Detecting and correcting partial errors: Evidence for efficient control without conscious access

Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed

Send more data: a systematic review of mathematical models of antimicrobial resistance

Abstract Background Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed. Objective The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models. Methods The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines. Results None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation. Conclusion Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Rapid, Plateau-like Increases in Intracellular Free Calcium Are Associated with Nod-Factor—Induced Root-Hair Deformation

Rhizobia excrete variously substituted lipo-oligosaccharide Nod factors into the legume rhizosphere. Homologous legumes respond to these signals through deformation of the root hairs and the development of nodulation foci in the root cortex. Cellular events in root hairs from the susceptible zone of nearly mature root hairs were studied in root segments loaded with the calcium indicators Fura-2 or Fluo-3. Application of 10⁻⁹ M Nod factors of the broad-host-range Rhizobium sp. NGR234 to the homologous legume Vigna unguiculata resulted, within seconds, in plateau-like increases in intracellular free calcium ([Ca²⁺]i) in the root hairs and root epidermal cells. Nod factors of R. meliloti at 10⁻⁹ M caused equally rapid increases in [Ca²⁺]i in the root hairs and epidermal cells of the nonhost V. unguiculata, and also induced root-hair deformation. The chitin tetramer, N-N′-N″-N′″-tetracetylchitotetraose, which represents the backbone of Nod factors, induced neither root-hair deformation nor changes in [Ca²⁺]i in V. unguiculata. Root hairs and epidermal cells of the nonlegume non-host Arabidopsis thaliana showed neither [Ca²⁺]i increases nor root-hair deformation in response to both factors

MycoDB, a Global Database of Plant Response to Mycorrhizal Fungi

Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems

MycoDB, a global database of plant response to mycorrhizal fungi

Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems