Perfect timing: Circadian rhythms, sleep, and immunity - an NIH workshop summary

Recent discoveries demonstrate a critical role for circadian rhythms and sleep in immune system homeostasis. Both innate and adaptive immune responses - ranging from leukocyte mobilization, trafficking, and chemotaxis to cytokine release and T cell differentiation -are mediated in a time of day-dependent manner. The National Institutes of Health (NIH) recently sponsored an interdisciplinary workshop, Sleep Insufficiency, Circadian Misalignment, and the Immune Response, to highlight new research linking sleep and circadian biology to immune function and to identify areas of high translational potential. This Review summarizes topics discussed and highlights immediate opportunities for delineating clinically relevant connections among biological rhythms, sleep, and immune regulation

A timely call to arms: COVID-19, the circadian clock, and critical care

We currently find ourselves in the midst of a global coronavirus disease 2019 (COVID-19) pandemic, caused by the highly infectious novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we discuss aspects of SARS-CoV-2 biology and pathology and how these might interact with the circadian clock of the host. We further focus on the severe manifestation of the illness, leading to hospitalization in an intensive care unit. The most common severe complications of COVID-19 relate to clock-regulated human physiology. We speculate on how the pandemic might be used to gain insights on the circadian clock but, more importantly, on how knowledge of the circadian clock might be used to mitigate the disease expression and the clinical course of COVID-19

Autophagy in Idiopathic Pulmonary Fibrosis

Background: Autophagy is a basic cellular homeostatic process important to cell fate decisions under conditions of stress. Dysregulation of autophagy impacts numerous human diseases including cancer and chronic obstructive lung disease. This study investigates the role of autophagy in idiopathic pulmonary fibrosis. Methods: Human lung tissues from patients with IPF were analyzed for autophagy markers and modulating proteins using western blotting, confocal microscopy and transmission electron microscopy. To study the effects of TGF-β1 on autophagy, human lung fibroblasts were monitored by fluorescence microscopy and western blotting. In vivo experiments were done using the bleomycin-induced fibrosis mouse model. Results: Lung tissues from IPF patients demonstrate evidence of decreased autophagic activity as assessed by LC3, p62 protein expression and immunofluorescence, and numbers of autophagosomes. TGF-β1 inhibits autophagy in fibroblasts in vitro at least in part via activation of mTORC1; expression of TIGAR is also increased in response to TGF-β1. In the bleomycin model of pulmonary fibrosis, rapamycin treatment is antifibrotic, and rapamycin also decreases expression of á-smooth muscle actin and fibronectin by fibroblasts in vitro. Inhibition of key regulators of autophagy, LC3 and beclin-1, leads to the opposite effect on fibroblast expression of á-smooth muscle actin and fibronectin. Conclusion: Autophagy is not induced in pulmonary fibrosis despite activation of pathways known to promote autophagy. Impairment of autophagy by TGF-β1 may represent a mechanism for the promotion of fibrogenesis in IPF

Biological rhythms in COVID-19 vaccine effectiveness in an observational cohort study of 1.5 million patients

BACKGROUNDCircadian rhythms are evident in basic immune processes, but it is unclear if rhythms exist in clinical endpoints like vaccine protection. Here, we examined associations between COVID-19 vaccination timing and effectiveness.METHODSWe retrospectively analyzed a large Israeli cohort with timestamped COVID-19 vaccinations (n = 1,515,754 patients over 12 years old, 99.2% receiving BNT162b2). Endpoints included COVID-19 breakthrough infection and COVID-19-associated emergency department visits and hospitalizations. Our main comparison was among patients vaccinated during morning (800-1159 hours), afternoon (1200-1559 hours), or evening hours (1600-1959 hours). We employed Cox regression to adjust for differences in age, sex, and comorbidities.RESULTSBreakthrough infections differed based on vaccination time, with lowest the rates associated with late morning to early afternoon and highest rates associated with evening vaccination. Vaccination timing remained significant after adjustment for patient age, sex, and comorbidities. Results were consistent in patients who received the basic 2-dose series and who received booster doses. The relationship between COVID-19 immunization time and breakthrough infections was sinusoidal, consistent with a biological rhythm that modifies vaccine effectiveness by 8.6%-25%. The benefits of daytime vaccination were concentrated in younger (\u3c20 years old) and older patients (\u3e50 years old). COVID-19-related hospitalizations varied significantly with the timing of the second booster dose, an intervention reserved for older and immunosuppressed patients (HR = 0.64, morning vs. evening; 95% CI, 0.43-0.97; P = 0.038).CONCLUSIONWe report a significant association between the time of COVID-19 vaccination and its effectiveness. This has implications for mass vaccination programs.FUNDINGNIH

Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories

Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. H-bonds involving atoms from residues that are close to each other in the main-chain sequence stabilize secondary structure elements. H-bonds between atoms from distant residues stabilize a protein’s tertiary structure. However, H-bonds greatly vary in stability. They form and break while a protein deforms. For instance, the transition of a protein from a nonfunctional to a functional state may require some H-bonds to break and others to form. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor. Other local interactions may reinforce (or weaken) an H-bond. This paper describes inductive learning methods to train a protein-independent probabilistic model of H-bond stability from molecular dynamics (MD) simulation trajectories. The training data describes H-bond occurrences at successive times along these trajectories by the values of attributes called predictors. A trained model is constructed in the form of a regression tree in which each non-leaf node is a Boolean test (split) on a predictor. Each occurrence of an H-bond maps to a path in this tree from the root to a leaf node. Its predicted stability is associated with the leaf node. Experimental results demonstrate that such models can predict H-bond stability quite well. In particular, their performance is roughly 20 % better than that of models based on H-bond energy alone. In addition, they can accurately identify a large fraction of the least stable H-bonds in a give

To reverse engineer an entire nervous system

There are many theories of how behavior may be controlled by neurons. Testing and refining these theories would be greatly facilitated if we could correctly simulate an entire nervous system so we could replicate the brain dynamics in response to any stimuli or contexts. Besides, simulating a nervous system is in itself one of the big dreams in systems neuroscience. However, doing so requires us to identify how each neuron's output depends on its inputs, a process we call reverse engineering. Current efforts at this focus on the mammalian nervous system, but these brains are mind-bogglingly complex, allowing only recordings of tiny subsystems. Here we argue that the time is ripe for systems neuroscience to embark on a concerted effort to reverse engineer a smaller system and that Caenorhabditis elegans is the ideal candidate system as the established optophysiology techniques can capture and control each neuron's activity and scale to hundreds of thousands of experiments. Data across populations and behaviors can be combined because across individuals the nervous system is largely conserved in form and function. Modern machine-learning-based modeling should then enable a simulation of C. elegans' impressive breadth of brain states and behaviors. The ability to reverse engineer an entire nervous system will benefit the design of artificial intelligence systems and all of systems neuroscience, enabling fundamental insights as well as new approaches for investigations of progressively larger nervous systems.Comment: 23 pages, 2 figures, opinion pape