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In humans born at term, maximal nephron number is reached by the time nephrogenesis is completed — at approximately 36 weeks’ gestation. The number of nephrons does not increase further and subsequently remains stable until loss occurs through ageing or disease. Nephron endowment is key to the functional capacity of the kidney and its resilience to disease; hence, any processes that impair kidney development in the developing fetus can have lifelong adverse consequences for renal health and, consequently, for quality and length of life. The timing of nephrogenesis underlies the vulnerability of developing human kidneys to adverse early life exposures. Indeed, exposure of the developing fetus to a suboptimal intrauterine environment during gestation — resulting in intrauterine growth restriction (IUGR) — and/or preterm birth can impede kidney development and lead to reduced nephron endowment. Furthermore, emerging research suggests that IUGR and/or preterm birth is associated with an elevated risk of chronic kidney disease in later life. The available data highlight the important role of early life development in the aetiology of kidney disease and emphasize the need to develop strategies to optimize nephron endowment in IUGR and preterm infants.Any processes that impair kidney development in the developing fetus can have lifelong adverse consequences for renal health. Here, the authors discuss the effects of preterm birth and/or intrauterine growth restriction on kidney development and the impact of these exposures on the later development of chronic kidney disease.

We discuss a laser-free, two-qubit geometric phase gate technique for generating high-fidelity entanglement between two trapped ions. The scheme works by ramping the spin-dependent force on and off slowly relative to the gate detunings, which adiabatically eliminates the spin-motion entanglement (AESE). We show how gates performed with AESE can eliminate spin-motion entanglement with multiple modes simultaneously, without having to specifically tune the control field detunings. This is because the spin-motion entanglement is suppressed by operating the control fields in a certain parametric limit, rather than by engineering an optimized control sequence. We also discuss physical implementations that use either electronic or ferromagnetic magnetic field gradients. In the latter, we show how to ‘AESE’ the system by smoothly turning on the effective spin-dependent force by shelving from a magnetic field insensitive state to a magnetic field sensitive state slowly relative to the gate mode frequencies. We show how to do this with a Rabi or adiabatic rapid passage transition. Finally, we show how gating with AESE significantly decreases the gate’s sensitivity to common sources of motional decoherence, making it easier to perform high-fidelity gates at Doppler temperatures.

Our everyday surroundings besiege us with information. The battle is for a share of our limited attention and memory, with the brain selecting the winners and discarding the losers. Previous research shows that both bottom-up and top-down factors bias competition in favor of high priority stimuli. We propose that arousal during an event increases this bias both in perception and in long-term memory of the event Arousal-biased competition theory provides specific predictions about when arousal will enhance memory for events and when it will impair it, which accounts for some puzzling contradictions in the emotional memory literature.

Inorganic perovskites such as CsPbX 3 (X=Cl, Br, I) have attracted attention due to their excellent thermal stability and high photoluminescence quantum efficiency. However, the electroluminescence quantum efficiency of their light-emitting diodes was <1%. We posited that this low efficiency was a result of high leakage current caused by poor perovskite morphology, high non-radiative recombination at interfaces and perovskite grain boundaries, and also charge injection imbalance. Here, we incorporated a small amount of methylammonium organic cation into the CsPbBr 3 lattice and by depositing a hydrophilic and insulating polyvinyl pyrrolidine polymer atop the ZnO electron-injection layer to overcome these issues. As a result, we obtained light-emitting diodes exhibiting a high brightness of 91,000 cd m −2 and a high external quantum efficiency of 10.4% using a mixed-cation perovskite Cs 0.87 MA 0.13 PbBr 3 as the emitting layer. To the best of our knowledge, this is the brightest and most-efficient green perovskite light-emitting diodes reported to date. Hybrid organic-inorganic perovskites are garnering attention for light emitting diode (LED) applications. Employing a thin hydrophilic insulating polymer, Zhang et al . report LEDs exhibiting a brightness of 91,000 cd m −2 and external quantum efficiency of 10.4% using a mixed-cation perovskite.

Universal control of multiple qubits—the ability to entangle qubits and to perform arbitrary individual qubit operations 1 —is a fundamental resource for quantum computing 2 , simulation 3 and networking 4 . Qubits realized in trapped atomic ions have shown the highest-fidelity two-qubit entangling operations 5 – 7 and single-qubit rotations 8 so far. Universal control of trapped ion qubits has been separately demonstrated using tightly focused laser beams 9 – 12 or by moving ions with respect to laser beams 13 – 15 , but at lower fidelities. Laser-free entangling methods 16 – 20 may offer improved scalability by harnessing microwave technology developed for wireless communications, but so far their performance has lagged the best reported laser-based approaches. Here we demonstrate high-fidelity laser-free universal control of two trapped-ion qubits by creating both symmetric and antisymmetric maximally entangled states with fidelities of 1 − 0.0017 + 0 and 0.9977 − 0.0013 + 0.0010 , respectively (68 per cent confidence level), corrected for initialization error. We use a scheme based on radiofrequency magnetic field gradients combined with microwave magnetic fields that is robust against multiple sources of decoherence and usable with essentially any trapped ion species. The scheme has the potential to perform simultaneous entangling operations on multiple pairs of ions in a large-scale trapped-ion quantum processor without increasing control signal power or complexity. Combining this technology with low-power laser light delivered via trap-integrated photonics 21 , 22 and trap-integrated photon detectors for qubit readout 23 , 24 provides an opportunity for scalable, high-fidelity, fully chip-integrated trapped-ion quantum computing. Laser-free universal control of two trapped-ion qubits using a combination of radiofrequency and microwave magnetic fields achieves some of the highest fidelities ever reported for two-qubit maximally entangled states.

Abstract BACKGROUND: Due to uncertain evidence, lumbar fusion for degenerative indications is associated with the greatest measured practice variation of any surgical procedure. OBJECTIVE: To summarize the current evidence on the comparative safety and efficacy of lumbar fusion, decompression-alone, or nonoperative care for degenerative indications. METHODS: A systematic review was conducted using PubMed, MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (up to June 30, 2016). Comparative studies reporting validated measures of safety or efficacy were included. Treatment effects were calculated through DerSimonian and Laird random effects models. RESULTS: The literature search yielded 65 studies (19 randomized controlled trials, 16 prospective cohort studies, 15 retrospective cohort studies, and 15 registries) enrolling a total of 302 620 patients. Disability, pain, and patient satisfaction following fusion, decompression-alone, or nonoperative care were dependent on surgical indications and study methodology. Relative to decompression-alone, the risk of reoperation following fusion was increased for spinal stenosis (relative risk [RR] 1.17, 95% confidence interval [CI] 1.06-1.28) and decreased for spondylolisthesis (RR 0.75, 95% CI 0.68-0.83). Among patients with spinal stenosis, complications were more frequent following fusion (RR 1.87, 95% CI 1.18-2.96). Mortality was not significantly associated with any treatment modality. CONCLUSION: Positive clinical change was greatest in patients undergoing fusion for spondylolisthesis while complications and the risk of reoperation limited the benefit of fusion for spinal stenosis. The relative safety and efficacy of fusion for chronic low back pain suggests careful patient selection is required (PROSPERO International Prospective Register of Systematic Reviews number, CRD42015020153).

Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessment and sharing platform for surgical performance and training. Here we present SmartForceps data app incorporating an Expert Room environment for tracking and analysing the objective performance and surgical finesse through multiple interfaces specific for surgeons and data scientists. The app is enriched by incoming geospatial information, data distribution for engineered features, performance dashboard compared to expert surgeon, and interactive skill prediction and task recognition tools to develop artificial intelligence models. The study launches the concept of democratizing surgical data through a connectivity interface between surgeons with a broad and deep capability of geographic reach through mobile devices with highly interactive infographics and tools for performance monitoring, comparison, and improvement.

Pancreatic and periampullary adenocarcinomas are associated with abnormal body composition visible on CT scans, including low muscle mass (sarcopenia) and low muscle radiodensity due to fat infiltration in muscle (myosteatosis). The biological and clinical correlates to these features are poorly understood. Clinical characteristics and outcomes were studied in 123 patients who underwent pancreaticoduodenectomy for pancreatic or non-pancreatic periampullary adenocarcinoma and who had available preoperative CT scans. In a subgroup of patients with pancreatic cancer (n = 29), rectus abdominus muscle mRNA expression was determined by cDNA microarray and in another subgroup (n = 29) 1H-NMR spectroscopy and gas chromatography-mass spectrometry were used to characterize the serum metabolome. Muscle mass and radiodensity were not significantly correlated. Distinct groups were identified: sarcopenia (40.7%), myosteatosis (25.2%), both (11.4%). Fat distribution differed in these groups; sarcopenia associated with lower subcutaneous adipose tissue (P<0.0001) and myosteatosis associated with greater visceral adipose tissue (P<0.0001). Sarcopenia, myosteatosis and their combined presence associated with shorter survival, Log Rank P = 0.005, P = 0.06, and P = 0.002, respectively. In muscle, transcriptomic analysis suggested increased inflammation and decreased growth in sarcopenia and disrupted oxidative phosphorylation and lipid accumulation in myosteatosis. In the circulating metabolome, metabolites consistent with muscle catabolism associated with sarcopenia. Metabolites consistent with disordered carbohydrate metabolism were identified in both sarcopenia and myosteatosis. Muscle phenotypes differ clinically and biologically. Because these muscle phenotypes are linked to poor survival, it will be imperative to delineate their pathophysiologic mechanisms, including whether they are driven by variable tumor biology or host response.

Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence provides surgeons with personalized and objective performance evaluation: a virtual surgical assist. Here we present machine learning models developed for analyzing surgical finesse using tool-tissue interaction force data in surgical dissection obtained from a sensorized bipolar forceps. Data modeling was performed using 50 neurosurgery procedures that involved elective surgical treatment for various intracranial pathologies. The data collection was conducted by 13 surgeons of varying experience levels using sensorized bipolar forceps, SmartForceps System. The machine learning algorithm constituted design and implementation for three primary purposes, i.e., force profile segmentation for obtaining active periods of tool utilization using T-U-Net, surgical skill classification into Expert and Novice , and surgical task recognition into two primary categories of Coagulation versus non-Coagulation using FTFIT deep learning architectures. The final report to surgeon was a dashboard containing recognized segments of force application categorized into skill and task classes along with performance metrics charts compared to expert level surgeons. Operating room data recording of > 161 h containing approximately 3.6 K periods of tool operation was utilized. The modeling resulted in Weighted F1-score = 0.95 and AUC = 0.99 for force profile segmentation using T-U-Net, Weighted F1-score = 0.71 and AUC = 0.81 for surgical skill classification, and Weighted F1-score = 0.82 and AUC = 0.89 for surgical task recognition using a subset of hand-crafted features augmented to FTFIT neural network. This study delivers a novel machine learning module in a cloud, enabling an end-to-end platform for intraoperative surgical performance monitoring and evaluation. Accessed through a secure application for professional connectivity, a paradigm for data-driven learning is established.

Chronic inflammatory diseases are frequently comorbid with depression and anxiety, often persisting during periods of inflammatory remission. This suggests functional changes to neural circuits involved in the contextual regulation of motivation and threat processing. Here, we test how chronic gut inflammation evoked by dextran sodium sulfate (DSS) affects gene expression in several limbic brain structures associated with these functions. We assessed post-mortem expression of mRNA transcripts in the anterior cingulate cortex (ACC), CA1 hippocampus, nucleus accumbens (NAc), and primary motor cortex (M1) as a non-limbic control. The levels of mRNA associated with mitochondrial function, inflammation, and synaptic connectivity were altered in DSS-treated animals, but the specific pattern of changes was heterogeneous among brain structures. Chronic gut inflammation affected transcript expression in the CA1 and NAc more so than in the ACC and M1. These differences involved genes related to antioxidant systems and mitochondrial function. For example, expression of the cytochrome oxidase 1 gene mt-co1, which is necessary for oxidative phosphorylation, was reduced in ACC and NAc of DSS animals, suggesting reduced capacity for ATP production in these regions. Markers of gut inflammation correlated with expression of several transcripts in the ACC, including markers of synapses and GABA synthesis. The NAc showed strong correlations of mitochondrial function and measures of mitochondrial fission, inflammation, synaptic connectivity, and GABA synthesis. In sum, the effects of chronic relapsing gut inflammation on mitochondrial and antioxidant transcriptional programs were heterogeneous across key limbic brain structures.