Deep Learning for the Pathologic Diagnosis of Hepatocellular Carcinoma, Cholangiocarcinoma, and Metastatic Colorectal Cancer

Diagnosing primary liver cancers, particularly hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC), is a challenging and labor-intensive process, even for experts, and secondary liver cancers further complicate the diagnosis. Artificial intelligence (AI) offers promising solutions to these diagnostic challenges by facilitating the histopathological classification of tumors using digital whole slide images (WSIs). This study aimed to develop a deep learning model for distinguishing HCC, CC, and metastatic colorectal cancer (mCRC) using histopathological images and to discuss its clinical implications. The WSIs from HCC, CC, and mCRC were used to train the classifiers. For normal/tumor classification, the areas under the curve (AUCs) were 0.989, 0.988, and 0.991 for HCC, CC, and mCRC, respectively. Using proper tumor tissues, the HCC/other cancer type classifier was trained to effectively distinguish HCC from CC and mCRC, with a concatenated AUC of 0.998. Subsequently, the CC/mCRC classifier differentiated CC from mCRC with a concatenated AUC of 0.995. However, testing on an external dataset revealed that the HCC/other cancer type classifier underperformed with an AUC of 0.745. After combining the original training datasets with external datasets and retraining, the classification drastically improved, all achieving AUCs of 1.000. Although these results are promising and offer crucial insights into liver cancer, further research is required for model refinement and validation.

Recent application of artificial intelligence on histopathologic image-based prediction of gene mutation in solid cancers

PURPOSE

Evaluation of genetic mutations in cancers is important because distinct mutational profiles help determine individualized drug therapy. However, molecular analyses are not routinely performed in all cancers because they are expensive, time-consuming and not universally available. Artificial intelligence (AI) has shown the potential to determine a wide range of genetic mutations on histologic image analysis. Here, we assessed the status of mutation prediction AI models on histologic images by a systematic review.

METHODS

A literature search using the MEDLINE, Embase and Cochrane databases was conducted in August 2021. The articles were shortlisted by titles and abstracts. After a full-text review, publication trends, study characteristic analysis and comparison of performance metrics were performed.

RESULTS

Twenty-four studies were found mostly from developed countries, and their number is increasing. The major targets were gastrointestinal, genitourinary, gynecological, lung and head and neck cancers. Most studies used the Cancer Genome Atlas, with a few using an in-house dataset. The area under the curve of some of the cancer driver gene mutations in particular organs was satisfactory, such as 0.92 of BRAF in thyroid cancers and 0.79 of EGFR in lung cancers, whereas the average of all gene mutations was 0.64, which is still suboptimal.

CONCLUSION

AI has the potential to predict gene mutations on histologic images with appropriate caution. Further validation with larger datasets is still required before AI models can be used in clinical practice to predict gene mutations.

Group 1 metabotropic glutamate receptor 5 is involved in synaptically-induced Ca2+-spikes and cell death in cultured rat hippocampal neurons

Group 1 metabotropic glutamate receptors (mGluRs) can positively affect postsynaptic neuronal excitability and epileptogenesis. The objective of the present study was to determine whether group 1 mGluRs might be involved in synaptically-induced intracellular free Ca²⁺ concentration ([Ca²⁺]_i) spikes and neuronal cell death induced by 0.1 mM Mg²⁺ and 10 µM glycine in cultured rat hippocampal neurons from embryonic day 17 fetal Sprague–Dawley rats using imaging methods for Ca²⁺ and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays for cell survival. Reduction of extracellular Mg²⁺ concentration ([Mg²⁺]_o) to 0.1 mM induced repetitive [Ca²⁺]_i spikes within 30 sec at day 11.5. The mGluR5 antagonist 6-Methyl-2-(phenylethynyl) pyridine (MPEP) almost completely inhibited the [Ca²⁺]_i spikes, but the mGluR1 antagonist LY367385 did not. The group 1 mGluRs agonist, 3,5-dihydroxyphenylglycine (DHPG), significantly increased the [Ca²⁺]_i spikes. The phospholipase C inhibitor U73122 significantly inhibited the [Ca²⁺]_i spikes in the absence or presence of DHPG. The IP₃ receptor antagonist 2-aminoethoxydiphenyl borate or the ryanodine receptor antagonist 8-(diethylamino)octyl 3,4,5-trimethoxybenzoate also significantly inhibited the [Ca²⁺]_i spikes in the absence or presence of DHPG. The TRPC channel inhibitors SKF96365 and flufenamic acid significantly inhibited the [Ca²⁺]_i spikes in the absence or presence of DHPG. The mGluR5 antagonist MPEP significantly increased the neuronal cell survival, but mGluR1 antagonist LY367385 did not. These results suggest a possibility that mGluR5 is involved in synaptically-induced [Ca²⁺]_i spikes and neuronal cell death in cultured rat hippocampal neurons by releasing Ca²⁺ from IP₃ and ryanodine-sensitive intracellular stores and activating TRPC channels.

Deep Learning-Based Classification of Uterine Cervical and Endometrial Cancer Subtypes from Whole-Slide Histopathology Images

Uterine cervical and endometrial cancers have different subtypes with different clinical outcomes. Therefore, cancer subtyping is essential for proper treatment decisions. Furthermore, an endometrial and endocervical origin for an adenocarcinoma should also be distinguished. Although the discrimination can be helped with various immunohistochemical markers, there is no definitive marker. Therefore, we tested the feasibility of deep learning (DL)-based classification for the subtypes of cervical and endometrial cancers and the site of origin of adenocarcinomas from whole slide images (WSIs) of tissue slides. WSIs were split into 360 × 360-pixel image patches at 20× magnification for classification. Then, the average of patch classification results was used for the final classification. The area under the receiver operating characteristic curves (AUROCs) for the cervical and endometrial cancer classifiers were 0.977 and 0.944, respectively. The classifier for the origin of an adenocarcinoma yielded an AUROC of 0.939. These results clearly demonstrated the feasibility of DL-based classifiers for the discrimination of cancers from the cervix and uterus. We expect that the performance of the classifiers will be much enhanced with an accumulation of WSI data. Then, the information from the classifiers can be integrated with other data for more precise discrimination of cervical and endometrial cancers.

Heart failure with improved ejection fraction (HFimpEF) in patients treated with sacubitril/valsartan (SV)

Introduction

Several studies demonstrated that patients with improvement of left ventricular ejection fraction (LVEF) and symptoms had good prognosis in heart failure with reduced ejection fraction (HFrEF). Based on these results, new classification of HF according to LVEF was currently proposed. Sacubitril/valsartan (SV) is recommended as one of the first-line therapy of HFrEF patients. SV reduced hospitalization for HF and cardiovascular mortality compared to enalapril in PARADIGM-HF trial. However, it is unclear that patients with improvement of LVEF also have better prognosis compared to patients without LVEF improvement among patients treated with SV.

Purpose

We aimed to evaluate the clinical characteristics and outcomes of heart failure with improved ejection fraction (HFimpEF) in heart failure with reduced ejection fraction (HFrEF) patients treated with SV.

Methods

We analyzed 230 patients with HFrEF taking SV in a multicenter retrospective cohort (RECORD-SV registry) from 2017 to 2019. Enrolled 230 patients were performed baseline and 1-year follow-up echocardiography. Based on 2 echocardiographic results, we defined “HFimpEF” as HF with a baseline LVEF ≤40%, ≥10% increase from baseline LVEF and a follow-up measurement of LVEF >40%. Others were defined as “Persistent HFrEF”. We analyzed and compared clinical characteristics and outcomes between two groups. Primary endpoint was a composite outcome of all-cause death and hospitalization for HF (HHF).

Results

From 230 patients, 65 patients with HFimpEF and 165 patients with Persistent HFrEF were analyzed. The median follow-up duration was 557 days (interquartile range 364 to 727 days). Patients with HFimpEF had a higher prevalence of female gender (50.8% vs. 30.3%) and de novo HF (44.6% vs. 21.2%). There were no significant differences for age, etiology (ischemic vs. non-ischemic), diabetes, atrial fibrillation, hypertension, and HF medications including SV dose between two groups. Patients with HFimpEF showed lower rate of all-cause death or HHF as a primary endpoint compared to patients with persistent HFrEF (6.2% vs. 22.4%; IPTW adjusted HR 0.24; 95% CI 0.13–0.46; p<0.001) (Table 1). It was also shown that HFimpEF patients had a reduced risk of primary endpoint in the Kaplan-Meier curves compared with persistent HFrEF (Log-rank p=0.045) (Figure 1). We demonstrated that Non-prior MI (adjusted OR 7.29; 95% CI 1.50–35.36; p=0.014) and de novo HF (adjusted OR 4.33; 95% CI 1.70–11.04; p=0.002) were independent prognostic factors of HFimpEF in HFrEF patients treated with SV.

Conclusions

HFimpEF patients had better clinical outcomes compared to those with persistent HFrEF in HFrEF patients treated with SV. Non-prior MI and de novo HF were independent predictors of HFimpEF in patients treated with SV.

Funding Acknowledgement

Type of funding sources: None.

Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology

Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost and technical barriers limit the application of these tests, hindering optimal treatment. Recently, deep learning (DL) has been applied to predict molecular test results from digitized images of tissue slides. Furthermore, treatment response and prognosis can be predicted from tissue slides using DL. In this review, we summarized DL-based studies regarding the prediction of genetic mutation, microsatellite instability, tumor mutational burden, molecular subtypes, gene expression, treatment response, and prognosis directly from hematoxylin- and eosin-stained tissue slides. Although performance needs to be improved, these studies clearly demonstrated the feasibility of DL-based prediction of key molecular features in cancer tissues. With the accumulation of data and technical advances, the performance of the DL system could be improved in the near future. Therefore, we expect that DL could provide cost- and time-effective alternative tools for patient stratification in the era of precision oncology.

Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach

BACKGROUND

Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer (GC). To facilitate this research, a cost- and time-effective method to analyze the mutational status is necessary. Deep learning (DL) has been successfully applied to analyze hematoxylin and eosin (H and E)-stained tissue slide images.

AIM

To test the feasibility of DL-based classifiers for the frequently occurring mutations from the H and E-stained GC tissue whole slide images (WSIs).

METHODS

From the GC dataset of The Cancer Genome Atlas (TCGA-STAD), wild-type/mutation classifiers for CDH1, ERBB2, KRAS, PIK3CA, and TP53 genes were trained on 360 × 360-pixel patches of tissue images.

RESULTS

The area under the curve (AUC) for the receiver operating characteristic (ROC) curves ranged from 0.727 to 0.862 for the TCGA frozen WSIs and 0.661 to 0.858 for the TCGA formalin-fixed paraffin-embedded (FFPE) WSIs. The performance of the classifier can be improved by adding new FFPE WSI training dataset from our institute. The classifiers trained for mutation prediction in colorectal cancer completely failed to predict the mutational status in GC, indicating that DL-based mutation classifiers are incompatible between different cancers.

CONCLUSION

This study concluded that DL could predict genetic mutations in H and E-stained tissue slides when they are trained with appropriate tissue data.

Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer

High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classifier as a screening tool for MSI status, we built a fully automated DL-based MSI classifier using pathology whole-slide images (WSIs) of CRCs. On small image patches of The Cancer Genome Atlas (TCGA) CRC WSI dataset, tissue/non-tissue, normal/tumor and MSS/MSI-H classifiers were applied sequentially for the fully automated prediction of the MSI status. The classifiers were also tested on an independent cohort. Furthermore, to test how the expansion of the training data affects the performance of the DL-based classifier, additional classifier trained on both TCGA and external datasets was tested. The areas under the receiver operating characteristic curves were 0.892 and 0.972 for the TCGA and external datasets, respectively, by a classifier trained on both datasets. The performance of the DL-based classifier was much better than that of previously reported histomorphology-based methods. We speculated that about 40% of CRC slides could be screened for MSI status without molecular testing by the DL-based classifier. These results demonstrated that the DL-based method has potential as a screening tool to discriminate molecular alteration in tissue slides.

Feasibility of fully automated classification of whole slide images based on deep learning

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.

Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning

BACKGROUND

Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-based molecular cancer subtyping can be performed directly from the standard hematoxylin and eosin (H&E) sections in diverse tumors including colorectal cancers (CRCs). Since H&E-stained tissue slides are ubiquitously available, mutation prediction with the pathology images from cancers can be a time- and cost-effective complementary method for personalized treatment.

AIM

To predict the frequently occurring actionable mutations from the H&E-stained CRC whole-slide images (WSIs) with deep learning-based classifiers.

METHODS

A total of 629 CRC patients from The Cancer Genome Atlas (TCGA-COAD and TCGA-READ) and 142 CRC patients from Seoul St. Mary Hospital (SMH) were included. Based on the mutation frequency in TCGA and SMH datasets, we chose APC, KRAS, PIK3CA, SMAD4, and TP53 genes for the study. The classifiers were trained with 360 × 360 pixel patches of tissue images. The receiver operating characteristic (ROC) curves and area under the curves (AUCs) for all the classifiers were presented.

RESULTS

The AUCs for ROC curves ranged from 0.693 to 0.809 for the TCGA frozen WSIs and from 0.645 to 0.783 for the TCGA formalin-fixed paraffin-embedded WSIs. The prediction performance can be enhanced with the expansion of datasets. When the classifiers were trained with both TCGA and SMH data, the prediction performance was improved.

CONCLUSION

APC, KRAS, PIK3CA, SMAD4, and TP53 mutations can be predicted from H&E pathology images using deep learning-based classifiers, demonstrating the potential for deep learning-based mutation prediction in the CRC tissue slides.

Applications of deep learning for the analysis of medical data

Over the past decade, deep learning has demonstrated superior performances in solving many problems in various fields of medicine compared with other machine learning methods. To understand how deep learning has surpassed traditional machine learning techniques, in this review, we briefly explore the basic learning algorithms underlying deep learning. In addition, the procedures for building deep learning-based classifiers for seizure electroencephalograms and gastric tissue slides are described as examples to demonstrate the simplicity and effectiveness of deep learning applications. Finally, we review the clinical applications of deep learning in radiology, pathology, and drug discovery, where deep learning has been actively adopted. Considering the great advantages of deep learning techniques, deep learning will be increasingly and widely utilized in a wide variety of different areas in medicine in the coming decades.

Quercetin Enhances the Function and Reduces Apoptosis of Mouse Islets

BACKGROUND

Quercetin (QE) is an antioxidant, anti-inflammatory, flavonoid compound. It was shown that islets are susceptible to oxidative stress due to their inherent low antioxidant capacity. In the present study, we investigated whether treatment of mouse islets with QE could enhance their function before transplantation.

METHODS

Balb/c mouse islets were treated with various concentrations of QE and their viability, function, and nitric oxide (NO) and the expression of inducible NO synthase (iNOS) were determined before and after cytokine treatment. The expression of antioxidant genes was determined. Apoptosis and apoptosis-associated gene expression was measured using INS-1 cells with or without QE treatment before and after cytokine treatment.

RESULTS

The QE-treated islets and INS-1 cells showed higher cell function compared to untreated control. The expression of heme oxygenase-1, manganese-dependent superoxide dismutase, and B-cell lymphoma-2 (Bcl-2) were enhanced, and the expression of NO, iNOS, and Bcl-2-associated X protein were reduced before and after cytokine treatment.

CONCLUSIONS

Our results show that QE could enhance the viability and reduce apoptosis of mouse islets and improve their function before transplantation.

The Neuroprotective Effect of Hericium erinaceus Extracts in Mouse Hippocampus after Pilocarpine-Induced Status Epilepticus

Hericium erinaceus (HE), a culinary-medicinal mushroom, has shown therapeutic potential in many brain diseases. However, the role of HE in status epilepticus (SE)-mediated neuronal death and its underlying mechanisms remain unclear. We investigated the neuroprotective effects of HE using a pilocarpine-induced SE model. Male C57BL/6 mice received crude extracts of HE (60 mg/kg, 120 mg/kg, or 300 mg/kg, p.o.) for 21 d from 14 d before SE to 6 d after SE. At 7 d after SE, cresyl violet and immunohistochemistry of neuronal nuclei revealed improved hippocampal neuronal survival in animals treated with 60 mg/kg and 120 mg/kg of HE, whereas those treated with 300 mg/kg of HE showed similar neuronal death to that of vehicle-treated controls. While seizure-induced reactive gliosis, assessed by immunohistochemistry, was not altered by HE, the number of hippocampal cyclooxygenase 2 (COX2)-expressing cells was significantly reduced by 60 and 120 mg/kg of HE. Triple immunohistochemistry demonstrated no overlap of COX2 labeling with Ox42, in addition to a decrease in COX2/GFAP-co-immunoreactivity in the group treated with 60 mg/kg HE, suggesting that the reduction of COX2 by HE promotes neuroprotection after SE. Our findings highlight the potential application of HE for preventing neuronal death after seizures.

Dual deep neural network-based classifiers to detect experimental seizures

Manually reviewing electroencephalograms (EEGs) is labor-intensive and demands automated seizure detection systems. To construct an efficient and robust event detector for experimental seizures from continuous EEG monitoring, we combined spectral analysis and deep neural networks. A deep neural network was trained to discriminate periodograms of 5-sec EEG segments from annotated convulsive seizures and the pre- and post-EEG segments. To use the entire EEG for training, a second network was trained with non-seizure EEGs that were misclassified as seizures by the first network. By sequentially applying the dual deep neural networks and simple pre- and post-processing, our autodetector identified all seizure events in 4,272 h of test EEG traces, with only 6 false positive events, corresponding to 100% sensitivity and 98% positive predictive value. Moreover, with pre-processing to reduce the computational burden, scanning and classifying 8,977 h of training and test EEG datasets took only 2.28 h with a personal computer. These results demonstrate that combining a basic feature extractor with dual deep neural networks and rule-based pre- and post-processing can detect convulsive seizures with great accuracy and low computational burden, highlighting the feasibility of our automated seizure detection algorithm.

Tetrahydrocurcumin Ameliorates Tacrolimus-Induced Nephrotoxicity Via Inhibiting Apoptosis

BACKGROUND

Calcineurin inhibitors are effective immunosuppressive agents, but associated adverse effects such as nephrotoxicity may limit efficacy. Tacrolimus (FK506) is an immunosuppressive drug used mainly to lower the risk of organ rejection after allogeneic organ transplant. Adverse effects of FK-506 can prompt patients to end treatment despite the efficacy. In the present study, we investigated the protective effect and mechanism of tetrahydrocurcumin (THC) on FK506-induced renal damage, apoptosis, and oxidative stress to evaluate its possible use for kidney protection.

MATERIALS AND METHODS

The effect of THC on FK506-induced kidney cell damage was investigated in LLC-PK1 cells. LLC-PK1 cells were pretreated with THC at concentrations of dose for 2 hours followed by addition of FK506 for 24 hours. LLC-PK1 cells were treated with FK506 and THC, and cell viability and glutathione was measured. The number of apoptotic cells was measured using an annexin V/propidium iodide staining with flow cytometry. The effect of apoptosis by THC in LLC-PK1 cells was determined by measuring the caspase-9, caspase-3, B-cell lymphoma-2 (Bcl-2), and Bcl-2-associated X protein levels using Western blotting analyses.

RESULTS

FK506-induced LLC-PK1 renal cell damage was markedly ameliorated by THC treatment. THC protected LLC-PK1 cells by preventing FK506-induced glutathione decrease. THC protects against FK506-induced apoptosis in LLC-PK1 cells. Apoptosis was significantly decreased, and Bcl-2 was elevated in the THC-treated group. Bcl-2-associated X protein, caspase-3, and caspase-9 were decreased in the THC-treated group.

CONCLUSION

These results collectively provide therapeutic evidence that THC ameliorates the FK506-induced renal damage via antioxidant effect and apoptosis inhibition.

Tetrahydrocurcumin Enhances Islet Cell Function and Attenuates Apoptosis in Mouse Islets

BACKGROUND

The transplantation of isolated pancreatic islets is a promising treatment for diabetes. Curcumin has been used for its pharmacologic effects, such as antidiabetic and anti-inflammatory activities. Tetrahydrocurcumin (THC), one of the major metabolites of curcumin, has been reported to have antioxidant and anti-inflammatory activities. This study examines the hypothesis that preoperative THC treatment can attenuate ischemic damage and apoptosis before islet transplantation.

METHODS

Islets isolated from Balb/c mice were randomly divided into 2 groups and cultured in medium supplemented with or without THC. In vitro islet viability and function were assessed. After treatment with a cytokine cocktail consisting of tumor necrosis factor-α, interferon-β, and interleukin-1β, islet cell viability, function, and apoptotic status were determined. Proteins related to apoptosis were analyzed using INS-1 cell after streptozocin treatment.

RESULTS

There was no difference in cell viability between the 2 groups. Islets cultured in the medium supplemented with THC showed 1.3-fold higher glucose-induced insulin secretion than the islets cultured in the medium without THC. After treatment with a cytokine cocktail, glucose-induced insulin release, and NO of the islets were significantly improved in THC-treated islets compared with islets not treated with THC. Apoptosis was significantly decreased, and B-cell lymphoma-2 was elevated in the THC-treated group. The streptozocin-treated INS-1 cell produced significantly higher levels of and B-cell lymphoma-2-associated X protein, caspase-3, and caspase-9 than INS-1 treated with THC.

CONCLUSIONS

These results suggest that preoperative THC administration enhances islet function before transplantation and attenuates the cytokine-induced damage associated with apoptosis.

A cost-effective cell- and matrix-based minimally invasive single-stage chondroregenerative technique developed with validated vertical translation methodology

Introduction The morbidity and significant health economic impact associated with the chondral lesion has led to a large number of strategies for therapeutic neochondrogenesis. The challenge has been to develop techniques that are cost effective single-stage procedures with minimal surgical trauma that have undergone rigorous preclinical scrutiny and robust reproducible assessment of effectiveness. A biological repair requires the generation of a cellular and matrix composite with appropriate signalling for chondrogenic differentiation. Methods and results A technique was developed that allowed chondrogenic primary (uncultured) cells from bone marrow aspirate concentrate, combined with a composite hydrophilic and fibrillar matrix to be applied arthroscopically to a site of a chondral lesion. The construct was tested in vitro and in animal experiments before clinical trials. Clinical trials involved 60 patients in a prospective study. Symptomatic International Cartilage Repair Society grade 3 and 4a lesions were mapped and treated. Pre- and postoperative clinical assessments showed statistically significant improved outcomes; Lysholm Knee Scoring Scale (mean 52.8 to > 76.4; P < 0.05) International Knee Documentation Committee (mean 39 to > 79 P < 0.05) and Knee injury and Osteoarthritis Outcome Score (64.5 to >89.2 P < 0.05). Postoperative magnetic resonance imaging was evaluated morphologically (magnetic resonance observation of cartilage repair tissue, average MOCART score 72) and qualitatively; the regenerate was comparable to native cartilage. Conclusions This technique is effective, affordable, requires no complex tools and delivers a single-stage treatment that is potentially accessible to any centre capable of performing arthroscopic surgery. Good clinical results were found to be sustained at five years of follow-up with a regenerate that appears hyaline like using multiple magnetic resonance measures.

Evaluation of treatment pattern and symptom control in patients with gastroesophageal reflux disease: multihospital questionnaire survey on the current situation in Korea

Proton pump inhibitors (PPIs) are the most effective treatment for gastroesophageal reflux disease (GERD); however, a considerable number of patients fail to respond to PPI therapy and complain of nocturnal heartburn and sleep disturbance. The aims of this study are to evaluate the treatment pattern of GERD-related medications and their efficacy in relieving nocturnal heartburn. A total of 334 patients with GERD receiving PPI therapy within 6 months were enrolled in a multihospital questionnaire survey from January, 2014 to March, 2015. GERD symptoms and patients' satisfaction were assessed by patient questionnaires, and treatment patterns of GERD-related medications were assessed by investigators. Among the 334 patients, 95.8% used PPI once daily and 58.6% used a half-dose of PPI. The PPI treatment pattern was changed in 26.6% of all patients, of those, 54% of the patients doubled the PPI dose, and 29.2% of the patients switched to another PPI. Approximately 60.3% of all patients were prescribed more than three GERD-related medications. The overall satisfaction rate was 61.8%, and 32.2% of patients experienced nocturnal heartburn and sleep disturbance. In the extended-release PPI group, there were fewer nocturnal symptoms compared with the conventional PPI group (10% vs. 33.7%, respectively, P = 0.027). The use of more than three medications was inversely associated with patients' satisfaction (OR = 0.355, 95% CI; 0.197-0.642, P = 0.001). Most patients were prescribed adjunctive medications other than PPIs; however, patients' satisfaction was inversely associated with multiple drugs. Patients' satisfaction was superior in extended-release PPIs than conventional PPIs for the relief of nocturnal heartburn in Korean patients.

Protective Effect of Polydeoxyribonucleotide Against Renal Ischemia-Reperfusion Injury in Mice

BACKGROUND

Polydeoxyribonucleotide (PDRN) is an A2A receptor agonist that induces vascular endothelial growth factor (VEGF) production during the pathological condition of low tissue perfusion. Ischemia-reperfusion injury (IRI) is a major problem after renal transplantation. In the present study, we investigated whether PDRN exhibits reno-protective effects against ischemia-reperfusion-induced acute kidney injury in mice.

METHODS

Renal ischemia-reperfusion injury was induced in male C57BL/6 mice by bilateral renal pedicle occlusion for 30 minutes, followed by reperfusion for 48 hours. PDRN (8 mg/kg body weight intraperitoneally) was administered 30 minutes before IRI.

RESULTS

Treatment with PDRN significantly decreased neutrophil gelatinase-associated lipocalin levels in the urine, blood urea nitrogen level, and serum creatinine levels as well as kidney tubular injury. Western blotting showed that PDRN significantly increased the levels of vascular endothelial growth factor and B-cell lymphoma protein and attenuated p38 mitogen-activated protein kinase, c-Jun N-terminal kinase, inducible nitric oxide synthase, and Bcl-2-associated X protein levels 48 hours after IRI.

CONCLUSIONS

Our findings suggest that PDRN is a potential therapeutic agent for acute ischemia-induced renal damage.

Protective Effect of Eupatilin Pretreatment Against Hepatic Ischemia-Reperfusion Injury in Mice

BACKGROUND

Eupatilin, a pharmacologically active flavone derived from Artemisia species, is known to have antioxidant and antiinflammatory activities. Ischemia-reperfusion injury (IRI) is a major critical event that commonly occurs after liver transplantation and resection. Furthermore, inflammatory responses to IRI exacerbate the resultant hepatic injury. In this study, we investigated whether eupatilin protects against IR-induced acute liver injury in mice.

MATERIALS AND METHODS

Partial (70%) hepatic IRI was induced in male C57BL/6 mice by portal triad pedicle occlusion for 90 minutes followed by reperfusion for 6 hours. Eupatilin (10 mg/kg body weight, oral) was administered 4 days before the IRI.

RESULTS

Treatment with eupatilin significantly decreased serum alanine aminotransferase and serum aspartate aminotransferase as well as liver histologic changes. Eupatilin also prevented hepatic glutathione depletion and increased malondialdehyde levels induced by IRI. Western blotting indicated that eupatilin significantly increased the levels of heat shock protein and B-cell lymphoma 2 protein, attenuated inducible nitric oxide synthase, and cleaved caspase-3 levels 6 hours after IRI. The expression of the Toll-like receptor 2/4, and phosphorylated nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor was significantly decreased in the eupatilin pretreatment group.

CONCLUSIONS

Eupatilin improved the acute hepatic IRI by reducing inflammation and apoptosis. These findings suggest that eupatilin is a promising therapeutic agent against acute IR-induced hepatic damage.

Red Ginseng Administration Before Islet Isolation Attenuates Apoptosis and Improves Islet Function and Transplant Outcome in a Syngeneic Mouse Marginal Islet Mass Model

BACKGROUND

Transplantation of isolated islets is a promising treatment for diabetes. Red ginseng (RG) is steamed ginseng and has been reported to enhance insulin secretion-stimulating and anti-apoptotic activities in pancreatic β-cells. In this study, we examined the hypothesis that pre-operative RG treatment enhances islet cell function and anti-apoptosis and investigated whether RG improves islet engraftment by transplant of a marginal mass of syngeneic islets pretreated with RG in diabetic mice.

METHODS

Balb/c mice were randomly divided into 2 groups, and 1 group was administered RG (400 mg/kg/day orally) for 7 days before islet isolation. In vitro islet viability and function were assessed. After cytokine treatment, cell viability, function, and apoptosis of islet cells were analyzed. Furthermore, we studied the effects of RG in a syngeneic islet graft model. A marginal mass of syngeneic mouse islets was transplanted into diabetic hosts.

RESULTS

Islet pretreatment with RG showed 1.4-fold higher glucose-induced insulin secretion than did control islets. RG pretreatment upregulated B-cell lymphoma 2 (Bcl-2) expression and downregulated Bcl-associated X protein (BAX), caspase-3, and inducible nitric oxide synthase (iNOS) expression. Glucose-induced insulin release, NO, and apoptosis were significantly improved in RG-pretreated islets compared with cytokine-treated islets. RG-pretreated mice exhibited improved marginal mass islet graft survival compared with controls.

CONCLUSIONS

These results suggest that pre-operative RG administration enhanced islet function before transplantation and attenuated cytokine-induced damage associated with apoptosis. These studies indicate that inhibition of apoptosis by RG significantly improved islet cell and graft function after isolation and transplantation, respectively.

Correlated Event-by-Event Fluctuations of Flow Harmonics in Pb-Pb Collisions at sqrt[s_{NN}]=2.76 TeV

We report the measurements of correlations between event-by-event fluctuations of amplitudes of anisotropic flow harmonics in nucleus-nucleus collisions, obtained for the first time using a new analysis method based on multiparticle cumulants in mixed harmonics. This novel method is robust against systematic biases originating from nonflow effects and by construction any dependence on symmetry planes is eliminated. We demonstrate that correlations of flow harmonics exhibit a better sensitivity to medium properties than the individual flow harmonics. The new measurements are performed in Pb-Pb collisions at the center-of-mass energy per nucleon pair of sqrt[s_{NN}]=2.76  TeV by the ALICE experiment at the Large Hadron Collider. The centrality dependence of correlation between event-by-event fluctuations of the elliptic v_{2} and quadrangular v_{4} flow harmonics, as well as of anticorrelation between v_{2} and triangular v_{3} flow harmonics are presented. The results cover two different regimes of the initial state configurations: geometry dominated (in midcentral collisions) and fluctuation dominated (in the most central collisions). Comparisons are made to predictions from Monte Carlo Glauber, viscous hydrodynamics, ampt, and hijing models. Together with the existing measurements of the individual flow harmonics the presented results provide further constraints on the initial conditions and the transport properties of the system produced in heavy-ion collisions.

Centrality Dependence of the Charged-Particle Multiplicity Density at Midrapidity in Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

The pseudorapidity density of charged particles, dN_{ch}/dη, at midrapidity in Pb-Pb collisions has been measured at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. For the 5% most central collisions, we measure a value of 1943±54. The rise in dN_{ch}/dη as a function of sqrt[s_{NN}] is steeper than that observed in proton-proton collisions and follows the trend established by measurements at lower energy. The increase of dN_{ch}/dη as a function of the average number of participant nucleons, ⟨N_{part}⟩, calculated in a Glauber model, is compared with the previous measurement at sqrt[s_{NN}]=2.76  TeV. A constant factor of about 1.2 describes the increase in dN_{ch}/dη from sqrt[s_{NN}]=2.76 to 5.02 TeV for all centrality classes, within the measured range of 0%-80% centrality. The results are also compared to models based on different mechanisms for particle production in nuclear collisions.

Measurement of an Excess in the Yield of J/ψ at Very Low p_{T} in Pb-Pb Collisions at sqrt[s]_{NN}=2.76 TeV

We report on the first measurement of an excess in the yield of J/ψ at very low transverse momentum (p_{T}<0.3  GeV/c) in peripheral hadronic Pb-Pb collisions at sqrt[s_{NN}]=2.76  TeV, performed by ALICE at the CERN LHC. Remarkably, the measured nuclear modification factor of J/ψ in the rapidity range 2.5<y<4 reaches about 7 (2) in the p_{T} range 0-0.3  GeV/c in the 70%-90% (50%-70%) centrality class. The J/ψ production cross section associated with the observed excess is obtained under the hypothesis that coherent photoproduction of J/ψ is the underlying physics mechanism. If confirmed, the observation of J/ψ coherent photoproduction in Pb-Pb collisions at impact parameters smaller than twice the nuclear radius opens new theoretical and experimental challenges and opportunities. In particular, coherent photoproduction accompanying hadronic collisions may provide insight into the dynamics of photoproduction and nuclear reactions, as well as become a novel probe of the quark-gluon plasma.

Anisotropic Flow of Charged Particles in Pb-Pb Collisions at √[s{NN}]=5.02 TeV

We report the first results of elliptic (v_{2}), triangular (v_{3}), and quadrangular (v_{4}) flow of charged particles in Pb-Pb collisions at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV with the ALICE detector at the CERN Large Hadron Collider. The measurements are performed in the central pseudorapidity region |η|<0.8 and for the transverse momentum range 0.2<p_{T}<5  GeV/c. The anisotropic flow is measured using two-particle correlations with a pseudorapidity gap greater than one unit and with the multiparticle cumulant method. Compared to results from Pb-Pb collisions at sqrt[s_{NN}]=2.76  TeV, the anisotropic flow coefficients v_{2}, v_{3}, and v_{4} are found to increase by (3.0±0.6)%, (4.3±1.4)%, and (10.2±3.8)%, respectively, in the centrality range 0%-50%. This increase can be attributed mostly to an increase of the average transverse momentum between the two energies. The measurements are found to be compatible with hydrodynamic model calculations. This comparison provides a unique opportunity to test the validity of the hydrodynamic picture and the power to further discriminate between various possibilities for the temperature dependence of shear viscosity to entropy density ratio of the produced matter in heavy-ion collisions at the highest energies.

Enhancement of GluN2B Subunit-Containing NMDA Receptor Underlies Serotonergic Regulation of Long-Term Potentiation after Critical Period in the Rat Visual Cortex

Serotonin [5-hydroxytryptamine (5-HT)] regulates synaptic plasticity in the visual cortex. Although the effects of 5-HT on plasticity showed huge diversity depending on the ages of animals and species, it has been unclear how 5-HT can show such diverse effects. In the rat visual cortex, 5-HT suppressed long-term potentiation (LTP) at 5 weeks but enhanced LTP at 8 weeks. We speculated that this difference may originate from differential regulation of neurotransmission by 5-HT between the age groups. Thus, we investigated the effects of 5-HT on apha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-, γ-aminobutyric acid receptor type A (GABA_AR)-, and N-methyl-D-aspartic acid receptor (NMDAR)-mediated neurotransmissions and their involvement in the differential regulation of plasticity between 5 and 8 weeks. AMPAR-mediated currents were not affected by 5-HT at both 5 and 8 weeks. GABA_AR-mediated currents were enhanced by 5-HT at both age groups. However, 5-HT enhanced NMDAR-mediated currents only at 8 weeks. The enhancement of NMDAR-mediated currents appeared to be mediated by the enhanced function of GluN2B subunit-containing NMDAR. The enhanced GABA_AR- and NMDAR-mediated neurotransmissions were responsible for the suppression of LTP at 5 weeks and the facilitation of LTP at 8 weeks, respectively. These results indicate that the effects of 5-HT on neurotransmission change with development, and the changes may underlie the differential regulation of synaptic plasticity between different age groups. Thus, the developmental changes in 5-HT function should be carefully considered while investigating the 5-HT-mediated metaplastic control of the cortical network.

5,7-dihydroxy-3,4,6-trimethoxyflavone attenuates ischemic damage and apoptosis in mouse islets

BACKGROUND

The transplantation of isolated pancreatic islets is a promising treatment for diabetes. 5,7-dihydroxy-3,4,6-trimethoxyflavone (Eupatilin), a pharmacologically active flavone derived from the Artemisia plant species, has been reported to have antioxidant and anti-inflammatory activities. This study examines the hypothesis that preoperative eupatilin treatment can attenuate ischemic damage and apoptosis before islet transplantation.

METHODS

Islets isolated from Balb/c mice were randomly divided into 2 groups, and cultured in medium supplemented with or without eupatilin. In vitro islet viability and function were assessed. After treatment with a cytokine cocktail consisting of tumor necrosis factor (TNF)-α, interferon (INF)-γ, and interleukin (IL)-1β, islet cell viability, function, and apoptotic status were determined. The glutathione (GSH) and nitrous oxide (NO) levels were also measured. Proteins related to apoptosis were analyzed using Western blotting.

RESULTS

There was no difference in cell viability between the 2 groups. Islets cultured in the medium supplemented with eupatilin showed 1.4-fold higher glucose-induced insulin secretion than the islets cultured in the medium without eupatilin. After treatment with a cytokine cocktail, glucose-induced insulin release and the total insulin content of the islets were significantly improved in eupatilin-pretreated islets compared with islets not treated with eupatilin. Apoptosis was significantly decreased, and GSH levels were elevated in the eupatilin-pretreated group. Cytokine-only treated islets produced significantly higher levels of NO, iNOS, and caspase-3 than islets pretreated with eupatilin before cytokine treatment.

CONCLUSIONS

These results suggest that preoperative eupatilin administration enhances islet function before transplantation and attenuates the cytokine-induced damage associated with NO production and apoptosis.

Measurement of pion, kaon and proton production in proton-proton collisions at [Formula: see text] TeV

The measurement of primary [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] production at mid-rapidity ([Formula: see text] 0.5) in proton-proton collisions at [Formula: see text][Formula: see text] 7 TeV performed with a large ion collider experiment at the large hadron collider (LHC) is reported. Particle identification is performed using the specific ionisation energy-loss and time-of-flight information, the ring-imaging Cherenkov technique and the kink-topology identification of weak decays of charged kaons. Transverse momentum spectra are measured from 0.1 up to 3 GeV/[Formula: see text] for pions, from 0.2 up to 6 GeV/[Formula: see text] for kaons and from 0.3 up to 6 GeV/[Formula: see text] for protons. The measured spectra and particle ratios are compared with quantum chromodynamics-inspired models, tuned to reproduce also the earlier measurements performed at the LHC. Furthermore, the integrated particle yields and ratios as well as the average transverse momenta are compared with results at lower collision energies.

Effortful swallow enhances vertical hyolaryngeal movement and prolongs duration after maximal excursion

Effortful swallowing (EFS) is a common compensatory swallowing manoeuver for dysphagia patients. We investigated the influence of EFS on temporal and spatial characteristics of the movements of the hyoid bone, larynx and epiglottis in healthy subjects. A total of 41 volunteers swallowed 10 mL of diluted barium solution using two swallowing strategies: usual and effortful swallowing (USS and EFS). The motions of the hyoid bone, larynx and epiglottis were tracked using frame-by-frame kinematic motion analysis of videofluoroscopic images. Maximal velocities and maximal displacements of hyoid and larynx, the maximal angle of the epiglottic tilt, and the durations of hyoid excursion, laryngeal elevation and epiglottic tilt were measured. Compared to USS, EFS was associated with significantly greater vertical displacement of the hyoid (P < 0.001), vertical and horizontal displacement of the larynx (P = 0.003, P = 0.019), and maximal angle of the epiglottic tilt (P = 0.001). In addition, the durations of the vertical and horizontal excursions of the hyoid, vertical excursion of the larynx and the epiglottic tilt were greater in EFS, compared with USS. Effortful swallowing was also associated with significantly greater maximum velocities of the hyoid and larynx during swallowing. In conclusion, the EFS manoeuver facilitates vertical speed and distance of hyolaryngeal excursion and epiglottic tilt and extends the duration of excursion and the epiglottic tilt, especially after reaching maximal excursion in healthy subjects. These results confirm the temporal and kinematic benefits of airway protection induced by the EFS manoeuver.

GluN2B-containing N-methyl-D-aspartate receptors compensate for the inhibitory control of synaptic plasticity during the early critical period in the rat visual cortex

In the visual cortex, synaptic plasticity is very high during the early developmental stage known as the critical period and declines with development after the critical period. Changes in the properties of N-methyl-D-aspartate receptor (NMDAR) and γ-aminobutyric acid type A receptor (GABAA R) have been suggested to underlie the changes in the characteristics of plasticity. However, it is largely unknown how the changes in the two receptors interact to regulate synaptic plasticity. The present study investigates the changes in the properties of NMDAR and GABAA R from 3 to 5 weeks of age in layer 2/3 pyramidal neurons of the rat visual cortex. The impact of these changes on the characteristics of long-term potentiation (LTP) is also investigated. The amplitude and decay time constant of GABAA R-mediated currents increased during this period. However, the decay time constant of NMDAR-mediated currents decreased as a result of the decrease in the proportion of the GluN2B subunit-mediated component. Induction of NMDAR-dependent LTP at 3 weeks depended on the GluN2B subunit, but LTP at 5 weeks did not. Enhancement of GABAA R-mediated inhibition suppressed the induction of LTP only at 5 weeks. However, partial inhibition of the GluN2B subunit with a low concentration of ifenprodil allowed the GABAA R-mediated suppression of LTP at 3 weeks. These results suggest that changes in the properties of NMDAR- and GABAA R-mediated synaptic transmission interact to determine the characteristics of synaptic plasticity during the critical period in the visual cortex.

Ginsenoside Rg3 enhances islet cell function and attenuates apoptosis in mouse islets

BACKGROUND

The transplantation of isolated islets is thought to be an attractive approach for curative treatment of diabetes mellitus. Panax ginseng has been used in oriental countries for its pharmacologic effects, such as antidiabetic and antiinflammatory activities. 20(S)-ginsenoside Rg3 (Rg3), an active ingredient of ginseng saponins, has been reported to enhance insulin secretion-stimulating and antiapoptotic activities in pancreatic beta cells. We performed this study to examine the hypothesis that preoperative Rg3 administration can enhance islet cell function and antiapoptosis before islet transplantation.

METHODS

Balb/c mice were randomly divided into 2 groups according to the administration of Rg3 after islet isolation. Mouse islets were cultured in medium supplemented with or without Rg3. In vitro, islet viability and function were assessed. After treatment of islets with a cytokine cocktail (tumor necrosis factor α, interferon-γ, and interleukin-1β), cell viability, function, and apoptosis were assessed.

RESULTS

Cell viability was similar between the 2 groups. Islets cultured in medium supplemented with Rg3 showed 2.3-fold higher glucose-induced insulin secretion than islets cultured in medium without Rg3. After treatment with a cytokine cocktail, glucose-induced insulin release, total insulin content of islets, and apoptosis were significantly improved in Rg3-treated islets compared with cytokine-treated islets. Cytokine-treated islets produced significantly higher levels of nitric oxide (NO) than islets treated with Rg3.

CONCLUSIONS

These results suggest that preoperative Rg3 administration enhanced islet function before islet transplantation and attenuated both cytokine-induced damage associated with NO production and apoptosis. Rg3 administration might be a prospective management to enhanced islet function and ameliorate early inflammation after transplantation.

Phasic and Tonic Inhibition are Maintained Respectively by CaMKII and PKA in the Rat Visual Cortex

Phasic and tonic γ-aminobutyric acid_A (GABA_A) receptor-mediated inhibition critically regulate neuronal information processing. As these two inhibitory modalities have distinctive features in their receptor composition, subcellular localization of receptors, and the timing of receptor activation, it has been thought that they might exert distinct roles, if not completely separable, in the regulation of neuronal function. Inhibition should be maintained and regulated depending on changes in network activity, since maintenance of excitation-inhibition balance is essential for proper functioning of the nervous system. In the present study, we investigated how phasic and tonic inhibition are maintained and regulated by different signaling cascades. Inhibitory postsynaptic currents were measured as either electrically evoked events or spontaneous events to investigate regulation of phasic inhibition in layer 2/3 pyramidal neurons of the rat visual cortex. Tonic inhibition was assessed as changes in holding currents by the application of the GABA_A receptor blocker bicuculline. Basal tone of phasic inhibition was maintained by intracellular Ca²⁺ and Ca²⁺/calmodulin-dependent protein kinase II (CaMKII). However, maintenance of tonic inhibition relied on protein kinase A activity. Depolarization of membrane potential (5 min of 0 mV holding) potentiated phasic inhibition via Ca²⁺ and CaMKII but tonic inhibition was not affected. Thus, phasic and tonic inhibition seem to be independently maintained and regulated by different signaling cascades in the same cell. These results suggest that neuromodulatory signals might differentially regulate phasic and tonic inhibition in response to changes in brain states.

Exclusive J/ψ photoproduction off protons in ultraperipheral p-Pb collisions at √(s(NN))=5.02 TeV

We present the first measurement at the LHC of exclusive J/ψ photoproduction off protons, in ultraperipheral proton-lead collisions at sqrt[s_{NN}]=5.02  TeV. Events are selected with a dimuon pair produced either in the rapidity interval, in the laboratory frame, 2.5<y<4 (p-Pb) or -3.6<y<-2.6 (Pb-p), and no other particles observed in the ALICE acceptance. The measured cross sections σ(γ+p→J/ψ+p) are 33.2±2.2(stat)±3.2(syst)±0.7(theor)  nb in p-Pb and 284±36(stat)_{-32}^{+27}(syst)±26(theor)  nb in Pb-p collisions. We measure this process up to about 700 GeV in the γp center of mass, which is a factor of two larger than the highest energy studied at HERA. The data are consistent with a power law dependence of the J/ψ photoproduction cross section in γp energies from about 20 to 700 GeV, or equivalently, from Bjorken x scaling variable between ∼2×10^{-2} and ∼2×10^{-5}, thus indicating no significant change in the gluon density behavior of the proton between HERA and LHC energies.

Measurement of prompt D-meson production in p-Pb collisions at √(s(NN))=5.02 TeV

The p_{T}-differential production cross sections of the prompt charmed mesons D^{0}, D^{+}, D^{*+}, and D_{s}^{+} and their charge conjugate in the rapidity interval -0.96<y_{cms}<0.04 were measured in p-Pb collisions at a center-of-mass energy sqrt[s_{NN}]=5.02  TeV with the ALICE detector at the LHC. The nuclear modification factor R_{pPb}, quantifying the D-meson yield in p-Pb collisions relative to the yield in pp collisions scaled by the number of binary nucleon-nucleon collisions, is compatible within the 15%-20% uncertainties with unity in the transverse momentum interval 1<p_{T}<24  GeV/c. No significant difference among the R_{pPb} of the four D-meson species is observed. The results are described within uncertainties by theoretical calculations that include initial-state effects. The measurement adds experimental evidence that the modification of the momentum spectrum of D mesons observed in Pb-Pb collisions with respect to pp collisions is due to strong final-state effects induced by hot partonic matter.

Comparison of RECIST 1.0 and RECIST 1.1 on computed tomography in patients with metastatic colorectal cancer

OBJECTIVE

We conducted this study to compare tumor measurement by computed tomography (CT) and tumor response assessment between Response Evaluation Criteria In Solid Tumors (RECIST) 1.0 and RECIST 1.1 in patients with metastatic colorectal cancer (CRC).

METHODS

We reviewed the medical records of patients with metastatic CRC who received first-line chemotherapy between January 2004 and December 2012 and compared CT tumor measurement using two RECIST versions.

RESULTS

A total of 58 patients who had target lesions according to RECIST 1.0 were included in the study. The number of target lesions recorded by RECIST 1.1 was significantly lower than that by RECIST 1.0, with a decrease experienced in 48 patients (82.7%). Six patients had no target lesions because of the new criteria of RECIST 1.1 for lymph node size. Out of 95 lymph nodes from 58 patients, only 40% were defined as target lesions according to RECIST 1.1. The overall response rate of first-line chemotherapy according to RECIST 1.0 and 1.1 was 41.5 and 40.4%, respectively. The best tumor responses showed almost perfect agreement between RECIST 1.1 and RECIST 1.0 (ĸ = 0.913). Three patients showed disagreement of the best responses between the two RECIST versions.

CONCLUSION

RECIST 1.1 showed a highly concordant response assessment with RECIST 1.0 in metastatic CRC and its clinical impact on therapeutic decisions was minimal.

Directed flow of charged particles at midrapidity relative to the spectator plane in Pb-Pb collisions at √(s(NN))=2.76 TeV

The directed flow of charged particles at midrapidity is measured in Pb-Pb collisions at √(s(NN))=2.76 TeV relative to the collision symmetry plane defined by the spectator nucleons. A negative slope of the rapidity-odd directed flow component with approximately 3 times smaller magnitude than found at the highest RHIC energy is observed. This suggests a smaller longitudinal tilt of the initial system and disfavors the strong fireball rotation predicted for the LHC energies. The rapidity-even directed flow component is measured for the first time with spectators and found to be independent of pseudorapidity with a sign change at transverse momenta p(T) between 1.2 and 1.7  GeV/c. Combined with the observation of a vanishing rapidity-even p(T) shift along the spectator deflection this is strong evidence for dipolelike initial density fluctuations in the overlap zone of the nuclei. Similar trends in the rapidity-even directed flow and the estimate from two-particle correlations at midrapidity, which is larger by about a factor of 40, indicate a weak correlation between fluctuating participant and spectator symmetry planes. These observations open new possibilities for investigation of the initial conditions in heavy-ion collisions with spectator nucleons.

K(S)0 and Λ production in Pb-Pb collisions at √(s(NN))=2.76 TeV

The ALICE measurement of K(S)(0) and Λ production at midrapidity in Pb-Pb collisions at √(s(NN))=2.76 TeV is presented. The transverse momentum (p(T)) spectra are shown for several collision centrality intervals and in the p(T) range from 0.4 GeV/c (0.6 GeV/c for Λ) to 12 GeV/c. The p(T) dependence of the Λ/K(S)(0) ratios exhibits maxima in the vicinity of 3 GeV/c, and the positions of the maxima shift towards higher p(T) with increasing collision centrality. The magnitude of these maxima increases by almost a factor of three between most peripheral and most central Pb-Pb collisions. This baryon excess at intermediate p(T) is not observed in pp interactions at √s=0.9 TeV and at √s=7 TeV. Qualitatively, the baryon enhancement in heavy-ion collisions is expected from radial flow. However, the measured p(T) spectra above 2 GeV/c progressively decouple from hydrodynamical-model calculations. For higher values of p(T), models that incorporate the influence of the medium on the fragmentation and hadronization processes describe qualitatively the p(T) dependence of the Λ/K(S)(0) ratio.

J/ψ elliptic flow in Pb-Pb collisions at √(s(NN))=2.76 TeV

We report on the first measurement of inclusive J/ψ elliptic flow v2 in heavy-ion collisions at the LHC. The measurement is performed with the ALICE detector in Pb-Pb collisions at √(s(NN))=2.76 TeV in the rapidity range 2.5<y<4.0. The dependence of the J/ψ v2 on the collision centrality and on the J/ψ transverse momentum is studied in the range 0≤p(T)<10 GeV/c. For semicentral Pb-Pb collisions at √(s(NN))=2.76 TeV, an indication of nonzero v2 is observed with a largest measured value of v2=0.116±0.046(stat)±0.029(syst) for J/ψ in the transverse momentum range 2≤p(T)<4 GeV/c. The elliptic flow measurement complements the previously reported ALICE results on the inclusive J/ψ nuclear modification factor and favors the scenario of a significant fraction of J/ψ production from charm quarks in a deconfined partonic phase.

D meson elliptic flow in noncentral Pb-Pb collisions at sqrt[sNN]=2.76 Tev

Azimuthally anisotropic distributions of D0, D+, and D*+ mesons were studied in the central rapidity region (|y|<0.8) in Pb-Pb collisions at a center-of-mass energy sqrt[sNN]=2.76  TeV per nucleon-nucleon collision, with the ALICE detector at the LHC. The second Fourier coefficient v2 (commonly denoted elliptic flow) was measured in the centrality class 30%-50% as a function of the D meson transverse momentum pT, in the range 2-16  GeV/c. The measured v2 of D mesons is comparable in magnitude to that of light-flavor hadrons. It is positive in the range 2<pT<6  GeV/c with 5.7σ significance, based on the combination of statistical and systematic uncertainties.

Measurement of inelastic, single- and double-diffraction cross sections in proton-proton collisions at the LHC with ALICE

Measurements of cross sections of inelastic and diffractive processes in proton-proton collisions at LHC energies were carried out with the ALICE detector. The fractions of diffractive processes in inelastic collisions were determined from a study of gaps in charged particle pseudorapidity distributions: for single diffraction (diffractive mass MX <200 GeV/c2) [Formula: see text], and [Formula: see text], respectively at centre-of-mass energies [Formula: see text]; for double diffraction (for a pseudorapidity gap Δη>3) σDD/σINEL=0.11±0.03,0.12±0.05, and [Formula: see text], respectively at [Formula: see text]. To measure the inelastic cross section, beam properties were determined with van der Meer scans, and, using a simulation of diffraction adjusted to data, the following values were obtained: [Formula: see text] mb at [Formula: see text] and [Formula: see text] at [Formula: see text]. The single- and double-diffractive cross sections were calculated combining relative rates of diffraction with inelastic cross sections. The results are compared to previous measurements at proton-antiproton and proton-proton colliders at lower energies, to measurements by other experiments at the LHC, and to theoretical models.

Biallelic expression of the L-arginine:glycine amidinotransferase gene with different methylation status between male and female primordial germ cells in chickens

The basic functions of DNA methylation include in gene silencing by methylation of specific gene promoters, defense of the host genome from retrovirus, and transcriptional suppression of transgenes. In addition, genomic imprinting, by which certain genes are expressed in a parent-of-origin-specific manner, has been observed in a wide range of plants and animals and has been associated with differential methylation. However, imprinting phenomena of DNA methylation effects have not been revealed in chickens. To analyze whether genomic imprinting occurs in chickens, methyl-DNA immunoprecipitation array analysis was applied across the entire genome of germ cells in early chick embryos. A differentially methylated region (DMR) was detected in the eighth intron of the l-arginine:glycine amidinotransferase (GATM) gene. When the DMR in GATM was analyzed by bisulfite sequencing, the methylation in male primordial germ cells (PGC) of 6-d-old embryos was higher than that in female PGC (57.5 vs. 35.0%). At 8 d, the DMR methylation of GATM in male PGC was 3.7-fold higher than that in female PGC (65.0 vs. 17.5%). Subsequently, to investigate mono- or biallelic expression of the GATM gene during embryo development, we found 2 indel sequences (GTTTAATGC and CAAAAA) within the GATM 3'-untranslated region in Korean Oge (KO) and White Leghorn (WL) chickens. When individual WL and KO chickens were genotyped for indel sequences, 3 allele combinations (homozygous insertion, homozygous deletion, and heterozygotes) were detected in both breeds using a gel shift assay and high-resolution melt assay. The deletion allele was predominant in KO, whereas the insertion allele was predominant in WL. Heterozygous animals were evenly distributed in both breeds (P < 0.01). Despite the different methylation status between male and female PGC, the GATM gene conclusively displayed biallelic expression in PGC as well as somatic embryonic, extraembryonic, and adult chicken tissues.

Net-charge fluctuations in Pb-Pb collisions at sqrt[sNN]=2.76 TeV

We report the first measurement of the net-charge fluctuations in Pb-Pb collisions at sqrt[sNN]=2.76  TeV, measured with the ALICE detector at the CERN Large Hadron Collider. The dynamical fluctuations per unit entropy are observed to decrease when going from peripheral to central collisions. An additional reduction in the amount of fluctuations is seen in comparison to the results from lower energies. We examine the dependence of fluctuations on the pseudorapidity interval, which may account for the dilution of fluctuations during the evolution of the system. We find that the fluctuations at the LHC are smaller compared to the measurements at the BNL Relativistic Heavy Ion Collider, and as such, closer to what has been theoretically predicted for the formation of a quark-gluon plasma.

Transverse momentum distribution and nuclear modification factor of charged particles in p+Pb collisions at sqrt[s(NN)] = 5.02 TeV

The transverse momentum (p(T)) distribution of primary charged particles is measured in minimum bias (non-single-diffractive) p+Pb collisions at sqrt[s(NN)]=5.02 TeV with the ALICE detector at the LHC. The p(T) spectra measured near central rapidity in the range 0.5<p(T) <20 GeV/c exhibit a weak pseudorapidity dependence. The nuclear modification factor R(pPb) is consistent with unity for p(T) above 2 GeV/c. This measurement indicates that the strong suppression of hadron production at high p(T) observed in Pb+Pb collisions at the LHC is not due to an initial-state effect. The measurement is compared to theoretical calculations.

Pseudorapidity density of charged particles in p+Pb collisions at √(s(NN))=5.02 TeV

The charged-particle pseudorapidity density measured over four units of pseudorapidity in nonsingle-diffractive p+Pb collisions at a center-of-mass energy per nucleon pair √(s(NN))=5.02 TeV is presented. The average value at midrapidity is measured to be 16.81±0.71 (syst), which corresponds to 2.14±0.17 (syst) per participating nucleon, calculated with the Glauber model. This is 16% lower than in nonsingle-diffractive pp collisions interpolated to the same collision energy and 84% higher than in d+Au collisions at s√(s(NN))=0.2 TeV. The measured pseudorapidity density in p+Pb collisions is compared to model predictions and provides new constraints on the description of particle production in high-energy nuclear collisions.