR predicted visually assessed MPR with outstanding discrimination (area under receiver operating characteristic curve, 0.98) and was associated with longer disease-free survival (hazard ratio [HR] = 0.30; 95% CI: 0.09-0.97, p = 0.033) and overall survival (HR = 0.14, 95% CI: 0.02-1.06, p = 0.027) versus no MPR. Digitally assessed PathR strongly correlated with visual measurements. CONCLUSIONS: Artificial intelligence-powered digital pathology exhibits promise in assisting pathologic assessments in neoadjuvant NSCLC clinical trials. The development of artificial intelligence-powered approaches in clinical settings may aid pathologists in clinical operations, including routine PathR assessments, and subsequently support improved patient care and long-term outcomes.

In-silico studies of Brassica oleracea active compounds and their role in thyroid peroxidase activity.

Cabbage, a leafy vegetable that is widely consumed across the globe, holds a significant place within the Brassica family. For almost a century, its potential anti-thyroid effects have captured attention. The presence of compounds such as thiocyanate and goitrin in cabbage has been extensively investigated for their ability to impede sodium-iodide symporter and thyroid peroxidase (TPO) activities. The present study is focused on uncovering the active constituents in cabbage that could interact with TPO, while also examining their stability under cooking temperatures. Employing molecular docking and molecular dynamic simulation techniques, we quantified the binding strength of phytochemicals present in cabbage with the target. Out of the 60 compounds identified in cabbage leaves, only 18 exhibited docking scores surpassing those of the commercially available anti-thyroid drug, methimazole. These chosen compounds were studied for binding free energy and pharmacokinetic properties. A specific compound, gamma-Terpinene, classified as a monoterpene, emerged as noteworthy due to its alignment with all criteria and the highest observed binding free energy compared to others. Furthermore, we explored the stability of gamma-Terpinene at 373.15K (cooking temperature) and observed its susceptibility to degradation. This might contribute to the relatively diminished anti-thyroid effects of cabbage when consumed in cooked form. Consequently, our findings suggest that the consumption of cooked cabbage could be more conducive to maintaining normal thyroid function, as opposed to its raw counterpart.Communicated by Ramaswamy H. Sarma.

In-silico screening and identification of potential drug-like compounds for dengue-associated thrombocytopenia from Carica papaya leaf extracts.

Dengue virus is a mosquito-borne pathogen that causes a variety of illnesses ranging from mild fever to severe and fatal dengue haemorrhagic fever or dengue shock syndrome. One of the major clinical manifestations of severe dengue infection is thrombocytopenia. The dengue non-structural protein 1 (NS1) is the primary protein that stimulates immune cells via toll-like receptor 4 (TLR4), induces platelets, and promotes aggregation, which could result in thrombocytopenia. The leaf extracts of Carica papaya seem to have therapeutic benefits in managing thrombocytopenia associated with dengue. The present study focuses on understanding the underlying mechanism of the use of papaya leaf extracts in treating thrombocytopenia. We have identified 124 phytocompounds that are present in the papaya leaf extract. The pharmacokinetics, molecular docking, binding free energy calculations, and molecular dynamic simulations were performed to investigate the drug-like properties, binding affinities, and interaction of phytocompounds with NS1 protein as well as the interactions of NS1 with TLR4. Three phytocompounds were found to bind with the ASN130, a crucial amino acid residue in the active site of the NS1 protein. Thus, we conclude that Rutin, Myricetin 3-rhamnoside, or Kaempferol 3-(2''-rhamnosylrutinoside) may serve as promising molecules by ameliorating thrombocytopenia in dengue-infected patients by interfering the interaction of NS1 with TLR4. These molecules can serve as drugs in the management of dengue-associated thrombocytopenia after verifying their effectiveness and assessing the drug potency, through additional in-vitro assays.Communicated by Ramaswamy H. Sarma.

Design-development of an at-home modular brain-computer interface (BCI) platform in a case study of cervical spinal cord injury.

OBJECTIVE: The objective of this study was to develop a portable and modular brain-computer interface (BCI) software platform independent of input and output devices. We implemented this platform in a case study of a subject with cervical spinal cord injury (C5 ASIA A). BACKGROUND: BCIs can restore independence for individuals with paralysis by using brain signals to control prosthetics or trigger functional electrical stimulation. Though several studies have successfully implemented this technology in the laboratory and the home, portability, device configuration, and caregiver setup remain challenges that limit deployment to the home environment. Portability is essential for transitioning BCI from the laboratory to the home. METHODS: The BCI platform implementation consisted of an Activa PC + S generator with two subdural four-contact electrodes implanted over the dominant left hand-arm region of the sensorimotor cortex, a minicomputer fixed to the back of the subject's wheelchair, a custom mobile phone application, and a mechanical glove as the end effector. To quantify the performance for this at-home implementation of the BCI, we quantified system setup time at home, chronic (14-month) decoding accuracy, hardware and software profiling, and Bluetooth communication latency between the App and the minicomputer. We created a dataset of motor-imagery labeled signals to train a binary motor imagery classifier on a remote computer for online, at-home use. RESULTS: Average bluetooth data transmission delay between the minicomputer and mobile App was 23 ± 0.014 ms. The average setup time for the subject's caregiver was 5.6 ± 0.83 min. The average times to acquire and decode neural signals and to send those decoded signals to the end-effector were respectively 404.1 ms and 1.02 ms. The 14-month median accuracy of the trained motor imagery classifier was 87.5 ± 4.71% without retraining. CONCLUSIONS: The study presents the feasibility of an at-home BCI system that subjects can seamlessly operate using a friendly mobile user interface, which does not require daily calibration nor the presence of a technical person for at-home setup. The study also describes the portability of the BCI system and the ability to plug-and-play multiple end effectors, providing the end-user the flexibility to choose the end effector to accomplish specific motor tasks for daily needs. Trial registration ClinicalTrials.gov: NCT02564419. First posted on 9/30/2015.

Implantable brain-computer interface for neuroprosthetic-enabled volitional hand grasp restoration in spinal cord injury.

Loss of hand function after cervical spinal cord injury severely impairs functional independence. We describe a method for restoring volitional control of hand grasp in one 21-year-old male subject with complete cervical quadriplegia (C5 American Spinal Injury Association Impairment Scale A) using a portable fully implanted brain-computer interface within the home environment. The brain-computer interface consists of subdural surface electrodes placed over the dominant-hand motor cortex and connects to a transmitter implanted subcutaneously below the clavicle, which allows continuous reading of the electrocorticographic activity. Movement-intent was used to trigger functional electrical stimulation of the dominant hand during an initial 29-weeks laboratory study and subsequently via a mechanical hand orthosis during in-home use. Movement-intent information could be decoded consistently throughout the 29-weeks in-laboratory study with a mean accuracy of 89.0% (range 78-93.3%). Improvements were observed in both the speed and accuracy of various upper extremity tasks, including lifting small objects and transferring objects to specific targets. At-home decoding accuracy during open-loop trials reached an accuracy of 91.3% (range 80-98.95%) and an accuracy of 88.3% (range 77.6-95.5%) during closed-loop trials. Importantly, the temporal stability of both the functional outcomes and decoder metrics were not explored in this study. A fully implanted brain-computer interface can be safely used to reliably decode movement-intent from motor cortex, allowing for accurate volitional control of hand grasp.

Perioperative Multimodal General Anesthesia Focusing on Specific CNS Targets in Patients Undergoing Cardiac Surgeries: The Pathfinder Feasibility Trial.

Multimodal general anesthesia (MMGA) is a strategy that utilizes the well-known neuroanatomy and neurophysiology of nociception and arousal control in designing a rational and clinical practical paradigm to regulate the levels of unconsciousness and antinociception during general anesthesia while mitigating side effects of any individual anesthetic. We sought to test the feasibility of implementing MMGA for seniors undergoing cardiac surgery, a high-risk cohort for hemodynamic instability, delirium, and post-operative cognitive dysfunction. Twenty patients aged 60 or older undergoing on-pump coronary artery bypass graft (CABG) surgery or combined CABG/valve surgeries were enrolled in this non-randomized prospective observational feasibility trial, wherein we developed MMGA specifically for cardiac surgeries. Antinociception was achieved by a combination of intravenous remifentanil, ketamine, dexmedetomidine, and magnesium together with bupivacaine administered as a pecto-intercostal fascial block. Unconsciousness was achieved by using electroencephalogram (EEG)-guided administration of propofol along with the sedative effects of the antinociceptive agents. EEG-guided MMGA anesthesia was safe and feasible for cardiac surgeries, and exploratory analyses found hemodynamic stability and vasopressor usage comparable to a previously collected cohort. Intraoperative EEG suppression events and postoperative delirium were found to be rare. We report successful use of a total intravenous anesthesia (TIVA)-based MMGA strategy for cardiac surgery and establish safety and feasibility for studying MMGA in a full clinical trial. Clinical Trial Number: www.clinicaltrials.gov; identifier NCT04016740 (https://clinicaltrials.gov/ct2/show/NCT04016740).

Etiology of Burst Suppression EEG Patterns.

Burst-suppression electroencephalography (EEG) patterns of electrical activity, characterized by intermittent high-power broad-spectrum oscillations alternating with isoelectricity, have long been observed in the human brain during general anesthesia, hypothermia, coma and early infantile encephalopathy. Recently, commonalities between conditions associated with burst-suppression patterns have led to new insights into the origin of burst-suppression EEG patterns, their effects on the brain, and their use as a therapeutic tool for protection against deleterious neural states. These insights have been further supported by advances in mechanistic modeling of burst suppression. In this Perspective, we review the origins of burst-suppression patterns and use recent insights to weigh evidence in the controversy regarding the extent to which burst-suppression patterns observed during profound anesthetic-induced brain inactivation are associated with adverse clinical outcomes. Whether the clinical intent is to avoid or maintain the brain in a state producing burst-suppression patterns, monitoring and controlling neural activity presents a technical challenge. We discuss recent advances that enable monitoring and control of burst suppression.

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-specific electroencephalographic (EEG) signatures of anesthesia-induced unconsciousness have been identified previously. We applied machine learning approaches to construct classification models for real-time tracking of unconscious state during anesthesia-induced unconsciousness. We used cross-validation to select and train the best performing models using 33,159 2s segments of EEG data recorded from 7 healthy volunteers who received increasing infusions of propofol while responding to stimuli to directly assess unconsciousness. Cross-validated models of unconsciousness performed very well when tested on 13,929 2s EEG segments from 3 left-out volunteers collected under the same conditions (median volunteer AUCs 0.99-0.99). Models showed strong generalization when tested on a cohort of 27 surgical patients receiving solely propofol collected in a separate clinical dataset under different circumstances and using different hardware (median patient AUCs 0.95-0.98), with model predictions corresponding with actions taken by the anesthesiologist during the cases. Performance was also strong for 17 patients receiving sevoflurane (alone or in addition to propofol) (median AUCs 0.88-0.92). These results indicate that EEG spectral features can predict unconsciousness, even when tested on a different anesthetic that acts with a similar neural mechanism. With high performance predictions of unconsciousness, we can accurately monitor anesthetic state, and this approach may be used to engineer infusion pumps to intelligibly respond to patients' neural activity.

Hopping trajectories due to long-range interactions determine surface accumulation of microalgae.

The accumulation of motile cells at solid interfaces increases the rate of surface encounters and the likelihood of surface attachment, leading to surface colonization and biofilm formation. The cell density distribution in the vicinity of a physical boundary is influenced by the interactions between the microswimmers and their physical environment, including hydrodynamic and steric interactions, as well as by stochastic effects. Disentangling the contributions of these effects remains an experimental challenge. Here, we use a custom-made four-camera view microscope to track a population of motile puller-type Chlamydomonas reinhardtii in a relatively unconstrained three-dimensional (3D) domain. Our experiments yield an extensive sample of 3D trajectories including cell-surface encounters with a planar wall, from which we extract a full description of the dynamics and the stochasticity of swimming cells. We use this large data sample and combine it with Monte Carlo simulations to determine the link between the dynamics at the single-cell level and the cell density. Our experiments demonstrate that the near-wall scattering is bimodal, corresponding to steric and hydrodynamic effects. We find, however, that this near-wall dynamics has little influence on the cell accumulation at the surface. On the other hand, we present evidence of a cell-induced surface-directed rotation leading to a vertical orbiting behavior and hopping trajectories, consistent with long-range hydrodynamic effects. We identify this long-range effect to be at the origin of the significant surface accumulation of cells.

Dual-Color Single-Cell Imaging of the Suprachiasmatic Nucleus Reveals a Circadian Role in Network Synchrony.

The suprachiasmatic nucleus (SCN) acts as a master pacemaker driving circadian behavior and physiology. Although the SCN is small, it is composed of many cell types, making it difficult to study the roles of particular cells. Here we develop bioluminescent circadian reporter mice that are Cre dependent, allowing the circadian properties of genetically defined populations of cells to be studied in real time. Using a Color-Switch PER2::LUCIFERASE reporter that switches from red PER2::LUCIFERASE to green PER2::LUCIFERASE upon Cre recombination, we assess circadian rhythms in two of the major classes of peptidergic neurons in the SCN: AVP (arginine vasopressin) and VIP (vasoactive intestinal polypeptide). Surprisingly, we find that circadian function in AVP neurons, not VIP neurons, is essential for autonomous network synchrony of the SCN and stability of circadian rhythmicity.

The malaria parasite has an intrinsic clock.

Malarial rhythmic fevers are the consequence of the synchronous bursting of red blood cells (RBCs) on completion of the malaria parasite asexual cell cycle. Here, we hypothesized that an intrinsic clock in the parasite Plasmodium chabaudi underlies the 24-hour-based rhythms of RBC bursting in mice. We show that parasite rhythms are flexible and lengthen to match the rhythms of hosts with long circadian periods. We also show that malaria rhythms persist even when host food intake is evenly spread across 24 hours, suggesting that host feeding cues are not required for synchrony. Moreover, we find that the parasite population remains synchronous and rhythmic even in an arrhythmic clock mutant host. Thus, we propose that parasite rhythms are generated by the parasite, possibly to anticipate its circadian environment.

Constructing a control-ready model of EEG signal during general anesthesia in humans.

Significant effort toward the automation of general anesthesia has been made in the past decade. One open challenge is in the development of control-ready patient models for closed-loop anesthesia delivery. Standard depth-of-anesthesia tracking does not readily capture inter-individual differences in response to anesthetics, especially those due to age, and does not aim to predict a relationship between a control input (infused anesthetic dose) and system state (commonly, a function of electroencephalography (EEG) signal). In this work, we developed a control-ready patient model for closed-loop propofol-induced anesthesia using data recorded during a clinical study of EEG during general anesthesia in ten healthy volunteers. We used principal component analysis to identify the low-dimensional state-space in which EEG signal evolves during anesthesia delivery. We parameterized the response of the EEG signal to changes in propofol target-site concentration using logistic models. We note that inter-individual differences in anesthetic sensitivity may be captured by varying a constant cofactor of the predicted effect-site concentration. We linked the EEG dose-response with the control input using a pharmacokinetic model. Finally, we present a simple nonlinear model predictive control in silico demonstration of how such a closed-loop system would work.

A simulation-based comparative analysis of PID and LQG control for closed-loop anesthesia delivery.

Closed loop anesthesia delivery (CLAD) systems can help anesthesiologists efficiently achieve and maintain desired anesthetic depth over an extended period of time. A typical CLAD system would use an anesthetic marker, calculated from physiological signals, as real-time feedback to adjust anesthetic dosage towards achieving a desired set-point of the marker. Since control strategies for CLAD vary across the systems reported in recent literature, a comparative analysis of common control strategies can be useful. For a nonlinear plant model based on well-established models of compartmental pharmacokinetics and sigmoid-Emax pharmacodynamics, we numerically analyze the set-point tracking performance of three output-feedback linear control strategies: proportional-integral-derivative (PID) control, linear quadratic Gaussian (LQG) control, and an LQG with integral action (ILQG). Specifically, we numerically simulate multiple CLAD sessions for the scenario where the plant model parameters are unavailable for a patient and the controller is designed based on a nominal model and controller gains are held constant throughout a session. Based on the numerical analyses performed here, conditioned on our choice of model and controllers, we infer that in terms of accuracy and bias PID control performs better than ILQG which in turn performs better than LQG. In the case of noisy observations, ILQG can be tuned to provide a smoother infusion rate while achieving comparable steady state response with respect to PID. The numerical analysis framework and findings reported here can help CLAD developers in their choice of control strategies. This paper may also serve as a tutorial paper for teaching control theory for CLAD.

Recent advances in modeling sleep: from the clinic to society and disease.

In the past few decades, advances in understanding sleep-wake neurophysiology have occurred hand-in-hand with advances in mathematical modeling of sleep and wake. In this review, we summarize recent updates in modeling the timing and durations of sleep and wake, the underlying neurophysiology of sleep and wake, and the application of these models in understanding cognition and disease. Throughout, we highlight the role modeling has played in developing our understanding of sleep and its underlying mechanisms. We present open questions and controversies in the field and propose the utility of individualized models of sleep for precision sleep medicine.

Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control.

The widespread adoption of closed-loop control in systems biology has resulted from improvements in sensors, computing, actuation, and the discovery of alternative sites of targeted drug delivery. Most control algorithms for circadian phase resetting exploit light inputs. However, recently identified small-molecule pharmaceuticals offer advantages in terms of invasiveness and potency of actuation. Herein, we develop a systematic method to control the phase of biological oscillations motivated by the recently identified small molecule circadian pharmaceutical KL001. The model-based control architecture exploits an infinitesimal parametric phase response curve (ipPRC) that is used to predict the effect of control inputs on future phase trajectories of the oscillator. The continuous time optimal control policy is first derived for phase resetting, based on the ipPRC and Pontryagin's maximum principle. Owing to practical challenges in implementing a continuous time optimal control policy, we investigate the effect of implementing the continuous time policy in a sampled time format. Specifically, we provide bounds on the errors incurred by the physiologically tractable sampled time control law. We use these results to select directions of resetting (i.e. phase advance or delay), sampling intervals, and prediction horizons for a nonlinear model predictive control (MPC) algorithm for phase resetting. The potential of this ipPRC-informed pharmaceutical nonlinear MPC is then demonstrated in silico using real-world scenarios of jet lag or rotating shift work.

Analysis of centrifugal homogenization and its applications for emulsification & mechanical cell lysis.

We detail the analysis of centrifugal homogenization process by a hydrodynamic model and the model-guided design of a low-cost centrifugal homogenizer. During operation, centrifugal force pushes a multiphase solution to be homogenized through a thin nozzle, consequently homogenizing its contents. We demonstrate and assess the homogenization of coarse emulsions into relatively monodisperse emulsions, as well as the application of centrifugal homogenization in the mechanical lysis of mpkCCD mouse kidney cells. To gain insight into the homogenization mechanism, we investigate the dependence of emulsion droplet size on geometrical parameters, centrifugal acceleration, and dispersed phase viscosity. Our experimental results are in qualitative agreement with models predicting the droplet size. Furthermore, they indicate that high shear rates kept constant throughout operation produce more monodisperse droplets. We show this ideal homogenization condition can be realized through hydrodynamic model-guided design minimizing transient effects inherent to centrifugal homogenization. Moreover, we achieved power densities comparable to commercial homogenizers by model guided optimization of homogenizer design and experimental conditions. Centrifugal homogenization using the proposed homogenizer design thus offers a low-cost alternative to existing technologies as it is constructed from off-the-shelf parts (Falcon tubes, syringe, needles) and used with a centrifuge, readily available in standard laboratory environment.

Entrainment of Circadian Rhythms Depends on Firing Rates and Neuropeptide Release of VIP SCN Neurons.

The mammalian suprachiasmatic nucleus (SCN) functions as a master circadian pacemaker, integrating environmental input to align physiological and behavioral rhythms to local time cues. Approximately 10% of SCN neurons express vasoactive intestinal polypeptide (VIP); however, it is unknown how firing activity of VIP neurons releases VIP to entrain circadian rhythms. To identify physiologically relevant firing patterns, we optically tagged VIP neurons and characterized spontaneous firing over 3 days. VIP neurons had circadian rhythms in firing rate and exhibited two classes of instantaneous firing activity. We next tested whether physiologically relevant firing affected circadian rhythms through VIP release. We found that VIP neuron stimulation with high, but not low, frequencies shifted gene expression rhythms in vitro through VIP signaling. In vivo, high-frequency VIP neuron activation rapidly entrained circadian locomotor rhythms. Thus, increases in VIP neuronal firing frequency release VIP and entrain molecular and behavioral circadian rhythms. VIDEO ABSTRACT.

Ontogeny of Circadian Rhythms and Synchrony in the Suprachiasmatic Nucleus.

In mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus coordinates daily rhythms including sleep-wake, hormone release, and gene expression. The cells of the SCN must synchronize to each other to drive these circadian rhythms in the rest of the body. The ontogeny of circadian cycling and intercellular coupling in the SCN remains poorly understood. Recent in vitro studies have recorded circadian rhythms from the whole embryonic SCN. Here, we tracked the onset and precision of rhythms in PERIOD2 (PER2), a clock protein, within the SCN isolated from embryonic and postnatal mice of undetermined sex. We found that a few SCN cells developed circadian periodicity in PER2 by 14.5 d after mating (E14.5) with no evidence for daily cycling on E13.5. On E15.5, the fraction of competent oscillators increased dramatically corresponding with stabilization of their circadian periods. The cells of the SCN harvested at E15.5 expressed sustained, synchronous daily rhythms. By postnatal day 2 (P2), SCN oscillators displayed the daily, dorsal-ventral phase wave in clock gene expression typical of the adult SCN. Strikingly, vasoactive intestinal polypeptide (VIP), a neuropeptide critical for synchrony in the adult SCN, and its receptor, VPAC2R, reached detectable levels after birth and after the onset of circadian synchrony. Antagonists of GABA or VIP signaling or action potentials did not disrupt circadian synchrony in the E15.5 SCN. We conclude that endogenous daily rhythms in the fetal SCN begin with few noisy oscillators on E14.5, followed by widespread oscillations that rapidly synchronize on E15.5 by an unknown mechanism.SIGNIFICANCE STATEMENT We recorded the onset of PER2 circadian oscillations during embryonic development in the mouse SCN. When isolated at E13.5, the anlagen of the SCN expresses high, arrhythmic PER2. In contrast, a few cells show noisy circadian rhythms in the isolated E14.5 SCN and most show reliable, self-sustained, synchronized rhythms in the E15.5 SCN. Strikingly, this synchrony at E15.5 appears before expression of VIP or its receptor and persists in the presence of blockers of VIP, GABA or neuronal firing. Finally, the dorsal-ventral phase wave of PER2 typical of the adult SCN appears ∼P2, indicating that multiple signals may mediate circadian synchrony during the ontogeny of the SCN.