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Direct information on space climate – the background on which space weather manifests – is limited to the space era, that began only in 1964. Before that date the only information on the solar – terrestrial relationship could be retrieved from the geomagnetic field variations recorded at geomagnetic observatories, thus extending back with ~150 years the information on the space climate, based on geomagnetic indices. Reconstructions of certain parameters of the solar activity to 1700, based on physical models and correlations, which we show here, present, besides the well-known decadal variation, related to solar cycles in the solar activity, variations at time scales of the Hale, magnetic and Gleissberg, ‘long’ solar cycles. We find that variations at inter-decadal (20-30 years) and sub-centennial (60-90 years) time scales are present in both geomagnetic observatories data and in some long-term models of the main geomagnetic field, such as gufm1 (Jackson et al., 2000). Based on such data the evolution of the space climate is discussed for the entire time interval of the validity of the model gufm1 (1590-1960)., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

We analyze the Earth’s surface temperature recorded at available 7 european meteorological stations with 300 years-long activity. We detect variations at several time scales, present in these recordings, namely decadal, inter-decadal (20-30 years), and sub-centennial (60-90 years). These are corelatable with the solar activity variations at the same time scales, indicating a source - effects relationship between the solar input and the air surface temperatures. First, the decadal variations, of amplitudes of ~1° C, are separated from a trend by a Hodrick and Prescott (1997) type analysis, then the inter-decadal and the sub-centennial variations (of several tenths and, respectively, ~1° C amplitude) are separated from the trend by Butterworth (1930) filtering. The analysis is coroborated with similar ones applied to (1) the Danube river discharge as an integrator of temperature and precipitation in the Central Europe and (2) to solar activity monitored or reconstructed parameters., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

BackgroundThe overdose crisis has generated innovative harm reduction and drug market monitoring strategies. In Toronto, Ontario, Canada, a multi-site drug checking service (DCS) pilot project was launched in October 2019. The project provides people who use drugs with information on the chemical composition of their substances, thereby increasing their capacity to make more informed decisions about their drug use and avoid overdose. DCS also provides real-time market monitoring to identify trends in the unregulated drug supply.MethodsSample data were obtained through analyses of drug and used drug administration equipment samples submitted anonymously and free of charge to DCS in downtown Toronto from October 10, 2019, to April 9, 2020, representing the first six months of DCS implementation. Analyses were conducted in clinical laboratories using liquid chromatography- and/or gas chromatography-mass spectrometry (LC-MS, GC-MS) techniques.ResultsOverall, 555 samples were submitted, with 49% (271) of samples that were found to contain high-potency opioids, of which 87% (235) also contained stimulants. Benzodiazepine-type drugs were found in 21% (116) of all samples, and synthetic cannabinoids in 1% (7) of all samples. Negative effects (including overdose, adverse health events, and extreme sedation) were reported for 11% (59) of samples submitted for analysis.ConclusionsToronto's DCS identified a range of high-potency opioids with stimulants, benzodiazepine-type drugs, and a synthetic cannabinoid, AMB-FUBINACA. This information can inform a range of evidence-informed overdose prevention efforts.

The geomagnetic field has been highly studied starting from the first measurements and scientific papers to the present monitoring with the help of satellites. Various methods are used in order to study the characteristics of the geomagnetic field, namely fast Fourier transform (Currie, 1973; Langel et al., 1986), wavelet analysis (Alexandrescu et al., 1995 and 1996; Chambodut and Mandea, 2005; Duka et al., 2012), empirical mode decomposition (Roberts et al., 2007; Jackson and Mound, 2010; Buffet et al., 2009). In this paper the vertical and horizontal components of the geomagnetic field at Earth’s surface were decomposed at various timescales using Empirical orthogonal functions and the Hodrick-Prescott filter., {"references":["Alexandrescu M., Gilbert D., Hulot G., Le Mouel J.-L., Saracco G. (1995). Detection of geomagnetic jerks using wavelet analysis. J. Geophys. Res., 100(B7), pp 12557–12572","Alexandrescu M., Gilbert D., Hulot G., Le Mouel J.-L., Saracco G. (1996). Worldwide wavelet 5 analysis of geomagnetic jerks. J. Geophys. Res., 101(B10), pp 21975–21994","Bjornsson H., Venegas S.A. (1997). A manual for EOF and SVD analyses of climate data, Tech. Rep. No. 97-1, Department of Atmospheric and Oceanic Sciences and Centre for Climate and Global Change Research, McGill University","Buffett B., Mound J., Jackson A. (2009). Inversion of torsional oscillations for the structure and dynamics of Earth's core. Geophys. J. Int. 177, pp 878–890. http://dx.doi.org/10.1111/j.1365-246X.2009.04129.x","Butterworth S. (1930). On the theory of filter amplifiers. Wireless Engineer 7, pp 536– 541","Chambodut A., Mandea M. (2005). Evidence for geomagnetic jerks in comprehensive models. Earth Planets Space, 57, pp 139–149","Currie R.G. (1973). Geomagnetic line spectra – 2 to 70 years. Astrophys. Space Sci. 21, pp 425–438","Duka B., De Santis A., Mandea M., Isac A., Qamili E. (2012). Geomagnetic jerks characterization via spectral analysis. Solid Earth, 3, pp 131–148","Gillet N., Barrois O., Finlay C.C. (2015). Stochastic forecasting of the geomagnetic field from the COV-OBS.x1 geomagnetic field model, and candidate models for IGRF-12. Earth Planet Space, 67, pp 71-85, DOI:10.1186/s40623-015-0225-z","Hodrick R. J., Prescott E. C. (1997). Postwar U. S. business cycles: An empirical investigation. J. Money, Credit, Banking, 29, pp 1-16","Jackson L.P., Mound J.E. (2010). Geomagnetic variations on decadal time scales: what can we learn from Empirical Mode Decomposition? Geophys. Res. Lett. 37, L14307. http://dx.doi.org/10.1029/2010GL043455","Langel R.A., Kerridge D.J., Barraclough D.R., Malin S.R.C. (1986). Geomagnetic temporal change: 1903–1982, A spline representation. J. Geomagn. Geoelec. 38, pp 573–597","Roberts P.H., Yu Z., Russell C. (2007). On the 60-year signal from the core. Geophys. Astrophys. Fluid Dyn. 101, pp 11–35. http://dx.doi.org/10.1080/03091920601083820"]}

Background: DNA microarray studies identified distinct molecular subtypes that are associated with different clinical outcome, defined as luminal A, luminal B, basal-like and Her2+ER-. This study aimed to evaluate the immunohistochemistry markers ER, PR and Her2 as surrogate markers for the previously identified molecular subtypes in a large retrospective cohort (n=1678) with invasive breast carcinomas with regard to various demographic, clinical and pathological features. Methods: All patients were diagnosed with primary breast cancer between 2000 and 2005 at the University Hospital Leuven. None of them received neo-adjuvant therapy, had bilateral cancer, tumors with direct extension to chest wall or skin, or nipple Paget’s disease. ER, PR and Her2 expression was determined by immunohistochemistry and cases with intermediary staining for Her2 were further subjected to two-color fluorescence in situ hybridization analysis. Clinical and pathological features included age at diagnosis, menopausal status, maximum tumor size, tumor grade, lymph node status and Nottingham Prognostic Index (NPI). Results: Of the 1678 patients with invasive breast carcinoma, 80% (n=1342) had luminal A subtype, 7% (n=119) had luminal B subtype, 9% (n=144) had basal-like type and 4% (n=73) had Her2+/ER- carcinomas. Within the luminal type, the majority of cases were PR+, with 87% and 83% for the A and B subtypes, respectively. Luminal A carcinomas were more often small in size (p=0.037), well/moderately differentiated (p