Production and nutrient composition of forage legume fractions produced by juicing and leaf stripping

The large-scale import of soybean products into the EU decreases the self-sufficiency of livestock production. The fractionation of grassland forage crops presents an opportunity to locally produce protein-rich feed for monogastrics. Two promising fractionation methods, twin-screw press juicing and leaf stripping, were evaluated in parallel in field experiments established in Norway and Sweden to compare the nutrient composition and yield of the resulting biorefined and residual fractions. The clearest delineation between the methods was in the ash-free neutral detergent fibre (aNDFom) concentration, with juicing producing a biorefined fraction with a lower aNDFom than leaf stripping. Variability in the allocation of crude protein (CP) and biomass to the biorefined fractions occurred in both methods between cuts and locations and is likely due to differing stand characteristics and inconsistency in machine functionality. Additional work is needed to understand how characteristics such as stand density, botanical composition, and plant phenological stage impact each fractionation method's ability to allocate protein, fibre, and biomass into the resulting fractions. Future studies should focus particularly on determining standardised settings for leaf stripping machinery based on a range of stand characteristics to ensure consistency in the yield and nutrient composition of the resulting fractions

Using Orbitrap mass spectrometry to assess the isotopic compositions of individual compounds in mixtures

The isotopic compositions of individual chemical species are routinely used by the geochemical, environmental, forensic, anthropological, chemical, and biomedical communities to elucidate the conditions, sources, and reaction pathways of the molecules in question. Mass spectrometric methods of measuring isotopic compositions of individual compounds generally require that analytes be pure to yield precise, accurate results, yet most applications examine materials that are mixtures of multiple components. Various methods of chemical purification, e.g., chromatography, are used to isolate analytes from mixtures prior to mass spectrometric analysis. However, these techniques take time and specialized instrumentation, both of which could potentially be obviated via the use of ultra-high-resolution mass spectrometry. Here we report on the use of Orbitrap™-based Fourier-transform mass spectrometry to perform isotope ratio measurements of single species within mixtures delivered to the mass spectrometer (MS) without prior chromatographic separation. We demonstrate that instrument biases (attributed here to space charge effects) within the Orbitrap mass analyzer can cause the measured ¹³C/¹²C ratio of a molecular ion in the presence of non-analyte-derived ‘contaminating’ species to spuriously decrease relative to the ¹³C/¹²C ratio measured for the same ion in a pure analyte. We observe that the decrease in ¹³C/¹²C is proportional to the relative concentrations of the additional ‘contaminating’ components. We then recommend several strategies by which this effect can be mediated such that accurate isotope ratios can be obtained

Using Orbitrap mass spectrometry to assess the isotopic compositions of individual compounds in mixtures

The isotopic compositions of individual chemical species are routinely used by the geochemical, environmental, forensic, anthropological, chemical, and biomedical communities to elucidate the conditions, sources, and reaction pathways of the molecules in question. Mass spectrometric methods of measuring isotopic compositions of individual compounds generally require that analytes be pure to yield precise, accurate results, yet most applications examine materials that are mixtures of multiple components. Various methods of chemical purification, e.g., chromatography, are used to isolate analytes from mixtures prior to mass spectrometric analysis. However, these techniques take time and specialized instrumentation, both of which could potentially be obviated via the use of ultra-high-resolution mass spectrometry. Here we report on the use of Orbitrap™-based Fourier-transform mass spectrometry to perform isotope ratio measurements of single species within mixtures delivered to the mass spectrometer (MS) without prior chromatographic separation. We demonstrate that instrument biases (attributed here to space charge effects) within the Orbitrap mass analyzer can cause the measured ¹³C/¹²C ratio of a molecular ion in the presence of non-analyte-derived ‘contaminating’ species to spuriously decrease relative to the ¹³C/¹²C ratio measured for the same ion in a pure analyte. We observe that the decrease in ¹³C/¹²C is proportional to the relative concentrations of the additional ‘contaminating’ components. We then recommend several strategies by which this effect can be mediated such that accurate isotope ratios can be obtained

Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)

Most clinical specialties have a plethora of studies that develop or validate one or more prediction models, for example, to inform diagnosis or prognosis. Having many prediction model studies in a particular clinical field motivates the need for systematic reviews and meta-analyses, to evaluate and summarise the overall evidence available from prediction model studies, in particular about the predictive performance of existing models. Such reviews are fast emerging, and should be reported completely, transparently, and accurately. To help ensure this type of reporting, this article describes a new reporting guideline for systematic reviews and meta-analyses of prediction model research

Postvaccination anti-S IgG levels predict anti-SARS-CoV-2 neutralising activity over 24 weeks in patients with RA

OBJECTIVES To correlate immune responses following a two-dose regimen of mRNA anti-SARS-CoV-2 vaccines in patients with rheumatoid arthritis (RA) to the development of a potent neutralising antiviral activity. METHODS The RECOVER study was a prospective, monocentric study including patients with RA and healthy controls (HCs). Assessments were performed before, and 3, 6, 12 and 24 weeks, after the first vaccine dose, respectively, and included IgG, IgA and IgM responses (against receptor binding domain, S1, S2, N), IFN-γ ELISpots as well as neutralisation assays. RESULTS In patients with RA, IgG responses developed slower with lower peak titres compared with HC. Potent neutralising activity assessed by a SARS-CoV-2 pseudovirus neutralisation assay after 12 weeks was observed in all 21 HCs, and in 60.3% of 73 patients with RA. A significant correlation between peak anti-S IgG levels 2 weeks after the second vaccine dose and potent neutralising activity against SARS-CoV-2 was observed at weeks 12 and 24. The analysis of IgG, IgA and IgM isotype responses to different viral proteins demonstrated a delay in IgG but not in IgA and IgM responses. T cell responses were comparable in HC and patients with RA but declined earlier in patients with RA. CONCLUSION In patients with RA, vaccine-induced IgG antibody levels were diminished, while IgA and IgM responses persisted, indicating a delayed isotype switch. Anti-S IgG levels 2 weeks after the second vaccine dose correlate with the development of a potent neutralising activity after 12 and 24 weeks and may allow to identify patients who might benefit from additional vaccine doses or prophylactic regimen

ICON 2019: International Scientific Tendinopathy Symposium Consensus: Clinical Terminology

© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.Background Persistent tendon pain that impairs function has inconsistent medical terms that can influence choice of treatment.1 When a person is told they have tendinopathy by clinician A or tendinitis by clinician B, they might feel confused or be alarmed at receiving what they might perceive as two different diagnoses. This may lead to loss of confidence in their health professional and likely adds to uncertainty if they were to search for information about their condition. Clear and uniform terminology also assists inter-professional communication. Inconsistency in terminology for painful tendon disorders is a problem at numerous anatomical sites. Historically, the term ‘tendinitis’ was first used to describe tendon pain, thickening and impaired function (online supplementary figure S1). The term ‘tendinosis’ has also been used in a small number of publications, some of which were very influential.2 3 Subsequently, ‘tendinopathy’ emerged as the most common term for persistent tendon pain.4 5 To our knowledge, experts (clinicians and researchers) or patients have never engaged in a formal process to discuss the terminology we use. We believe that health professionals have not yet agreed on the appropriate terminology for painful tendon conditions.Peer reviewedFinal Accepted Versio

Dorsal Periaqueductal gray ensembles represent approach and avoidance states

Animals must balance needs to approach threats for risk assessment and to avoid danger. The dorsal periaqueductal gray (dPAG) controls defensive behaviors, but it is unknown how it represents states associated with threat approach and avoidance. We identified a dPAG threatavoidance ensemble in mice that showed higher activity farther from threats such as the open arms of the elevated plus maze and a predator. These cells were also more active during threat avoidance behaviors such as escape and freezing, even though these behaviors have antagonistic motor output. Conversely, the threat approach ensemble was more active during risk assessment behaviors and near threats. Furthermore, unsupervised methods showed that avoidance/approach states were encoded with shared activity patterns across threats. Lastly, the relative number of cells in each ensemble predicted threat avoidance across mice. Thus, dPAG ensembles dynamically encode threat approach and avoidance states, providing a flexible mechanism to balance risk assessment and danger avoidance

Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed

Objectives: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement. Study Design and Setting: We searched PubMed (January 2018–May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs. Results: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD. Conclusion: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this

Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models:a review shows improvements are needed

OBJECTIVES: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement.STUDY DESIGN AND SETTING: We searched PubMed (January 2018-May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs.RESULTS: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD.CONCLUSION: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this.</p

Is it possible to assess the effects of dynamic arm supports on upper extremity range of motion during activities of daily living in the domestic setting using a portable motion capturing device? - A pilot study

BACKGROUND: Understanding how dynamic arm supports affect the ability to perform activities of daily living (ADL) in daily life situations is essential for improved prescription. OBJECTIVE: To determine whether the newly developed MMAAS is a useful tool to assess the RoM at home. Secondly, to investigate differences in RoM and ADL performance with and without dynamic arm support. METHODS: Five dynamic arm support users performed nine activities with and without dynamic arm support at home. A reference group of five participants was included. Shoulder and elbow RoM were assessed for the three most difficult tasks. RESULTS: The measurement of the elbow joint RoM appeared unreliable. In most participants shoulder RoM increased with dynamic arm support, but the magnitude of change differed. Variation was also found regarding whether people could perform ADL with and without support. CONCLUSIONS: In its current state the MMAAS is not regarded a useful tool for assessing the RoM in the domestic setting. The ability to perform ADL and RoM seem influenced by the environment, users' needs and abilities. Future studies investigating effects and benefits of dynamic arm supports should be conducted in a broader daily life context