Multisystem physiological perspective of human frailty and its modulation by physical activity.

"Frailty" is a term used to refer to a state characterized by enhanced vulnerability to, and impaired recovery from, stressors compared with a nonfrail state, which is increasingly viewed as a loss of resilience. With increasing life expectancy and the associated rise in years spent with physical frailty, there is a need to understand the clinical and physiological features of frailty and the factors driving it. We describe the clinical definitions of age-related frailty and their limitations in allowing us to understand the pathogenesis of this prevalent condition. Given that age-related frailty manifests in the form of functional declines such as poor balance, falls, and immobility, as an alternative we view frailty from a physiological viewpoint and describe what is known of the organ-based components of frailty, including adiposity, the brain, and neuromuscular, skeletal muscle, immune, and cardiovascular systems, as individual systems and as components in multisystem dysregulation. By doing so we aim to highlight current understanding of the physiological phenotype of frailty and reveal key knowledge gaps and potential mechanistic drivers of the trajectory to frailty. We also review the studies in humans that have intervened with exercise to reduce frailty. We conclude that more longitudinal and interventional clinical studies are required in older adults. Such observational studies should interrogate the progression from a nonfrail to a frail state, assessing individual elements of frailty to produce a deep physiological phenotype of the syndrome. The findings will identify mechanistic drivers of frailty and allow targeted interventions to diminish frailty progression.

Microscopic Model for Fractional Quantum Hall Nematics.

Geometric fluctuations of the density mode in a fractional quantum Hall (FQH) state can give rise to a nematic FQH phase, a topological state with a spontaneously broken rotational symmetry. While experiments on FQH states in the second Landau level have reported signatures of putative FQH nematics in anisotropic transport, a realistic model for this state has been lacking. We show that the standard model of particles in the lowest Landau level interacting via the Coulomb potential realizes the FQH nematic transition, which is reached by a progressive reduction of the strength of the shortest-range Haldane pseudopotential. Using exact diagonalization and variational wave functions, we demonstrate that the FQH nematic transition occurs when the system's neutral gap closes in the long-wavelength limit while the charge gap remains open. We confirm the symmetry-breaking nature of the transition by demonstrating the existence of a "circular moat" potential in the manifold of states with broken rotational symmetry, while its geometric character is revealed through the strong fluctuations of the nematic susceptibility and Hall viscosity.

Controlling the Uptake and Release of Semiochemicals in Channel-Type Metal-Organic Frameworks Through Pore Expansion.

Semiochemicals can be used to manipulate insect behaviour for sustainable pest management strategies, but their high volatility is a major issue for their practical implementation. Inclusion of these molecules within porous materials is a potential solution to this issue, as it can allow for a slower and more controlled release. In this work, we demonstrate that a series of Zr(IV) and Al(III) metal-organic frameworks (MOFs) with channel-type pores enable controlled release of three semiochemicals over 100 days by pore size design, with the uptake and rate of release highly dependent on the pore size. Insight from grand canonical Monte Carlo simulations indicates that this is due to weaker MOF-guest interactions per guest molecule as the pore size increases. These MOFs are all stable post-release and can be reloaded to show near-identical re-release profiles. These results provide valuable insight on the diffusion behaviour of volatile guests in MOFs, and for the further development of porous materials for sustainable agriculture applications.

Network Effects of Brain Lesions Causing Central Poststroke Pain.

OBJECTIVE: This study was undertaken to test whether lesions causing central poststroke pain (CPSP) are associated with a specific connectivity profile, whether these connections are associated with metabolic changes, and whether this network aligns with neuromodulation targets for pain. METHODS: Two independent lesion datasets were utilized: (1) subcortical lesions from published case reports and (2) thalamic lesions with metabolic imaging using 18F- fluorodeoxyglucose positron emission tomography-computed tomography. Functional connectivity between each lesion location and the rest of the brain was assessed using a normative connectome (n = 1,000), and connections specific to CPSP were identified. Metabolic changes specific to CPSP were also identified and related to differences in lesion connectivity. Therapeutic relevance of the network was explored by testing for alignment with existing brain stimulation data and by prospectively targeting the network with repetitive transcranial magnetic stimulation (rTMS) in 7 patients with CPSP. RESULTS: Lesion locations causing CPSP showed a specific pattern of brain connectivity that was consistent across two independent lesion datasets (spatial r = 0.82, p < 0.0001). Connectivity differences were correlated with postlesion metabolism (r = -0.48, p < 0.001). The topography of this lesion-based pain network aligned with variability in pain improvement across 12 prior neuromodulation targets and across 32 patients who received rTMS to primary motor cortex (p < 0.05). Prospectively targeting this network with rTMS improved CPSP in 6 of 7 patients. INTERPRETATION: Lesions causing pain are connected to a specific brain network that shows metabolic abnormalities and promise as a neuromodulation target. ANN NEUROL 2022;92:834-845.

Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome.

INTRODUCTION: Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients. OBJECTIVES: In this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome. METHODS: A targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3',4'-didehydro-3'-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients' levels. RESULTS & CONCLUSION: Finally, we demonstrate the added value of the kynurenic acid/tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.

PDL1 shapes the classical Hodgkin lymphoma microenvironment without inducing T-cell exhaustion.

Classical Hodgkin lymphoma (CHL) is unusually sensitive to PD1 inhibition and PDL1 is highly expressed on CHL cells and in the tumor microenvironment. This could be interpreted as evidence of exhaustion, but paradoxically, PD1+ lymphocyte infiltration does not predict response to PD1 inhibitors and no increase in cytotoxic markers is seen after PD1 therapy as might be expected with reversal of exhaustion. In contrast to PD1, elevated PDL1 does predict response to PD1 inhibitors and recent data associate both retained CHL MHC-II expression and increased T helper (TH) T-cell receptor diversity with response, suggesting a connection to the TH compartment. We performed a phenotypic, spatial and functional assessment of T-cell exhaustion in CHL and found co-expression of an exhaustion marker and lower PD1 expression in CHL than in reactive nodes whereas the proliferative and cytokine production capacity were similar in CHL and the reactive nodes. We found no correlation between PDL1 expression and exhaustion signatures. Instead, we identified a strong association between PDL1 expression and CHL MHC-II expression, TH recruitment, and enrichment of TH1 regulatory cells. These data suggest that a dominant effect of PDL1 expression in CHL may be TH engagement and promotion of a regulatory microenvironment rather than maintenance of exhaustion.

The association between psychosocial factors and mental health symptoms in cervical spine pain with or without radiculopathy on health outcomes: a systematic review.

BACKGROUND: Neck pain, with or without radiculopathy, can have significant negative effects on physical and mental wellbeing. Mental health symptoms are known to worsen prognosis across a range of musculoskeletal conditions. Understanding the association between mental health symptoms and health outcomes in this population has not been established. Our aim was to systematically review the association between psychosocial factors and/or mental health symptoms on health outcomes in adults with neck pain, with or without radiculopathy. METHODS: A systematic review of published and unpublished literature databases was completed. Studies reporting mental health symptoms and health outcomes in adults with neck pain with or without radiculopathy were included. Due to significant clinical heterogeneity, a narrative synthesis was completed. Each outcome was assessed using GRADE. RESULTS: Twenty-three studies were included (N = 21,968 participants). Sixteen studies assessed neck pain only (N = 17,604 participants); seven studies assessed neck pain with radiculopathy (N = 4,364 participants). Depressive symptoms were associated with poorer health outcomes in people with neck pain and neck pain with radiculopathy. These findings were from seven low-quality studies, and an additional six studies reported no association. Low-quality evidence reported that distress and anxiety symptoms were associated with poorer health outcomes in people with neck pain and radiculopathy and very low-quality evidence showed this in people with neck pain only. Stress and higher job strain were negatively associated with poorer health outcomes measured by the presence of pain in two studies of very low quality. CONCLUSIONS: Across a small number of highly heterogenous, low quality studies mental health symptoms are negatively associated with health outcomes in people with neck pain with radiculopathy and neck pain without radiculopathy. Clinicians should continue to utilise robust clinical reasoning when assessing the complex factors impacting a person's presentation with neck pain with or without radiculopathy. PROSPERO REGISTRATION NUMBER: CRD42020169497.

Landscape context affects the sustainability of organic farming systems.

Organic agriculture promotes sustainability compared to conventional agriculture. However, the multifunctional sustainability benefits of organic farms might be mediated by landscape context. Assessing how landscape context affects sustainability may aid in targeting organic production to landscapes that promote high biodiversity, crop yields, and profitability. We addressed this using a meta-analysis spanning 60 crop types on six continents that assessed whether landscape context affected biodiversity, yield, and profitability of organic vs. conventional agroecosystems. We considered landscape metrics reflecting landscape composition (percent cropland), compositional heterogeneity (number and diversity of cover types), and configurational heterogeneity (spatial arrangement of cover types) across our study systems. Organic sites had greater biodiversity (34%) and profits (50%) than conventional sites, despite lower yields (18%). Biodiversity gains increased as average crop field size in the landscape increased, suggesting organic farms provide a "refuge" in intensive landscapes. In contrast, as crop field size increased, yield gaps between organic and conventional farms increased and profitability benefits of organic farming decreased. Profitability of organic systems, which we were only able to measure for studies conducted in the United States, varied across landscapes in conjunction with production costs and price premiums, suggesting socioeconomic factors mediated profitability. Our results show biodiversity benefits of organic farming respond differently to landscape context compared to yield and profitability benefits, suggesting these sustainability metrics are decoupled. More broadly, our results show that the ecological, but not the economic, sustainability benefits of organic agriculture are most pronounced in more intensive agricultural landscapes.

A trait-based framework for predicting foodborne pathogen risk from wild birds.

Recent foodborne illness outbreaks have heightened pressures on growers to deter wildlife from farms, jeopardizing conservation efforts. However, it remains unclear which species, particularly birds, pose the greatest risk to food safety. Using >11,000 pathogen tests and 1565 bird surveys covering 139 bird species from across the western United States, we examined the importance of 11 traits in mediating wild bird risk to food safety. We tested whether traits associated with pathogen exposure (e.g., habitat associations, movement, and foraging strategy) and pace-of-life (clutch size and generation length) mediated foodborne pathogen prevalence and proclivities to enter farm fields and defecate on crops. Campylobacter spp. were the most prevalent enteric pathogen (8.0%), while Salmonella and Shiga-toxin producing Escherichia coli (STEC) were rare (0.46% and 0.22% prevalence, respectively). We found that several traits related to pathogen exposure predicted pathogen prevalence. Specifically, Campylobacter and STEC-associated virulence genes were more often detected in species associated with cattle feedlots and bird feeders, respectively. Campylobacter was also more prevalent in species that consumed plants and had longer generation lengths. We found that species associated with feedlots were more likely to enter fields and defecate on crops. Our results indicated that canopy-foraging insectivores were less likely to deposit foodborne pathogens on crops, suggesting growers may be able to promote pest-eating birds and birds of conservation concern (e.g., via nest boxes) without necessarily compromising food safety. As such, promoting insectivorous birds may represent a win-win-win for bird conservation, crop production, and food safety. Collectively, our results suggest that separating crop production from livestock farming may be the best way to lower food safety risks from birds. More broadly, our trait-based framework suggests a path forward for co-managing wildlife conservation and food safety risks in farmlands by providing a strategy for holistically evaluating the food safety risks of wild animals, including under-studied species.

Use of long term aprepitant as a treatment for refractory nausea following oesophageal stent insertion - a case report.

BACKGROUND: Aprepitant, a substance P neurokinin-1 receptor antagonist, is licenced for the prevention of acute and delayed nausea and vomiting associated with highly and moderately emetogenic cancer chemotherapy. CASE: A 33 year-old male with metastatic gastro-oesophageal cancer had multiple admissions for refractory nausea and vomiting following insertion of an oesophageal stent. ACTION: Mechanical issues with the stent, stent removal and central causes were excluded. Multiple anti-emetic agents were trialled in combination and with varying routes of administration without significant symptomatic improvement. FORMULATION: A trial of aprepitant was proposed as an off-licence therapy. OUTCOME: One hundred sixty-five milligrammes of aprepitant was given orally every 3 days and then up titrated to once daily with significant symptomatic improvement enabling the patient to tolerate an oral diet. The patient remained stable at 12 weeks and has been accepted into two clinical trials for potential further cancer treatment. LESSONS: Aprepitant can be effective in refractory nausea and vomiting outside of emetogenic chemotherapy and safely used as a chronic treatment. The prevalence of refractory nausea and vomiting as a rare adverse outcome post-oesophageal stent insertion should be studied. WHAT NOW?: Further research of neurokinin-1 inhibitors for indications other than chemotherapy-induced nausea and vomiting is indicated.

Untargeted metabolomics of COVID-19 patient serum reveals potential prognostic markers of both severity and outcome.

INTRODUCTION: The diagnosis of COVID-19 is normally based on the qualitative detection of viral nucleic acid sequences. Properties of the host response are not measured but are key in determining outcome. Although metabolic profiles are well suited to capture host state, most metabolomics studies are either underpowered, measure only a restricted subset of metabolites, compare infected individuals against uninfected control cohorts that are not suitably matched, or do not provide a compact predictive model. OBJECTIVES: Here we provide a well-powered, untargeted metabolomics assessment of 120 COVID-19 patient samples acquired at hospital admission. The study aims to predict the patient's infection severity (i.e., mild or severe) and potential outcome (i.e., discharged or deceased). METHODS: High resolution untargeted UHPLC-MS/MS analysis was performed on patient serum using both positive and negative ionization modes. A subset of 20 intermediary metabolites predictive of severity or outcome were selected based on univariate statistical significance and a multiple predictor Bayesian logistic regression model was created. RESULTS: The predictors were selected for their relevant biological function and include deoxycytidine and ureidopropionate (indirectly reflecting viral load), kynurenine (reflecting host inflammatory response), and multiple short chain acylcarnitines (energy metabolism) among others. Currently, this approach predicts outcome and severity with a Monte Carlo cross validated area under the ROC curve of 0.792 (SD 0.09) and 0.793 (SD 0.08), respectively. A blind validation study on an additional 90 patients predicted outcome and severity at ROC AUC of 0.83 (CI 0.74-0.91) and 0.76 (CI 0.67-0.86). CONCLUSION: Prognostic tests based on the markers discussed in this paper could allow improvement in the planning of COVID-19 patient treatment.

Phactr1 regulates Slack (KCNT1) channels via protein phosphatase 1 (PP1).

The Slack (KCNT1) gene encodes sodium-activated potassium channels that are abundantly expressed in the central nervous system. Human mutations alter the function of Slack channels, resulting in epilepsy and intellectual disability. Most of the disease-causing mutations are located in the extended cytoplasmic C-terminus of Slack channels and result in increased Slack current. Previous experiments have shown that the C-terminus of Slack channels binds a number of cytoplasmic signaling proteins. One of these is Phactr1, an actin-binding protein that recruits protein phosphatase 1 (PP1) to certain phosphoprotein substrates. Using co-immunoprecipitation, we found that Phactr1 is required to link the channels to actin. Using patch clamp recordings, we found that co-expression of Phactr1 with wild-type Slack channels reduces the current amplitude but has no effect on Slack channels in which a conserved PKC phosphorylation site (S407) that regulates the current amplitude has been mutated. Furthermore, a Phactr1 mutant that disrupts the binding of PP1 but not that of actin fails to alter Slack currents. Our data suggest that Phactr1 regulates the Slack by linking PP1 to the channel. Targeting Slack-Phactr1 interactions may therefore be helpful in developing the novel therapies for brain disorders associated with the malfunction of Slack channels.

Estimation of neuron parameters from imperfect observations.

The estimation of parameters controlling the electrical properties of biological neurons is essential to determine their complement of ion channels and to understand the function of biological circuits. By synchronizing conductance models to time series observations of the membrane voltage, one may construct models capable of predicting neuronal dynamics. However, identifying the actual set of parameters of biological ion channels remains a formidable theoretical challenge. Here, we present a regularization method that improves convergence towards this optimal solution when data are noisy and the model is unknown. Our method relies on the existence of an offset in parameter space arising from the interplay between model nonlinearity and experimental error. By tuning this offset, we induce saddle-node bifurcations from sub-optimal to optimal solutions. This regularization method increases the probability of finding the optimal set of parameters from 67% to 94.3%. We also reduce parameter correlations by implementing adaptive sampling and stimulation protocols compatible with parameter identifiability requirements. Our results show that the optimal model parameters may be inferred from imperfect observations provided the conditions of observability and identifiability are fulfilled.

Machine Learning Analysis for Phenolic Compound Monitoring Using a Mobile Phone-Based ECL Sensor.

Machine learning (ML) can be an appropriate approach to overcoming common problems associated with sensors for low-cost, point-of-care diagnostics, such as non-linearity, multidimensionality, sensor-to-sensor variations, presence of anomalies, and ambiguity in key features. This study proposes a novel approach based on ML algorithms (neural nets, Gaussian Process Regression, among others) to model the electrochemiluminescence (ECL) quenching mechanism of the [Ru(bpy)3]2+/TPrA system by phenolic compounds, thus allowing their detection and quantification. The relationships between the concentration of phenolic compounds and their effect on the ECL intensity and current data measured using a mobile phone-based ECL sensor is investigated. The ML regression tasks with a tri-layer neural net using minimally processed time series data showed better or comparable detection performance compared to the performance using extracted key features without extra preprocessing. Combined multimodal characteristics produced an 80% more enhanced performance with multilayer neural net algorithms than a single feature based-regression analysis. The results demonstrated that the ML could provide a robust analysis framework for sensor data with noises and variability. It demonstrates that ML strategies can play a crucial role in chemical or biosensor data analysis, providing a robust model by maximizing all the obtained information and integrating nonlinearity and sensor-to-sensor variations.

Generation lengths of the world's birds and their implications for extinction risk.

Birds have been comprehensively assessed on the International Union for Conservation of Nature (IUCN) Red List more times than any other taxonomic group. However, to date, generation lengths have not been systematically estimated to scale population trends when undertaking assessments, as required by the criteria of the IUCN Red List. We compiled information from major databases of published life-history and trait data for all birds and imputed missing life-history data as a function of species traits with generalized linear mixed models. Generation lengths were derived for all species, based on our modeled values of age at first breeding, maximum longevity, and annual adult survival. The resulting generation lengths varied from 1.42 to 27.87 years (median 2.99). Most species (61%) had generation lengths <3.33 years, meaning that the period of 3 generations-over which population declines are assessed under criterion A-was <10 years, which is the value used for IUCN Red List assessments of species with short generation times. For these species, our trait-informed estimates of generation length suggested that 10 years is a robust precautionary value for threat assessment. In other cases, however, for whole families, genera, or individual species, generation length had a substantial impact on their estimated extinction risk, resulting in higher extinction risk in long-lived species than in short-lived species. Although our approach effectively addressed data gaps, generation lengths for some species may have been underestimated due to a paucity of life-history data. Overall, our results will strengthen future extinction-risk assessments and augment key databases of avian life-history and trait data.

Duraciones Generacionales de las Aves del Mundo y sus Implicaciones para el Riesgo de Extinción Resumen Las aves han sido valoradas integralmente en la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) más veces que cualquier otro grupo taxonómico. Sin embargo, a la fecha, las duraciones generacionales no han sido estimadas sistemáticamente para escalar las tendencias poblacionales cuando se realizan las valoraciones, como lo requieren los criterios de la Lista Roja de la UICN. Compilamos información a partir de las principales bases de datos de historias de vida y datos de características publicadas para todas las aves e imputamos los datos faltantes de historias de vida como una función de las características de especies con modelos lineales mixtos generalizados. La duración por generación estuvo derivada para todas las especies con base en nuestros valores modelados de edad durante la primera reproducción, la longevidad máxima y la supervivencia anual de adultos. La duración por generación resultante varió de 1.42 a 27.87 años (mediana: 2.99). La mayoría de las especies (61%) tuvo una duración generacional <3.33 años, lo que significa que el periodo de tres generaciones - durante el cual se valoran las declinaciones poblacionales bajo el Criterio A - es <10 años, el cual es el valor usado por la Lista Roja de la UICN para la valoración de especies con tiempos generacionales cortos. Para estas especies, nuestras estimaciones de duración por generación informados por características sugieren que diez años es un valor preventivo sólido para la valoración de amenazas. Para otros casos, sin embargo, como familias o géneros enteros o especies individuales, la duración generacional tuvo un impacto sustancial sobre su riesgo de extinción estimado, resultando así en un riesgo de extinción más elevado para las especies con mayor longevidad que aquellas especies con una menor longevidad. Aunque nuestra estrategia lidió efectivamente con los vacíos en los datos, la duración generacional para algunas especies podría estar subestimada debido a la escasez de datos de historia de vida. En general, nuestros resultados fortalecerán las futuras valoraciones de extinción de riesgo y aumentarán las bases de datos importantes de la historia de vida de las aves y los datos de características.

Salvage or Solution: Alloplastic Reconstruction in Hemifacial Microsomia.

INTRODUCTION: Skeletal reconstruction in severe grades of hemifacial microsomia (HFM) continues to be challenging. Traditional techniques of autografts and osseous distraction for reconstruction of the glenoid fossa, condyle, and ramus can fall short of expectations and can create new problems. This intercontinental study analyzes the role of alloplastic skeletal rehabilitation in severe HFM. METHODS: Ten consecutive patients with Pruzansky grade III HFM were reconstructed between October 2014 and July 2017 at 2 craniofacial centers following the same protocol. Data were gathered retrospectively from the medical records, including photographs and virtual planning records. Pre and postoperative photos were taken to compare occlusal status, interincisal opening, sagittal mandibular projection, and posterior facial height. Alloplastic reconstruction was accomplished using a custom designed titanium implant. RESULTS: Ten consecutive skeletally mature patients with HFM with failed traditional reconstructions were successfully treated with virtually planned alloplastic reconstructions (11 joints) and simultaneous orthognathic surgery. The glenoid fossa, condyle, and ramus on the affected sides were reconstructed with custom designed titanium implants. All patients achieved occlusal stabilization, normalization of posterior facial height and sagittal mandibular projection, and maintenance or improved inter-incisal opening. There were no major complications or repeated surgeries. Follow-up ranges from 6 to 50 months. CONCLUSION: Alloplastic reconstruction allows for precise vertical reconstruction of the ramus and condyle and sagittal repositioning of the mandibular body. The glenoid fossa component is firmly anchored to the skull base assuring a stable centric relation on the reconstructed side. Consistent and acceptable results can be achieved in skeletally mature patients.

Microenvironment abnormalities and lymphomagenesis: Immunological aspects.

Innate and adaptive immune cells within the microenvironment identify and eliminate cells displaying signs of malignant potential. Immunosurveillance effector Natural Killer (NK) cells and Cytotoxic T Lymphocytes (CTL) identify malignant cells through germline receptors such as NKG2D and in the case of CTLs, presentation of antigen through the T cell receptor. Manipulation of immunosurveillance through altered tumor-identifying ligand expression or secretion, resistance to cytotoxicity, or compromised cytotoxic cell activity through immune tolerance mechanisms all contribute to failure of these systems to prevent cancer development. This review examines the diverse mechanisms by which alterations in the immune microenvironment can promote lymphomagenesis.

Fetal and Neonatal Effects of N-Acetylcysteine When Used for Neuroprotection in Maternal Chorioamnionitis.

OBJECTIVE: To evaluate the clinical safety of antenatal and postnatal N-acetylcysteine (NAC) as a neuroprotective agent in maternal chorioamnionitis in a randomized, controlled, double-blinded trial. STUDY DESIGN: Twenty-two mothers >24 weeks gestation presenting within 4 hours of diagnosis of clinical chorioamnionitis were randomized with their 24 infants to NAC or saline treatment. Antenatal NAC (100 mg/kg/dose) or saline was given intravenously every 6 hours until delivery. Postnatally, NAC (12.5-25 mg/kg/dose, n = 12) or saline (n = 12) was given every 12 hours for 5 doses. Doppler studies of fetal umbilical and fetal and infant cerebral blood flow, cranial ultrasounds, echocardiograms, cerebral oxygenation, electroencephalograms, and serum cytokines were evaluated before and after treatment, and 12, 24, and 48 hours after birth. Magnetic resonance spectroscopy and diffusion imaging were performed at term age equivalent. Development was followed for cerebral palsy or autism to 4 years of age. RESULTS: Cardiovascular measures, cerebral blood flow velocity and vascular resistance, and cerebral oxygenation did not differ between treatment groups. Cerebrovascular coupling was disrupted in infants with chorioamnionitis treated with saline but preserved in infants treated with NAC, suggesting improved vascular regulation in the presence of neuroinflammation. Infants treated with NAC had higher serum anti-inflammatory interleukin-1 receptor antagonist and lower proinflammatory vascular endothelial growth factor over time vs controls. No adverse events related to NAC administration were noted. CONCLUSIONS: In this cohort of newborns exposed to chorioamnionitis, antenatal and postnatal NAC was safe, preserved cerebrovascular regulation, and increased an anti-inflammatory neuroprotective protein. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00724594.