Proximal binding of dCas9 at a DNA double strand break stimulates homology-directed repair as a local inhibitor of classical non-homologous end joining.

In CRISPR/Cas9 genome editing, the tight and persistent target binding of Cas9 provides an opportunity for efficient genetic and epigenetic modification on genome. In particular, technologies based on catalytically dead Cas9 (dCas9) have been developed to enable genomic regulation and live imaging in a site-specific manner. While post-cleavage target residence of CRISPR/Cas9 could alter the pathway choice in repair of Cas9-induced DNA double strand breaks (DSBs), it is possible that dCas9 residing adjacent to a break may also determine the repair pathway for this DSB, providing an opportunity to control genome editing. Here, we found that loading dCas9 onto a DSB-adjacent site stimulated homology-directed repair (HDR) of this DSB by locally blocking recruitment of classical non-homologous end-joining (c-NHEJ) factors and suppressing c-NHEJ in mammalian cells. We further repurposed dCas9 proximal binding to increase HDR-mediated CRISPR genome editing by up to 4-fold while avoiding exacerbation of off-target effects. This dCas9-based local inhibitor provided a novel strategy of c-NHEJ inhibition in CRISPR genome editing in place of small molecule c-NHEJ inhibitors, which are often used to increase HDR-mediated genome editing but undesirably exacerbate off-target effects.

MyoFold: Joint myocardial tissue composition and wall motion quantification via a highly folded sequence.

PURPOSE: This study aims to develop and evaluate a novel cardiovascular MR sequence, MyoFold, designed for the simultaneous quantifications of myocardial tissue composition and wall motion. METHODS: MyoFold is designed as a 2D single breathing-holding sequence, integrating joint T1/T2 mapping and cine imaging. The sequence uses a 2-fold accelerated balanced SSFP (bSSFP) for data readout and incorporates electrocardiogram synchronization to align with the cardiac cycle. MyoFold initially acquires six single-shot inversion-recovery images, completed during the diastole of six successive heartbeats. T2 preparation (T2-prep) is applied to introduce T2 weightings for the last three images. Subsequently, over the following six heartbeats, segmented bSSFP is performed for the movie of the entire cardiac cycle, synchronized with an electrocardiogram. A neural network trained using numerical simulations of MyoFold is used for T1 and T2 calculations. MyoFold was validated through phantom and in vivo experiments, with comparisons made against MOLLI, SASHA, T2-prep bSSFP, and the conventional cine. RESULTS: In phantom studies, MyoFold exhibited a 10% overestimation in T1 measurements, whereas T2 measurements demonstrated high accuracy. In vivo experiments revealed that MyoFold T1 had comparable accuracy to SASHA and precision similar to MOLLI. MyoFold demonstrated good agreement with T2-prep bSSFP in myocardial T2 measurements. No significant differences were observed in the quantification of left-ventricle wall thickness and function between MyoFold and the conventional cine. CONCLUSION: MyoFold presents as a rapid, simple, and multitasking approach for quantitative cardiovascular MR examinations, offering simultaneous assessment of tissue composition and wall motion. The sequence's multitasking capabilities make it a promising tool for comprehensive cardiac evaluations in clinical settings.

Effects of elevated levels of intracellular nitric oxide on Pseudomonas aeruginosa biofilm in chronic skin wound and slow-killing infection models.

Nitric oxide (NO), produced through the denitrification pathway, regulates biofilm dynamics through the quorum sensing system in Pseudomonas aeruginosa. NO stimulates P. aeruginosa biofilm dispersal by enhancing phosphodiesterase activity to decrease cyclic di-GMP levels. In a chronic skin wound model containing a mature biofilm, the gene expression of nirS, encoding nitrite reductase to produce NO, was low, leading to reduced intracellular NO levels. Although low-dose NO induces biofilm dispersion, it is unknown whether it influences the formation of P. aeruginosa biofilms in chronic skin wounds. In this study, a P. aeruginosa PAO1 strain with overexpressed nirS was established to investigate NO effects on P. aeruginosa biofilm formation in an ex vivo chronic skin wound model and unravel the underlying molecular mechanisms. Elevated intracellular NO levels altered the biofilm structure in the wound model by inhibiting the expression of quorum sensing-related genes, which was different from an in vitro model. In Caenorhabditis elegans as a slow-killing infection model, elevated intracellular NO levels increased worms' lifespan by 18%. Worms that fed on the nirS-overexpressed PAO1 strain for 4 h had complete tissue, whereas worms that fed on empty plasmid-containing PAO1 had biofilms on their body, causing severe damage to the head and tail. Thus, elevated intracellular NO levels can inhibit P. aeruginosa biofilm growth in chronic skin wounds and reduce pathogenicity to the host. Targeting NO is a potential approach to control biofilm growth in chronic skin wounds wherein P. aeruginosa biofilms are a persistent problem.

Identification and Validation of Basement Membrane Related LncRNA Signatures as a Novel Prognostic Model for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a significant cancer with limited treatments and a poor prognosis, with the basement membrane (BM) playing a crucial role in its initiation and growth. This study utilized data from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases to identify basement membrane-related genes differentially expressed in HCC. Through gene co-expression analysis, BM-associated long non-coding RNAs (lncRNAs) were discovered. LncRNAs related to HCC survival were selected via univariate analysis, and a prognostic model was constructed using LASSO regression and multivariate analysis. This model effectively classified HCC patients into high and low-risk groups, uncovering significant differences in prognosis, immune response, mutation, and drug sensitivity. Six BM-related lncRNAs (GSEC, MIR4435-2HG, AC092614.1, AC127521.1, LINC02580, and AC008050.1) were validated in normal and HCC cell lines, and the key role of AC092614.1 in regulating proliferation, migration, and invasion of HCC cells in vitro was explored. This research emphasizes the prognostic and therapeutic relevance of BM-related lncRNAs in HCC, highlighting AC092614.1's role in disease progression and as a potential target for targeted therapy.

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.

BACKGROUND: Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. OBJECTIVE: This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. METHODS: In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. RESULTS: A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. CONCLUSIONS: The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Climate warming worsens thermal resource utilization for practical rice cultivation in China.

Rice production is sensitive to climate change and significantly affected by warming in recent years. To what extent climate warming shifted rice phenology and varied thermal resource condition were explored across five agro-ecological zones in China, based on up-to-date observations of meteorology and rice cultivation in 1981-2020. It was clearly signaled that there was a general advance of 0.3-3.8 days in observed sowing date and a delay of 0.4-3.5 days in observed maturity date in 2001-2020 relative to 1981-2000 in major zones. A vacant time slice of 2.6-28.8 days between observed sowing date and potential sowing date, and a lag of 15.4-56.7 days in potential maturity date compared to observed maturity date were identified in 2001-2020. Within longer growing season, useful accumulated temperature increased by 76.7-117.6 °C·d in 2001-2020 relative to 1981-2000, while disactive accumulated temperature also increased. In Northeast China, actual rice cultivation was undergoing earlier sowing date than potential sowing date and longer growing duration than potential duration, yet leading to upward disactive accumulated temperature. The decrease in the thermal resource utilization in 2001-2020 relative to 1981-2000 was highlighted at 55.3-78.3% stations in major zones, with a decrement of 0.006-0.018 in average magnitude. The changes in thermal resource utilization unveiled that the shifts in actual rice cultivation still could not compensate for the suitability in thermal resource utilization benefited from climate warming.

Three-dimensional High-Resolution Dark-Blood Late Gadolinium Enhancement Imaging for Improved Atrial Scar Evaluation.

Background Radiofrequency ablation (RFA) is a widely used treatment for atrial fibrillation, reducing the risk of cardiac arrhythmia. Detailed visualization and quantification of atrial scarring has the potential to improve preprocedural decision-making and postprocedural prognosis. Conventional bright-blood late gadolinium enhancement (LGE) MRI can help detect atrial scars; however, its suboptimal myocardium to blood contrast inhibits accurate scar estimation. Purpose To develop and test a free-breathing LGE cardiac MRI approach that simultaneously provides high-spatial-resolution dark-blood and bright-blood images for improved atrial scar detection and quantification. Materials and Methods A free-breathing, independent navigator-gated, dark-blood phase-sensitive inversion recovery (PSIR) sequence with whole-heart coverage was developed. Two coregistered high-spatial-resolution (1.25 × 1.25 × 3 mm3) three-dimensional (3D) volumes were acquired in an interleaved manner. The first volume combined inversion recovery and T2 preparation to achieve dark-blood imaging. The second volume functioned as the reference for phase-sensitive reconstruction with built-in T2 preparation for improved bright-blood contrast. The proposed sequence was tested in prospectively enrolled participants who had undergone RFA for atrial fibrillation (mean time since RFA, 89 days ± 26 [SD]) from October 2019 to October 2021. Image contrast was compared with conventional 3D bright-blood PSIR images using the relative signal intensity difference. Furthermore, native scar area quantification obtained from both imaging approaches was compared with measurements obtained with electroanatomic mapping (EAM) as the reference standard. Results A total of 20 participants (mean age, 62 years ± 9; 16 male) who underwent RFA for atrial fibrillation were included. The proposed PSIR sequence successfully acquired 3D high-spatial-resolution volumes in all participants, with a mean scan time of 8.3 minutes ± 2.4. The developed PSIR sequence improved scar to blood contrast compared with conventional PSIR sequence (mean contrast, 0.60 arbitrary units [au] ± 0.18 vs 0.20 au ± 0.19, respectively; P < .01) and correlated with EAM regarding scar area quantification (r = 0.66 [P < .01] vs r = 0.13 [P = .63]). Conclusion In participants who had undergone RFA for atrial fibrillation, an independent navigator-gated dark-blood PSIR sequence produced high-spatial-resolution dark-blood and bright-blood images with improved image contrast and native scar quantification compared with conventional bright-blood images. © RSNA, 2023 Supplemental material is available for this article.

Construction and evaluation of intrauterine adhesion model in rats by different methods of mechanical injury.

PURPOSE: The study aimed to establish a stable and effective animal model for the experimental study of intrauterine adhesion (IUA) by evaluating various mechanical injury methods. METHODS: A total of 140 female rats were divided into four groups according to the extent and area of endometrial injury: group A (excision area: 2.0 × 0.5 cm2), group B (excision area: 2.0 × 0.25 cm2), group C (endometrial curettage) and group D (sham operation). On the 3rd, 7th, 15th and 30th day after the operation, the tissue samples of each group were collected, and the uterine cavity stenosis and histological changes were recorded by HE and Masson staining. Immunohistochemistry of CD31 was applied to visualize microvessel density (MVD). The pregnancy rate and the number of gestational sacs were used to evaluate the reproductive outcome. RESULTS: The results showed that endometrium injured by small-area endometrial excision or simple curettage could be repaired. The ratio of fibrosis in groups A and B was higher than that in groups C and group D 30 days after modeling (P < 0.001). The number of endometrial glands and MVD in group A was significantly lower than those in groups B, C and D (P < 0.05). The pregnancy rate in group A was 20%, which was lower than that in groups B (33.3%), C (89%) and D (100%) (P < 0.05). CONCLUSION: Full-thickness endometrial excision has a high rate of success in constructing stable and effective IUA models in rats.

Clinical Diagnostic Value of Atypical Glandular Cells in Cervical Cytology: A Single Center Experience From China.

OBJECTIVE: This study aimed to investigate the diagnostic value of atypical glandular cells (AGCs) by analyzing the prevalence and histopathology of AGCs according to cervical cytology. METHODS: The authors retrospectively reviewed and analyzed the demographic characteristics and histopathological outcomes including pathological diagnosis, pathological site, and epithelial distribution of the AGC cases that were diagnosed by cervical cytology. RESULTS: A total of 387 AGC patients with follow-up records were included. Among them, the prevalence of AGC-not otherwise specified (NOS) and AGC-favor neoplastic (FN) was 73.39% (284/387) and 26.62% (103/387), respectively. The high-risk human papillomavirus (hr-HPV)-positive rate was higher in AGC-FN than in AGC-NOS ( p = .002). The difference in pathological severity was statistically significant between hr-HPV-positive and negative AGC patients ( p = .010). Hr-HPV-positive AGC mainly occurs in cervical diseases, whereas hr-HPV-negative AGC is mainly related to endometrial lesions. Precancerous or malignant lesions were found in 36.43% (141/387) of AGC cases and were more commonly seen in AGC-FN than AGC-NOS ( p < .001). The histopathological severity and the incidence of uterine disease were higher among AGC women aged 40 years and older than those younger than 40 years ( p < .05). The possibility of the abnormal origin of glandular epithelial was higher than that of squamous epithelial in AGC patients aged 40 years and older ( p = .0003). CONCLUSIONS: The management of AGC women by age triage is reasonable because the incidence of the glandular epithelial lesion and uterine disease increases in AGC patients 40 years or older. Standardized clinical diagnosis and regular follow-up are recommended for all AGC patients.

What Matters in Radiological Image Segmentation? Effect of Segmentation Errors on the Diagnostic Related Features.

Segmentation is a crucial step in extracting the medical image features for clinical diagnosis. Though multiple metrics have been proposed to evaluate the segmentation performance, there is no clear study on how or to what extent the segmentation errors will affect the diagnostic related features used in clinical practice. Therefore, we proposed a segmentation robustness plot (SRP) to build the link between segmentation errors and clinical acceptance, where relative area under the curve (R-AUC) was designed to help clinicians to identify the robust diagnostic related image features. In experiments, we first selected representative radiological series from time series (cardiac first-pass perfusion) and spatial series (T2 weighted images on brain tumors) of magnetic resonance images, respectively. Then, dice similarity coefficient (DSC) and Hausdorff distance (HD), as the widely used evaluation metrics, were used to systematically control the degree of the segmentation errors. Finally, the differences between diagnostic related image features extracted from the ground truth and the derived segmentation were analyzed, using the statistical method large sample size T-test to calculate the corresponding p values. The results are denoted in the SRP, where the x-axis indicates the segmentation performance using the aforementioned evaluation metric, and the y-axis shows the severity of the corresponding feature changes, which are expressed in either the p values for a single case or the proportion of patients without significant change. The experimental results in SRP show that when DSC is above 0.95 and HD is below 3 mm, the segmentation errors will not change the features significantly in most cases. However, when segmentation gets worse, additional metrics are required for further analysis. In this way, the proposed SRP indicates the impact of the segmentation errors on the severity of the corresponding feature changes. By using SRP, one could easily define the acceptable segmentation errors in a challenge. Additionally, the R-AUC calculated from SRP provides an objective reference to help the selection of reliable features in image analysis.

Evaluation of moisture migration characteristics of permeable asphalt pavement: Field research.

To analyse the moisture migration characteristics of permeable asphalt pavement (PAP) in engineering applications, a PAP sample with a length and width of 163 m and 12 m, respectively, was designed and paved. The pavement comprised PAC-13, PAC-20, ATPB-25, graded grade, and sandy soil subgrade from the top to the bottom. Moisture sensors were set at 4 cm, 10 cm, 28 cm, 46 cm, 61 cm, 76 cm, 101 cm, 126 cm, 176 cm, and 226 cm below the pavement surface to ascertain the volumetric water content during and after rainfall. This data were used to analyse the changes in the infiltration depth, infiltration rate, water level height, and water emptying time of the PAP under different rainfall conditions. The results show that the prediction model for the infiltration depth can be established using the water adhesion rate and rainfall. According to the moisture changes of the pavement layer after rainfall, the water migration process of the PAP can be divided into the drying stage, wetting stage, emptying stage, and recovery drying stage. The relationship between the average rainfall intensity and the average infiltration rate is a linear function. The water emptying time at the depth of 0-10 cm is less than 20 h, and the emptying time at a depth below 10 cm is less than 6 d.

Preparation of Aliphatic Hydroxamic Acid from Litsea cubeba Kernel Oil and Its Application to Flotation of Fe(III)-Activated Wolframite.

Litsea cubeba is a characteristic woody oil resource in Hunan. As a solid waste of woody oil resources, Litsea cubeba kernels are rich in Litsea cubeba kernel oil with a carbon chain length of C10-12 fatty acid. In this work, aliphatic hydroxamic acids (AHAs) with carbon chain lengths of C10-12 were prepared from Litsea cubeba kernel oil via methylation and hydroximation reactions. The adsorption and hydrophobicity mechanism of AHA towards wolframite was explored by contact angle, zeta potential, Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The flotation results demonstrated that AHA was a superior collector than the traditional collector such as benzoyl hydroxamic acid (BHA). Zeta potential and contact angle results have shown that AHA was adsorbed on the surface of the Fe(III)-activated wolframite in its anionic form, which significantly improved the surface hydrophobicity of wolframite. FTIR and XPS revealed that AHA was chemically adsorbed on the surface of Fe(III)-activated wolframite in the form of a five-member ring, which made the hydrophobic chain reach into the solution, come in contact with bubbles, and achieve flotation separation.

LncRNA OSTM1-AS1 acts as an oncogenic factor in Wilms' tumor by regulating the miR-514a-3p/MELK axis.

Wilms' tumor (WT) is the most typical basic renal tumor in children and is associated with a high recurrence rate and improper diagnosis. Long noncoding RNAs (lncRNAs) play important roles in WT development. However, the impact of the OSTM1 antisense RNA 1 (OSTM1-AS1) lncRNA on WT remains largely unexplored. Differential expression of OSTM1-AS1, miR-514a-3p and maternal embryonic leucine zipper kinase (MELK) in mice with WT cells was assessed via quantitative reverse transcription-PCR and western blotting. Changes in the proliferation, migration and apoptosis of WT cells after OSTM1-AS1, miR-514a-3p or MELK knockdown were assessed using the cell counting kit-8, Transwell and caspase-3 activity assays, respectively. Additionally, the tumorigenicity of WT cells after OSTM1-AS1 knockdown in vivo was analyzed using a xenograft tumor assay. The association among OSTM1-AS1, MELK and miR-514a-3p was confirmed using the RNA binding protein immunoprecipitation and luciferase reporter assays. OSTM1-AS1 and MELK were upregulated in WT cells, whereas miR-514a-3p was downregulated. OSTM1-AS1 was mostly observed in the cytoplasm, and its knockout suppressed WT cell migration and proliferation in vitro , triggered apoptosis and attenuated tumor development in vivo . MiR-514a-3p was sponged by OSTM1-AS1, and miR-514a-3p interference counteracted the tumoricidal effect of OSTM1-AS1 knockdown. MiR-514a-3p reduced WT progression by downregulating the expression of MELK, which is the target gene of miR-514a-3p. lncRNA OSTM1-AS1 acts as an oncogenic factor in WT by releasing MELK through sponging miR-514a-3p and could be a useful target for WT diagnosis and therapy.

[Intelligent fault diagnosis expert system for multi-parameter monitor based on fault tree].

Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.

Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study.

BACKGROUND: Multiple organ failure (MOF) may lead to an increased mortality rate of moderately severe (MSAP) or severe acute pancreatitis (SAP). This study is aimed to use machine learning to predict the risk of MOF in the course of disease. METHODS: Clinical and laboratory features with significant differences between patients with and without MOF were screened out by univariate analysis. Prediction models were developed for selected features through six machine learning methods. The models were internally validated with a five-fold cross-validation, and a series of optimal feature subsets were generated in corresponding models. A test set was used to evaluate the predictive performance of the six models. RESULTS: 305 (68%) of 455 patients with MSAP or SAP developed MOF. Eighteen features with significant differences between the group with MOF and without it in the training and validation set were used for modeling. Interleukin-6 levels, creatinine levels, and the kinetic time were the three most important features in the optimal feature subsets selected by K-fold cross-validation. The adaptive boosting algorithm (AdaBoost) showed the best predictive performance with the highest AUC value (0.826; 95% confidence interval: 0.740 to 0.888). The sensitivity of AdaBoost (80.49%) and specificity of logistic regression analysis (93.33%) were the best scores among the six models in the test set. CONCLUSIONS: A predictive model of MOF complicated by MSAP or SAP was successfully developed based on machine learning. The predictive performance was evaluated by a test set, for which AdaBoost showed a satisfactory predictive performance. The study is registered with the China Clinical Trial Registry (Identifier: ChiCTR1800016079).

The Frequency and Associated Factors of Asymmetrical Prominent Veins: A Predictor of Unfavorable Outcomes in Patients with Acute Ischemic Stroke.

Objectives: The present study is aimed at investigating the frequency and associated factors of asymmetrical prominent veins (APV) in patients with acute ischemic stroke (AIS). Methods: Consecutive patients with AIS admitted to the Comprehensive Stroke Center of Shanghai Fourth People's Hospital between January 2013 and December 2017 were enrolled. MRI including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and susceptibility-weighted imaging (SWI) was performed within 12 hours of symptom onset. The volume of asymmetrical prominent veins (APV) was evaluated using the Signal Processing In nuclear magnetic resonance software (SPIN, Detroit, Michigan, USA). Multivariate analysis was used to assess relationships between APV findings and medical history, clinical variables as well as cardio-metabolic indices. Results: Seventy-six patients met the inclusion criteria. The frequency of APV ≥ 10 mL was 46.05% (35/76). Multivariate analyses showed that proximal artery stenosis or occlusion (≥50%) (P < 0.001, adjusted odds ratio (OR) = 660.0, 95%CI = 57.28-7604.88) and history of atrial fibrillation (P < 0.001, adjusted OR = 10.48, 95%CI = 1.78-61.68) were independent factors associated with high APV (≥10 mL). Conclusion: Our findings suggest that the frequency of APV ≥ 10 mL is high in patients with AIS within 12 hours of symptom onset. History of atrial fibrillation and severe proximal artery stenosis or occlusion are strong predictors of high APV as calculated by SPIN on the SWI map.

CaFtsH06, A Novel Filamentous Thermosensitive Protease Gene, Is Involved in Heat, Salt, and Drought Stress Tolerance of Pepper (Capsicum annuum L.).

Harsh environmental factors have continuous negative effects on plant growth and development, leading to metabolic disruption and reduced plant productivity and quality. However, filamentation temperature-sensitive H protease (FtsH) plays a prominent role in helping plants to cope with these negative impacts. In the current study, we examined the transcriptional regulation of the CaFtsH06 gene in the R9 thermo-tolerant pepper (Capsicum annuum L.) line. The results of qRT-PCR revealed that CaFtsH06 expression was rapidly induced by abiotic stress treatments, including heat, salt, and drought. The CaFtsH06 protein was localized to the mitochondria and cell membrane. Additionally, silencing CaFtsH06 increased the accumulation of malonaldehyde content, conductivity, hydrogen peroxide (H2O2) content, and the activity levels of superoxide dismutase and superoxide (·O2-), while total chlorophyll content decreased under these abiotic stresses. Furthermore, CaFtsH06 ectopic expression enhanced tolerance to heat, salt, and drought stresses, thus decreasing malondialdehyde, proline, H2O2, and ·O2- contents while superoxide dismutase activity and total chlorophyll content were increased in transgenic Arabidopsis. Similarly, the expression levels of other defense-related genes were much higher in the transgenic ectopic expression lines than WT plants. These results suggest that CaFtsH06 confers abiotic stress tolerance in peppers by interfering with the physiological indices through reducing the accumulation of reactive oxygen species, inducing the activities of stress-related enzymes and regulating the transcription of defense-related genes, among other mechanisms. The results of this study suggest that CaFtsH06 plays a very crucial role in the defense mechanisms of pepper plants to unfavorable environmental conditions and its regulatory network with other CaFtsH genes should be examined across variable environments.

[Intelligent fault diagnosis of medical equipment based on long short term memory network].

In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and unknown circuit board signal direction, the symptom phenomenon and port electrical signal of 7 different fault categories were collected, and the feature coding, normalization, fusion and screening were preprocessed. Then, the intelligent fault diagnosis model was built based on LSTM, and the fused and screened multi-modal features were used to carry out the fault diagnosis classification and identification experiment. The results were compared with those using port electrical signal, symptom phenomenon and the fusion of the two types. In addition, the fault diagnosis algorithm was compared with BP neural network (BPNN), recurrent neural network (RNN) and convolution neural network (CNN). The results show that based on the fused and screened multi-modal features, the average classification accuracy of LSTM algorithm model reaches 0.970 9, which is higher than that of using port electrical signal alone, symptom phenomenon alone or the fusion of the two types. It also has higher accuracy than BPNN, RNN and CNN, which provides a relatively feasible new idea for intelligent fault diagnosis of similar equipment.

Templated Polymerization of Nucleobase Complexes via Molecular Recognition.

Macromolecules have a strong tendency to interact with each other in solution to form a supramolecular structure through various secondary binding forces. In this study, nucleobase-containing templates poly(9-(4-vinylbenzyl)adenine) (PS AH) and poly(1-(4-vinylbenzyl)cytosine) (PS CH) are prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization. Vinylbenzyl thymine (MS T) is polymerized in the presence of these two nucleobase-containing templates. MS T shows higher affinities toward the template PS AH compared with the template PS CH. In accordance with the Watson-Crick pairing principle, thymine forms hydrogen bonding (H-bonding) with adenine, but not between thymine and cytosine. A complex is formed when PS AH is used as template which indicates that there is a template polymerization of nucleobase complexes via molecular recognition.

Risk of High-Grade Histopathology Diagnosed by Cervical Conization in Endocervical Curettage Cervical Intraepithelial Neoplasia 1: A Case-Control Study.

OBJECTIVE: The aim of the study was to estimate risks of cervical intraepithelial neoplasia 2+ (CIN 2+) on loop electrosurgical excisional procedure (LEEP) specimens with the diagnosis of endocervical curettage (ECC) CIN 1 compared with biopsy CIN 1. MATERIALS AND METHODS: We performed a retrospective computer-based search for subjects enrolled in the Obstetrics and Gynecology Hospital of Fudan University. The case group comprised women with an ECC CIN 1 (ECC results of CIN 1 with colposcopy-directed biopsy results ≤CIN 1), and the control group comprised women with a biopsy CIN 1 (colposcopy-directed biopsy results of CIN 1 with negative ECC findings) diagnosis. Variables, including age, cytology, high-risk human papillomavirus, and ECC results, were included in univariate and multivariate logistic regression analyses. p < .05 was defined statistically significant. RESULTS: Overall, 1,195 women with ECC CIN 1 and/or biopsy CIN 1 diagnosis who underwent LEEP participated in the study. ECC CIN 1 comprised 400 women, with LEEP histopathology results revealing 104 (26.00%) CIN 2+. Biopsy CIN 1 comprised 795 women, with LEEP histopathology results showing 150 (18.87%) CIN 2+. Univariate logistic regression showed that cytology (p < .001) and ECC (p = .005) results differ significantly between less than CIN 2+ and CIN 2+. Multivariate logistic regression revealed that the cytology of atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions (OR = 4.73, 95% CI = 2.78-8.05, p < .001) and high-grade squamous intraepithelial lesions or worse (HSIL+, OR = 4.88, 95% CI = 3.00-7.94, p < .001), and ECC CIN 1 (OR = 1.80, 95% CI = 1.33-2.44, p < .001) were risk factors for CIN 2 + . CONCLUSIONS: Endocervical curettage CIN 1 has a greater risk of CIN 2+ diagnosis than biopsy CIN 1, but high-grade cytology has a higher risk than ECC CIN 1.