Linear-time list recovery of high-rate expander codes

We show that expander codes, when properly instantiated, are high-rate list recoverable codes with linear-time list recovery algorithms. List recoverable codes have been useful recently in constructing efficiently list-decodable codes, as well as explicit constructions of matrices for compressive sensing and group testing. Previous list recoverable codes with linear-time decoding algorithms have all had rate at most 1/2; in contrast, our codes can have rate $1 - \epsilon$ for any $\epsilon > 0$. We can plug our high-rate codes into a construction of Meir (2014) to obtain linear-time list recoverable codes of arbitrary rates, which approach the optimal trade-off between the number of non-trivial lists provided and the rate of the code. While list-recovery is interesting on its own, our primary motivation is applications to list-decoding. A slight strengthening of our result would implies linear-time and optimally list-decodable codes for all rates, and our work is a step in the direction of solving this important problem

Elevated CO₂ does not increase eucalypt forest productivity on a low-phosphorus soil

Rising atmospheric CO2 stimulates photosynthesis and productivity of forests, offsetting CO2 emissions. Elevated CO2 experiments in temperate planted forests yielded ~23% increases in productivity over the initial years. Whether similar CO2 stimulation occurs in mature evergreen broadleaved forests on low-phosphorus (P) soils is unknown, largely due to lack of experimental evidence. This knowledge gap creates major uncertainties in future climate projections as a large part of the tropics is P-limited. Here,we increased atmospheric CO2 concentration in a mature broadleaved evergreen eucalypt forest for three years, in the first large-scale experiment on a P-limited site. We show that tree growth and other aboveground productivity components did not significantly increase in response to elevated CO2 in three years, despite a sustained 19% increase in leaf photosynthesis. Moreover, tree growth in ambient CO2 was strongly P-limited and increased by ~35% with added phosphorus. The findings suggest that P availability may potentially constrain CO2-enhanced productivity in P-limited forests; hence, future atmospheric CO2 trajectories may be higher than predicted by some models. As a result, coupled climate-carbon models should incorporate both nitrogen and phosphorus limitations to vegetation productivity in estimating future carbon sinks

Exclusive neuronal expression of SUCLA2 in the human brain

SUCLA2 encodes the ATP-forming subunit (A-SUCL-) of succinyl-CoA ligase, an enzyme of the citric acid cycle. Mutations in SUCLA2 lead to a mitochondrial disorder manifesting as encephalomyopathy with dystonia, deafness and lesions in the basal ganglia. Despite the distinct brain pathology associated with SUCLA2 mutations, the precise localization of SUCLA2 protein has never been investigated. Here we show that immunoreactivity of A-SUCL- in surgical human cortical tissue samples was present exclusively in neurons, identified by their morphology and visualized by double labeling with a fluorescent Nissl dye. A-SUCL- immunoreactivity co-localized >99% with that of the d subunit of the mitochondrial F0-F1 ATP synthase. Specificity of the anti-A-SUCL- antiserum was verified by the absence of labeling in fibroblasts from a patient with a complete deletion of SUCLA2. A-SUCL- immunoreactivity was absent in glial cells, identified by antibodies directed against the glial markers GFAP and S100. Furthermore, in situ hybridization histochemistry demonstrated that SUCLA2 mRNA was present in Nissl-labeled neurons but not glial cells labeled with S100. Immunoreactivity of the GTP-forming subunit (G-SUCL-) encoded by SUCLG2, or in situ hybridization histochemistry for SUCLG2 mRNA could not be demonstrated in either neurons or astrocytes. Western blotting of post mortem brain samples revealed minor G-SUCL- immunoreactivity that was however, not upregulated in samples obtained from diabetic versus non-diabetic patients, as has been described for murine brain. Our work establishes that SUCLA2 is expressed exclusively in neurons in the human cerebral cortex

Genetic Background Can Result in a Marked or Minimal Effect of Gene Knockout (GPR55 and CB2 Receptor) in Experimental Autoimmune Encephalomyelitis Models of Multiple Sclerosis

PMCID: PMC379391

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

In silico modelling to differentiate the contribution of sugar frequency versus total amount in driving biofilm dysbiosis in dental caries

Dental caries is the most prevalent infection globally and a substantial economic burden in developed countries. Dietary sugars are the main risk factor, and drive increased proportions of acid-producing and acid-tolerating (aciduric) bacterial species within dental bio lms. Recent longitudinal studies have suggested that caries is most strongly correlated with total sugar intake, contrasting with the prevailing view that intake frequency is the primary determinant. To explore this possibility, we employed a computational model for supragingival plaque to systematically sample combinations of sugar frequency and total amount, allowing their independent contributions on the ratio of aciduric (i.e. cariogenic) to non-aciduric bacteria to be unambiguously determined. Sugar frequency was found to be irrelevant for either very high or very low daily total amounts as the simulated bio lm was predicted to be always or never cariogenic, respectively. Frequency was a determining factor for intermediate total amounts of sugar, including the estimated average human consumption. An increased risk of caries (i.e. high prevalence of aciduric/non-aciduric species) was predicted for high intake frequencies. Thus, both total amount and frequency of sugar intake may combine to in uence plaque cariogenicity. These ndings could be employed to support public guidance for dietary change, leading to improved oral healthcare

Tracking of fatness during childhood, adolescence and young adulthood: a 7-year follow-up study in Madeira Island, Portugal

Aims: Investigating tracking of fatness from childhood to adolescence, early adolescence to young adulthood and late adolescence to young adulthood. Subjects and methods: Participants from the Madeira Growth Study were followed during an average period of 7.2 years. Height, body mass, skin-folds and circumferences were measured, nine health- and performance-related tests were administered and the Baecke questionnaire was used to assess physical activity. Skeletal maturity was estimated using the TW3 method. Results: The prevalence of overweight plus obesity ranged from 8.2–20.0% at baseline and from 20.4–40.0% at followup, in boys. Corresponding percentages for girls were 10.6– 12.0% and 13.2–18.0%. Inter-age correlations for fatness indicators ranged from 0.43–0.77. BMI, waist circumference and sum of skin-folds at 8, 12 and 16-years old were the main predictors of these variables at 15, 19 and 23-years old, respectively. Strength, muscular endurance and aerobic fitness were negatively related to body fatness. Physical activity and maturation were independently associated with adolescent (15 years) and young adult (19 years) fatness. Conclusions: Over 7.2 years, tracking was moderate-to-high for fatness. Variance was explained by fatness indicators and to a small extent by physical fitness, physical activity and maturation

Genetic and neurological foundations of customer orientation: field and experimental evidence

We explore genetic and neurological bases for customer orientation (CO) and contrast them with sales orientation (SO). Study 1 is a field study that establishes that CO, but not SO, leads to greater opportunity recognition. Study 2 examines genetic bases for CO and finds that salespeople with CO are more likely to have the 7R variant of the DRD4 gene. This is consistent with basic research on dopamine receptor activity in the brain that underlies novelty seeking, the reward function, and risk taking. Study 3 examines the neural basis of CO and finds that salespeople with CO, but not SO, experience greater activation of their mirror neuron systems and neural processes associated with empathy. Managerial and research implications are discussed

Dynamic updating of clinical survival prediction models in a changing environment

Background Over time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. In this study, we investigate dynamic model updating of clinical survival prediction models. In contrast to discrete or one-time updating, dynamic updating refers to a repeated process for updating a prediction model with new data. We aim to extend previous research which focused largely on binary outcome prediction models by concentrating on time-to-event outcomes. We were motivated by the rapidly changing environment seen during the COVID-19 pandemic where mortality rates changed over time and new treatments and vaccines were introduced. Methods We illustrate three methods for dynamic model updating: Bayesian dynamic updating, recalibration, and full refitting. We use a simulation study to compare performance in a range of scenarios including changing mortality rates, predictors with low prevalence and the introduction of a new treatment. Next, the updating strategies were applied to a model for predicting 70-day COVID-19-related mortality using patient data from QResearch, an electronic health records database from general practices in the UK. Results In simulated scenarios with mortality rates changing over time, all updating methods resulted in better calibration than not updating. Moreover, dynamic updating outperformed ad hoc updating. In the simulation scenario with a new predictor and a small updating dataset, Bayesian updating improved the C-index over not updating and refitting. In the motivating example with a rare outcome, no single updating method offered the best performance. Conclusions We found that a dynamic updating process outperformed one-time discrete updating in the simulations. Bayesian updating offered good performance overall, even in scenarios with new predictors and few events. Intercept recalibration was effective in scenarios with smaller sample size and changing baseline hazard. Refitting performance depended on sample size and produced abrupt changes in hazard ratio estimates between periods