In the 1998 enterovirus 71 epidemic in Taiwan, the chief neurologic complication was rhombencephalitis, which had a fatality rate of 14 percent. The most common initial symptoms were myoclonic jerks, and MRI usually showed evidence of brainstem involvement.

We report a computational, structure-based redesign of the phenylalanine adenylation domain of the nonribosomal peptide synthetase enzyme gramicidin S synthetase A (GrsA-PheA) for a set of noncognate substrates for which the wild-type enzyme has little or virtually no specificity. Experimental validation of a set of top-ranked computationally predicted enzyme mutants shows significant improvement in the specificity for the target substrates. We further present enhancements to the methodology for computational enzyme redesign that are experimentally shown to result in significant additional improvements in the target substrate specificity. The mutant with the highest activity for a noncognate substrate exhibits 1/6 of the wild-type enzyme/wild-type substrate activity, further confirming the feasibility of our computational approach. Our results suggest that structure-based protein design can identify active mutants different from those selected by evolution.

Contrast enhanced CT imaging offered crucial evidence not only for the diagnosis of gallstone ileus but also for decision making in management strategy.

The new classification announced by the World Health Organization in 2016 recognized five molecular subtypes of diffuse gliomas based on isocitrate dehydrogenase (IDH) and 1p/19q genotypes in addition to histologic phenotypes. We aim to determine whether clinical MRI can stratify these molecular subtypes to benefit the diagnosis and monitoring of gliomas. The data from 456 subjects with gliomas were obtained from The Cancer Imaging Archive. Overall, 214 subjects, including 106 cases of glioblastomas and 108 cases of lower grade gliomas with preoperative MRI, survival data, histology, IDH, and 1p/19q status were included. We proposed a three-level machine-learning model based on multimodal MR radiomics to classify glioma subtypes. An independent dataset with 70 glioma subjects was further collected to verify the model performance. The IDH and 1p/19q status of gliomas can be classified by radiomics and machine-learning approaches, with areas under ROC curves between 0.922 and 0.975 and accuracies between 87.7% and 96.1% estimated on the training dataset. The test on the validation dataset showed a comparable model performance with that on the training dataset, suggesting the efficacy of the trained classifiers. The classification of 5 molecular subtypes solely based on the MR phenotypes achieved an 81.8% accuracy, and a higher accuracy of 89.2% could be achieved if the histology diagnosis is available. The MR radiomics-based method provides a reliable alternative to determine the histology and molecular subtypes of gliomas. .

BackgroundLung adenocarcinoma is the leading cause of cancer-related deaths among both men and women in the world. Despite recent advances in diagnosis and treatment, the mortality rates with an overall 5-year survival of only 15%. This high mortality is probably attributable to early metastasis. Although several well-known markers correlated with poor/metastasis prognosis in lung adenocarcinoma patients by immunohistochemistry was reported, the molecular mechanisms of lung adenocarcinoma development are still not clear. To explore novel molecular markers and their signaling pathways will be crucial for aiding in treatment of lung adenocarcinoma patients.Methodology/Principal FindingsTo identify novel lung adenocarcinoma-associated /metastasis genes and to clarify the underlying molecular mechanisms of these targets in lung cancer progression, we created a bioinformatics scheme consisting of integrating three gene expression profile datasets, including pairwise lung adenocarcinoma, secondary metastatic tumors vs. benign tumors, and a series of invasive cell lines. Among the novel targets identified, FLJ10540 was overexpressed in lung cancer tissues and is associated with cell migration and invasion. Furthermore, we employed two co-expression strategies to identify in which pathway FLJ10540 was involved. Lung adenocarcinoma array profiles and tissue microarray IHC staining data showed that FLJ10540 and VEGF-A, as well as FLJ10540 and phospho-AKT exhibit positive correlations, respectively. Stimulation of lung cancer cells with VEGF-A results in an increase in FLJ10540 protein expression and enhances complex formation with PI3K. Treatment with VEGFR2 and PI3K inhibitors affects cell migration and invasion by activating the PI3K/AKT pathway. Moreover, knockdown of FLJ10540 destabilizes formation of the P110-α/P85-α-(PI3K) complex, further supporting the participation of FLJ10540 in the VEGF-A/PI3K/AKT pathway.Conclusions/SignificanceThis finding set the stage for further testing of FLJ10540 as a new therapeutic target for treating lung cancer and may contribute to the development of new therapeutic strategies that are able to block the PI3K/AKT pathway in lung cancer cells.

Protein tyrosine phosphatases (PTPs) are known to be regulated by phosphorylation, localization, and protein-protein interactions. More recently, redox-dependent inactivation has emerged as a critical factor in attenuating PTP activity in response to cellular stimuli. The tandem Src homology 2 domain-containing PTPs (SHPs) belong to the family of nonreceptor PTPs whose activity can be modulated by reversible oxidation in vivo. Herein we have investigated in vitro the kinetic and mechanistic details of reversible oxidation of SHP-1 and SHP-2. We have confirmed the susceptibility of the active site cysteines of SHPs to oxidative inactivation, with rate constants for oxidation similar to other PTPs (2-10 M(-1) s(-1)). Both SHP-1 and SHP-2 can be reduced and reactivated with the reductants DTT and gluthathione, whereas only the catalytic domain of SHP-2 is subject to reactivation by thioredoxin. Stabilization of the reversible oxidation state of the SHPs proceeds via a novel mechanism unlike for other PTPs wherein oxidation yields either a disulfide between the catalytic cysteine and a nearby "backdoor" cysteine or a sulfenylamide bond with the amide backbone nitrogen of the adjacent amino acid. Instead, in the reversibly oxidized and inactivated SHPs, the catalytic cysteine is rereduced while two conserved backdoor cysteines form an intramolecular disulfide. Formation of this backdoor-backdoor disulfide is dependent on the presence of the active site cysteine and can proceed via either active site cysteine-backdoor cysteine intermediate. Removal of both backdoor cysteines leads to irreversible oxidative inactivation, demonstrating that these two cysteines are necessary and sufficient for ensuring reversible oxidation of the SHPs. Our results extend the mechanisms by which redox regulation of PTPs is used to modulate intracellular signaling pathways.

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A technique suitable for diffusion tensor imaging (DTI) at high field strengths is presented in this work. The method is based on a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) k-space trajectory using EPI as the signal readout module, and hence is dubbed PRO-PELLER EPI. The implementation of PROPELLER EPI included a series of correction schemes to reduce possible errors associated with the intrinsically higher sensitivity of EPI to off-resonance effects. Experimental results on a 3.0 Tesla MR system showed that the PROPELLER EPI images exhibit substantially reduced geometric distortions compared with single-shot EPI, at a much lower RF specific absorption rate (SAR) than the original version of the PROPELLER fast spin-echo (FSE) technique. For DTI, the self-navigated phase-correction capability of the PROPELLER EPI sequence was shown to be effective for in vivo imaging. A higher signal-to-noise ratio (SNR) compared to single-shot EPI at an identical total scan time was achieved, which is advantageous for routine DTI Key words: PROPELLER imaging; EPI; geometric distortions; specific absorption rate; diffusion tensor imagingThe importance of diffusion tensor imaging (DTI) in white matter diseases is now well recognized by the clinical neurology community. It has several applications, including the detection of pathologically induced alterations in neural fiber architecture resulting from multiple sclerosis (1), traumatic axonal injury (2), adrenoleukodystrophy (3), or tumors (4,5). The current implementation of DTI often uses single-shot echo-planar imaging (EPI) as the signal readout module following diffusion-weighted (DW) magnetization preparation. Due to strong susceptibility effects from the air-tissue interface, however, the EPI images show severe geometric distortions that are prominent especially near the skull base (6,7). As a consequence, image mapping methods based on DTI, such as fractional anisotropy maps or neural fiber tractograms, are inherently prone to errors in regions such as the frontal lobe near the frontal sinus and optic chiasm in the central brain base.Reductions in geometric distortions can be accomplished via a decrease in the total data acquisition time following the RF excitation pulse, so as to reduce influences from off-resonance spins. A typical method to achieve this purpose is the multishot EPI or segmented EPI technique, which splits the series of gradient-echo acquisitions into several TRs, at the expense of possible motion artifacts (8). In DW imaging (DWI) using multishot EPI, navigator phase correction is further needed because of phase inconsistencies in the presence of involuntary motion sensitized by the DW gradients (6,7,9). Alternatively, imaging methods based on spin-echo acquisitions are intrinsically immune to off-resonance effects due to the refocusing functions of the 180°pulses. One way to achieve distortion-free DTI images is to use a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELL...