Antibiotic resistance in the wild: an eco-evolutionary perspective

The legacy of the use and misuse of antibiotics in recent decades has left us with a global public health crisis: antibiotic-resistant bacteria are on the rise, making it harder to treat infections. At the same time, evolution of antibiotic resistance is probably the best-documented case of contemporary evolution. To date, research on antibiotic resistance has largely ignored the complexity of interactions that bacteria engage in. However, in natural populations, bacteria interact with other species; for example, competition and grazing are import interactions influencing bacterial population dynamics. Furthermore, antibiotic leakage to natural environments can radically alter bacterial communities. Overall, we argue that eco-evolutionary feedback loops in microbial communities can be modified by residual antibiotics and evolution of antibiotic resistance. The aim of this review is to connect some of the well-established key concepts in evolutionary biology and recent advances in the study of eco-evolutionary dynamics to research on antibiotic resistance. We also identify some key knowledge gaps related to eco-evolutionary dynamics of antibiotic resistance, and review some of the recent technical advantages in molecular microbiology that offer new opportunities for tackling these questions. Finally, we argue that using the full potential of evolutionary theory and active communication across the different fields is needed for solving this global crisis more efficiently. This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'.Peer reviewe

Method for constructing an AOD-related atmospheric correction time series for the CLARA-A2 SAL data record

In the Satellite Application Facility on Climate Monitoring (CM SAF) project, financially supported by EUMETSAT, the 34-year long (1982-2015) broadband albedo time series CLARA-A2 SAL (the Surface ALbedo from the CM SAF cLoud, Albedo and RAdiation data record, second version) was produced from Advanced Very High Resolution Radiometer (AVHRR) measurements. CLARA-A2 SAL data record uses a Simplified Method for Atmospheric Correction algorithm SMAC for correcting for atmospheric effects. Aerosol optical depth (AOD) is the main input of the algorithm. Because there were no global AOD time series for the whole needed time period (1982-2015), the AOD-related time series were constructed, and the method for calculating it is described in this report

A longitudinal follow-up study of a type 2 diabetes “lost to follow-up” cohort–positive effect on glycaemic control after changes in medication

The aim of this study was to evaluate whether patients with type 2 diabetes (T2D) who had stopped attending their diabetes treatment system (referred to as “lost to follow-up”, LTF) but who succeeded in improving their glycaemic control after returning to the diabetes treatment system had changes in their diabetes medication when compared with similar patients who did not show improvement. “LTFs” who had baseline haemoglobin A1 c (HbA1 c) ≥53 mmol/mol and succeeded in reducing HbA1 c ≥ 6 mmol/mol during a 12–30 month follow-up period after adhering again to their diabetes treatment system were compared with “LTFs” who had an unsatisfactory change in HbA1 c or with “LTFs” who maintained good glycaemic control throughout the 12–30 month follow-up period. Unsatisfactory change in HbA1 c was determined as HbA1 c ≥ 53 mmol/mol and change <6 mmol/mol after the 12–30 month follow-up period in their diabetes treatment system or HbA1 c < 53 mmol/mol when returning to the diabetes treatment system but ≥53 mmol/mol at the end of the 12–30 month follow-up period. “LTFs” with improvement in glycaemic control used a higher number of different anti-hyperglycaemic agents (P < 0.001) and their dosages of metformin increased (P < 0.05) when compared with “LTFs” without improvement or “LTFs” with satisfactory glycaemic control. Cholesterol-, LDL-cholesterol- and triglyceride-concentrations decreased during the 12–30 month follow-up period (P < 0.05) in “LTFs” with improved glycaemic control, but not in the other groups. “LTFs” with T2D who had poor glycaemic control seemed to require an increase in their anti-diabetic medication when attempting to improve their glycaemic control. © 2020, © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Peer reviewe

Filter Likelihood as an Observation-Based Verification Metric in Ensemble Forecasting

In numerical weather prediction (NWP), ensemble forecasting aims to quantify the flow-dependent forecast uncertainty. The focus here is on observation-based verification of the reliability of ensemble forecasting systems. In particular, at short forecast lead times, forecast errors tend to be relatively small compared to observation errors and hence it is very important that the verification metric also accounts for observational uncertainties. This paper studies the so-called filter likelihood score which is deep-rooted in Bayesian estimation theory and fits naturally to the filtering setup of NWP. The filter likelihood score considers observation errors, ensemble mean skill, and ensemble spread in one metric. Importantly, it can be made multivariate and effortlessly expanded to simultaneous verification against all observation types through the observation operators contained in the parental data assimilation scheme. Here observations from the global radiosonde network and satellites (AMSU-A channel 5) are included in the verification of OpenIFS-based ensemble forecasts using different types of initial state perturbations. Our results show that the filter likelihood score is sensitive to the ensemble prediction system quality and compares consistently with other verification metrics such as the relationships between ensemble spread and ensemble mean forecast error, and Dawid-Sebastiani score. Our conclusion is that the filter likelihood score provides a very well-behaving verification metric, that can be made truly multivariate by including covariances, for ensemble prediction systems with a strong foundation in estimation theory.Peer reviewe

Relationship between number of contacts between previous dropouts with type 2 diabetes and health care professionals on glycaemic control : A cohort study in public primary health care

Aim: Previous study findings have shown that more frequent contacts with the diabetes care team predict better diabetes control. It is unknown whether this is true also for previous dropouts with type 2 diabetes (T2D). The aim of this study was to evaluate if those previous dropouts with T2D who succeeded to improve their glycaemic control had more frequent contacts with health care professionals in the public primary diabetes health care system than those dropouts who did not show improvement. Methods: In this "real life" retrospective cohort study, we identified 115 dropouts with T2D who were contacted by trained diabetes nurses and who returned to a public T2D-care system. Those previous dropouts who had baseline haemoglobin A(1c) >= 53 mmoVmol (7%) and had a reduction in HbA(1c) >= 6 mmol/mol (0.5%) during the follow-up were compared with those with unsatisfactory change in HbA(1c) (baseline HbA(1c) >= 53 mmoVmol and change Results: Previous dropouts showing improvement had more visits to the diabetes nurse (p = 0.003) and other nurses (p <0.001) than those with no improvement or those with satisfactory glycaemic control. Telephone calls not focusing on diabetes (p <0.001) were also more frequent among previous dropouts with improvement than among the others. Conclusions: Especially previous dropouts with T2D who had poor glycaemic control, may benefit from more frequent contacts including visits and telephone calls. Recalling dropouts does not seem to lead to overuse of the T2D care-system by those recalled patients whose glycaemic control does not require special care. (C) 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.Peer reviewe

Asiakkaiden toimintakyky, työn organisointi ja henkilöstön hyvinvointi vanhusten pitkäaikaisessa laitoshoidossa

HoiToVa-hankkeen osaraportti, toteutettu Työsuojelurahaston ja Suomen Akatemian rahoituksell

The influence of electronic reminders on recording diagnoses in a primary health care emergency department : a register-based study in a Finnish town

Objective This study examines whether implementation of electronic reminders is associated with a change in the amount and content of diagnostic data recorded in primary health care emergency departments (ED). Design A register-based 12-year follow-up study with a before-and-after design. Setting This study was performed in a primary health care ED in Finland. An electronic reminder was installed in the health record system to remind physicians to include the diagnosis code of the visit to the health record. Subjects and main outcome measures The report generator of the electronic health record-system provided monthly figures for the number of different recorded diagnoses by using the International Classification of Diagnoses (ICD-10th edition) and the total number of ED physician visits, thus allowing the calculation of the recording rate of diagnoses on a monthly basis and the comparison of diagnoses before and after implementing electronic reminders. Results The most commonly recorded diagnoses in the ED were acute upper respiratory infections of various and unspecified sites (5.8%), abdominal and pelvic pain (4.8%), suppurative and unspecified otitis media (4.5%) and dorsalgia (4.0%). The diagnosis recording rate in the ED doubled from 41.2 to 86.3% (p < 0.001) after the application of electronic reminders. The intervention especially enhanced the recording rate of symptomatic diagnoses (ICD-10 group-R) and alcohol abuse-related diagnoses (ICD-10 code F10). Mental and behavioural disorders (group F) and injuries (groups S-Y) were also better recorded after this intervention. Conclusion Electronic reminders may alter the documentation habits of physicians and recording of clinical data, such as diagnoses, in the EDs. This may be of use when planning resource managing in EDs and planning their actions.Peer reviewe

Circulating Fluidized Bed Combustion-Build-Up and Validation of a Three-Dimensional Model

This paper presents the validated simulation of a full-scale circulating fluidized bed boiler as obtained via a comprehensive three-dimensional CFB process model. The model is utilized in boiler design and scale-up as well as to study and optimize boiler performance. Feedstock characterization tests, which are also presented, are used to provide data for those parts of the process where up-to-date modeling is not fully reliable, thus enabling the model to provide accurate results