Spontaneous bilateral subdural haematomas in the posterior cranial fossa revealed by MRI

A 52-year-old woman treated for acute myeloproliferative disease developed progressive stupor. CT showed obstructive hydrocephalus resulting from unexplained mass effect on the fourth ventricle. MRI revealed bilateral extra-axial collections in the posterior cranial fossa, giving high signal on T1- and T2-weighted images, suggesting subacute subdural haematomas. Subdural haematomas can be suspected on CT when there is unexplained mass effect. MRI may be essential to confirm the diagnosis and plan appropriate treatmen

Catalog of quasars from the Kilo-Degree Survey Data Release 3

We present a catalog of quasars selected from broad-band photometric ugri data of the Kilo-Degree Survey Data Release 3 (KiDS DR3). The QSOs are identified by the random forest (RF) supervised machine learning model, trained on SDSS DR14 spectroscopic data. We first cleaned the input KiDS data from entries with excessively noisy, missing or otherwise problematic measurements. Applying a feature importance analysis, we then tune the algorithm and identify in the KiDS multiband catalog the 17 most useful features for the classification, namely magnitudes, colors, magnitude ratios, and the stellarity index. We used the t-SNE algorithm to map the multi-dimensional photometric data onto 2D planes and compare the coverage of the training and inference sets. We limited the inference set to r<22 to avoid extrapolation beyond the feature space covered by training, as the SDSS spectroscopic sample is considerably shallower than KiDS. This gives 3.4 million objects in the final inference sample, from which the random forest identified 190,000 quasar candidates. Accuracy of 97%, purity of 91%, and completeness of 87%, as derived from a test set extracted from SDSS and not used in the training, are confirmed by comparison with external spectroscopic and photometric QSO catalogs overlapping with the KiDS footprint. The robustness of our results is strengthened by number counts of the quasar candidates in the r band, as well as by their mid-infrared colors available from WISE. An analysis of parallaxes and proper motions of our QSO candidates found also in Gaia DR2 suggests that a probability cut of p(QSO)>0.8 is optimal for purity, whereas p(QSO)>0.7 is preferable for better completeness. Our study presents the first comprehensive quasar selection from deep high-quality KiDS data and will serve as the basis for versatile studies of the QSO population detected by this survey.Comment: Data available from the KiDS website at http://kids.strw.leidenuniv.nl/DR3/quasarcatalog.php and the source code from https://github.com/snakoneczny/kids-quasar

Evaluating resective surgery targets in epilepsy patients: a comparison of quantitative EEG methods.

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.BACKGROUND: Quantitative analysis of intracranial EEG is a promising tool to assist clinicians in the planning of resective brain surgery in patients suffering from pharmacoresistant epilepsies. Quantifying the accuracy of such tools, however, is nontrivial as a ground truth to verify predictions about hypothetical resections is missing. NEW METHOD: As one possibility to address this, we use customized hypotheses tests to examine the agreement of the methods on a common set of patients. One method uses machine learning techniques to enable the predictive modeling of EEG time series. The other estimates nonlinear interrelation between EEG channels. Both methods were independently shown to distinguish patients with excellent post-surgical outcome (Engel class I) from those without improvement (Engel class IV) when assessing the electrodes associated with the tissue that was actually resected during brain surgery. Using the AND and OR conjunction of both methods we evaluate the performance gain that can be expected when combining them. RESULTS: Both methods' assessments correlate strongly positively with the similarity between a hypothetical resection and the corresponding actual resection in class I patients. Moreover, the Spearman rank correlation between the methods' patient rankings is significantly positive. COMPARISON WITH EXISTING METHOD(S): To our best knowledge, this is the first study comparing surgery target assessments from fundamentally differing techniques. CONCLUSIONS: Although conceptually completely independent, there is a relation between the predictions obtained from both methods. Their broad consensus supports their application in clinical practice to provide physicians additional information in the process of presurgical evaluation.This work was supported by the Swiss National Science Foundation (SNF) (Project No: SNF 32003B 155950). M.G. gratefully acknowledges the financial support of the EPSRC via grant EP/N014391/1. The contribution of M.G. was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA)

The VIMOS Ultra Deep Survey. Luminosity and stellar mass dependence of galaxy clustering at z~3

We present the study of the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 2$<$z$<$3.5 using 3236 galaxies with robust spectroscopic redshifts from the VIMOS Ultra Deep Survey (VUDS). We measure the two-point real-space correlation function $w_p(r_p)$ for four volume-limited stellar mass and four luminosity, M$_{UV}$ absolute magnitude selected, sub-samples. We find that the scale dependent clustering amplitude $r_0$ significantly increases with increasing luminosity and stellar mass indicating a strong galaxy clustering dependence on these properties. This corresponds to a strong relative bias between these two sub-samples of $\Delta$b/b$^*$=0.43. Fitting a 5-parameter HOD model we find that the most luminous and massive galaxies occupy the most massive dark matter haloes with $\langle$M$_h$$\rangle$ = 10$^{12.30}$ h$^{-1}$ M$_{\odot}$. Similar to the trends observed at lower redshift, the minimum halo mass M$_{min}$ depends on the luminosity and stellar mass of galaxies and grows from M$_{min}$ =10$^{9.73}$ h$^{-1}$M$_{\odot}$ to M$_{min}$=10$^{11.58}$ h$^{-1}$M$_{\odot}$ from the faintest to the brightest among our galaxy sample, respectively. We find the difference between these halo masses to be much more pronounced than is observed for local galaxies of similar properties. Moreover, at z~3, we observe that the masses at which a halo hosts, on average, one satellite and one central galaxy is M$_1$$\approx$4M$_{min}$ over all luminosity ranges, significantly lower than observed at z~0 indicating that the halo satellite occupation increases with redshift. The luminosity and stellar mass dependence is also reflected in the measurements of the large scale galaxy bias, which we model as b$_{g,HOD}$($>$L)=1.92+25.36(L/L$^*$)$^{7.01}$. We conclude our study with measurements of the stellar-to-halo mass ratio (SHMR).Comment: 20 pages, 11 figures, A&A in press, v2. revised discussion in sec. 5.5, changed Fig. 4 and Fig. 11, added reference

Psychometric Properties of the Brazilian Version of the Quality of Dying and Death for Adult Family Members of ICU Patients

Death is a complex, subjective phenomenon that requires an understanding of experiences to be qualified to provide care during the end-of-life process. This study aimed to analyze the psychometric properties of the Portuguese version (Brazil) of the Quality of Dying and Death (QODD) scale on family members of patients who died in adult intensive care units. A methodological study was conducted with 326 family members of patients that died in three ICUs of public hospitals in the state of São Paulo, Brazil. For this study, the QODD 3.2a (25 items and six domains) was administered during the period from December 2020 to March 2022. The analysis was performed using the classic theory of the tests and the goodness of fit of the model was tested using confirmatory factor analysis. We have used Spearman's correlation coefficients between the scores of the overall scale and domains. Cronbach's alpha coefficient and the intraclass correlation coefficient (ICC) were used for the evaluation of internal consistency and temporal stability, respectively. The Horn's parallel analysis indicated two factors that were not confirmed in the exploratory factor analysis. A single factor retained 18 of the initial 25 items and the analysis of the goodness of fit to the unidimensional model resulted in the following: CFI = 0.7545, TLI = 0.690, chi-squared = 767.33, df = 135, RMSEA = 0.121 with 90%CI, and p = 5.04409. The inter-item correlations indicated a predominance of weak correlations among the items of the instrument. The items with the largest number of moderate correlations were questions 13b, 9b, and 10b and a strong correlation was found between questions 15b and 16b. Cronbach's alpha coefficient was 0.8 and the ICC was 0.9. The Quality of Dying and Death-Version 3.2a (intensive therapy) in Brazilian Portuguese has a unidimensional structure and acceptable reliability. However, it did not obtain a good fit to the proposed factorial model

Thalamic Nuclei Clustering on High Angular Resolution Diffusion Images.

Thalamic nuclei can be distinguished by their characteristic fiber orientations, which influence the diffusion. Fiber orientations are relatively aligned within a nucleus due to the fact that the cerebrocortical striations within a nucleus all target the same region of cortex. The number of thalamic nuclei reported with histological methods varies with the method employed, although most cyto/myeloarchitec stains identify 14 major nuclei. We present a new approach for thalamic nuclei segmentation on High Angular Diffusion Resolution Images (HARDI), performed with a constrained k-means clustering. As described by John D.Carew[1], it is possible to classify HARDI data based on the shape of the diffusion, thanks to the complex information coming from them. Mette R. Wiegell [2] proposed a thalamic nuclei clustering with k- means on diffusion tensor images, using a combination of a voxel distance and a diffusion tensor distance. In the same way, we use the k-mean algorithm with a weighted sum of two distances to cluster the thalamic nuclei on HARDI data

Quality of life of patients living with psoriasis: a qualitative study

Background: Psoriasis is a multifactorial inflammatory disease prevalent in dermatology. We aimed to understand the perceptions of patients living with psoriasis in relation to their quality of life and to identify aspects to improve it. Methods: This is qualitative research carried out in a dermatology outpatient clinic of the São Paulo State University (UNESP) medical school, Botucatu, Brazil, with 81 psoriasis patients. The interviews were transcribed and analysed using the Discourse of the Collective Subject method (DCS). Results: Quality of life was linked to well-being, happiness, leisure, good food and financial stability. However, disease symptoms, social and clothing restrictions, impairment of professional activities and the absence of a cure, negatively influenced their perceptions. Suggestions for improvements included an increase of public awareness, stress reduction, disease acceptance and multidisciplinary care. Conclusion: The meanings of quality of life revealed by the participants are subjective, multidimensional, linked to moments experienced by them and to the health-disease process. Public health policies promoting reduction in social stigma and stress as well as multidisciplinary approaches towards care can contribute to improvements of QoL in psoriasi

Psychometric characteristics of DLQI-BRA and Skindex-16 to measure the impact of dermatological diseases on quality of life in Brazilian patients

OBJECTIVE: To compare the psychometric performance of the Dermatology Life Quality Index (DLQI-BRA) and Skindex-16 to assess quality of life (QoL) in Brazilian patients with dermatological diseases. METHODS: This was a cross-sectional study carried out in a dermatology outpatient clinic of the São Paulo State University, with 188 patients with dermatological diseases. QoL was evaluated using the Dermatology Life Quality Index (DLQI-BRA) and Skindex-16. Cronbach’s alpha and Intraclass Correlation for Perfect Concordance (ICC) were used to analyse the reliability and temporal stability, respectively. RESULTS: A positive correlation was found between the total Skindex-16 score and DLQI-BRA (0.75). Both instruments showed a significant (p0,7), but Skindex-16 displayed the highest Cronbach alpha (0.94; CI = 0.93–0.95). CONCLUSION: Both instruments tested showed a good psychometric performance assessing QoL in patients with skin dermatoses. The instruments displayed reliability and temporal stability as well as responsiveness