Guiding antibiotics towards their target using bacteriophage proteins.

Novel therapeutic strategies against difficult-to-treat bacterial infections are desperately needed, and the faster and cheaper way to get them might be by repurposing existing antibiotics. Nanodelivery systems enhance the efficacy of antibiotics by guiding them to their targets, increasing the local concentration at the site of infection. While recently described nanodelivery systems are promising, they are generally not easy to adapt to different targets, and lack biocompatibility or specificity. Here, nanodelivery systems are created that source their targeting proteins from bacteriophages. Bacteriophage receptor-binding proteins and cell-wall binding domains are conjugated to nanoparticles, for the targeted delivery of rifampicin, imipenem, and ampicillin against bacterial pathogens. They show excellent specificity against their targets, and accumulate at the site of infection to deliver their antibiotic payload. Moreover, the nanodelivery systems suppress pathogen infections more effectively than 16 to 32-fold higher doses of free antibiotics. This study demonstrates that bacteriophage sourced targeting proteins are promising candidates to guide nanodelivery systems. Their specificity, availability, and biocompatibility make them great options to guide the antibiotic nanodelivery systems that are desperately needed to combat difficult-to-treat infections.

The asbestos-asbestosis exposure-response relationship: a cohort study of the general working population.

OBJECTIVES: The association between asbestos exposure and asbestosis in high-exposed industrial cohorts is well-known, but there is a lack of knowledge about the exposure-response relationship for asbestosis in a general working population setting. We examined the exposure-response relationship between occupational asbestos exposure and asbestosis in asbestos-exposed workers of the Danish general working population. METHODS: We followed all asbestos-exposed workers from 1979 to 2015 and identified incident cases of asbestosis using the Danish National Patient Register. Individual asbestos exposure was estimated with a quantitative job exposure matrix (SYN-JEM) from 1976 onwards and back-extrapolated to age 16 for those exposed in 1976. Exposure-response relations for cumulative exposure and other exposure metrics were analyzed using a discrete time hazard model and adjusted for potential confounders. RESULTS: The range of cumulative exposure in the population was 0.001 to 18 fibers per milliliter-year (f/ml-year). We found increasing incidence rate ratios (IRR) of asbestosis with increasing cumulative asbestos exposure with a fully adjusted IRR per 1 f/ml-years of 1.18 [95% confidence interval (CI) 1.15- -1.22]. The IRR was 1.94 (95% CI 1.53-2.47) in the highest compared to the lowest exposure tertile. We similarly observed increasing risk with increasing cumulative exposure in the inception population. CONCLUSIONS: This study found exposure-response relations between cumulative asbestos exposure and incident asbestosis in the Danish general working population with mainly low-level exposed occupations, but there is some uncertainty regarding the exposure levels.

The efficacy and safety of ankle blocks for foot and ankle surgery: A systematic review with meta-analysis and trial sequential analysis.

BACKGROUND: Peripheral nerve blocks may be essential elements in a multimodal pain management regime following foot and ankle surgery. We assessed the effects of ankle blocks compared with no intervention/sham block or a sciatic nerve block in patients undergoing surgery of the foot or ankle. METHODS: We searched CENTRAL, Medline, and Embase for randomised clinical trials comparing ankle block with no intervention/sham block or a sciatic nerve block for patients undergoing surgery of the foot or ankle. Our primary outcomes were duration of analgesia and cumulative 24-hour opioid consumption. We followed the recommendations of the Cochrane Handbook, and performed meta-analysis, Trial Sequential Analysis (TSA), and assessed the risk of bias and certainty of the evidence using the GRADE approach. RESULTS: We included five trials (362 participants) comparing ankle block with no intervention/sham block and three trials (247 participants) comparing ankle block with a sciatic nerve block. Ankle block may increase the duration of analgesia when compared with no intervention/sham block (MD 431 min; 96.7% CI 208 to 654), but the evidence was very uncertain. Duration was decreased when compared with a sciatic nerve block (MD -410 min; 96.7% CI -462 to -358). The ankle block duration was probably important in both comparisons. The effects on cumulative 24-hour opioid consumption were very uncertain in both comparisons. CONCLUSIONS: Ankle block may increase the duration of analgesia when compared with no intervention/sham block, but the evidence was very uncertain, and decrease the duration of analgesia when compared with a sciatic nerve block. The ankle block duration was probably clinically important in both comparisons. The effects on cumulative 24-hour opioid consumption were very uncertain.

Combined Dexamethasone and Dexmedetomidine as Adjuncts to Popliteal and Saphenous Nerve Blocks in Patients Undergoing Surgery of the Foot or Ankle: A Randomized, Blinded, Placebo-controlled Clinical Trial.

BACKGROUND: Both dexamethasone and dexmedetomidine increase the duration of analgesia of peripheral nerve blocks. The authors hypothesized that combined intravenous dexamethasone and intravenous dexmedetomidine would result in a greater duration of analgesia when compared with intravenous dexamethasone alone and placebo. METHODS: The authors randomly allocated participants undergoing surgery of the foot or ankle under general anesthesia and with a combined popliteal (sciatic) and saphenous nerve block to a combination of 12 mg dexamethasone and 1 µg/kg dexmedetomidine, 12 mg dexamethasone, or placebo (saline). The primary outcome was the duration of analgesia measured as the time from block performance until the first sensation of pain in the surgical area as reported by the participant. The authors predefined a 33% difference in the duration of analgesia as clinically relevant. RESULTS: A total of 120 participants from two centers were randomized and 119 analyzed for the primary outcome. The median [interquartile range] duration of analgesia was 1,572 min [1,259 to 1,715] with combined dexamethasone and dexmedetomidine, 1,400 min [1,133 to 1,750] with dexamethasone alone, and 870 min [748 to 1,138] with placebo. Compared with placebo, the duration was greater with combined dexamethasone and dexmedetomidine (difference, 564 min; 98.33% CI, 301 to 794; P < 0.001) and with dexamethasone (difference, 489 min; 98.33% CI, 265 to 706; P < 0.001). The prolongations exceeded the authors' predefined clinically relevant difference. The duration was similar when combined dexamethasone and dexmedetomidine was compared with dexamethasone alone (difference, 61 min; 98.33% CI, -222 to 331; P = 0.614). CONCLUSIONS: Dexamethasone with or without dexmedetomidine increased the duration of analgesia in patients undergoing surgery of the foot or ankle with a popliteal (sciatic) and saphenous nerve block. Combined dexamethasone and dexmedetomidine did not increase the duration of analgesia when compared with dexamethasone.

Trained recurrent neural networks develop phase-locked limit cycles in a working memory task.

Neural oscillations are ubiquitously observed in many brain areas. One proposed functional role of these oscillations is that they serve as an internal clock, or 'frame of reference'. Information can be encoded by the timing of neural activity relative to the phase of such oscillations. In line with this hypothesis, there have been multiple empirical observations of such phase codes in the brain. Here we ask: What kind of neural dynamics support phase coding of information with neural oscillations? We tackled this question by analyzing recurrent neural networks (RNNs) that were trained on a working memory task. The networks were given access to an external reference oscillation and tasked to produce an oscillation, such that the phase difference between the reference and output oscillation maintains the identity of transient stimuli. We found that networks converged to stable oscillatory dynamics. Reverse engineering these networks revealed that each phase-coded memory corresponds to a separate limit cycle attractor. We characterized how the stability of the attractor dynamics depends on both reference oscillation amplitude and frequency, properties that can be experimentally observed. To understand the connectivity structures that underlie these dynamics, we showed that trained networks can be described as two phase-coupled oscillators. Using this insight, we condensed our trained networks to a reduced model consisting of two functional modules: One that generates an oscillation and one that implements a coupling function between the internal oscillation and external reference. In summary, by reverse engineering the dynamics and connectivity of trained RNNs, we propose a mechanism by which neural networks can harness reference oscillations for working memory. Specifically, we propose that a phase-coding network generates autonomous oscillations which it couples to an external reference oscillation in a multi-stable fashion.

Comparison of Otsu and an adapted Chan-Vese method to determine thyroid active volume using Monte Carlo generated SPECT images.

BACKGROUND: The Otsu method and the Chan-Vese model are two methods proven to perform well in determining volumes of different organs and specific tissue fractions. This study aimed to compare the performance of the two methods regarding segmentation of active thyroid gland volumes, reflecting different clinical settings by varying the parameters: gland size, gland activity concentration, background activity concentration and gland activity concentration heterogeneity. METHODS: A computed tomography was performed on three playdough thyroid phantoms with volumes 20, 35 and 50 ml. The image data were separated into playdough and water based on Hounsfield values. Sixty single photon emission computed tomography (SPECT) projections were simulated by Monte Carlo method with isotope Technetium-99 m ([Formula: see text]Tc). Linear combinations of SPECT images were made, generating 12 different combinations of volume and background: each with both homogeneous thyroid activity concentration and three hotspots of different relative activity concentrations (48 SPECT images in total). The relative background levels chosen were 5 %, 10 %, 15 % and 20 % of the phantom activity concentration and the hotspot activities were 100 % (homogeneous case) 150 %, 200 % and 250 %. Poisson noise, (coefficient of variation of 0.8 at a 20 % background level, scattering excluded), was added before reconstruction was done with the Monte Carlo-based SPECT reconstruction algorithm Sahlgrenska Academy reconstruction code (SARec). Two different segmentation algorithms were applied: Otsu's threshold selection method and an adaptation of the Chan-Vese model for active contours without edges; the results were evaluated concerning relative volume, mean absolute error and standard deviation per thyroid volume, as well as dice similarity coefficient. RESULTS: Both methods segment the images well and deviate similarly from the true volumes. They seem to slightly overestimate small volumes and underestimate large ones. Different background levels affect the two methods similarly as well. However, the Chan-Vese model deviates less and paired t-testing showed significant difference between distributions of dice similarity coefficients (p-value [Formula: see text]). CONCLUSIONS: The investigations indicate that the Chan-Vese model performs better and is slightly more robust, while being more challenging to implement and use clinically. There is a trade-off between performance and user-friendliness.

Simulation-based inference for efficient identification of generative models in computational connectomics.

Recent advances in connectomics research enable the acquisition of increasing amounts of data about the connectivity patterns of neurons. How can we use this wealth of data to efficiently derive and test hypotheses about the principles underlying these patterns? A common approach is to simulate neuronal networks using a hypothesized wiring rule in a generative model and to compare the resulting synthetic data with empirical data. However, most wiring rules have at least some free parameters, and identifying parameters that reproduce empirical data can be challenging as it often requires manual parameter tuning. Here, we propose to use simulation-based Bayesian inference (SBI) to address this challenge. Rather than optimizing a fixed wiring rule to fit the empirical data, SBI considers many parametrizations of a rule and performs Bayesian inference to identify the parameters that are compatible with the data. It uses simulated data from multiple candidate wiring rule parameters and relies on machine learning methods to estimate a probability distribution (the 'posterior distribution over parameters conditioned on the data') that characterizes all data-compatible parameters. We demonstrate how to apply SBI in computational connectomics by inferring the parameters of wiring rules in an in silico model of the rat barrel cortex, given in vivo connectivity measurements. SBI identifies a wide range of wiring rule parameters that reproduce the measurements. We show how access to the posterior distribution over all data-compatible parameters allows us to analyze their relationship, revealing biologically plausible parameter interactions and enabling experimentally testable predictions. We further show how SBI can be applied to wiring rules at different spatial scales to quantitatively rule out invalid wiring hypotheses. Our approach is applicable to a wide range of generative models used in connectomics, providing a quantitative and efficient way to constrain model parameters with empirical connectivity data.

A selected organosilicone spray adjuvant does not enhance lethal effects of a pyrethroid and carbamate insecticide on honey bees.

As part of the agricultural landscape, non-target organisms, such as bees, may be exposed to a cocktail of agrochemicals including insecticides and spray adjuvants like organosilicone surfactants (OSS). While the risks of insecticides are evaluated extensively in their approval process, in most parts of the world however, authorization of adjuvants is performed without prior examination of the effects on bees. Nevertheless, recent laboratory studies evidence that adjuvants can have a toxicity increasing effect when mixed with insecticides. Therefore, this semi-field study aims to test whether an OSS mixed with insecticides can influence the insecticidal activity causing increased effects on bees and bee colonies under more realistic exposure conditions. To answer this question a pyrethroid (Karate Zeon) and a carbamate (Pirimor Granulat) were applied in a highly bee attractive crop (oil seed rape) during bee flight either alone or mixed with the OSS Break-Thru S 301 at field realistic application rates. The following parameters were assessed: mortality, flower visitation, population and brood development of full-sized bee colonies. Our results show that none of the above mentioned parameters was significantly affected by the insecticides alone or their combination with the adjuvant, except for a reduced flower visitation rate in both carbamate treatments (Tukey-HSD, p < 0.05). This indicates that the OSS did not increase mortality to a biologically relevant extent or any of the parameters observed on honey bees and colonies in this trial. Hence, social buffering may have played a crucial role in increasing thresholds for such environmental stressors. We confirm that the results of laboratory studies on individual bees cannot necessarily be extrapolated to the colony level and further trials with additional combinations are required for a well-founded evaluation of these substances.

The Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M): Preliminary psychometric properties and longitudinal validation within a clinical trial.

The use of cannabis for medical symptoms is increasing despite limited evidence for its efficacy. Expectancies-prior beliefs about a substance or medicine-can modulate use patterns and effects of medicines on target symptoms. To our knowledge, cannabis expectancies have not been studied for their predictive value for symptom relief. The 21-item Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M) is the first longitudinally validated measure of expectancies for cannabis used for medical symptoms. The questionnaire was developed for a randomized clinical trial of the effect of state cannabis registration (SCR) card ownership on symptoms of pain, insomnia, anxiety, and depression in adults (N = 269 across six questionnaire administrations). Item-level analyses (n = 188) demonstrated between-person stability of expectancies and no aggregate, within-person expectancy changes 3 months after individuals gained access to SCR cards. Exploratory factor analysis (n = 269) indicated a two-factor structure. Confirmatory factor analysis at a later timepoint (n = 193) demonstrated good fit and scalar invariance of the measurement model. Cross-lagged panel models across 3 and 12 months (n = 187 and 161, respectively) indicated that CEEQ-M-measured expectancies did not predict changes in self-reported cannabis use; symptoms of pain, insomnia, anxiety, and depression; and well-being. However, greater baseline cannabis use predicted more positive expectancy changes. The findings suggest that the CEEQ-M is psychometrically sound. Future work should clarify at what timescales cannabis expectancies have predictive value and how cannabis expectancies for medical symptoms are maintained and diverge from other substance use expectancies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Risk of epithelial ovarian tumors among women with polycystic ovary syndrome: A nationwide population-based cohort study.

An association between polycystic ovary syndrome (PCOS) and epithelial ovarian tumors is biologically plausible as conditions inherent to PCOS such as excessive androgenic hormones, reproductive factors and obesity are also risk factors for these hormone-sensitive tumors. However, previous studies have showed conflicting results and have various methodological limitations. This population-based cohort study investigates the association between PCOS and epithelial ovarian tumors and includes all women born in Denmark between January 1, 1940 and December 31, 1993 (n = 1 719 304). PCOS diagnoses, ovarian cancer and borderline ovarian tumor diagnoses, covariates, migration and vital status were obtained from the Danish national registers. Adjusted cox proportional hazard regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) for epithelial ovarian cancer and for borderline ovarian tumors overall as well as for histological subtypes separately. During median 26 years of follow-up we identified 6490 women with ovarian cancer and 2990 women with borderline ovarian tumors. Overall, we observed no marked associations between a diagnosis of PCOS and overall epithelial ovarian cancer or overall epithelial borderline ovarian tumors, irrespective of time since diagnosis. However, we found an increased risk of ovarian cancer among postmenopausal women with PCOS (HR 2.28 95% CI 1.02-5.09) and an increased risk of serous borderline ovarian tumors (HR 2.34 95% CI 1.21-4.53) in women with PCOS compared with women without PCOS. Importantly, low statistical precision is a crucial limitation of our study and in previous studies and larger studies with longer follow-up are therefore warranted.

Elevated Levels of Interleukin-1ß and Interleukin-10 Are Associated With Faster Lung Function Decline in People With Well-Treated Human Immunodeficiency Virus.

BACKGROUND: People with human immunodeficiency virus (PWH) have an increased risk of chronic lung diseases and chronic inflammation. We aimed to investigate if inflammatory markers and monocyte activation are associated with faster lung function decline in PWH. METHODS: We included 655 PWH from the Copenhagen Comorbidity in HIV Infection (COCOMO) Study. Eligible participants were aged ≥25 years and had 2 spirometries separated by >2 years. Inflammatory markers (interleukin [IL]-1ß, IL-2, IL-6, IL-10, tumor necrosis factor-α, and interferon-γ) were measured at baseline by Luminex, and soluble CD14 and soluble CD163 by enzyme-linked immunosorbent assay. Using linear mixed models, we investigated whether elevated cytokine levels were associated with faster lung function decline. RESULTS: The majority of PWH were males (85.2%) with undetectable viral replication (95.3%). We found a faster decline in forced expiratory volume in 1 second (FEV1) in PWH with elevated IL-1ß and IL-10, with an additional decline of 10.3 mL/year (95% confidence interval [CI], 2.1-18.6; P = .014) and 10.0 mL/year (95% CI, 1.8-18.2; P = .017), respectively. We found no interaction between smoking and IL-1ß or IL-10 on FEV1 decline. CONCLUSIONS: Elevated IL-1ß and IL-10 were independently associated with faster lung function decline in PWH, suggesting that dysregulated systemic inflammation may play a role in the pathogenesis of chronic lung diseases.

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference.

We combine amortized neural posterior estimation with importance sampling for fast and accurate gravitational-wave inference. We first generate a rapid proposal for the Bayesian posterior using neural networks, and then attach importance weights based on the underlying likelihood and prior. This provides (1) a corrected posterior free from network inaccuracies, (2) a performance diagnostic (the sample efficiency) for assessing the proposal and identifying failure cases, and (3) an unbiased estimate of the Bayesian evidence. By establishing this independent verification and correction mechanism we address some of the most frequent criticisms against deep learning for scientific inference. We carry out a large study analyzing 42 binary black hole mergers observed by LIGO and Virgo with the SEOBNRv4PHM and IMRPhenomXPHM waveform models. This shows a median sample efficiency of ≈10% (2 orders of magnitude better than standard samplers) as well as a tenfold reduction in the statistical uncertainty in the log evidence. Given these advantages, we expect a significant impact on gravitational-wave inference, and for this approach to serve as a paradigm for harnessing deep learning methods in scientific applications.

Perineural and Systemic Dexamethasone and Ulnar Nerve Block Duration: A Randomized, Blinded, Placebo-controlled Trial in Healthy Volunteers.

BACKGROUND: The authors hypothesized that both perineural and systemic dexamethasone as adjuncts to bupivacaine increase the duration of an ulnar nerve block compared with bupivacaine alone, and that systemic dexamethasone is noninferior to perineural dexamethasone. METHODS: The authors performed bilateral ulnar nerve blocks with 3 ml bupivacaine 5 mg/ml in 16 healthy volunteers on two trial days. According to randomization, subjects received adjunct treatment with 1 ml dexamethasone 4 mg/ml + 1 ml of saline (perineural condition) in one arm and 2 ml saline in the other arm (systemic condition, through absorption and redistribution of the contralaterally administered perineural dexamethasone) on one trial day; and 2 ml saline in one arm (placebo condition) and 2 ml of lidocaine in the other arm (lidocaine condition) on the other trial day. The primary outcome was the duration of the sensory nerve block assessed by temperature discrimination. RESULTS: Mean sensory block duration was 706 ± 94 min for the perineural condition, 677 ± 112 min for the systemic condition, and 640 ± 121 min for the placebo condition. The duration of the sensory nerve block was greater with perineural dexamethasone versus placebo (mean difference 66 min (95% CI, 23 to 108). Block duration was similar between systemic dexamethasone and placebo (mean difference 36 min; 95% CI, -30 to 103). CONCLUSIONS: Perineural dexamethasone as an adjunct to bupivacaine in healthy volunteers resulted in a greater duration of an ulnar nerve block when compared with placebo. Systemic dexamethasone resulted in a similar duration as placebo.

Mask mandates save lives.

We quantify the effect of statewide mask mandates in the United States in 2020. Our regression discontinuity design exploits county-level variation in COVID-19 outcomes across the border between states with and without mandates. State mask mandates reduced new weekly COVID-19 cases, hospital admissions, and deaths by 55, 11, and 0.7 per 100,000 inhabitants on average. The effect depends on political leaning with larger effects in Democratic-leaning counties. Our results imply that statewide mandates saved 87,000 lives through December 19, 2020, while a nationwide mandate could have saved 57,000 additional lives. This suggests that mask mandates can help counter pandemics, particularly if widely accepted.

Effects of Flupyradifurone and Two Reference Insecticides Commonly Used in Toxicological Studies on the Larval Proteome of the Honey bee Apis mellifera.

The western honey bee Apis mellifera is globally distributed due to its beekeeping advantages and plays an important role in the global ecology and economy. In recent decades, several studies have raised concerns about bee decline. Discussed are multiple reasons such as increased pathogen pressure, malnutrition or pesticide use. Insecticides are considered to be one of the major factors. In 2013, the use of three neonicotinoids in the field was prohibited in the EU. Flupyradifurone was introduced as a potential successor; it has a comparable mode of action as the banned neonicotinoids. However, there is a limited number of studies on the effects of sublethal concentrations of flupyradifurone on honey bees. Particularly, the larval physiological response by means of protein expression has not yet been studied. Hence, the larval protein expression was investigated via 2D gel electrophoresis after following a standardised protocol to apply sublethal concentrations of the active substance (flupyradifurone 10 mg/kg diet) to larval food. The treated larvae did not show increased mortality or an aberrant development. Proteome comparisons showed clear differences concerning the larval metabolism, immune response and energy supply. Further field studies are needed to validate the in vitro results at a colony level.

How to account for Inuit ancestry in lung function prediction.

Rigorous lung function prediction equations for the Inuit are lacking. We used spirometry from 351 Inuit and 29 people of other ancestry obtained during an occupational survey in Greenland to determine how to obtain valid lung function predictions for the Inuit using Global Lung Function Initiative (GLI) equations for Europeans. Standing height for the Inuit was used in the predictions as well as their height modified in line with the known differences in standing to sitting height ratio (SHR) for the Inuit. With recorded height in predicting lung function, mean±SD Inuit z-scores for FVC and FEV1 were significantly higher than predicted (0.81±1.20 and 0.53±1.36, respectively, p<0.0001) which was not true for the non-Inuit participants (-0.01±1.04 and 0.15±1.17, respectively). When using height modified for SHR the mean±SD Inuit z-scores for FVC and FEV1 were no longer significantly different from predicted (0.10±1.10 and -0.12±1.24, respectively). The mean±SD Inuit FEV1/FVC z-scores were not significantly different from the non-Inuit, being respectively -0.45±0.98 and -0.01±1.04. Modified height changed the mean±SD Inuit FEV1/FVC z-scores to -0.39±0.99. Representative lung function predictions from GLI equations can be made for Inuit by using standing height modified for the known differences in SHR between Inuit and those of European ancestry.

Duration of Device-Based Fever Prevention after Cardiac Arrest.

BACKGROUND: Guidelines recommend active fever prevention for 72 hours after cardiac arrest. Data from randomized clinical trials of this intervention have been lacking. METHODS: We randomly assigned comatose patients who had been resuscitated after an out-of-hospital cardiac arrest of presumed cardiac cause to device-based temperature control targeting 36°C for 24 hours followed by targeting of 37°C for either 12 or 48 hours (for total intervention times of 36 and 72 hours, respectively) or until the patient regained consciousness. The primary outcome was a composite of death from any cause or hospital discharge with a Cerebral Performance Category of 3 or 4 (range, 1 to 5, with higher scores indicating more severe disability; a category of 3 or 4 indicates severe cerebral disability or coma) within 90 days after randomization. Secondary outcomes included death from any cause and the Montreal Cognitive Assessment score (range, 0 to 30, with higher scores indicating better cognitive ability) at 3 months. RESULTS: A total of 393 patients were randomly assigned to temperature control for 36 hours, and 396 patients were assigned to temperature control for 72 hours. At 90 days after randomization, a primary end-point event had occurred in 127 of 393 patients (32.3%) in the 36-hour group and in 133 of 396 patients (33.6%) in the 72-hour group (hazard ratio, 0.99; 95% confidence interval, 0.77 to 1.26; P = 0.70) and mortality was 29.5% in the 36-hour group and 30.3% in the 72-hour group. At 3 months, the median Montreal Cognitive Assessment score was 26 (interquartile range, 24 to 29) and 27 (interquartile range, 24 to 28), respectively. There was no significant between-group difference in the incidence of adverse events. CONCLUSIONS: Active device-based fever prevention for 36 or 72 hours after cardiac arrest did not result in significantly different percentages of patients dying or having severe disability or coma. (Funded by the Novo Nordisk Foundation; BOX ClinicalTrials.gov number, NCT03141099.).

Systemic glucocorticoids as an adjunct to treatment of postoperative pain after total hip and knee arthroplasty: A systematic review with meta-analysis and trial sequential analysis.

BACKGROUND: Postoperative analgesic effects of systemic glucocorticoids given as an adjunct to treatment are largely undetermined in alloplastic procedures. OBJECTIVES: To investigate the beneficial and harmful effects of peri-operative systemic glucocorticoid treatment for pain after total hip arthroplasty (THA) or total knee arthroplasty (TKA). DESIGN: A systematic review of randomised clinical trials (RCTs) with meta-analyses, trial sequential analyses and GRADE. Primary outcome was 24 h intravenous (i.v.) morphine (or equivalent) consumption with a predefined minimal important difference (MID) of 5 mg. Secondary outcomes included pain at rest and during mobilisation (MID, VAS 10 mm), adverse and serious adverse events (SAEs). DATA SOURCES: We searched EMBASE, Cochrane CENTRAL, PubMed and Google Scholar up to October 2021. ELIGIBILITY CRITERIA: RCTs investigating peri-operative systemic glucocorticoid versus placebo or no intervention, for analgesic pain management of patients at least 18 years undergoing planned THA or TKA, irrespective of publication date and language. RESULTS: We included 32 RCTs with 3521 patients. Nine trials were at a low risk of bias. Meta-analyses showed evidence of a reduction in 24 h cumulative morphine consumption with glucocorticoids by 5.0 mg (95% CI 2.2 to 7.7; P  = 0.0004). Pain at rest was reduced at 6 h by 7.8 mm (95% CI 5.5 to 10.2; P  < 0.00001), and at 24 h by 6.3 mm (95% CI 3.8 to 8.8; P  < 0.00001). Pain during mobilisation was reduced at 6 h by 9.8 mm (95% CI 6.9 to 12.8; P  < 0.00001), and at 24 h by 9.0 mm (95% CI 5.5 to 12.4, P  < 0.00001). Incidence of adverse events was generally lower in the glucocorticoid treatment group. SAEs were rarely reported. The GRADE rated quality of evidence was low to very low. CONCLUSION: Peri-operative systemic glucocorticoid treatment reduced postoperative morphine consumption to an individually relevant level following hip and knee arthroplasty. Pain levels were reduced but were below the predefined MID. The quality of evidence was generally low. REGISTRATION: PROSPERO ID: CRD42019135034.

Estimation of skeletal kinematics in freely moving rodents.

Forming a complete picture of the relationship between neural activity and skeletal kinematics requires quantification of skeletal joint biomechanics during free behavior; however, without detailed knowledge of the underlying skeletal motion, inferring limb kinematics using surface-tracking approaches is difficult, especially for animals where the relationship between the surface and underlying skeleton changes during motion. Here we developed a videography-based method enabling detailed three-dimensional kinematic quantification of an anatomically defined skeleton in untethered freely behaving rats and mice. This skeleton-based model was constrained using anatomical principles and joint motion limits and provided skeletal pose estimates for a range of body sizes, even when limbs were occluded. Model-inferred limb positions and joint kinematics during gait and gap-crossing behaviors were verified by direct measurement of either limb placement or limb kinematics using inertial measurement units. Together we show that complex decision-making behaviors can be accurately reconstructed at the level of skeletal kinematics using our anatomically constrained model.