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The reticulon family has been found to induce apoptosis, inhibit axon regeneration and regulate protein trafficking. However, little is known about the mechanisms of how reticulon proteins are involved in neuronal death-promoting processes during ischemia. Here, we report that the expression of Reticulon Protein 1-C (RTN1-C) was associated with the progression of cerebral ischemia/reperfusion (I/R) injury. Using a combination of rat middle cerebral artery occlusion (MCAO) stroke and oxygen-glucose deprivation followed by reoxygenation (OGD/R) models, we determined that the expression of RTN1-C was significantly increased during cerebral ischemic/reperfusion. RTN1-C overexpression induced apoptosis and increased the cell vulnerability to ischemic injury, whereas RTN1-C knockdown reversed ischemia-induced apoptosis and attenuated the vulnerability of OGD/R-treated neural cells. Mechanistically, we demonstrated that RTN1-C mediated OGD/R-induced apoptosis through ER stress and mitochondria-associated pathways. RTN1-C interacted with Bcl-xL and increased its localization in the ER, thus reducing the anti-apoptotic activity of Bcl-xL. Most importantly, knockdown of Rtn1-c expression in vivo attenuated apoptosis in MCAO rats and reduced the extent of I/R-induced brain injury, as assessed by infarct volume and neurological score. Collectively, these data support for the first time that RTN1-C may represent a novel candidate for therapies against cerebral ischemia/reperfusion injury.

Accurate and continuous monitoring of cerebral blood flow is valuable for clinical neurocritical care and fundamental neurovascular research. Transcranial Doppler (TCD) ultrasonography is a widely used non-invasive method for evaluating cerebral blood flow 1 , but the conventional rigid design severely limits the measurement accuracy of the complex three-dimensional (3D) vascular networks and the practicality for prolonged recording 2 . Here we report a conformal ultrasound patch for hands-free volumetric imaging and continuous monitoring of cerebral blood flow. The 2 MHz ultrasound waves reduce the attenuation and phase aberration caused by the skull, and the copper mesh shielding layer provides conformal contact to the skin while improving the signal-to-noise ratio by 5 dB. Ultrafast ultrasound imaging based on diverging waves can accurately render the circle of Willis in 3D and minimize human errors during examinations. Focused ultrasound waves allow the recording of blood flow spectra at selected locations continuously. The high accuracy of the conformal ultrasound patch was confirmed in comparison with a conventional TCD probe on 36 participants, showing a mean difference and standard deviation of difference as −1.51 ± 4.34 cm s −1 , −0.84 ± 3.06 cm s −1 and −0.50 ± 2.55 cm s −1 for peak systolic velocity, mean flow velocity, and end diastolic velocity, respectively. The measurement success rate was 70.6%, compared with 75.3% for a conventional TCD probe. Furthermore, we demonstrate continuous blood flow spectra during different interventions and identify cascades of intracranial B waves during drowsiness within 4 h of recording. A conformal ultrasound patch can be used for hands-free volumetric imaging and continuous monitoring of cerebral blood flow

Bombyx mori (Lepidoptera: Bombycidae) is an important economic insect and a classic Lepidopteran model system. Although immune-related genes have been identified at a genome-wide scale in the silkworm, proteins involved in immune defense of the silkworm have not been comprehensively characterized. In this study, two types of bacteria were injected into the silkworm larvae, Gram-negative Escherichia coli (Enterobacteriales: Enterobacteriaceae), or Gram-positive Staphylococcus aureus (Bacillales: Staphylococcaceae). After injection, proteomic analyses of hemolymph were performed by liquid chromatography—tandem mass spectrometry. In total, 514 proteins were identified in the uninduced control group, 540 were identified in the E. coli-induced group, and 537 were identified in the S. aureus-induced group. Based on Uniprot annotations, 32 immunological recognition proteins, 28 immunological signaling proteins, and 21 immunological effector proteins were identified. We found that 127 proteins showed significant upregulation, including 10 immunological recognition proteins, 4 immunological signaling proteins, 11 immunological effector proteins, and 102 other proteins. Using real-time quantitative polymerase chain reaction in the fat body, we verified that immunological recognition proteins, signaling proteins, and effector proteins also showed significant increases at the transcriptional level after infection with E. coli and S. aureus. Five newly identified proteins showed upregulation at both protein and transcription levels after infection, including 30K protein, yellow-d protein, chemosensory protein, and two uncharacterized proteins. This study identified many new immune-related proteins, deepening our understanding of the immune defense system in B. mori. The data have been deposited to the iProX with identifier IPX0001337000.

Facility-based emergency care delivery in low-income and middle- income countries is expanding rapidly, particularly in Africa. Unfortunately, these efforts rarely include measurement of the quality or the impact of care provided, which is essential for improvement of care provision. Our aim was to determine context-appropriate quality indicators that will allow uniform and objective data collection to enhance emergency care delivery throughout Africa. We undertook a multiphase expert consensus process to identify, rank and refine quality indicators. A comprehensive review of the literature identified existing indicators; those associated with a substantial burden of disease in Africa were categorised and presented to consensus conference delegates. Participants selected indicators based on inclusion criteria and priority clinical conditions. The indicators were then presented to a group of expert clinicians via on-line survey; all meeting agreements were refined in-person by a separate panel and ranked according to validity, feasibility and value. The consensus working group selected seven conditions addressing nearly 75% of mortality in the African region to prioritise during indicator development, and the final product at the end of the multiphase study was a list of 76 indicators. This comprehensive process produced a robust set of quality indicators for emergency care that are appropriate for use in the African setting. The adaptation of a standardised set of indicators will enhance the quality of care provided and allow for comparison of system strengthening efforts and resource distribution.

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. Enhancer network is a gene regulation model we proposed that not only delineates the mapping between enhancers and target genes, but also quantifies the underlying regulatory relationship between enhancers. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important in enhancer networks. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. The establishment of enhancer networks drives gene expression during lineage commitment. Applying eNet in various datasets in human or mouse tissues across different single-cell platforms, we demonstrate eNet is robust and widely applicable. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells, without requiring the cell type identity in advance. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://github.com/xmuhuanglab/eNet