N6-Methyladenosine Guides mRNA Alternative Translation during Integrated Stress Response.

The integrated stress response (ISR) facilitates cellular adaptation to stress conditions via the common target eIF2α. During ISR, the selective translation of stress-related mRNAs often relies on alternative mechanisms, such as leaky scanning or reinitiation, but the underlying mechanism remains incompletely understood. Here we report that, in response to amino acid starvation, the reinitiation of ATF4 is not only governed by the eIF2α signaling pathway, but is also subjected to regulation by mRNA methylation in the form of N6-methyladenosine (m6A). While depleting m6A demethylases represses ATF4 reinitiation, knocking down m6A methyltransferases promotes ATF4 translation. We demonstrate that m6A in the 5' UTR controls ribosome scanning and subsequent start codon selection. Global profiling of initiating ribosomes reveals widespread alternative translation events influenced by dynamic mRNA methylation. Consistently, Fto transgenic mice manifest enhanced ATF4 expression, highlighting the critical role of m6A in translational regulation of ISR at cellular and organismal levels.

Q-space trajectory imaging with positivity constraints (QTI+).

Q-space trajectory imaging (QTI) enables the estimation of useful scalar measures indicative of the local tissue structure. This is accomplished by employing generalized gradient waveforms for diffusion sensitization alongside a diffusion tensor distribution (DTD) model. The first two moments of the underlying DTD are made available by acquisitions at low diffusion sensitivity (b-values). Here, we show that three independent conditions have to be fulfilled by the mean and covariance tensors associated with distributions of symmetric positive semidefinite tensors. We introduce an estimation framework utilizing semi-definite programming (SDP) to guarantee that these conditions are met. Applying the framework on simulated signal profiles for diffusion tensors distributed according to non-central Wishart distributions demonstrates the improved noise resilience of QTI+ over the commonly employed estimation methods. Our findings on a human brain data set also reveal pronounced improvements, especially so for acquisition protocols featuring few number of volumes. Our method's robustness to noise is expected to not only improve the accuracy of the estimates, but also enable a meaningful interpretation of contrast in the derived scalar maps. The technique's performance on shorter acquisitions could make it feasible in routine clinical practice.

Q-space trajectory imaging for multidimensional diffusion MRI of the human brain.

This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

Individualized QT interval (QTi) is a powerful diagnostic tool in long QT syndrome: results from a large validation study.

Aims: Diagnosis of Long QT syndrome (LQTS) is based on prolongation of the QT interval corrected for heart rate (QTc) on surface ECG and genotyping. However, up to 25% of genotype positive patients have a normal QTc interval. We recently showed that individualized QT interval (QTi) derived from 24 h holter data and defined as the QT value at the intersection of an RR interval of 1,000 ms with the linear regression line fitted through QT-RR data points of each individual patient was superior over QTc to predict mutation status in LQTS families. This study aimed to confirm the diagnostic value of QTi, fine-tune its cut-off value and evaluate intra-individual variability in patients with LQTS. Methods: From the Telemetric and Holter ECG Warehouse, 201 recordings from control individuals and 393 recordings from 254 LQTS patients were analysed. Cut-off values were obtained from ROC curves and validated against an in house LQTS and control cohort. Results: ROC curves indicated very good discrimination between controls and LQTS patients with QTi, both in females (AUC 0.96) and males (AUC 0.97). Using a gender dependent cut-off of 445 ms in females and 430 ms in males, a sensitivity of 88% and specificity of 96% were achieved, which was confirmed in the validation cohort. No significant intra-individual variability in QTi was observed in 76 LQTS patients for whom at least two holter recordings were available (483 ± 36 ms vs. 489 ± 42 ms, p = 0.11). Conclusions: This study confirms our initial findings and supports the use of QTi in the evaluation of LQTS families. Using the novel gender dependent cut-off values, a high diagnostic accuracy was achieved.

Individualized corrected QT interval is superior to QT interval corrected using the Bazett formula in predicting mutation carriage in families with long QT syndrome.

BACKGROUND: Long QT syndrome (LQTS) is characterized by reduced penetrance and variable QT prolongation over time, resulting in an estimate of 25% carriers of a pathogenic mutation with a normal corrected QT (QTc) interval on the resting electrocardiogram (ECG). OBJECTIVE: The purpose of this study was to test the hypothesis that an individualized corrected QT interval derived from 24-hour Holter data more accurately predicts carriage of a pathogenic LQTS mutation than did QT derived from a standard 12-lead ECG and corrected using the Bazett formula (QTc interval). METHODS: Carriers of a pathogenic LQTS mutation and their genotype-negative family members who had both resting ECG and Holter recordings available were included. Automated and manual measurements of QTc were performed. QTi was derived from 24-hour Holter recordings and defined as the QT value at the intersection of an RR interval of 1000 ms, with the linear regression line fitted through QT-RR data points of each individual patient. RESULTS: In total, 69 patients with LQTS (23 long QT type 1, 39 long QT type 2, and 7 long QT type 3) and 55 controls were selected. Demographic characteristics were comparable. A comparison of the receiver operating characteristic curves indicates that the test added diagnostic value compared to manual measurement (P = .02) or automated measurement (P = .005). The diagnostic accuracy of manually measured QTc using conventional cutoff criteria was 72%, while it was 92% using a sex-independent QTi cutoff of 445 ms. This was caused by a 39% increase in sensitivity without compromising the specificity. CONCLUSION: QTi derived from Holter recordings is superior to conventional QTc measured from a standard 12-lead ECG in predicting the mutation carrier state in families with LQTS.