Differential Hydrogen/Deuterium Exchange during Proteoform Separation Enables Characterization of Conformational Differences between Coexisting Protein States

Characterization of structural differences between coexisting conformational states of protein is difficult with conventional biophysical techniques. Hydrogen/deuterium exchange (HDX) coupled with top-down mass spectrometry (MS) allows different conformers to be deuterated to different extents and distinguished through gas-phase separation based on molecular weight distributions prior to determination of deuteration levels at local sites for each isolated conformer. However, application of this strategy to complex systems is hampered by the interference from conformers with only minor differences in overall deuteration levels. In this work, we performed differential HDX while the different conformers were separated according to their differing charge to size ratios in capillary electrophoresis. Mixtures of holo- and apo-myoglobin (Mb) and disulfide isomers of lysozyme (Lyz) were characterized in a conformer-specific fashion using this strategy, followed by conformation interrogation for the sequentially eluted 2H-labeled species in real-time using top-down MS. Under mildly denaturing conditions that minimize the charge difference, disulfide isomers of Lyz were differentially labeled with 2H during separation based on their disulfide-dependent sizes. The resulting differences in deuteration pattern between these isomers are in line with their difference in covalent structural constraints set by the disulfide patterns. Under physiologically relevant conditions, we identified the segments undergoing conformational changes of Mb in the absence of the heme group by comparing the deuteration patterns of holo- and apo-Mb

Confocal image of Brdu (red) and Nestin (green) co-immunofluorescence staining in the ipsilateral SVZ 7 days after surgery.

<p>Panels A–C show staining of Brdu⁺/Nestin⁺ positive cells in the ipsilateral SVZ from Sham (A), MCAO (B), and rTMS (C) groups (Bar = 20 µm). (D) Quantification analysis of the number of Brdu⁺/Nestin⁺ positive cells in the ipsilateral SVZ 7 days after surgery. Brdu positive cells were labeled red (E), Nestin positive cells were labeled green (F) and Brdu⁺/Nestin⁺ positive cells were double-labeled (G), Bar = 20 µm. ^#<b>P<</b>0.001 for rTMS group versus Sham group; ^*<b>P</b> = 0.001 for rTMS group versus MCAO group. ^&<b>P</b> = 0.044 for MCAO group versus Sham group. SVZ, subventricular zone.</p

Infarct volume assessed by TTC staining 1 day after the tMCAO.

<p>(A) Position of SVZ in the coronal section of brain. Areas imaged for immunofluorescence studies are indicated by box. (B) Coronal brain section stained by TTC 1 day after tMCAO. The white areas without deep red-staining indicate ischemic areas. SVZ, subventricular zone.</p

Data_Sheet_1_Genetic mechanisms underlying local spontaneous brain activity in episodic migraine.docx

Advances in neuroimaging techniques during the past few decades have captured impaired functional brain activity in migraine disorders, yet the molecular mechanisms accounting for its alterations in migraine remain largely unknown. A total of 27 patients with episodic migraine (EM) and 30 matched healthy controls (HCs) underwent resting-state functional and structural magnetic resonance imaging (MRI) scans. Regional homogeneity (ReHo), low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) of fMRI were compared between the two groups. Based on the Allen Human Brain Atlas and risk genes in migraine, we identified gene expression profiles associated with ReHo alterations in EM. Compared with HCs, patients with EM showed increased ReHo in the left orbital part of the superior frontal gyrus (P < 0.05, cluster-level FWE-corrected). The expression profiles of 16 genes were significantly correlated with ReHo alterations in EM (P < 0.05/5,013, Bonferroni corrected). These genes were mainly enriched for transcription regulation, synaptic transmission, energy metabolism, and migraine disorders. Furthermore, the neural activation was positively correlated with Hamilton Rating Scale for Anxiety (HAMA) scores. To test the stability of our results, we repeated our procedure by using ALFF and fALFF and found these results had a high degree of consistency. Overall, these findings not only demonstrated that regional brain activity was increased in patients with EM, which was associated with emotional regulation but also provided new insights into the genetic mechanisms underlying these changes in migraine.</p

Antagomir-25 injection resulted in decreased proliferation of NSCs 7days after tMCAO.

<p>Panels A–C show staining of Brdu⁺(red)/Nestin⁺(green) positive cells in the ipsilateral SVZ from rTMS (A), antagomir-25/rTMS (B), and control antagomir/rTMS (C) groups(Bar = 20 µm). (D) Quantification analysis of the number of Brdu⁺/Nestin⁺ positive cells in the ipsilateral SVZ at 7 days after tMCAO. ^#<b>P</b> = 0.006 versus rTMS group; ^*<b>P</b> = 0.013 versus Scr group. SVZ, subventricular zone.</p

Experimental protocol.

<p>Experimental protocol.</p

Effects of Ant-25 and Scr on p21 and p57 in the ischemic cortex 7 days after surgery.

<p>(A) Electrophoresis of p21, p57 and GAPDH on gel. (B) Relative levels of p21 and p57 protein from the different groups. ^#<b>P</b> = 0.018 compared to the rTMS group; ^*<b>P</b> = 0.012 compared to the Scr group.</p

Neurobehavioral function was improved by rTMS after cerebral ischemia.

<p>NSSs were improved in MCAO rats treated with rTMS as compared with other groups. Data are presented as mean±SD. ^&P<0.001 versus Sham group. ^*P = 0.005 for MCAO group between day 7 and day 1. ^**P<0.001 for rTMS group between day 7 and day 1. ^#P = 0.019 between rTMS group and MCAO group 7 days after surgery.</p

Expression changes of p57 and PTEN in the ipsilateral cortex 7 days after surgery.

<p>(A) Electrophoresis of p57, PTEN and GAPDH on gel. (B) The ratio of the target genes to GAPDH in different groups. ^#<b>P</b> = 0.005 for p57 compared to the Sham group; ^#<b>P</b> = 0.004 for PTEN compared to the Sham group; ^*<b>P</b> = 0.007 for PTEN compared to MCAO group.</p

Dynamic prediction of hypoxemia risk at different time points based on preoperative and intraoperative features: machine learning applications in outpatients undergoing esophagogastroduodenoscopy

Hypoxemia often occurs in outpatients undergoing anesthesia-assisted esophagogastroduodenoscopy (EGD). However, there is a scarcity in tools to predict the hypoxemia risk. We aimed to solve this problem by developing and validating machine learning (ML) models based on preoperative and intraoperative features. All data were retrospectively collected from June 2021 to February 2022. The most appropriate predictive features were selected by the least absolute shrinkage and selection operator, which were incorporated and modelled by 4 ML algorithms. The area under the precision-recall curve (AUPRC) was used as the main evaluation metric to select the best models, and the selected models were compared with the STOP-BANG score. Their predictive performance was visually interpreted by SHapley Additive exPlanations. The primary endpoint of this study was hypoxemia during the procedure, defined as at least one reading of pulse oximetry Of 1160 patients in the derivation cohort, 112 patients (9.6%) developed intraoperative hypoxemia, of which 102 (8.8%) occurred during the induction period. In temporal and external validation, no matter whether based on preoperative variables or still based on preoperative plus intraoperative variables, our models showed excellent predictive performance for the two endpoints, significantly better than STOP-BANG score. In the model interpretation section, preoperative variables (airway assessment indicators, pulse oximeter oxygen saturation and BMI) and intraoperative variables (the induced propofol dose) made the highest contribution to the predictions. To our knowledge, our ML models were the first to predict hypoxemia risk, which achieved excellent overall predictive ability integrating various clinical indicators. These models have the potential to become an effective tool for adjusting sedation strategies flexibly and reducing the workload of anesthesiologists.KEY MESSAGESThis study is the first model employing ML methods based on preoperative and preoperative plus intraoperative variables for predicting the risk of hypoxemia during induction and the whole EGD procedure respectively.Our four models achieved satisfactory predictive performance and outperformed STOP-BANG score in terms of AUPRC in the temporal and external validation cohorts respectively.We found that the relevant variables of airway assessment should be fully taken into account when analyzing the risk factor of hypoxemia, and the effect of patients’ age on their hypoxemia risk should be considered in conjunction with the propofol dose. This study is the first model employing ML methods based on preoperative and preoperative plus intraoperative variables for predicting the risk of hypoxemia during induction and the whole EGD procedure respectively. Our four models achieved satisfactory predictive performance and outperformed STOP-BANG score in terms of AUPRC in the temporal and external validation cohorts respectively. We found that the relevant variables of airway assessment should be fully taken into account when analyzing the risk factor of hypoxemia, and the effect of patients’ age on their hypoxemia risk should be considered in conjunction with the propofol dose.</p