Capturing Mercury-197m/g for Auger Electron Therapy and Cancer Theranostic with Sulfur-Containing Cyclen-Based Macrocycles.

The interest in mercury radioisotopes, 197mHg (t1/2 = 23.8 h) and 197gHg (t1/2 = 64.14 h), has recently been reignited by the dual diagnostic and therapeutic nature of their nuclear decays. These isotopes emit γ-rays suitable for single photon emission computed tomography imaging and Auger electrons which can be exploited for treating small and metastatic tumors. However, the clinical utilization of 197m/gHg radionuclides is obstructed by the lack of chelators capable of securely binding them to tumor-seeking vectors. This work aims to address this challenge by investigating a series of chemically tailored macrocyclic platforms with sulfur-containing side arms, namely, 1,4,7,10-tetrakis[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane (DO4S), 1,4,7-tris[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane (DO3S), and 1,7-bis[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane-4,10-diacetic acid (DO2A2S). 1,4,7,10-Tetrazacyclododecane-1,4,7,10-tetracetic acid (DOTA), the widest explored chelator in nuclear medicine, and the nonfunctionalized backbone 1,4,7,10-tetrazacyclododecane (cyclen) were considered as well to shed light on the role of the sulfanyl arms in the metal coordination. To this purpose, a comprehensive experimental and theoretical study encompassing aqueous coordination chemistry investigations through potentiometry, nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, and density functional theory (DFT) calculations, as well as concentration- and temperature-dependent [197m/gHg]Hg2+ radiolabeling and in vitro stability assays in human serum was conducted. The obtained results reveal that the investigated chelators rapidly complex Hg2+ in aqueous media, forming extremely thermodynamically stable 1:1 metal-to-ligand complexes with superior stabilities compared to those of DOTA or cyclen. These complexes exhibited 6- to 8-fold coordination environments, with donors statically bound to the metal center, as evidenced by the presence of 1H-199Hg spin-spin coupling via NMR. A similar octacoordinated environment was also found for DOTA in both solution and solid state, but in this case, multiple slowly exchanging conformers were detected at ambient temperature. The sulfur-rich ligands quantitatively incorporate cyclotron-produced [197m/gHg]Hg2+ under relatively mild reaction conditions (pH = 7 and T = 50 °C), with the resulting radioactive complexes exhibiting decent stability in human serum (up to 75% after 24 h). By developing viable chelators and understanding the impact of structural modifications, our research addresses the scarcity of suitable chelating agents for 197m/gHg, offering promise for its future in vivo application as a theranostic Auger-emitter radiometal.

Electric Field Gradient Calculations for Ice VIII and IX Using Polarizable Embedding: A Comparative Study on Classical Computers and Quantum Simulators.

We test the performance of the polarizable embedding variational quantum eigensolver self-consistent field (PE-VQE-SCF) model for computing electric field gradients with comparisons to conventional complete active space self-consistent-field (CASSCF) calculations and experimental results. We compute quadrupole coupling constants for ice VIII and ice IX. We find close agreement of the quantum-computing PE-VQE-SCF results with the results from the classical PE-CASSCF calculations and with experiment. Furthermore, we observe that the inclusion of the environment is crucial for obtaining results that match the experimental data. The calculations for ice VIII are within the experimental uncertainty for both CASSCF and VQE-SCF for oxygen and lie close to the experimental value for ice IX as well. With the VQE-SCF, which is based on an adaptive derivative-assembled problem-tailored (ADAPT) ansatz, we find that the inclusion of the environment and the size of the different basis sets do not directly affect the gate counts. However, by including an explicit environment, the wavefunction and therefore the optimization problem become more complicated, which usually results in the need to include more operators from the operator pool, thereby increasing the depth of the circuit.

Combining muscle-computer interface guided training with bihemispheric tDCS improves upper limb function in patients with chronic stroke.

Transcranial direct current stimulation (tDCS) may facilitate neuroplasticity but with a limited effect when administered while patients with stroke are at rest. Muscle-computer interface (MCI) training is a promising approach for training patients with stroke even if they cannot produce overt movements. However, using tDCS to enhance MCI training has not been investigated. We combined bihemispheric tDCS with MCI training of the paretic wrist and examined the effect of this intervention in patients with chronic stroke. A crossover, double-blind, randomized trial was conducted. Twenty-six patients with chronic stroke performed MCI wrist training for three consecutive days at home while receiving either real tDCS or sham tDCS in counterbalanced order and separated by at least 8 mo. The primary outcome measure was the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE) that was measured 1 wk before training, on the first training day, on the last training day, and 1 wk after training. There was neither a significant difference in the baseline FMA-UE score between groups nor between intervention periods. Patients improved 3.9 ± 0.6 points in FMA-UE score when receiving real tDCS, and 1.0 ± 0.7 points when receiving sham tDCS (P = 0.003). In addition, patients also showed continuous improvement in their motor control of the MCI tasks over the training days. Our study showed that the training paradigm could lead to functional improvement in patients with chronic stroke. We argue that appropriate MCI training in combination with bihemispheric tDCS could be a useful adjuvant for neurorehabilitation in patients with stroke.NEW & NOTEWORTHY Bihemispheric tDCS combined with a novel MCI training for motor control of wrist extensor can improve upper limb function especially a training-specific effect on the wrist movement in patients with chronic stroke. The training regimen can be personalized with adjustments made daily to accommodate the functional change throughout the intervention. This demonstrates that bihemispheric tDCS with MCI training could complement conventional poststroke neurorehabilitation.

Quantum Equation of Motion with Orbital Optimization for Computing Molecular Properties in Near-Term Quantum Computing.

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is how to use imperfect near-term quantum computers to solve problems of practical value. Inspired by the recently developed variants of the quantum counterpart of the equation-of-motion (qEOM) approach and the orbital-optimized variational quantum eigensolver (oo-VQE), we present a quantum algorithm (oo-VQE-qEOM) for the calculation of molecular properties by computing expectation values on a quantum computer. We perform noise-free quantum simulations of BeH2 in the series of STO-3G/6-31G/6-31G* basis sets and of H4 and H2O in 6-31G using an active space of four electrons and four spatial orbitals (8 qubits) to evaluate excitation energies, electronic absorption, and, for twisted H4, circular dichroism spectra. We demonstrate that the proposed algorithm can reproduce the results of conventional classical CASSCF calculations for these molecular systems.

Subspace Methods for the Simulation of Molecular Response Properties on a Quantum Computer.

We explore Davidson methods for obtaining excitation energies and other linear response properties within the recently developed quantum self-consistent linear response (q-sc-LR) method. Davidson-type methods allow for obtaining only a few selected excitation energies without explicitly constructing the electronic Hessian since they only require the ability to perform Hessian-vector multiplications. We apply the Davidson method to calculate the excitation energies of hydrogen chains (up to H10) and analyze aspects of statistical noise for computing excitation energies on quantum simulators. Additionally, we apply Davidson methods for computing linear response properties such as static polarizabilities for H2, LiH, H2O, OH-, and NH3, and show that unitary coupled cluster outperforms classical projected coupled cluster for molecular systems with strong correlation. Finally, we formulate the Davidson method for damped (complex) linear response, with application to the nitrogen K-edge X-ray absorption of ammonia, and the C6 coefficients of H2, LiH, H2O, OH-, and NH3.

On the geometry dependence of the nuclear magnetic resonance chemical shift of mercury in thiolate complexes: A relativistic density functional theory study.

Thiolate containing mercury(II) complexes of the general formula [Hg(SR) n $$ {}_n $$ ] 2 - n $$ {}^{2-n} $$ have been of great interest since the toxicity of mercury was recognized. 199Hg nuclear magnetic resonance spectroscopy (NMR) is a powerful tool for characterization of mercury complexes. In this work, the Hg shielding constants in a series of [Hg(SR) n $$ {}_n $$ ] 2 - n $$ {}^{2-n} $$ complexes are therefore investigated computationally with particular emphasis on their geometry dependence. Geometry optimizations and NMR chemical shift calculations are performed at the density functional theory (DFT) level with both the zeroth-order regular approximation (ZORA) and four-component relativistic methods. The four exchange-correlation (XC) functionals PBE0, PBE, B3LYP, and BLYP are used in combination with either Dyall's Gaussian-type (GTO) or Slater-type orbitals (STOs) basis sets. Comparing ZORA and four-component calculations, one observes that the calculated shielding constants for a given molecular geometry have a constant difference of ∼ $$ \sim $$ 1070 ppm. This confirms that ZORA is an acceptable relativistic method to compute NMR chemical shifts. The combinations of four-component/PBE0/v3z and ZORA/PBE0/QZ4P are applied to explore the geometry dependence of the isotropic shielding. For a given coordination number, the distance between mercury and sulfur is the key factor affecting the shielding constant, while changes in bond and dihedral angles and even different side groups have relatively little impact.

Performance of range-separated long-range SOPPA short-range density functional theory method for vertical excitation energies.

In this paper, benchmark results are presented on the calculation of vertical electronic excitation energies using a long-range second-order polarization propagator approximation (SOPPA) description with a short-range density functional theory description based on the Perdew-Burke-Ernzerhof (PBE) functional. The excitation energies are investigated for 132 singlet states and 71 triplet states across 28 medium-sized organic molecules. The results show that overall SOPPA-srPBE always performs better than PBE and that SOPPA-srPBE performs better than SOPPA for singlet states, but slightly worse than SOPPA for triplet states when CC3 results are the reference values.

Which Options Exist for NISQ-Friendly Linear Response Formulations?

Linear response (LR) theory is a powerful tool in classic quantum chemistry crucial to understanding photoinduced processes in chemistry and biology. However, performing simulations for large systems and in the case of strong electron correlation remains challenging. Quantum computers are poised to facilitate the simulation of such systems, and recently, a quantum linear response formulation (qLR) was introduced [Kumar et al., J. Chem. Theory Comput. 2023, 19, 9136-9150]. To apply qLR to near-term quantum computers beyond a minimal basis set, we here introduce a resource-efficient qLR theory, using a truncated active-space version of the multiconfigurational self-consistent field LR ansatz. Therein, we investigate eight different near-term qLR formalisms that utilize novel operator transformations that allow the qLR equations to be performed on near-term hardware. Simulating excited state potential energy curves and absorption spectra for various test cases, we identify two promising candidates, dubbed "proj LRSD" and "all-proj LRSD".

The Importance of Anharmonicity and Solvent Effects on the OH Radical Attack on Nucleobases.

Previous theoretical investigations of the reactions between an OH radical and a nucleobase have stated the most important pathways to be the C5-C6 addition for pyrimidines and the C8 addition for purines. Furthermore, the abstraction of a methyl hydrogen from thymine has also been proven an important pathway. The conclusions were based solely on gas-phase calculations and harmonic vibrational frequencies. In this paper, we supplement the calculations by applying solvent corrections through the polarizable continuum model (PCM) solvent model and applying anharmonicity in order to determine the importance of anharmonicity and solvent effects. Density functional theory (DFT) at the ωB97-D/6-311++G(2df,2pd) level with the Eckart tunneling correction is used. The total reaction rate constants are found to be 1.48 ×10-13 cm3 molecules-1s-1 for adenine, 1.02 ×10-11 cm3 molecules-1s-1 for guanine, 5.52 ×10-13 cm3 molecules-1s-1 for thymine, 1.47 ×10-13 cm3 molecules-1s-1 for cytosine and 7.59 ×10-14 cm3 molecules-1s-1 for uracil. These rates are found to be approximately two orders of magnitude larger than experimental values. We find that the tendencies observed for preferred pathways for reactions calculated in a solvent are comparable to the preferred pathways for reactions calculated in gas phase. We conclude that applying a solvent has a larger impact on more parameters compared to the inclusion of anharmonicity. For some reactions the inclusion of anharmonicity has no effect, whereas for others it does impact the energetics.

Evidence of brain metabolism redistribution from neocortex to primitive brain structures in early acute COVID-19 respiratory syndrome.

BACKGROUND: Neuropsychiatric sequelae of COVID-19 have been widely documented in patients with severe neurological symptoms during the chronic or subacute phase of the disease. However, it remains unclear whether subclinical changes in brain metabolism can occur early in the acute phase of the disease. The aim of this study was to identify and quantify changes in brain metabolism in patients hospitalized for acute respiratory syndrome due to COVID-19 with no or mild neurological symptoms. RESULTS: Twenty-three non-intubated patients (13 women; mean age 55.5 ± 12.1 years) hospitalized with positive nasopharyngeal swab test (RT-PCR) for COVID-19, requiring supplemental oxygen and no or mild neurological symptoms were studied. Serum C-reactive protein measured at admission ranged from 6.43 to 189.0 mg/L (mean: 96.9 ± 54.2 mg/L). The mean supplemental oxygen demand was 2.9 ± 1.4 L/min. [18F]FDG PET/CT images were acquired with a median of 12 (4-20) days of symptoms. After visual interpretation of the images, semiquantitative analysis of [18F]FDG uptake in multiple brain regions was evaluated using dedicated software and the standard deviation (SD) of brain uptake in each region was automatically calculated in comparison with reference values of a normal database. Evolutionarily ancient structures showed positive SD mean values of [18F]FDG uptake. Lenticular nuclei were bilaterally hypermetabolic (> 2 SD) in 21/23 (91.3%) patients, and thalamus in 16/23 (69.6%), bilaterally in 11/23 (47.8%). About half of patients showed hypermetabolism in brainstems, 40% in hippocampi, and 30% in cerebellums. In contrast, neocortical regions (frontal, parietal, temporal and occipital lobes) presented negative SD mean values of [18F]FDG uptake and hypometabolism (< 2 SD) was observed in up to a third of patients. Associations were found between hypoxia, inflammation, coagulation markers, and [18F]FDG uptake in various brain structures. CONCLUSIONS: Brain metabolism is clearly affected during the acute phase of COVID-19 respiratory syndrome in neurologically asymptomatic or oligosymptomatic patients. The most frequent finding is marked hypermetabolism in evolutionary ancient structures such as lenticular nucleus and thalami. Neocortical metabolism was reduced in up to one third of patients, suggesting a redistribution of brain metabolism from the neocortex to evolutionary ancient brain structures in these patients.

The variational quantum eigensolver self-consistent field method within a polarizable embedded framework.

We formulate and implement the Variational Quantum Eigensolver Self Consistent Field (VQE-SCF) algorithm in combination with polarizable embedding (PE), thereby extending PE to the regime of quantum computing. We test the resulting algorithm, PE-VQE-SCF, on quantum simulators and demonstrate that the computational stress on the quantum device is only slightly increased in terms of gate counts compared to regular VQE-SCF. On the other hand, no increase in shot noise was observed. We illustrate how PE-VQE-SCF may lead to the modeling of real chemical systems using a simulation of the reaction barrier of the Diels-Alder reaction between furan and ethene as an example.

On the performance of HRPA(D) for NMR spin-spin coupling constants: Smaller molecules, aromatic and fluoroaromatic compounds.

In this study, the performance of the doubles-corrected higher random-phase approximation [HRPA(D)] has been investigated in calculations of nuclear magnetic resonance spin-spin coupling constants (SSCCs) for 58 molecules with the experimental values used as the reference values. HRPA(D) is an approximation to the second-order polarization propagator approximation (SOPPA) and is, therefore, computationally less expensive than SOPPA. HRPA(D) performs comparable and sometimes even better than SOPPA, and therefore, when calculating SSCCs, it should be considered as an alternative to SOPPA. Furthermore, it was investigated whether a coupled-cluster singles, doubles and perturbative triples [CCSD(T)] or Møller-Plesset second order (MP2) geometry optimization was optimal for a SOPPA and a HRPA(D) SSCC calculation for eight smaller molecules. CCSD(T) is the optimal geometry optimization for the SOPPA calculation, and MP2 was optimal for HRPA(D) SSCC calculations.

Exploring Alternate Methods for the Calculation of High-Level Vibrational Corrections of NMR Spin-Spin Coupling Constants.

Traditional nuclear magnetic resonance (NMR) calculations typically treat systems with a Born-Oppenheimer-derived electronic wave function that is solved for a fixed nuclear geometry. One can numerically account for this neglected nuclear motion by averaging over property values for all nuclear geometries with a vibrational wave function and adding this expectation value as a correction to an equilibrium geometry property value. Presented are benchmark coupled-cluster singles and doubles (CCSD) vibrational corrections to spin-spin coupling constants (SSCCs) computed at the level of vibrational second-order perturbation theory (VPT2) using the vibrational averaging driver of the CFOUR program. As CCSD calculations of vibrational corrections are very costly, cheaper electronic structure methods are explored via a newly developed Python vibrational averaging program within the Dalton Project. Namely, results obtained with the second-order polarization propagator approximation (SOPPA) and density functional theory (DFT) with the B3LYP and PBE0 exchange-correlation functionals are compared to the benchmark CCSD//CCSD(T) and experimental values. CCSD//CCSD(T) corrections are also combined with literature CC3 equilibrium geometry values to form the highest-order vibrationally corrected values available (i.e., CC3//CCSD(T) + CCSD//CCSD(T)). CCSD//CCSD(T) statistics showed favorable statistics in comparison to experimental values, albeit at an unfavorably high computational cost. A cheaper CCSD//CCSD(T) + B3LYP method showed quite similar mean absolute deviation (MAD) values as CCSD//CCSD(T), concluding that CCSD//CCSD(T) + B3LYP is optimal in terms of cost and accuracy. With reference to experimental values, a vibrational correction was not worth the cost for all of the other methods tested. Finally, deviation statistics showed that CC3//CCSD(T) + CCSD//CCSD(T) vibrational-corrected equilibrium values deteriorated in comparison to CCSD//CCSD(T) attributed to the use of a smaller basis set or lack of solvation effects for the CC3 equilibrium calculations.

Neural correlates of transfer of learning in motor coordination tasks: role of inhibitory and excitatory neurometabolites.

We aimed to investigate transfer of learning, whereby previously acquired skills impact new task learning. While it has been debated whether such transfer may yield positive, negative, or no effects on performance, very little is known about the underlying neural mechanisms, especially concerning the role of inhibitory (GABA) and excitatory (Glu) (measured as Glu + glutamine (Glx)) neurometabolites, as measured by magnetic resonance spectroscopy (MRS). Participants practiced a bimanual coordination task across four days. The Experimental group trained a task variant with the right hand moving faster than the left (Task A) for three days and then switched to the opposite variant (Task B) on Day4. The control group trained Task B across four days. MRS data were collected before, during, and after task performance on Day4 in the somatosensory (S1) and visual (MT/V5) cortex. Results showed that both groups improved performance consistently across three days. On Day4, the Experimental group experienced performance decline due to negative task transfer while the control group continuously improved. GABA and Glx concentrations obtained during task performance showed no significant group-level changes. However, individual Glx levels during task performance correlated with better (less negative) transfer performance. These findings provide a first window into the neurochemical mechanisms underlying task transfer.

Probing intrahemispheric interactions with a novel dual-site TMS setup.

OBJECTIVE: Using dual-site transcranial magnetic stimulation (dsTMS), the effective connectivity between the primary motor cortex (M1) and adjacent brain areas such as the dorsal premotor cortex (PMd) can be investigated. However, stimulating two brain regions in close proximity (e.g., ±2.3 cm for intrahemispheric PMd-M1) is subject to considerable spatial restrictions that potentially can be overcome by combining two standard figure-of-eight coils in a novel dsTMS setup. METHODS: After a technical evaluation of its induced electric fields, the dsTMS setup was tested in vivo (n = 23) by applying a short-interval intracortical inhibition (SICI) protocol. Additionally, the intrahemispheric PMd-M1 interaction was probed. E-field modelling was performed using SimNIBS. RESULTS: The technical evaluation yielded no major alterations of the induced electric fields due to coil overlap. In vivo, the setup reliably elicited SICI. Investigating intrahemispheric PMd-M1 interactions was feasible (inter-stimulus interval 6 ms), resulting in modulation of M1 output. CONCLUSIONS: The presented dsTMS setup provides a novel way to stimulate two adjacent brain regions with fewer technical and spatial limitations than previous attempts. SIGNIFICANCE: This dsTMS setup enables more accurate and repeatable targeting of brain regions in close proximity and can facilitate innovation in the field of effective connectivity.

Targeted memory reactivation during post-learning sleep does not enhance motor memory consolidation in older adults.

Targeted memory reactivation (TMR) during sleep enhances memory consolidation in young adults by modulating electrophysiological markers of neuroplasticity. Interestingly, older adults exhibit deficits in motor memory consolidation, an impairment that has been linked to age-related degradations in the same sleep features sensitive to TMR. We hypothesised that TMR would enhance consolidation in older adults via the modulation of these markers. A total of 17 older participants were trained on a motor task involving two auditory-cued sequences. During a post-learning nap, two auditory cues were played: one associated to a learned (i.e., reactivated) sequence and one control. Performance during two delayed re-tests did not differ between reactivated and non-reactivated sequences. Moreover, both associated and control sounds modulated brain responses, yet there were no consistent differences between the auditory cue types. Our results collectively demonstrate that older adults do not benefit from specific reactivation of a motor memory trace by an associated auditory cue during post-learning sleep. Based on previous research, it is possible that auditory stimulation during post-learning sleep could have boosted motor memory consolidation in a non-specific manner.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep.

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Baseline GABA+ levels in areas associated with sensorimotor control predict initial and long-term motor learning progress.

Synaptic plasticity relies on the balance between excitation and inhibition in the brain. As the primary inhibitory and excitatory neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate (Glu), play critical roles in synaptic plasticity and learning. However, the role of these neurometabolites in motor learning is still unclear. Furthermore, it remains to be investigated which neurometabolite levels from the regions composing the sensorimotor network predict future learning outcome. Here, we studied the role of baseline neurometabolite levels in four task-related brain areas during different stages of motor skill learning under two different feedback (FB) conditions. Fifty-one healthy participants were trained on a bimanual motor task over 5 days while receiving either concurrent augmented visual FB (CA-VFB group, N = 25) or terminal intrinsic visual FB (TA-VFB group, N = 26) of their performance. Additionally, MRS-measured baseline GABA+ (GABA + macromolecules) and Glx (Glu + glutamine) levels were measured in the primary motor cortex (M1), primary somatosensory cortex (S1), dorsolateral prefrontal cortex (DLPFC), and medial temporal cortex (MT/V5). Behaviorally, our results revealed that the CA-VFB group outperformed the TA-VFB group during task performance in the presence of augmented VFB, while the TA-VFB group outperformed the CA-VFB group in the absence of augmented FB. Moreover, baseline M1 GABA+ levels positively predicted and DLPFC GABA+ levels negatively predicted both initial and long-term motor learning progress in the TA-VFB group. In contrast, baseline S1 GABA+ levels positively predicted initial and long-term motor learning progress in the CA-VFB group. Glx levels did not predict learning progress. Together, these findings suggest that baseline GABA+ levels predict motor learning capability, yet depending on the FB training conditions afforded to the participants.

Circulating NK cells establish tissue residency upon acute infection of skin and mediate accelerated effector responses to secondary infection.

Natural killer (NK) cells are present in the circulation and can also be found residing in tissues, and these populations exhibit distinct developmental requirements and are thought to differ in terms of ontogeny. Here, we investigate whether circulating conventional NK (cNK) cells can develop into long-lived tissue-resident NK (trNK) cells following acute infections. We found that viral and bacterial infections of the skin triggered the recruitment of cNK cells and their differentiation into Tcf1hiCD69hi trNK cells that share transcriptional similarity with CD56brightTCF1hi NK cells in human tissues. Skin trNK cells arose from interferon (IFN)-γ-producing effector cells and required restricted expression of the transcriptional regulator Blimp1 to optimize Tcf1-dependent trNK cell formation. Upon secondary infection, trNK cells rapidly gained effector function and mediated an accelerated NK cell response. Thus, cNK cells redistribute and permanently position at sites of previous infection via a mechanism promoting tissue residency that is distinct from Hobit-dependent developmental paths of NK cells and ILC1 seeding tissues during ontogeny.

Laboratory mice with a wild microbiota generate strong allergic immune responses.

Allergic disorders are caused by a combination of hereditary and environmental factors. The hygiene hypothesis postulates that early-life microbial exposures impede the development of subsequent allergic disease. Recently developed "wildling" mice are genetically identical to standard laboratory specific pathogen-free (SPF) mice but are housed under seminatural conditions and have rich microbial exposures from birth. Thus, by comparing conventional SPF mice with wildlings, we can uncouple the impact of lifelong microbial exposures from genetic factors on the allergic immune response. We found that wildlings developed larger populations of antigen-experienced T cells than conventional SPF mice, which included interleukin-10-producing CD4 T cells specific for commensal Lactobacilli strains and allergy-promoting T helper 2 (TH2) cells. In models of airway exposure to house dust mite (HDM), recombinant interleukin-33, or Alternaria alternata, wildlings developed strong allergic inflammation, characterized by eosinophil recruitment, goblet cell metaplasia, and antigen-specific immunoglobulin G1 (IgG1) and IgE responses. Wildlings developed robust de novo TH2 cell responses to incoming allergens, whereas preexisting TH2 cells could also be recruited into the allergic immune response in a cytokine-driven and TCR-independent fashion. Thus, wildling mice, which experience diverse and lifelong microbial exposures, were not protected from developing pathological allergic immune responses. Instead, wildlings mounted robust allergic responses to incoming allergens, shedding new light on the hygiene hypothesis.