Cerebral choline metabolism is crucial for normal brain function, and its homoeostasis depends on carrier-mediated transport. Here, we report on four individuals from three families with neurodegenerative disease and homozygous frameshift mutations (Asp517Metfs*19, Ser126Metfs*8, and Lys90Metfs*18) in the SLC44A1 gene encoding choline transporter-like protein 1. Clinical features included progressive ataxia, tremor, cognitive decline, dysphagia, optic atrophy, dysarthria, as well as urinary and bowel incontinence. Brain MRI demonstrated cerebellar atrophy and leukoencephalopathy. Moreover, low signal intensity in globus pallidus with hyperintensive streaking and low signal intensity in substantia nigra were seen in two individuals. The Asp517Metfs*19 and Ser126Metfs*8 fibroblasts were structurally and functionally indistinguishable. The most prominent ultrastructural changes of the mutant fibroblasts were reduced presence of free ribosomes, the appearance of elongated endoplasmic reticulum and strikingly increased number of mitochondria and small vesicles. When chronically treated with choline, those characteristics disappeared and mutant ultrastructure resembled healthy control cells. Functional analysis revealed diminished choline transport yet the membrane phosphatidylcholine content remained unchanged. As part of the mechanism to preserve choline and phosphatidylcholine, choline transporter deficiency was implicated in impaired membrane homeostasis of other phospholipids. Choline treatments could restore the membrane lipids, repair cellular organelles and protect mutant cells from acute iron overload. In conclusion, we describe a novel childhood-onset neurometabolic disease caused by choline transporter deficiency with autosomal recessive inheritance.

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The paper presents and analyzes the state-of-the-art machine learning techniques that can be applied as a decision-support system in the estimation of resource consumption in the construction of reinforced concrete and prestressed concrete road bridges. The formed database on the consumption of concrete in the construction of bridges, along with their project characteristics, was the basis for the formation of the assessment model. The models were built using information from 181 reinforced concrete bridges in the eastern and southern branches of Corridor X in Serbia, with a value of more than 100 million euros. The application of artificial neural network models (ANNs), models based on regression trees (RTs), models based on support vector machines (SVM), and Gaussian processes regression (GPR) were analyzed. The accuracy of each model is determined by multi-criterion evaluation against four accuracy criteria root mean square error (RMSE), mean absolute error (MAE), Pearson’s linear correlation coefficient (R), and mean absolute percentage error (MAPE). According to all established criteria, the model based on GPR demonstrated the greatest accuracy in calculating the concrete consumption of bridges. According to the study, using automatic relevance determination (ARD) covariance functions results in the most accurate and optimal models and also makes it possible to see how important each input variable is to the model’s accuracy.

Background Autoimmune hypophysitis is a rare condition that often results in enlargement of the pituitary gland and hypopituitarism due to inflammatory infiltration. Management of autoimmune hypophysitis can include long-term hormonal replacement and close control of the inflammatory pituitary mass. Mass-related symptoms in patients with autoimmune hypophysitis are treated with anti-inflammatory therapy, surgery, and/or radiotherapy. Case presentation We present a 25-year-old White man with visual field defects of the right eye, headache, and weight loss. Magnetic resonance imaging showed a sellar mass, and the patient underwent transcranial surgery. Histopathology revealed autoimmune hypophysitis with predominantly CD20 positive B-cell infiltration. Progression of visual field defects necessitated postoperatively anti-inflammatory treatment with prednisolone. Azathioprine was initiated under gradual tapering of prednisolone with stable conditions at first, but relapse followed after dose reduction. Therefore, rituximab treatment was initiated, which resulted in regression of the pituitary mass. Rituximab treatment was discontinued after 25 months. The patient has continuously been in remission for 4 years after rituximab treatment was stopped. Conclusion This case illustrates that rituximab might be an effective alternative treatment in B-cell predominant autoimmune hypophysitis.

Introduction: We investigated the correlation between amide proton transfer-weighted magnetic resonance imaging (APTw MRI) and dynamic susceptibility contrast (DSC) perfusion in order to assess the potential of APTw MRI as an alternative to DSC in adult brain tumor (glioma) imaging. Methods: After Ethical Committee approval, forty adult patients, treated for histopathologically confirmed glioma (World Health Organization (WHO) grade II-IV), were prospectively imaged at 3 Tesla (3 T) with DSC perfusion and a commercially available three-dimensional (3D) APTw sequence. Two consultant neuroradiologists independently performed region of interest (ROI) measurements on relative cerebral blood volume (rCBV) and APTw maps, co-registered with anatomical images. The correlation APTw MRI-DSC perfusion was assessed using Spearman's rank-order test. Inter-observer agreement was evaluated by the intraclass correlation coefficient (ICC) and Bland-Altman (BA) plots. Results: A statistically significant moderately strong positive correlation was observed between maximum rCBV (rCBV max ) and maximum APTw (APTw max ) values (observer 1: r ¼ 0.73; p < 0.01; observer 2: r ¼ 0.62; p < 0.01). We found good inter-observer agreement for APTw max (ICC ¼ 0.82; 95% confidence interval (CI) 0.66e0.90), with somewhat broad outer 95% CI for the BA Limits of Agreement (LoA) (À1.6 to 1.9). ICC for APTw max was higher than ICC for rCBV max (ICC ¼ 0.74; 95%; CI 0.50e0.86), but the difference was not statistically significant. Conclusion: APTw max values correlate positively with rCBV max in patients treated for brain glioma. APTw imaging is a reproducible technique, with some observer dependence. Results need to be confirmed by a larger population analysis. Implications for practice: APTw MRI can be a useful addition to glioma follow-up imaging and a potential alternative to DSC perfusion, especially in patients where contrast agent is contraindicated.