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Abstract Background The yeast Starmerella bombicola is renowned for its highly efficient sophorolipid production, reaching titers and productivities of (over) 200 g/L and 2 g/(L h), respectively. This inherent efficiency has led to the commercialization of sophorolipids. While the sophorolipid biosynthetic pathway has been elucidated a few years ago, in this study, it is revisited and true key intermediates are revealed. Results Recently, Starmerella bombicola strains developed and evaluated in the past were reevaluated unveiling unexpected findings. The AT enzyme encoded in the sophorolipid biosynthetic gene cluster is the only described enzyme known to acetylate sophorolipids, while the SBLE enzyme encoded by the SBLE gene is described to catalyze the conversion of (acetylated) acidic sophorolipids into lactonic sophorolipids. A double knockout of both genes was described to result in the generation of bolaform sophorolipids. However, new experiments performed with respective S. bombicola strains Δsble, Δat Δsble, and ∆at revealed inconsistencies with the current understanding of the SL pathway. It was observed that the ∆sble strain produces mainly bolaform sophorolipids with higher acetylation degrees instead of acidic sophorolipids. Furthermore, the ∆at strain produces predominantly bolaform sophorolipids and lactonic sophorolipids with lower acetylation degrees, while the ∆at ∆sble strain predominantly produces bolaform sophorolipids with lower acetylation degrees. These results indicate that the AT enzyme is not the only enzyme responsible for acetylation of sophorolipids, while the SBLE enzyme performs an intramolecular transesterification reaction on bolaform glycolipids instead of an esterification reaction on acidic sophorolipids. These findings, together with recent in vitro data, led us to revise the sophorolipid biosynthetic pathway. Conclusions Bolaform sophorolipids instead of acidic sophorolipids are the key intermediates in the biosynthetic pathway towards lactonic sophorolipids. Bolaform sophorolipids are found in very small amounts in extracellular S. bombicola wild type broths as they are very efficiently converted into lactonic sophorolipids, while acidic sophorolipids build up as they cannot be converted. Furthermore, acetylation of sophorolipids is not exclusively performed by the AT enzyme encoded in the sophorolipid biosynthetic gene cluster and acetylation of bolaform sophorolipids promotes their transesterification. These findings led to the revision of the industrially relevant sophorolipid biosynthetic pathway.

Abstract Automated quantification of brain tissues on MR images has greatly contributed to the diagnosis and follow-up of neurological pathologies across various life stages. However, existing solutions are specifically designed for certain age ranges, limiting their applicability in monitoring brain development from infancy to late adulthood. This retrospective study aims to develop and validate a brain segmentation model across pediatric and adult populations. First, we trained a deep learning model to segment tissues and brain structures using T1-weighted MR images from 390 patients (age range: 2–81 years) across four different datasets. Subsequently, the model was validated on a cohort of 280 patients from six distinct test datasets (age range: 4–90 years). In the initial experiment, the proposed deep learning-based pipeline, icobrain-dl, demonstrated segmentation accuracy comparable to both pediatric and adult-specific models across diverse age groups. Subsequently, we evaluated intra- and inter-scanner variability in measurements of various tissues and structures in both pediatric and adult populations computed by icobrain-dl. Results demonstrated significantly higher reproducibility compared to similar brain quantification tools, including childmetrix, FastSurfer, and the medical device icobrain v5.9 (p-value< 0.01). Finally, we explored the potential clinical applications of icobrain-dl measurements in diagnosing pediatric patients with Cerebral Visual Impairment and adult patients with Alzheimer’s Disease.

The free water elimination (FWE) model and its kurtosis variant (DKI-FWE) can separate tissue and free water signal contributions, thus providing tissue-specific diffusional information. However, a downside of these models is that the associated parameter estimation problem is ill-conditioned, necessitating the use of advanced estimation techniques that can potentially bias the parameter estimates. In this work, we propose the T2-DKI-FWE model that exploits the T2 relaxation properties of both compartments, thereby better conditioning the parameter estimation problem and providing, at the same time, an additional potential biomarker (the T2 of tissue). In our approach, the T2 of tissue is estimated as an unknown parameter, whereas the T2 of free water is assumed known a priori and fixed to a literature value (1573 ms). First, the error propagation of an erroneous assumption on the T2 of free water is studied. Next, the improved conditioning of T2-DKI-FWE compared to DKI-FWE is illustrated using the Cramér-Rao lower bound matrix. Finally, the performance of the T2-DKI-FWE model is compared to that of the DKI-FWE and T2-DKI models on both simulated and real datasets. The error due to a biased approximation of the T2 of free water was found to be relatively small in various diffusion metrics and for a broad range of erroneous assumptions on its underlying ground truth value. Compared to DKI-FWE, using the T2-DKI-FWE model is beneficial for the identifiability of the model parameters. Our results suggest that the T2-DKI-FWE model can achieve precise and accurate diffusion parameter estimates, through effective reduction of free water partial volume effects and by using a standard nonlinear least squares approach. In conclusion, incorporating T2 relaxation properties into the DKI-FWE model improves the conditioning of the model fitting, while only requiring an acquisition scheme with at least two different echo times.

Abstract Objectives Zilucoplan (complement C5 inhibitor) has profound effects on inhibiting acute lung injury post COVID-19, and can promote lung repair mechanisms that lead to improvement in lung oxygenation parameters. The purpose of this study is to investigate the efficacy and safety of Zilucoplan in improving oxygenation and short- and long-term outcome of COVID-19 patients with acute hypoxic respiratory failure. Trial design This is a phase 2 academic, prospective, 2:1 randomized, open-label, multi-center interventional study. Participants Adult patients (≥18y old) will be recruited at specialized COVID-19 units and ICUs at 9 Belgian hospitals. The main eligibility criteria are as follows: 1) Inclusion criteria: a. Recent (≥6 days and ≤16 days) SARS-CoV-2 infection. b. Chest CT scan showing bilateral infiltrates within the last 2 days prior to randomisation. c. Acute hypoxia (defined as PaO2/FiO2 below 350 mmHg or SpO2 below 93% on minimal 2 L/min supplemental oxygen). d. Signs of cytokine release syndrome characterized by either high serum ferritin, or high D-dimers, or high LDH or deep lymphopenia or a combination of those. 2) Exclusion criteria: e. Mechanical ventilation for more than 24 hours prior to randomisation. f. Active bacterial or fungal infection. g. History of meningococcal disease (due to the known high predisposition to invasive, often recurrent meningococcal infections of individuals deficient in components of the alternative and terminal complement pathways). Intervention and comparator Patients in the experimental arm will receive daily 32,4 mg Zilucoplan subcutaneously and a daily IV infusion of 2g of the antibiotic ceftriaxone for 14 days (or until hospital discharge, whichever comes first) in addition to standard of care. These patients will receive additional prophylactic antibiotics until 14 days after the last Zilucoplan dose: hospitalized patients will receive a daily IV infusion of 2g of ceftriaxone, discharged patients will switch to daily 500 mg of oral ciprofloxacin. The control group will receive standard of care and a daily IV infusion of 2g of ceftriaxone for 1 week (or until hospital discharge, whichever comes first), to control for the effects of antibiotics on the clinical course of COVID-19. Main outcomes The primary endpoint is the improvement of oxygenation as measured by mean and/or median change from pre-treatment (day 1) to post-treatment (day 6 and 15 or at discharge, whichever comes first) in PaO2/FiO2 ratio, P(A-a)O2 gradient and a/A PO2 ratio. (PAO2= Partial alveolar pressure of oxygen, PaO2=partial arterial pressure of oxygen, FiO2=Fraction of inspired oxygen). Randomisation Patients will be randomized in a 2:1 ratio (Zilucoplan: control). Randomization will be done using an Interactive Web Response System (REDCap). Blinding (masking) In this open-label trial neither participants, caregivers, nor those assessing the outcomes will be blinded to group assignment. Numbers to be randomised (sample size) A total of 81 patients will be enrolled: 54 patients will be randomized to the experimental arm and 27 patients to the control arm. Trial Status ZILU-COV protocol Version 4.0 (June 10 2020). Participant recruitment started on June 23 2020 and is ongoing. Given the uncertainty of the pandemic, it is difficult to predict the anticipated end date. Trial registration The trial was registered on Clinical Trials.gov on May 11th, 2020 (ClinicalTrials.gov Identifier: NCT04382755 ) and on EudraCT (Identifier: 2020-002130-33 ). Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

This retrospective correlation study investigated the putative link between methylene tetrahydrofolate reductase (MTHFR) A1298C mutations and chemotherapy-related brain function changes in adult childhood-leukemia survivors. To this end, we determined the relationship between the particular MTHFR1298 genotype (AA, AC or CC) of 31 adult childhood-leukemia survivors, and (1) their CSF Tau and phosphorylated Tau (pTau) levels at the time of treatment, (2) their adult performance intelligence quotient (PIQ), and (3) their regional brain connectivity using diffusion magnetic resonance imaging (dMRI) and resting-state functional MRI (rsfMRI). We confirmed that neuropathology markers Tau and pTau significantly increased in CSF of children after intrathecal methotrexate administration. Highest concentrations of these toxicity markers were found during the induction phase of the therapy. Moreover, CSF concentrations of Tau and pTau during treatment were influenced by the children's particular MTHFR1298 genotype. CSF Tau (but not pTau) levels significantly dropped after folinic acid supplementation. At adult age (on average 13.1 years since the end of their treatment), their particular MTHFR1298 genotype (AA, AC or CC) influenced the changes in PIQ and cortical connectivity that we found to be related to their childhood exposure to chemotherapeutics. In summary, we suggest that homozygous MTHFR1298CC individuals are more vulnerable to the adult sequelae of antifolate chemotherapy.

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.

Introduction: The histopathological basis of “unidentified bright objects” (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. Methods: 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO–cNAWM pairs. Results: No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. Conclusion: Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in ‘extracellular-like’, intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo.

Nitrogen return by leaf litterfall was compared with atmospheric nitrogen deposition for two deciduous Nothofagus stands in southern Chile, located in areas with contrasting land use. The litterfall return of nitrogen in a Nothofagus alpina (Poepp. et Endl.) Oerst. stand at San Pablo de Tregua, in the Cordillera de los Andes, was similar to the litterfall return in a Nothofagus obliqua (Mirb.) Oerst. stand at Paillaco, in the Central Depression. In contrast, the net throughfall and stemflow deposition differed significantly between the two stands. At San Pablo de Tregua, the annual bulk deposition of NH4+ and NO3- was significantly higher than the throughfall and stemflow deposition reaching the forest floor. This demonstrates an uptake of inorganic nitrogen by the aboveground biomass, which was correlated with month-to-month variation in the bulk inorganic nitrogen deposition by precipitation (r² > 0.73). At Paillaco, the canopy uptake of nitrogen was not directly detectable due to an estimated dry deposition input of 4-8 kg inorganic N ha-1 y-1. In both stands, nitrogen return through leaf litterfall (~ 50 kg N ha-1 y-1) was much higher than the atmospheric N deposition load (< 10 kg N ha-1 y-1). The results consequently confirm the low level of atmospheric pollution in the forests of this region. However, the clear difference in net throughfall deposition of inorganic nitrogen between the two stands suggests that the external N input by dry deposition may be considerably higher in the Central depression than in Cordillera de los Andes. More emphasis on monitoring dry atmospheric N deposition is a necessary tool for evaluating the consequences of future emission changes

Background: Macro‐ and micro‐structural degeneration in cortical grey matter (CGM) accompany the progression of frontotemporal lobar degeneration (FTLD). The former can be measured by brain volumetry from magnetic resonance imaging (MRI) and the latter by mean diffusivity (MD) from diffusion tensor imaging (DTI). While disease‐modifying treatment is expected to slow the progression of both metrics, unexpected treatment effects such as inflammation may alter the relationship between them. Here, we evaluate the cross‐sectional and longitudinal relationships between lobar volume and average MD of CGM in untreated FTLD. Method: 24 patients with behavioral variant frontotemporal dementia (BV), 21 with semantic variant primary progressive aphasia (SV), 20 with nonfluent agrammatic variant primary progressive aphasia (PNFA), and 75 cognitively‐normal controls (CON) from the FTLD Neuroimaging Initiative (FTLDNI) were assessed longitudinally with MRI and DTI. CGM volumes were measured with icobrain dm using T1‐weighted and FLAIR images. CGM MD maps were extracted from DTI and partial‐volume corrected. Volume and average MD were calculated for each lobe using two timepoints approximately 1 year apart, adjusted for age and sex, and z‐scored relative to CON. For each lobe, multiple linear regression models with Bonferroni correction assessed the effect of FTLD phenotype on the relationship between 1) baseline MD and volume, and 2) percent change from baseline in MD and volume. Result: At baseline, BV, SV, and PNFA demonstrated significantly more negative associations between MD and volume in the frontal lobes relative to CON (all p values <.05), such that greater MD related to lesser volume in each phenotype. Significantly more negative associations between MD and volume relative to CON were observed for BV and SV in the temporal lobe, and for PNFA in the parietal lobe (p <.05). For percent change from baseline, BV demonstrated a significantly more negative association between MD and volume in the frontal and parietal lobes relative to CON (p <.05), such that percent increase in MD related to percent decrease in volume. Conclusion: Our results elucidate phenotypic differences in cortical macro‐ and micro‐structural degeneration in FTLD and provide a novel frame of reference for MRI and DTI for interventional clinical trials. [ABSTRACT FROM AUTHOR]

Background: MRI allows detecting functional and structural connectivity changes in Alzheimer's disease (AD). However, the relative importance of the corresponding MRI‐biomarkers is not fully understood. Moreover, several of these connectivity changes are not only driven by AD but also by healthy aging, which can limit the use of these biomarkers. Therefore, we looked at how 31‐different MRI biomarkers change due to aging and the presence of AD. Furthermore, we trained a set of machine‐learning‐models to distinguish AD from control subjects. The models were used to rank the features in terms of classification‐performance and analyze the impact of including age. Method: 20 AD patients and 20 age and gender‐matched healthy controls underwent MRI scanning (3T GE), including T1‐weighted, diffusion‐MRI, and resting‐state‐fMRI (rsfMRI). Whole‐brain (WB), white matter (WM), gray matter (GM), cortical GM and left and right hippocampi volumes were measured using T1‐images and icobrain. rsfMRI between regions of the default mode network was assessed using group independent component analysis. Median diffusivity and kurtosis values in GM and WM were determined. T‐tests between groups and ANOVA analysis using a Generalized‐Linear‐Model that included age and AD‐status as covariates were conducted for each feature. For assessing the ability of each feature to separate AD subjects from controls, a Support‐Vector‐Machine (SVM) model was trained using each feature separately and each feature with age. Performance was measured using 10‐fold cross‐validation. Result: Figure 1 shows the table with the ANOVA results. Generally, rsfMRI features showed only a significant association with disease‐status, whereas structural and diffusion‐derived features showed both an association with age and disease‐status. Figure 2 shows the classification performance for the different SVM models. Regarding classification performance, the models trained with the total volume of the hippocampus achieved the highest performance (accuracy:77%, sensitivity:64%, specificity:89%). Despite several of the features changing with both age and AD‐status, the inclusion of age in the SVM‐models didn't provide an advantage in classification performance. Conclusion: Multiple MRI‐biomarkers are able to detect structural and functional connectivity changes associated with AD. From those, the hippocampi volumes are the ones that better distinguish AD patients from cognitively‐healthy subjects. [ABSTRACT FROM AUTHOR]

• The information regarding the pattern and amount of brain atrophy in MOGAD is currently very limited. • We compared cross-sectional brain volume measures in clinically stable MOGAD to MS, NMOSD and HC, and longitudinal trajectories of brain volume changes in a subset of clinically stable MOGAD, MS and NMOSD patients. • We found a distinct pattern of brain atrophy in MOGAD, suggesting that a subclinical neurodegenerative process may occur in this rare condition. • Our findings may shed light on the distinct pathogenic mechanisms underlying the various neuroinflammatory CNS diseases. Relatively little is known about how global and regional brain volumes changes in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) compare with Multiple Sclerosis (MS), Neuromyelitis optica spectrum disorder (NMOSD), and healthy controls (HC). To compare global and regional brain volumes in MOGAD, MS, NMOSD, and HC cross-sectionally as well as longitudinally in a subset of patients. We retrospectively reviewed all adult MOGAD and NMOSD patients with brain MRI performed in stable remission and compared them with MS patients and HC. Volumetric parameters were assessed using the FDA-approved icobrain software. adjusted for age and sex. Twenty-four MOGAD, 47 NMOSD, 40 MS patients, and 37 HC were included in the cross-sectional analyses. Relative to HC, the age-adjusted whole brain (WB) volume was significantly lower in patients with MOGAD (p=0.0002), NMOSD (p=0.042), and MS (p=0.01). Longitudinal analysis of a subset of 8 MOGAD, 22 NMOSD, and 34 MS patients showed a reduction in the WB and cortical gray matter (CGM) volumes over time in all three disease groups, without statistically significant differences between groups. The MOGAD group had a greater loss of thalamic volume compared to MS (p=0.028) and NMOSD (p=0.023) and a greater loss of hippocampal volumes compared to MS (p=0.007). Age-adjusted WB volume loss was evident in all neuroinflammatory conditions relative to HC in cross-sectional comparisons. In longitudinal analyses, MOGAD patients had a higher thalamic atrophy rate relative to MS and NMOSD, and a higher hippocampal atrophy rate relative to MS. Larger studies are needed to validate these findings and to investigate their clinical implications. [ABSTRACT FROM AUTHOR]

• Patients with RRMS were treated with natalizumab and followed for up to 5 years. • More than 98% of patients had no new or enlarging FLAIR lesions in years 2–5. • 52% of patients achieved NEDA-3 in year 1, increasing to >68% in years 2–5. • Similar results were obtained for other MRI and clinical endpoints. • This study provides evidence for the long-term real-world efficacy of natalizumab. Magnetic resonance imaging (MRI) data from multiple sclerosis (MS) patients treated in real-world settings are important for understanding disease-modifying therapy effects, including no evidence of disease activity (NEDA) assessment. This longitudinal, retrospective, single-cohort analysis assessed MRI and clinical disease outcomes in patients with relapsing-remitting MS treated with natalizumab for up to 5 years in Prague, the Czech Republic. The primary study endpoint was the proportion of patients free of new or enlarging fluid-attenuated inversion recovery (FLAIR) lesions after at least 2 years of natalizumab treatment. Secondary endpoints included percentage brain volume change over time, the number of new T1-hypointense lesions that persisted for ≥6 months, FLAIR and T1-hypointense lesion volume change over time, and the proportion of patients with NEDA-3 (defined as no relapses, no confirmed disability worsening, and no new or enlarging FLAIR lesions). A total of 193 patients were included in the study. During year 1 of natalizumab treatment, 78.9% of patients had no new or enlarging FLAIR lesions and 79.5% had no new T1 lesions. These proportions increased in years 2–5, with ≥98.0% of patients free of new or enlarging FLAIR lesions and ≥98.8% free of new T1 lesions. During year 1 on natalizumab, 52.2% of patients achieved NEDA-3; this proportion increased to ≥69.2% in years 2–5. This study provides additional evidence that long-term MS disease activity, as measured by both MRI activity and NEDA-3, is well-controlled in patients treated with natalizumab in real-world settings. [ABSTRACT FROM AUTHOR]

In most cases coccidioidomycosis presents as a benign mildly severe respiratory disease with a benign course and spontaneous resolution. Rarely dissemination can lead to complications. We believe this is the first published case of a patient with a disseminated coccidioidomycosis, as shown on a urinary sample, in association with Wegener's disease. It was a challenge to diagnose and consecutively treat the patient as therapies seem to be conflictual. This case illustrates how migration, changing habits and attitudes, travelling, changing geo-ecological circumstances can lead to a change in medical environment. It is therefore essential that the microbiologist becomes a clinical microbiologist who communicates intensively with his fellow clinicians.