Statistical and dynamical fluctuations of Binder ratios in heavy ion collisions

Higher moments of net-proton Binder ratio, which is suggested to be a good experimental measurement to locate the QCD critical point, is measured in relativistic heavy ion collisions. We firstly estimate the effect of statistical fluctuations of the third and forth order Binder ratios. Then the dynamical Binder ratio is proposed and investigated in both transport and statistical models. The energy dependence of dynamical Binder ratios with different system sizes at RHIC beam scan energies are presented and discussed.Comment: 5 pages, 3 figure

Improving Pneumonia Classification and Lesion Detection Using Spatial Attention Superposition and Multilayer Feature Fusion

Pneumonia is a severe inflammation of the lung that could cause serious complications. Chest X-rays (CXRs) are commonly used to make a diagnosis of pneumonia. In this paper, we propose a deep-learning-based method with spatial attention superposition (SAS) and multilayer feature fusion (MFF) to facilitate pneumonia diagnosis based on CXRs. Specifically, an SAS module, which takes advantage of the channel and spatial attention mechanisms, was designed to identify intrinsic imaging features of pneumonia-related lesions and their locations, and an MFF module was designed to harmonize disparate features from different channels and emphasize important information. These two modules were concatenated to extract critical image features serving as the basis for pneumonia diagnosis. We further embedded the proposed modules into a baseline neural network and developed a model called SAS-MFF-YOLO to diagnose pneumonia. To validate the effectiveness of our model, extensive experiments were conducted on two CXR datasets provided by the Radiological Society of North America (RSNA) and the AI Research Institute. SAS-MFF-YOLO achieved a precision of 88.1%, a recall of 98.2% for pneumonia classification and an AP50 of 99% for lesion detection on the AI Research Institute dataset. The visualization of intermediate feature maps showed that our method could facilitate uncovering pneumonia-related lesions in CXRs. Our results demonstrated that our approach could be used to enhance the performance of the overall pneumonia detection on CXR imaging

ESSM: An Extractive Summarization Model with Enhanced Spatial-Temporal Information and Span Mask Encoding

Extractive reading comprehension is to extract consecutive subsequences from a given article to answer the given question. Previous work often adopted Byte Pair Encoding (BPE) that could cause semantically correlated words to be separated. Also, previous features extraction strategy cannot effectively capture the global semantic information. In this paper, an extractive summarization model is proposed with enhanced spatial-temporal information and span mask encoding (ESSM) to promote global semantic information. ESSM utilizes Embedding Layer to reduce semantic segmentation of correlated words, and adopts TemporalConvNet Layer to relief the loss of feature information. The model can also deal with unanswerable questions. To verify the effectiveness of the model, experiments on datasets SQuAD1.1 and SQuAD2.0 are conducted. Our model achieved an EM of 86.31% and a F1 score of 92.49% on SQuAD1.1 and the numbers are 80.54% and 83.27% for SQuAD2.0. It was proved that the model is effective for extractive QA task

Is ultrasound combined with computed tomography useful for distinguishing between primary thyroid lymphoma and Hashimoto’s thyroiditis?

Introduction: The aim of the study is to investigate the usefulness of ultrasound combined with computed tomography (CT) for distinguishing between primary thyroid lymphoma (PTL) and Hashimoto’s thyroiditis (HT). Material and methods: The investigation was conducted retrospectively in 80 patients from January 2000 to July 2018. All patients underwent pathological tests to be classified into one of two groups: PTL group and HT group. The cut-off value of CT density was determined using receiver-operating characteristic (ROC) curve analysis. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of diagnosis for thyroid by CT alone, ultrasound alone, and the combination of CT plus ultrasound were calculated. Results: Of the 80 study patients, 27 patients were PTL and 53 patients were HT. Mean CT density had a sensitivity of 90.6% and a specificity of 88.9% at a cut-off value of 53.5 HU, with area under the curve (AUC) 0.88. Ultrasound combined with CT had the highest specificity, accuracy, and PPV compared with CT alone and ultrasound alone (p value < 0.05). Conclusions: Features such as extremely hypoechogenicity, enhanced posterior echo, cervical lymphadenopathy in ultrasound image, and linear high-density strand signs, and very low density in CT imaging have high sensitivity and specificity in thyroid lymphoma. Therefore, ultrasound combined with CT may be useful for distinguishing between PTL and HT.

Synthesis, Characterization, and Evaluation of a Novel Amphiphilic Polymer RGD-PEG-Chol for Target Drug Delivery System

An amphiphilic polymer RGD-PEG-Chol which can be produced in large scale at a very low cost has been synthesized successfully. The synthesized intermediates and final products were characterized and confirmed by 1H nuclear magnetic resonance spectrum (1H NMR) and Fourier transform infrared spectrum (FT-IR). The paclitaxel- (PTX-) loaded liposomes based on RGD-PEG-Chol were then prepared by film formation method. The liposomes had a size within 100 nm and significantly enhanced the cytotoxicity of paclitaxel to B16F10 cell as demonstrated by MTT test (IC50 = 0.079 μg/mL of RGD-modified PTX-loaded liposomes compared to 9.57 μg/mL of free PTX). Flow cytometry analysis revealed that the cellular uptake of coumarin encapsulated in the RGD-PEG-Chol modified liposome was increased for HUVEC cells. This work provides a reasonable, facile, and economic approach to prepare peptide-modified liposome materials with controllable performances and the obtained linear RGD-modified PTX-loaded liposomes might be attractive as a drug delivery system

Combined Structure-Based Pharmacophore and 3D-QSAR Studies on Phenylalanine Series Compounds as TPH1 Inhibitors

Tryptophan hydroxylase-1 (TPH1) is a key enzyme in the synthesis of serotonin. As a neurotransmitter, serotonin plays important physiological roles both peripherally and centrally. In this study, a combination of ligand-based and structure-based methods is used to clarify the essential quantitative structure-activity relationship (QSAR) of known TPH1 inhibitors. A multicomplex-based pharmacophore (MCBP) guided method has been suggested to generate a comprehensive pharmacophore of TPH1 kinase based on three crystal structures of TPH1-inhibitor complex. This model has been successfully used to identify the bioactive conformation and align 32 structurally diverse substituted phenylalanine derivatives. The QSAR analyses have been performed on these TPH1 inhibitors based on the MCBP guided alignment. These results may provide important information for further design and virtual screening of novel TPH1 inhibitors

Efficacy and safety of inclisiran in stroke or cerebrovascular disease prevention: a systematic review and meta-analysis of randomized controlled trials

Aims: As the impact of inclisiran in stroke prevention in atherosclerotic cardiovascular disease (ASCVD) patients or those at high risk of ASCVD is still unclear, we conducted a systematic review and meta-analysis of randomized controlled trials (RCT) to quantify the effectiveness of inclisiran in stroke prevention in these patients.Methods: Literature research was conducted in four electronic databases (PubMed, EMBASE, Web of Science, CENTRAL) and two clinical trials registers (ClinicalTrials.gov, WHO ICTRP) from the inception of the study to 17 October 2022, and was updated by the end of the study on 5 January 2023. Two authors independently screened the studies, extracted the data, and assessed the bias. The risk of bias was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). The intervention effect was estimated by calculating risk ratio (RR), weighted mean difference (WMD), and 95% confidence interval (CI) with R 4.0.5. Sensitivity analysis by changing meta-analysis model was also performed to test the robustness of the pooled results. If this was not possible, a descriptive analysis was conducted.Results: Four RCTs (n = 3,713 patients) were rated as high-risk bias. Meta-analysis of three RCTs (ORION-9, ORION-10, and ORION-11) showed that inclisiran reduced myocardial infarction (MI) risk by 32% (RR = 0.68, 95%CI = 0.48–0.96) but did not reduce stroke (RR = 0.92, 95%CI = 0.54–1.58) and major cardiovascular events (MACE) (RR = 0.81, 95%CI = 0.65–1.02) risk. Sensitivity analysis results were stable. Safety was similar to the placebo group but had frequent injection-site reactions (RR = 6.56, 95%CI = 3.83–11.25), which were predominantly mild or moderate. A descriptive analysis of one RCT (ORION-5) was conducted due to different study designs, and suggested that inclisiran might be given semiannually from the beginning.Conclusion: Inclisiran is not beneficial for stroke or MACE prevention in ASCVD or patients at high risk of ASCVD but is associated with the reduction of MI. Given the limited number and quality of the available studies and the lack of a standardized definition for cardiovascular events, further studies are essential for confirming the results