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Introduction: The Enhanced Control of Hypertension and Thrombolysis Stroke Study (ENCHANTED) showed that a low-dose alteplase was safe but not clearly non-inferior to standard-dose alteplase in acute ischemic stroke (AIS). Given the significant cost of this medicine, we undertook a cost-effectiveness analysis to determine the probability that low-dose is cost-effective relative to standard-dose alteplase in China. Methods: For ENCHANTED participants in China with available health cost data, cost-effectiveness and cost-utility analyses were undertaken in which death or disability (modified Rankin scale scores 2–6) at 90 days and quality-adjusted life-years (QALYs) were used as outcome measures, respectively. There was adherence to standard guidelines for health economic evaluations alongside non-inferiority trials and according to a health-care payer’s perspective. The equivalence margin for cost and effectiveness was set at USD 691 and −0.025 QALYs, respectively, for the base-case analysis. Probabilistic sensitivity analyses were used to evaluate the probability of low-dose alteplase being non-inferior. Results: While the mean cost of alteplase was lower in the low-dose group (USD 1,569 vs. USD 2,154 in the standard-dose group), the total cost was USD 56 (95% confidence interval [CI]: −1,000–1,113) higher compared to the standard-dose group due to higher hospitalization costs in the low-dose group. There were 462 (95% CI: 415–509) and 410 (95% CI: 363–457) patients with death or disability per 1,000 patients in the low-dose and standard-dose groups, respectively. The low-dose group had marginally lower (0.008, 95% CI: −0.016–0.001) QALYs compared to their standard-dose counterparts. The low-dose group was found to have an 88% probability of being non-inferior based on cost-effectiveness versus the standard-dose group. Conclusions: This health economic evaluation alongside the ENCHANTED indicates that the use of low-dose alteplase does not save overall healthcare costs nor lead to a gain in QALYs in the management of Chinese patients with AIS compared to the use of standard dose. There is little justification on economic grounds to shift from standard-of-care thrombolysis in AIS.

抽象 本文在地域上將粵東潮陽地區分為郊區與中心區，基於陰上調的讀音差異，將發音人區分為老派和新派，通過詳細考察這「兩區四派」共81位發音人的聲調材料，發現該地區的聲調在地域及年齡上的共時變異可用兩條鏈式演化加以解釋：一是陰上調的槽形鏈移，陰上由高緩降演變為高平（或中平），繼而演變為微升（或高升）；二是陰上、陽去、陰平參與的拉鏈鏈移，該鏈移由陰上的變化啟動，利用聲調的人際差異可確定聲調的演化方向。本文還以潮陽郊區方言23位老派發音人為例，分析其聲調系統中四個降調的對立實質，發現斜率是兩個高降調（高緩降與高直降）的最主要的區別特徵，時長則是重要的伴隨特徵。潮陽地區四降調系統的演化過程體現了漢語方言聲調發展的一個趨勢，即朝著曲拱對立更為豐富的格局發展。

Aim To expand our current understanding of the genetic basis of subarachnoid hemorrhage (SAH), and reveal the susceptibility genes in SAH risk. Methods We conducted whole-exome sequencing (WES) in a cohort of 196 individuals, including 94 SAH patients and 94 controls, as well as 8 samples that belong to two pedigrees. Systematically examination for rare variations (through direct genotyping) and common variations (through genotyping and imputation) for SAHs were performed in this study. Results A total of 16,029 single-nucleotide polymorphisms (SNPs) and 108,999 short indels were detected in all samples, and among them, 30 SNPs distributed on 17 genes presented a strong association signal with SAH. Two novel pathogenic gene variants were identified as associated risk loci, including mutation in TPO and PALD1. The statistical analysis for rare, damaging variations in SAHs identified several susceptibility genes which were involved in degradation of the extracellular matrix and transcription factor signal pathways. And 25 putative pathogenic genes for SAH were also identified basic on functional interaction network analysis with the published SAH-associated genes. Additionally, pedigree analysis revealed autosomal dominant inheritance of pathogenic genes. Conclusion Systematical analysis revealed a key role for rare variations in SAH risk and discovered SNPs in new complex loci. Our study expanded the list of candidate genes associated with SAH risk, and will facilitate the investigation of disease-related mechanisms and potential clinical therapies.

The aim of this multicenter study was to demonstrate the distribution pattern of atherosclerotic stenosis and its trend with aging between extracranial and intracranial arteries and its distribution between the anterior and posterior circulations in Chinese patients hospitalized with ischemic stroke. In addition, the risk factors for the distribution pattern were illustrated. From June 2015 to May 2016, 9,346 patients with ischemic stroke from 20 hospitals were enrolled. Carotid artery ultrasonography and transcranial color-coded sonography/transcranial Doppler were used to evaluate the extracranial and intracranial arteries. The distribution pattern of atherosclerotic stenosis and its trend with aging were analyzed. Logistic regression was used to analyze the risk factors for the distribution pattern. Among the 9,346 patients, 2,882 patients (30.8%) had at least one artery with a degree of stenosis ≥50%. Among patients with arterial stenosis, the proportion of patients with intracranial artery stenosis was higher than those with extracranial artery stenosis (52.6% vs. 27.6%), and the proportion of anterior circulation artery stenosis was higher than that in the posterior circulation (52.2% vs.26.2%). With aging, the proportion of intracranial artery stenosis alone decreased; at the same time, the proportion of extracranial artery stenosis and extracranial plus intracranial artery stenosis increased (trend χ2=6.698, P=0.001). Hypertension (OR 1.416, P=0.008) and family history of stroke (OR 1.479, P=0.014) were risk factors for intracranial artery stenosis. Male, aging, and smoking were factors more related to extracranial artery stenosis. Aging (OR 1.022, P

This chapter deals with the tonal development in the Chaoyang area, with a special focus on the change of T2a. The age-related differences and geographical variations can be accounted for by two tonal chain shifts: one is the groove chain shift of Yinshang (T2a), in which T2a has changed from a high convex falling tone to a high level tone (or middle level tone), and subsequently a rising tone; the other is the pull chain shift involving Yinping (T1a), Yinshang (T2a) and Yangqu (T3b), whose initiator is T2a. The direction of this pull chain shift is determined by the tonal variations of different speakers. The features of four falling tones are discussed on the basis of the firsthand acoustic data of 23 older speakers in the suburban area. We argue that slope is the main distinct feature of the two high falling tones, with length an important supplementary feature. The evolution trend of the four-falling-tone system in the Chaoyang area is towards the system with diversified pitch contours.

This chapter examines the checked tones of Chaoshan dialects with an abundant of firsthand acoustic data. By comparing with Fujian Jinjiang dialect, an evolutionary path for checked tones of Chaoshan dialects is proposed. At the first stage, the pattern of checked tones of Chaoshan dialects is the same as that in Zhangquan dialect, such as Jinjiang dialect, being “Yin-high versus yang-low”; At the second stage, the pattern of checked tones is “Yin-mid-falling versus yang-mid-rising”, and just like the case in Yun’ao dialect; At the third stage, the pattern of checked tones is “Yin-falling-low versus yang-rising-high”, and the example is drawn from Dahao daielct. The last stage is “Yin-low versus yang-high”, which can be found in most Chaoshan dialects. We argue that the historical “flip-flop” of Chaoshan checked tones is not a sudden change, but is accomplished via a process of gradual phonetic change. Being the transitional stages, Yun’ao and Dahao dialects are characterized by distinctive pitch contours, which are triggered by different phonation types. Experimental measures of acoustic cues using data from ten Yun’ao and Shen’ao speakers confirm that there are different phonation types in T4a and T4b, with creaky voice in T4a and fortis voice (the final glottal stop) in T4b, respectively.

This chapter deals with the tone evolutions in the Huipu area. Two tonal chain shifts are proposed to account for the diversified tonal patterns within this area. The V-shaped shift involving the downward shift of falling tones and the upward shift of rising tones, can explain the tonal development from Jinghai dialect to Liusha dialect. The downward chain shift of level tones is hypothesized to explain the age-related differences of Jinghai dialect. At the same time, tonal merger will serve as an obstacle to interrupt these tonal shifts, such as the case in central Huilai County where falling tone’s downward shift is blocked by the merger of T3a and T3b.

With the fast development of various techniques, more and more data have been accumulated with the unique properties of large size (tall) and high dimension (wide). The era of big data is coming. How to understand and discover new knowledge from these data has attracted more and more scholars' attention and has become the most important task in data mining. As one of the most important techniques in data mining, clustering analysis, a kind of unsupervised learning, could group a set data into objectives(clusters) that are meaningful, useful, or both. Thus, the technique has played very important role in knowledge discovery in big data. However, when facing the large-sized and high-dimensional data, most of the current clustering methods exhibited poor computational efficiency and high requirement of computational source, which will prevent us from clarifying the intrinsic properties and discovering the new knowledge behind the data. Based on this consideration, we developed a powerful clustering method, called MUFOLD-CL. The principle of the method is to project the data points to the centroid, and then to measure the similarity between any two points by calculating their projections on the centroid. The proposed method could achieve linear time complexity with respect to the sample size. Comparison with K-Means method on very large data showed that our method could produce better accuracy and require less computational time, demonstrating that the MUFOLD-CL can serve as a valuable tool, at least may play a complementary role to other existing methods, for big data clustering. Further comparisons with state-of-the-art clustering methods on smaller datasets showed that our method was fastest and achieved comparable accuracy. For the convenience of most scholars, a free soft package was constructed.

Background and Purpose— Advanced imaging to identify tissue pathophysiology may provide more accurate prognostication than the clinical measures used currently in stroke. This study aimed to derive and validate a predictive model for functional outcome based on acute clinical and advanced imaging measures. Methods— A database of prospectively collected sub-4.5 hour patients with ischemic stroke being assessed for thrombolysis from 5 centers who had computed tomographic perfusion and computed tomographic angiography before a treatment decision was assessed. Individual variable cut points were derived from a classification and regression tree analysis. The optimal cut points for each assessment variable were then used in a backward logic regression to predict modified Rankin scale (mRS) score of 0 to 1 and 5 to 6. The variables remaining in the models were then assessed using a receiver operating characteristic curve analysis. Results— Overall, 1519 patients were included in the study, 635 in the derivation cohort and 884 in the validation cohort. The model was highly accurate at predicting mRS score of 0 to 1 in all patients considered for thrombolysis therapy (area under the curve [AUC] 0.91), those who were treated (AUC 0.88) and those with recanalization (AUC 0.89). Next, the model was highly accurate at predicting mRS score of 5 to 6 in all patients considered for thrombolysis therapy (AUC 0.91), those who were treated (0.89) and those with recanalization (AUC 0.91). The odds ratio of thrombolysed patients who met the model criteria achieving mRS score of 0 to 1 was 17.89 (4.59–36.35, P P Conclusions— This study has derived and validated a highly accurate model at predicting patient outcome after ischemic stroke.

Background and Purpose: The benefit of thrombolysis in ischemic stroke patients without a visible vessel occlusion still requires investigation. This study tested the hypothesis that non-lacunar stroke patients with no visible vessel occlusion on baseline imaging would have a favorable outcome regardless of treatment with alteplase.Methods: We utilized a prospectively collected registry of ischemic stroke patients [the International Stroke Perfusion Imaging Registry (INSPIRE)] who had baseline computed tomographic perfusion and computed tomographic angiography. The rates of patients achieving modified Rankin Scale (mRS) 0–1 were compared between alteplase treated and untreated patients using logistic regression to generate odds ratios.Results: Of 1569 patients in the INSPIRE registry, 1,277 were eligible for inclusion. Of these, 306 (24%) had no identifiable occlusion and were eligible for alteplase, with 141 (46%) of these patients receiving thrombolysis. The treated and untreated groups had significantly different median baseline National Institutes of Health Stroke Scale (NIHSS) [alteplase 8, interquartile range (IQR) 5–10, untreated 6, IQR 4–8, P < 0.001] and median volume of baseline perfusion lesion [alteplase 5.6 mL, IQR 1.3–17.7 mL, untreated 2.6 mL, IQR 0–6.7 mL, P < 0.001]. After propensity analysis, alteplase treated patients without a vessel occlusion were less likely to have an excellent outcome (mRS 0–1; 56%) than untreated (78.8%, OR, 0.42, 95% confidence interval, 0.24–0.75, P = 0.003).Conclusions: In this non-randomized comparison, alteplase treatment in patients without an identifiable vessel occlusion did not result in higher rates of favorable outcome compared to untreated. However, treated patients displayed less favorable baseline prognostic factors than the untreated group. Further studies may be required to confirm this data.

Introduction The use of multimodal computed tomography imaging (MMCT) in routine clinical assessment of stroke patients improves the identification of patients with large regions of salvageable brain tissue, lower risk for haemorrhagic transformation, or a large vessel occlusion requiring endovascular therapy. Aim To evaluate the cost-effectiveness of using MMCT compared to usual practice for determining eligibility for reperfusion therapy with alteplase using real world data from the International Stroke Perfusion Imaging Registry (INSPIRE). Methods We performed a cost-utility analysis. Mean costs and quality-adjusted life years (QALYs) per patient for two alternative screening protocols were calculated. Protocol 1 represented usual practice, while Protocol 2 reflected treatment targeting using multimodal imaging. Cost-effectiveness was assessed using the net-benefit framework. Results Protocol 1 had a total mean per patient cost of $2,013 USD and 0.148 QALYs. Protocol 2 had a total mean per patient cost of $1,519 USD and 0.153 QALYs. For a range of willingness-to-pay values, representing implicit thresholds of cost-effectiveness, the lower bound of the incremental net monetary benefit statistic was consistently greater than zero, indicating that MMCT is cost- effective compared to usual practice. The results were most sensitive to variation in the mean number of alteplase vials administered. Conclusion In a healthcare setting where multimodal imaging technologies are available and reimbursed, their use in screening patients presenting with acute stroke to determine eligibility for alteplase treatment is cost-effective given a range of willingness-to-pay thresholds and warrants consideration as an alternative to routine practice.

In recent years in silico protein structure prediction reached a level where fully automated servers can generate large pools of near-native structures. However, the identification and further refinement of the best structures from the pool of models remain problematic. To address these issues, we have developed (i) a target-specific selective refinement (SR) protocol; and (ii) molecular dynamics (MD) simulation based ranking (SMDR) method. In SR the all-atom refinement of structures is accomplished via the Rosetta Relax protocol, subject to specific constraints determined by the size and complexity of the target. The best-refined models are selected with SMDR by testing their relative stability against gradual heating through all-atom MD simulations. Through extensive testing we have found that Mufold-MD, our fully automated protein structure prediction server updated with the SR and SMDR modules consistently outperformed its previous versions.

Protein structure Quality Assessment (QA) is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA. In this work, we developed a new Hidden Markov Model (HMM) to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities: (1) encoding local structure of each position by jointly considering sequence and structure information, and (2) assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP, and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets.

Introduction: Stroke shortens an individual’s disability-free life. We aimed to assess the relative prognostic influence of pre- and post-treatment perfusion CT imaging variables (e.g. ischemic core and penumbral volumes) compared to standard clinical predictors (such as onset-to-treatment time) on long-term stroke disability in patients undergoing thrombolysis. Methods: We used data from a prospectively collected international, multicenter, observational registry of acute ischemic stroke patients who had perfusion CT and CT angiography before treatment with intravenous alteplase. Baseline perfusion CT and follow-up MRI were analysed to derive the baseline penumbra volume, baseline ischemic core volume, and penumbra salvaged from infarction. The primary outcome measure was the effect of imaging and clinical variables on disability-adjusted life years (DALY). Clinical variables were age, sex, NIHSS score, and onset-to-treatment time. Age, sex, country, and 3-month modified Rankin Scale were extracted from the registry to calculate DALY due to stroke, such that one year of DALY equates to 1 year of healthy life lost due to stroke. Results: Seven hundred seventy two patients were treated with alteplase therapy. 17.5 DALY-days were lost per 1 mL of baseline ischemic core volume (95%CI, 13.2 - 21.9 days, p < 0.001). For every mL of penumbra salvaged, 7.2 days of DALY-days were saved (95%CI, 4.1 - 10.4 days, p < 0.001). Each minute of earlier onset-to-treatment time resulted in a saving of 4.4 disability-free days after stroke (1.3 - 7.5 days, p = 0.006). However, after adjustment for imaging variables, onset-to-treatment time was not significantly associated with savings in DALY-days. Conclusions: Pre-treatment perfusion CT scan defined penumbra (independently of clinical variables) predict significant gains, or loss, of disability-free life in patients undergoing reperfusion therapy for stroke. The effect of earlier treatment on disability-free life appears explained by salvage of penumbra.

Objective To evaluate the effect of acute arterial ischemic stroke patients with atrial fibrillation in embolectomy and thrombolytic therapy with intravenous rt-PA which benefit more. Methods Consecutive patients from January 2012 to December 2016 to the Baotou Central Hospital for treatment of acute ischemic stroke with atrial fibrillation. The study group included direct arterial embolectomy and thrombolysis interventional therapy bridging collected 20 cases; the control group received intravenous thrombolysis group. According to the patient treatment group, compared with the general situation, the history of stroke risk factors, onset to treatment time, admission, immediately after surgery, postoperative 24h, postoperative 72h NIHSS score, 90dmRS score, complications, mortality and other indicators, evaluation for arteries from Suppository, intravenous thrombolysis bridged endovascular treatment, curative effect, simple intravenous thrombolysis and three treatment safety, nerve function recovery of patients.Results 68 cases with atrial fibrillation were recruited, the study group of 34 cases, 24 cases were selected into the thrombectomy group, 10 cases were bridging group (intravenous thrombolysis bridging artery stent thrombectomy), the control group of 34 cases, 2 cases were lost, 32 cases were effective. The results showed that no significant difference between the two group survival of patients, the difference was not statistically significant. Excluding the preoperative NIHSS score u22647 cases, results showed that the two groups had no significant difference in the survival of patients. Conclusion With atrial fibrillation in patients with AIS artery embolectomy and thrombolytic therapy can benefit. But no obvious benefit in bridging artery embolectomy intravenous thrombolytic therapy.

Objective This study aims to analyse the causes of complications of acute ischemic stroke mechanical thrombectomy treatment. Methods 115 patients data were collected from with acute ischemic stroke treated with Solitaire AB stent mechanical embolization from January 2013 to December 2016 in Baotou Central Hospital Department of Neurology (Including intravenous thrombolysis after bridging mechanical thrombectomy, mechanical embolization compound arterial thrombolysis, balloon dilatation, stent implantation and other treatment ). Results Among the 115 cases of mechanical thrombectomy, 41 cases (35.65%) were complicated. There was no significant difference in the incidence of complications between different occlusive vessels; The incidence of complications in mechanical thrombectomy alone IS 35%uff0814/40uff09uff0ccompound embolization mechanical thrombectomy IS 36%uff0827/75uff09uff0cThe incidence of complications was statistically analyzed by chi-square testuff0cThe difference was not statistically significantuff08Puff1e0.05uff09. Conclusion The incidence of complications of anterior circulation mechanical thrombectomy is higher but there was no significant difference in the incidence of complications anterior and posterior circulation.There was no significant difference between the two groups in the occurrence of complications on mechanical thrombectomy alone and compound embolization mechanical thrombectomy,security is similar.

Objective This study aims to analyse the causes of complications of acute ischemic stroke mechanical thrombectomy treatment. Methods 115 patients data were collected from with acute ischemic stroke treated with Solitaire AB stent mechanical embolization from January 2013 to December 2016 in Baotou Central Hospital Department of Neurology (Including intravenous thrombolysis after bridging mechanical thrombectomy, mechanical embolization compound arterial thrombolysis, balloon dilatation, stent implantation and other treatment ). Results Among the 115 cases of mechanical thrombectomy, 41 cases (35.65%) were complicated. There was no significant difference in the incidence of complications between different occlusive vessels; The incidence of complications in mechanical thrombectomy alone IS 35%uff0814/40uff09uff0ccompound embolization mechanical thrombectomy IS 36%uff0827/75uff09uff0cThe incidence of complications was statistically analyzed by chi-square testuff0cThe difference was not statistically significantuff08Puff1e0.05uff09. Conclusion The incidence of complications of anterior circulation mechanical thrombectomy is higher but there was no significant difference in the incidence of complications anterior and posterior circulation.There was no significant difference between the two groups in the occurrence of complications on mechanical thrombectomy alone and compound embolization mechanical thrombectomy,security is similar.

The prognostic importance of the speed of early hematoma growth in acute intracerebral hemorrhage (ICH) has not been well established. We aimed to determine the association between the rate of increase in hematoma volume and major clinical outcomes in the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT) studies. The effects of early intensive blood pressure (BP) lowering according to the speed of hematoma growth were also investigated.Pooled analyses of the INTERACT1 (n = 404) and INTERACT2 (n = 2,839) studies-randomized controlled trials of patients with spontaneous ICH with elevated systolic BP, randomly assigned to intensive (target systolic BP140 mm Hg) or guideline-based (180 mm Hg) BP management. The speed of ultraearly hematoma growth (UHG) was defined as hematoma volume (mL)/onset-to-CT time (hours). Primary outcome was death or major disability (modified Rankin Scale score of 3-6) at 90 days.Among a total of 2,909 patients (90%) with information on UHG and outcome, median speed of UHG was 6.2 mL/h. There was a linear association between UHG and outcome: multivariable-adjusted odd ratios 1.90 (95% confidence interval 1.50-2.39) for 5-10 mL/h and 2.96 (2.36-3.71) for10 mL/h vs the5 mL/h group. There were no clear differences in the effects of intensive BP lowering according to 3 speeds of UHG on outcome (p = 0.75 for homogeneity).The speed of UHG in patients with ICH was continuously associated with increased risks of death or major disability, and from lower levels than previously reported (≥5 mL/h). The benefits of intensive BP lowering appear to be independent of the speed of bleeding.

Schwann cells (SCs) are the myelin forming cells in the peripheral nervous system, they play a key role in the pathology of various polyneuropathies and provide trophic support to axons via expression of various neurotrophic factors, such as nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF). Ethanol (EtOH) adversely affected both SCs proliferation and myelin formation in culture. Resveratrol (Res) has been shown to regulate many cellular processes and to display multiple protective and therapeutic effects. Whether Res has protective effects on SCs with EtOH-induced toxicity is still unclear. The protective efficacy of Res on EtOH-treated SCs in vitro was investigated in the present study. Res improved cell viability of the EtOH-treated SCs. Hoechst 33342 staining and terminal deoxynucleotidyl transferase (TdT)-mediated deoxyuridine triphosphate nick-end labeling analysis showed that the EtOH-induced apoptosis was inhibited by Res. The effects of Res were blocked by the 5′-adenosine monophosphate-activated protein kinase inhibitor Compound C and the silencing information regulator T1 inhibitor nicotinamide. Res could increase the mRNA and protein levels of BDNF and GDNF in the EtOH-treated SCs. However, the EtOH-induced increase of NGF in the SCs is inhibited by Res. The data from the present study indicate that Res protects SCs from EtOH-induced cell death and regulates the expression of neurotrophic factors. Res and its derivative may be effective for the treatment of neuropathic diseases induced by EtOH.

While more than a thousand protein kinases (PK) have been identified in the Arabidopsis thaliana genome, relatively little progress has been made toward identify- ing their individual client proteins. Herein we describe the use of a mass spectrometry-based in vitro phosphorylation strategy, termed Kinase Client assay (KiC assay), to study a targeted- aspect of signaling. A synthetic peptide library comprising 377 in vivo phosphorylation sequences from developing seed was screened using 71 recombinant A. thaliana PK. Among the initial results, we identified 23 proteins as putative clients of 17 PK. In one instance protein phosphatase inhibitor-2 (AtPPI-2) was phosphorylated at multiple- sites by three distinct PK, casein kinase1-like 10, AME3, and a Ser PK-like protein. To confirm this result, full-length recombinant AtPPI-2 was reconstituted with each of these PK. The results confirmed multiple distinct phosphorylation sites within this protein. Biochemical analyses indicate that AtPPI-2 inhibits type 1 protein phosphatase (TOPP) activity, and that the phosphorylated forms of AtPPI-2 are more potent inhibitors. Structural modeling revealed that phosphorylation of AtPPI-2 induces conformational changes that modulate TOPP binding.

De novo protein structure prediction often generates a large population of candidates (models), and then selects near-native models through clustering. Existing structural model clustering methods are time consuming due to pairwise distance calculation between models. In this paper, we present a novel method for fast model clustering without losing the clustering accuracy. Instead of the commonly used pairwise root mean square deviation and TM-score values, we propose two new distance measures, Dscore1 and Dscore2, based on the comparison of the protein distance matrices for describing the difference and the similarity among models, respectively. The analysis indicates that both the correlation between Dscore1 and root mean square deviation and the correlation between Dscore2 and TM-score are high. Compared to the existing methods with calculation time quadratic to the number of models, our Dscore1-based clustering achieves a linearly time complexity while obtaining almost the same accuracy for near-native model selection. By using Dscore2 to select representatives of clusters, we can further improve the quality of the representatives with little increase in computing time. In addition, for large size (~500 k) models, we can give a fast data visualization based on the Dscore distribution in seconds to minutes. Our method has been implemented in a package named MUFOLD-CL, available at http://mufold.org/clustering.php.

See Saver (doi:10.1093/awx020) for a scientific commentary on this article.Stroke shortens an individual's disability-free life. We aimed to assess the relative prognostic influence of pre- and post-treatment perfusion computed tomography imaging variables (e.g. ischaemic core and penumbral volumes) compared to standard clinical predictors (such as onset-to-treatment time) on long-term stroke disability in patients undergoing thrombolysis. We used data from a prospectively collected international, multicentre, observational registry of acute ischaemic stroke patients who had perfusion computed tomography and computed tomography angiography before treatment with intravenous alteplase. Baseline perfusion computed tomography and follow-up magnetic resonance imaging were analysed to derive the baseline penumbra volume, baseline ischaemic core volume, and penumbra salvaged from infarction. The primary outcome measure was the effect of imaging and clinical variables on Disability-Adjusted Life Year. Clinical variables were age, sex, National Institutes of Health Stroke Scale score, and onset-to-treatment time. Age, sex, country, and 3-month modified Rankin Scale were extracted from the registry to calculate disability-adjusted life-year due to stroke, such that 1 year of disability-adjusted life-year equates to 1 year of healthy life lost due to stroke. There were 772 patients receiving alteplase therapy. The number of disability-adjusted life-year days lost per 1 ml of baseline ischaemic core volume was 17.5 (95% confidence interval, 13.2-21.9 days, P < 0.001). For every millilitre of penumbra salvaged, 7.2 days of disability-adjusted life-year days were saved (β = -7.2, 95% confidence interval, -10.4 to -4.1 days, P < 0.001). Each minute of earlier onset-to-treatment time resulted in a saving of 4.4 disability-free days after stroke (1.3-7.5 days, P = 0.006). However, after adjustment for imaging variables, onset-to-treatment time was not significantly associated with savings in disability-adjusted life-year days. Pretreatment perfusion computed tomography can (independently of clinical variables) predict significant gains, or loss, of disability-free life in patients undergoing reperfusion therapy for stroke. The effect of earlier treatment on disability-free life appears explained by salvage of penumbra, particularly when the ischaemic core is not too large.

The study aimed to analyze the influencing factors of thrombolysis therapy in acute ischemic stroke patients with onset time less than 4.5 hours.We consecutively prospectively screened acute ischemic stroke patients with onset time less than 4.5 hours from emergency department, outpatients and inpatients of neurology department, and image center in our hospital over a 31-month time period (April 2012-November 2014). The rate of thrombolysis and the reasons for not receiving thrombolysis were analyzed.A total of 538 patients who met the inclusion criteria were included (68.2% males, mean age 67±13 years old). Only 104 (19.3%) patients received thrombolysis. The main reasons for the patients not receiving thrombolysis included minor symptoms (172 cases, 39.6%), rapidly improving symptoms and high possibility of transient ischemic attack (TIA) (59 cases, 13.6%), patients or families refusing thrombolysis (44, 10.1%), in-hospital delay (38, 8.8%), elderly people with age over than 80 years old (38, 8.8%).The thrombolysis rate within time window of acute ischemic stroke is remarkably higher than that of several years ago in China. The main reasons for not receiving thrombolysis are minor and rapidly improving symptoms, patients or families' refusal, in-hospital delay, elderly people with age over than 80 years old.

In present study, novel composite nanocarriers comprised of O-carboxymethyl chitosan/β-cyclodextrin (O-CMC/β-CD) nanoparticles (NPS) were prepared and used to improve the bioavailability of hydrophobic drugs. Ibuprofen (IBU) was selected as a model drug and chitosan/β-CD (CS/β-CD) NPS were also prepared as control. The prepared NPS were characterized by FT-IR spectroscopy and X-ray diffraction. IBU entrapment of up to 93.25 ± 2.89% was obtained as determined by UV spectrophotometer. The NPS were spherical in shape with average particle sizes of 166 nm. The in vitro release studies were performed in simulated gastric medium (pH 1.2) and simulated intestinal medium (pH 6.8). The release rate of IBU from the O-CMC/β-CD NPS was slower than CS/β-CD NPS in simulated gastric medium. However, the converse tendency was observed in simulated intestinal medium. These results suggested that O-CMC/β-CD NPS were more suitable for the oral delivery of hydrophobic drugs compared with the CS/β-CD NPS.

Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy.

There have been steady improvements in protein structure prediction during the past 2 decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. Toward achieving more accurate and efficient structure prediction, we developed a number of novel methods and integrated them into a software package, MUFOLD. First, a systematic protocol was developed to identify useful templates and fragments from Protein Data Bank for a given target protein. Then, an efficient process was applied for iterative coarse-grain model generation and evaluation at the Calpha or backbone level. In this process, we construct models using interresidue spatial restraints derived from alignments by multidimensional scaling, evaluate and select models through clustering and static scoring functions, and iteratively improve the selected models by integrating spatial restraints and previous models. Finally, the full-atom models were evaluated using molecular dynamics simulations based on structural changes under simulated heating. We have continuously improved the performance of MUFOLD by using a benchmark of 200 proteins from the Astral database, where no template with25% sequence identity to any target protein is included. The average root-mean-square deviation of the best models from the native structures is 4.28 A, which shows significant and systematic improvement over our previous methods. The computing time of MUFOLD is much shorter than many other tools, such as Rosetta. MUFOLD demonstrated some success in the 2008 community-wide experiment for protein structure prediction CASP8.

Tandem mass spectra contain noisy peaks which make peak picking for peptide identification difficult. Moreover, all spectral peaks can be shifted due to systematic measurement errors. In this paper, a novel use of an isotope pattern vector (IPV) is proposed for denoising and systematic measurement error prediction. By matching the experimental IPVs with the theoretical IPVs of candidate fragment ions, true ionic peaks can be identified. Furthermore, these identified experimental IPVs and their corresponding theoretical IPVs are used in an optimization process to predict the systematic measurement error associated with the target spectrum. In return, the subsequent spectral data calibration based on the predicted systematic measurement error enhances the data quality. We show that such an integrated denoising and calibration process leads to significantly improved peptide and protein identification. Different from the commonly employed chemical calibration methods, our IPV-based method is a purely computational method for individual spectra analysis and globally optimizes the use of spectral data.

We present a new preprocessing method, PeakSelect, to improve the accuracy and efficiency of Tandem Mass-Spec peptide (protein) identification. The fundamental difference between noise and fragment ions in spectra is that ions have isotopes but noise does not. We propose a new and important concept of an Isotope Pattern Vector (IPV) which characterizes the isotope cluster of fragment ions. Then the noise and real peaks can be distinguished by the quantitative IPV values. PeakSelect first uses a new method of the Gaussian Mixture Model and Expectation-Maximization (EM) algorithm to find the base intensity level (baseline) in a spectrum. Then PeakSelect selects features based on the IPV and baseline, and constructs a decision tree to automatically classify the peaks into different categories such as noise, single ion peaks, and overlapping peaks. Experiments show that PeakSelect can help to reduce the Mascot searching time and increase the reliability of peptide identifications. In particular, PeakSelect performs well on complex spectra with a large number of peaks from large peptides, and supports more sequence identification than other well-known systems.

In protein identification through tandem mass spectrometry, it is critical to accurately predict the theoretical spectrum for a peptide sequence. The widely used prediction models, such as SEQUEST and MASCOT, ignore the intensity of the ions with important neutral losses, including water loss and ammonia loss. However, ignoring these neutral losses results in a significant deviation between the predicted theoretical spectrum and its experimental counterpart. Here, based on the "one peak, multiple explanations" observation, we proposed an expectation-maximization (EM) method to automatically learn the probabilities of water loss and ammonia loss for each amino acid. Then we employed these probabilities to design an improved statistical model for theoretical spectrum prediction. We implemented these methods and tested them on practical data. On a training set containing 1803 spectra, the experimental results show a good agreement with some known knowledge about neutral losses, such as the tendency of water loss from Asp, Glu, Ser, and Thr. Furthermore, on a testing set containing 941 spectra, the improved similarity between the experimental and predicted spectra demonstrates that this method can generate more reasonable predictions relative to the model that ignores neutral losses. As an application of the derived probabilities, we implemented a database searching method adopting the improved theoretical spectrum model with neutral loss ions estimated. Experimental results on Keller's data set demonstrate that this method can identify peptides more accurately than SEQUEST. In another application to validate SEQUEST's results, the reported peptide-spectrum pairs are reranked with respect to the similarity between experimental and predicted spectra. Experimental results on both LTQ and QSTAR data sets suggest that this reranking strategy can effectively distinguish the false negative predictions reported by SEQUEST.