ISCEV standard for clinical multifocal electroretinography (mfERG) (2021 update)

The multifocal electroretinogram (mfERG) is an electrophysiological test that allows the function of multiple discrete areas of the retina to be tested simultaneously. This document, from the International Society for Clinical Electrophysiology of Vision (ISCEV), presents an updated and revised ISCEV standard for clinical mfERG and defines minimum protocols for basic clinical mfERG recording and reporting so that responses can be recognized and compared from different laboratories worldwide. The major changes compared with the previous mfERG standard relate to the minimum length of m-sequences used for recording, reporting of results and a change in document format, to be more consistent with other ISCEV standards

Simultaneous whole-animal 3D-imaging of neuronal activity using light field microscopy

3D functional imaging of neuronal activity in entire organisms at single cell level and physiologically relevant time scales faces major obstacles due to trade-offs between the size of the imaged volumes, and spatial and temporal resolution. Here, using light-field microscopy in combination with 3D deconvolution, we demonstrate intrinsically simultaneous volumetric functional imaging of neuronal population activity at single neuron resolution for an entire organism, the nematode Caenorhabditis elegans. The simplicity of our technique and possibility of the integration into epi-fluoresence microscopes makes it an attractive tool for high-speed volumetric calcium imaging.Comment: 25 pages, 7 figures, incl. supplementary informatio

High effectiveness of self-help programs after drug addiction therapy

BACKGROUND: The self-help groups Alcoholics Anonymous (AA) and Narcotics Anonymous (NA) are very well established. AA and NA employ a 12-step program and are found in most large cities around the world. Although many have argued that these organizations are valuable, substantial scepticism remains as to whether they are actually effective. Few treatment facilities give clear recommendations to facilitate participation, and the use of these groups has been disputed. The purpose of this study was to examine whether the use of self-help groups after addiction treatment is associated with higher rates of abstinence. METHODS: One hundred and fourteen patients, 59 with alcohol dependency and 55 with multiple drug dependency, who started in self-help groups after addiction treatment, were examined two years later using a questionnaire. Return rate was 66%. Six (5%) of the patients were dead. RESULTS: Intention-to-treat-analysis showed that 38% still participated in self-help programs two years after treatment. Among the regular participants, 81% had been abstinent over the previous 6 months, compared with only 26% of the non-participants. Logistic regression analysis showed OR = 12.6, 95% CI (4.1–38.3), p < 0.001, for participation and abstinence. CONCLUSION: The study has several methodological problems; in particular, correlation does not necessarily indicate causality. These problems are discussed and we conclude that the probability of a positive effect is sufficient to recommend participation in self-help groups as a supplement to drug addiction treatment. PREVIOUS PUBLICATION: This article is based on a study originally published in Norwegian: Kristensen O, Vederhus JK: Self-help programs in drug addiction therapy. Tidsskr Nor Laegeforen 2005, 125:2798–2801

The Reform of Employee Compensation in China’s Industrial Enterprises

Although employee compensation reform in Chinese industrial sector has been discussed in the literature, the real changes in compensation system and pay practices have received insufficient attention and warrant further examination. This paper briefly reviews the pre- and post-reform compensation system, and reports the results of a survey of pay practices in the four major types of industrial enterprises in China. The research findings indicate that the type of enterprise ownership has little influence on general compensation practices, adoption of profit-sharing plans, and subsidy and allowance packages. In general, pay is linked more to individual performance and has become an important incentive to Chinese employees. However, differences are found across the enterprise types with regard to performance-related pay. Current pay practices are positively correlated to overall effectiveness of the enterprise

Long-range transfer of electron-phonon coupling in oxide superlattices

The electron-phonon interaction is of central importance for the electrical and thermal properties of solids, and its influence on superconductivity, colossal magnetoresistance, and other many-body phenomena in correlated-electron materials is currently the subject of intense research. However, the non-local nature of the interactions between valence electrons and lattice ions, often compounded by a plethora of vibrational modes, present formidable challenges for attempts to experimentally control and theoretically describe the physical properties of complex materials. Here we report a Raman scattering study of the lattice dynamics in superlattices of the high-temperature superconductor $\bf YBa_2 Cu_3 O_7$ and the colossal-magnetoresistance compound $\bf La_{2/3}Ca_{1/3}MnO_{3}$ that suggests a new approach to this problem. We find that a rotational mode of the MnO$_6$ octahedra in $\bf La_{2/3}Ca_{1/3}MnO_{3}$ experiences pronounced superconductivity-induced lineshape anomalies, which scale linearly with the thickness of the $\bf YBa_2 Cu_3 O_7$ layers over a remarkably long range of several tens of nanometers. The transfer of the electron-phonon coupling between superlattice layers can be understood as a consequence of long-range Coulomb forces in conjunction with an orbital reconstruction at the interface. The superlattice geometry thus provides new opportunities for controlled modification of the electron-phonon interaction in complex materials.Comment: 13 pages, 4 figures. Revised version to be published in Nature Material

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Shifting Global Invasive Potential of European Plants with Climate Change

Global climate change and invasions by nonnative species rank among the top concerns for agents of biological loss in coming decades. Although each of these themes has seen considerable attention in the modeling and forecasting communities, their joint effects remain little explored and poorly understood. We developed ecological niche models for 1804 species from the European flora, which we projected globally to identify areas of potential distribution, both at present and across 4 scenarios of future (2055) climates. As expected from previous studies, projections based on the CGCM1 climate model were more extreme than those based on the HadCM3 model, and projections based on the a2 emissions scenario were more extreme than those based on the b2 emissions scenario. However, less expected were the highly nonlinear and contrasting projected changes in distributional areas among continents: increases in distributional potential in Europe often corresponded with decreases on other continents, and species seeing expanding potential on one continent often saw contracting potential on others. In conclusion, global climate change will have complex effects on invasive potential of plant species. The shifts and changes identified in this study suggest strongly that biological communities will see dramatic reorganizations in coming decades owing to shifting invasive potential by nonnative species

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure