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Mapping neurotransmitter identities to neurons is key to understanding information flow in a nervous system. It also provides valuable entry points for studying the development and plasticity of neuronal identity features. In the Caenorhabditis elegans nervous system, neurotransmitter identities have been largely assigned by expression pattern analysis of neurotransmitter pathway genes that encode neurotransmitter biosynthetic enzymes or transporters. However, many of these assignments have relied on multicopy reporter transgenes that may lack relevant cis-regulatory information and therefore may not provide an accurate picture of neurotransmitter usage. We analyzed the expression patterns of 16 CRISPR/Cas9-engineered knock-in reporter strains for all main types of neurotransmitters in C. elegans (glutamate, acetylcholine, GABA, serotonin, dopamine, tyramine, and octopamine) in both the hermaphrodite and the male. Our analysis reveals novel sites of expression of these neurotransmitter systems within both neurons and glia, as well as non-neural cells, most notably in gonadal cells. The resulting expression atlas defines neurons that may be exclusively neuropeptidergic, substantially expands the repertoire of neurons capable of co-transmitting multiple neurotransmitters, and identifies novel sites of monoaminergic neurotransmitter uptake. Furthermore, we also observed unusual co-expression patterns of monoaminergic synthesis pathway genes, suggesting the existence of novel monoaminergic transmitters. Our analysis results in what constitutes the most extensive whole-animal-wide map of neurotransmitter usage to date, paving the way for a better understanding of neuronal communication and neuronal identity specification in C. elegans.

We prove a stability result of isometric immersions of hypersurfaces in Riemannian manifolds, with respect to $L^p$ -perturbations of their fundamental forms: For a manifold ${\mathcal M}^d$ endowed with a reference metric and a reference shape operator, we show that a sequence of immersions $f_n:{\mathcal M}^d\to {\mathcal N}^{d+1}$ , whose pullback metrics and shape operators are arbitrary close in $L^p$ to the reference ones, converge to an isometric immersion having the reference shape operator. This result is motivated by elasticity theory and generalizes a previous result [AKM22] to a general target manifold ${\mathcal N}$ , removing a constant curvature assumption. The method of proof differs from that in [AKM22]: it extends a Young measure approach that was used in codimension-0 stability results, together with an appropriate relaxation of the energy and a regularity result for immersions satisfying given fundamental forms. In addition, we prove a related quantitative (rather than asymptotic) stability result in the case of Euclidean target, similar to [CMM19] but with no a priori assumed bounds.

We present a scalable method for learning local quantum channels using local expectation values measured on a single state—their steady state. Our method is inspired by the algorithms for learning local Hamiltonians from their ground states. For it to succeed, the steady state must be non-trivial, and therefore the channel needs to be non-unital. Such non-unital channels are readily implementable on present day quantum computers using mid-circuit measurements or RESET gates. We demonstrate that the full structure of such channels is encoded in their steady states, and can be learned efficiently using only the expectation values of local observables on these states. We emphasize two immediate applications to illustrate our approach: (i) Using engineered dissipative dynamics, we offer a straightforward way to assess the accuracy of a given noise model in a regime where all qubits are actively utilized for a significant duration. (ii) Given a parameterized noise model for the entire system, our method can learn its underlying parameters. We demonstrate both applications using numerical simulations and experimental trials conducted on an IBMQ machine.

Abstract The COVID-19 pandemic has been spreading worldwide since December 2019, presenting an urgent threat to global health. Due to the limited understanding of disease progression and of the risk factors for the disease, it is a clinical challenge to predict which hospitalized patients will deteriorate. Moreover, several studies suggested that taking early measures for treating patients at risk of deterioration could prevent or lessen condition worsening and the need for mechanical ventilation. We developed a predictive model for early identification of patients at risk for clinical deterioration by retrospective analysis of electronic health records of COVID-19 inpatients at the two largest medical centers in Israel. Our model employs machine learning methods and uses routine clinical features such as vital signs, lab measurements, demographics, and background disease. Deterioration was defined as a high NEWS2 score adjusted to COVID-19. In the prediction of deterioration within the next 7–30 h, the model achieved an area under the ROC curve of 0.84 and an area under the precision-recall curve of 0.74. In external validation on data from a different hospital, it achieved values of 0.76 and 0.7, respectively.

Homeobox genes are prominent regulators of neuronal identity, but the extent to which their function has been probed in animal nervous systems remains limited. In the nematode Caenorhabditis elegans, each individual neuron class is defined by the expression of unique combinations of homeobox genes, prompting the question of whether each neuron class indeed requires a homeobox gene for its proper identity specification. We present here progress in addressing this question by extending previous mutant analysis of homeobox gene family members and describing multiple examples of homeobox gene function in different parts of the C. elegans nervous system. To probe homeobox function, we make use of a number of reporter gene tools, including a novel multicolor reporter transgene, NeuroPAL, which permits simultaneous monitoring of the execution of multiple differentiation programs throughout the entire nervous system. Using these tools, we add to the previous characterization of homeobox gene function by identifying neuronal differentiation defects for 14 homeobox genes in 24 distinct neuron classes that are mostly unrelated by location, function and lineage history. 12 of these 24 neuron classes had no homeobox gene function ascribed to them before, while in the other 12 neuron classes, we extend the combinatorial code of transcription factors required for specifying terminal differentiation programs. Furthermore, we demonstrate that in a particular lineage, homeotic identity transformations occur upon loss of a homeobox gene and we show that these transformations are the result of changes in homeobox codes. Combining the present with past analyses, 113 of the 118 neuron classes of C. elegans are now known to require a homeobox gene for proper execution of terminal differentiation programs. Such broad deployment indicates that homeobox function in neuronal identity specification may be an ancestral feature of animal nervous systems.

Pemphigus vulgaris is a rare autoimmune skin disease. Although herpes simplex virus has been associated with autoimmune diseases, evidence regarding its association with pemphigus vulgaris exacerbations is scarce. This retrospective cohort study aimed to characterize the epidemiological and clinical features of patients with pemphigus vulgaris who were herpes simplex-positive, compared with those who were herpes simplex-negative, during disease onset. Of 62 patients with pemphigus vulgaris who underwent PCR testing for herpes simplex virus, 25 (40.3%) were positive, with a mean age of 56.1 ± 15.5 years; 35.5% were male. The herpes-positive group had significantly elevated levels of C-reactive protein, Pemphigus Disease Activity Index score, and shorter time to relapse. The time to remission, number of exacerbations per year, and remission status were non-significantly elevated in the herpes-positive group. Thus, routine testing lesions from patients with pemphigus for herpes simplex virus should be performed. If positive, antiviral treatment should be initiated; and preventive antiviral treatment should be considered in severe cases.

Abstract Background Caenorhabditis elegans nematodes are powerful model organisms, yet quantification of visible phenotypes is still often labor-intensive, biased, and error-prone. We developed WorMachine, a three-step MATLAB-based image analysis software that allows (1) automated identification of C. elegans worms, (2) extraction of morphological features and quantification of fluorescent signals, and (3) machine learning techniques for high-level analysis. Results We examined the power of WorMachine using five separate representative assays: supervised classification of binary-sex phenotype, scoring continuous-sexual phenotypes, quantifying the effects of two different RNA interference treatments, and measuring intracellular protein aggregation. Conclusions WorMachine is suitable for analysis of a variety of biological questions and provides an accurate and reproducible analysis tool for measuring diverse phenotypes. It serves as a “quick and easy,” convenient, high-throughput, and automated solution for nematode research.

BACKGROUND: In contrast to fine particles, less is known of the inflammatory and coagulation impacts of coarse particulate matter (PM10-2.5, particulate matter with aerodynamic diameter ≤10μm and>2.5μm). Toxicological research suggests that these pathways might be important processes by which PM10-2.5 impacts health, but there are relatively few epidemiological studies due to a lack of a national PM10-2.5 monitoring network. OBJECTIVES: We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average PM10-2.5 concentrations with markers of inflammation and coagulation. METHODS: We leveraged data from 7,071 Multi-Ethnic Study of Atherosclerosis and ancillary study participants 45-84 y of age who had repeated plasma measures of inflammatory and coagulation biomarkers. We estimated PM10-2.5 at participant addresses 1 y and 1 month before each of up to four exams (2000-2012) using spatiotemporal models that incorporated satellite, regulatory monitoring, and local geographic data and accounted for spatial correlation. We used random effects models to estimate associations with interleukin-6 (IL-6), C-reactive protein (CRP), fibrinogen, and D-dimer, controlling for potential confounders. RESULTS: Increases in PM10-2.5 were not associated with greater levels of inflammation or coagulation. A 10-μg/m3 increase in annual average PM10-2.5 was associated with a 2.5% decrease in CRP [95% confidence interval (CI): -5.5, 0.6]. We saw no association between annual average PM10-2.5 and the other markers (IL-6: -0.7%, 95% CI: -2.6, 1.2; fibrinogen: -0.3%, 95% CI: -0.9, 0.3; D-dimer: -0.2%, 95% CI: -2.6, 2.4). Associations consistently showed that a 10-μg/m3 increase in 1-month average PM10-2.5 was associated with reduced inflammation and coagulation, though none were distinguishable from no association (IL-6: -1.2%, 95% CI: -3.0 , 0.5; CRP: -2.5%, 95% CI: -5.3, 0.4; fibrinogen: -0.4%, 95% CI: -1.0, 0.1; D-dimer: -2.0%, 95% CI: -4.3, 0.3). DISCUSSION: We found no evidence that PM10-2.5 is associated with higher inflammation or coagulation levels. More research is needed to determine whether the inflammation and coagulation pathways are as important in explaining observed PM10-2.5 health impacts in humans as they have been shown to be in toxicology studies or whether PM10-2.5 might impact human health through alternative biological mechanisms. https://doi.org/10.1289/EHP12972.

The highly reactive dihalogens play a significant role in the oxidative chemistry of the troposphere. One of the main reservoirs of these halogens is hypohalous acids, HOX, which produce dihalogens in the presence of halides (Y-), where X, Y = Cl, Br, I. These reactions occur in and on aerosol particles and seawater surfaces and have been studied experimentally and by field observations. However, the mechanisms of these atmospheric reactions are still unknown. Here, we establish the atomistic mechanism of HOCl + Cl- → Cl2 + OH- at the surface of the water slab by performing ab initio molecular dynamics (AIMD) simulations. Main findings are (1) This reaction proceeds by halogen-bonded complexes of (HOCl)···(Cl-)aq surrounded with the neighboring water molecules. (2) The halogen bonded (HOCl)···(Cl-)aq complexes undergo charge transfer from Cl- to OH- to form transient Cl2 at neutral pH. (3) The addition of a proton to one proximal water greatly facilitates the Cl2 formation, which explains the enhanced rate at low pH.

Recent works have shown that generic local Hamiltonians can be efficiently inferred from local measurements performed on their eigenstates or thermal states. Realistic quantum systems are often affected by dissipation and decoherence due to coupling to an external environment. This raises the question whether the steady states of such open quantum systems contain sufficient information allowing for full and efficient reconstruction of the system’s dynamics. We find that such a reconstruction is possible for generic local Markovian dynamics. We propose a recovery method that uses only local measurements; for systems with finite-range interactions, the method recovers the Lindbladian acting on each spatial domain using only observables within that domain. We numerically study the accuracy of the reconstruction as a function of the number of measurements, type of open-system dynamics and system size. Interestingly, we show that couplings to external environments can in fact facilitate the reconstruction of Hamiltonians composed of commuting terms.

Ultralight axion-like particles are well-motivated relics that might compose the cosmological dark matter and source anomalous time-dependent magnetic fields. We report on terrestrial bounds from the Noble And Alkali Spin Detectors for Ultralight Coherent darK matter (NASDUCK) collaboration on the coupling of axion-like particles to neutrons and protons. The detector uses nuclei of noble-gas and alkali-metal atoms and operates in the Spin-Exchange Relaxation-Free (SERF) regime, achieving high sensitivity to axion-like dark matter fields. Conducting a month-long search, we cover the mass range of 1.4 × 10-12 eV/c2 to 2 × 10-10 eV/c2 and provide limits which supersede robust astrophysical bounds, and improve upon previous terrestrial constraints by over two orders of magnitude for many masses within this range for protons, and up to two orders of magnitude for neutrons. These are the sole reliable terrestrial bounds reported on the coupling of protons with axion-like dark matter, covering an unexplored terrain in its parameter space.