‘Forgotten Europeans’: transnational minority activism in the age of European integration

YesThis article examines transnational activism by coalitions of national minorities in Europe from the early 20th century to the present, setting this within the broader ‘security versus democracy dilemma’ that continues to surround international discussions on minority rights. Specifically, we analyse two organisations – the European Nationalities Congress (1925–1938) and the Federal Union of European Nationalities (1949–) – which, while linked, have never been subject to a detailed comparison based on primary sources. In so far as comparisons do exist, they present these bodies in highly negative terms, as mere fronts for inherently particularistic nationalisms that threaten political stability, state integrity and peace. Our more in‐depth analysis provides a fresh and more nuanced perspective: it shows that, in both cases, concepts of European integration and ‘unity in diversity’ have provided the motivating goals and frameworks for transnational movements advocating common rights for all minorities and seeking positive interaction with the interstate world

Correction to: Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium (<em>Journal of NeuroEngineering and Rehabilitation</em>, (2023), 20, 1, (78), 10.1186/s12984-023-01198-5)

\ua9 The Author(s) 2024.Following publication of the original article [1], the author noticed the errors in Table 1, and in Discussion section. In Table 1 under Metric (Gait sequence detection) column, the algorithms GSDB was updated with wrong description, input, output, language and citation and GSDc with wrong description has been corrected as shown below: (Table presented.) Description of algorithms for each metric: gait sequence detection (GSD), initial contact event detection (ICD), cadence estimation (CAD) and stride length estimation (SL) Metric Name Description Input Output Language References GSDA Based on a frequency-based approach, this algorithm is implemented on the vertical and anterior–posterior acceleration signals. First, these are band pass filtered to keep frequencies between 0.5 and 3 Hz. Next, a convolution of a 2 Hz sinewave (representing a template for a gait cycle) is performed, from which local maxima will be detected to define the regions of gait acc_v: vertical acceleration acc_ap: anterior–posterior acceleration WinS = 3 s; window size for convolution OL = 1.5 s; overlap of windows Activity_thresh = 0.01; Motion threshold Fs: sampling frequency Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Iluz, Gazit [40] GSDB This algorithm, based on a time domain-approach, detects the gait periods based on identified steps. First, the norm of triaxial acceleration signal is low-pass filtered (FIR, fc = 3.2 Hz), then a peak detection procedure using a threshold of 0.1 [g] is applied to identify steps. Consecutive steps, detected using an adaptive step duration threshold are associated to gait sequences acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.1 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] GSDc This algorithm utilizes the same approach as GSDBthe only difference being a different threshold for peak detection of 0.15 [g] acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.15 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] In Discussion section, the paragraph should read as "Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings. Moreover, the use of adaptive threshold, that are derived from the features of a subject’s data and applied to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns" instead of “Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings [41]. Moreover, the use of adaptive thresholds, that are derived from the features of a subject’s data and applied to the amplitude of acceleration norm and to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns”

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

IGF2 stimulates fetal growth in a sex- and organ-dependent manner

BackgroundInsulin-like growth factor 2 (IGF2) is a key determinant of fetal growth, and the altered expression of IGF2 is implicated in fetal growth disorders and maternal metabolic derangements including gestational diabetes. Here we studied how increased levels of IGF2 in late pregnancy affect fetal growth.MethodsWe employed a rat model of repeated intrafetal IGF2 administration in late pregnancy, i.e., during GD19-GD21, and measured the consequences on fetal organ weight and expression of insulin/IGF-axis components.ResultsIGF2 treatment tended to increase fetal weight, but only weight increase of the fetal stomach reached significance (+33±9%; P<0.01). Sex-dependent data analysis revealed a sexual dimorphism of IGF2 action. In male fetuses, IGF2 administration significantly increased fetal weight (+13±3%; P<0.05) and weight of fetal stomach (+42±10%; P<0.01), intestine (+26±5%; P<0.05), liver (+13±4%; P<0.05), and pancreas (+25±8%; P<0.05). Weights of heart, lungs, and kidneys were unchanged. In female fetuses, IGF2 increased only stomach weight (+26±9%; P<0.05). Furthermore, gene expression of insulin/IGF axis in the heart, lungs, liver, and stomach was more sensitive toward IGF2 treatment in male than in female fetuses.ConclusionData suggest that elevated circulating IGF2 in late pregnancy predominantly stimulates organ growth of the digestive system, and male fetuses are more susceptible toward the IGF2 effects than female fetuses.Fil: White, Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; ArgentinaFil: Jawerbaum, Alicia Sandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; ArgentinaFil: Mazzucco, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; ArgentinaFil: Gauster, Martin. Medizinische Universität Graz; AustriaFil: Desoye, Gernot. Medizinische Universität Graz; AustriaFil: Hiden, Ursula. Medizinische Universität Graz; Austri

Histopathological placental lesions in mild gestational hyperglycemic and diabetic women

Objective: To investigate and compare the incidence of histopathological placental lesions in mild gestational hyperglycemia, gestational diabetes and overt diabetes at term and preterm gestation.Research design and methods: One-hundred-and-thirty-one placental samples were collected from Diabetes mellitus (DM) positive screened patients. Two diagnostic tests, glycemic profile and 100 g oral glucose tolerance test (OGTT) in parallel identified 4 groups normoglycemic, mild gestational hyperglycemia (MGH), gestational DM (GDM) or overt DM (DM). Placental tissue specimens and sections from 4 groups were obtained by uniform random sampling and stained with hematoxylin-eosin.Results: Placentas from MGH group presented 17 types of histopathological change and higher rates of syncytial nodes and endarteritis. GDM placentas presented only nine types of histopathological change, high rates of dysmaturity, low rates of calcification and no syncytial nodes. Overt DM placentas showed 22 types of histopathological change, 21 of which were present in the preterm period. There were histopathological similarities between MGH and DM placentas, but the former exhibited a higher incidence of endarteritis, which has been described as a post-mortem phenomenon.Conclusion: Our results confirmed that the distinct placental changes associated with DM and MGH depend on gestational period during which the diabetic insult occurs. It may reasonably be inferred that subclinical maternal hyperglycemia during pregnancy, as showed in MGH group, is responsible for increased placental endarteritis, a postmortem lesion in the live fetus

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings. Methods: Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data. Results and discussion: The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of −0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, −0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases