bluuebunny/crossref_metadata_2025 huggingface dataset:
The “Bait and Switch” of Sexual Assault Response: Expanded Carceral Power at a Rape Crisis Center
Authors: Whalley Elizabeth
Published: December 2019

Rape crisis centers (RCCs) were established during the mainstream anti-rape movement in the United States during the 1970s. In the decades that followed, RCCs began to depend on governmental grants to stay open, shifting the antagonistic relationship that existed between many RCCs and state structures. Previous research has conceptualized this RCC institutionalization as a reluctant concession requisite to the continuation of victim services and the anti-rape movement. This article draws upon three years of ethnographic research and 40 interviews at a United States RCC to illustrate how institutionalization facilitated one RCC’s complicity in the expansion of the carceral state. I propose the transformation of this RCC illuminates a sexual assault response “bait and switch” that serves carceral agendas. I reach this conclusion using data drawn from three themes: (1) the outsourcing of the hotline and conversion to criminal-legal victim services, (2) criminal-legal integration that did not expand the influence of the RCC, and (3) the facilitation of the criminalization of victims through a process of net widening. Building from previous research, these findings document the result of criminal-legal integration at one RCC: the expansion of the carceral state into the center, to the detriment of victims and efforts to end sexual assault.
Exploring the relationships between environmental management and financial sustainability in the energy industry: Linear and nonlinear effects
Authors: Xu Xin-Long , Chen Hsing Hung
Published: December 2019

Environmental management plays a pivotal role in the financial performance of the energy industry. A number of studies have focused on the relationship between environmental management and financial sustainability, but the results are inconsistent. In addition, the existing literature failed to study the indirect and nonlinear relationship between the two. To fill this gap, this paper aims to seek out a mediator (debt financing) and employ a threshold effect model to explore the relationship between environmental management and financial sustainability in the energy industry. First, this paper uses least square dummy variable method to examine the relationship among environmental management, debt financing, and financial sustainability, and the results show that environmental management and debt financing have a positive relationship with financial sustainability. Second, the mediating effect model and threshold effect model are employed to examine the relationship among environmental management, debt financing, and financial sustainability, and the results reveal that debt financing can mediate the effect of environmental management on financial sustainability, and there is a nonlinear impact of debt financing on financial sustainability for different thresholds of environmental management. Finally, this paper presents policy proposals to promote the development of the energy industry based on the conclusions.
Molecular mechanisms of cell death induced in glioblastoma by experimental and antineoplastic drugs: New and old drugs induce apoptosis in glioblastoma
Authors: Contreras-Ochoa CO , López-Arellano ME , Roblero-Bartolon G , Díaz-Chávez J , Moreno-Banda GL , Reyna-Figueroa J , Munguía-Moreno JA , Madrid-Marina V , Lagunas-Martínez A
Published: December 2019

Glioblastoma multiforme (GBM) is one of the most aggressive astrocytic tumors; it is resistant to most chemotherapeutic agents currently available and is associated with a poor patient survival. Thus, the development of new anticancer compounds is urgently required. Herein, we studied the molecular mechanisms of cell death induced by the experimental drugs resveratrol and MG132 or the antineoplastic drugs cisplatin and etoposide on a human GBM cell line (D54) and on primary cultured mouse astrocytes (PCMAs). Caspases, Bcl-2, inhibitors of apoptosis proteins (IAP) family members, and p53 were identified as potential molecular targets for these drugs. All drugs had a cytotoxic effect on D54 cells and PCMAs, with a similar inhibitory concentration (IC50) after 24 h. However, MG132 and cisplatin were more effective to induce apoptosis and autophagy than resveratrol and etoposide. Cell death by apoptosis involved the activation of caspases-3/7, -8, and -9, increased lysosomal permeability, LC3 lipidation, poly-(ADP-ribose) polymerase (PARP)-1 fragmentation, and a differential expression of genes related with apoptosis and autophagy like Mcl-1, Survivin, Noxa, LC3, and Beclin. In addition, apoptosis activation was partially dependent on p53 activation. Since experimental and antineoplastic drugs yielded similar results, further work is required to justify their use in clinical protocols.
Cyclooxygenase 2 Promotes Proliferation and Invasion in Ovarian Cancer Cells via the PGE2/NF-κB Pathway
Authors: Zhang Xiao , Yan Keqin , Deng Lin , Liang Jing , Liang Haiyan , Feng Dingqing , Ling Bin
Published: December 2019

Ovarian cancer is the leading cause of death among gynecological malignancies. Cyclooxygenase 2 is widely expressed in various cancer cells and participates in the occurrence and development of tumors by regulating a variety of downstream signaling pathways. However, the function and molecular mechanisms of cyclooxygenase 2 remain unclear in ovarian cancer. Here, we demonstrated that cyclooxygenase 2 was highly expressed in ovarian cancer and the expression level was highly correlated with ovarian tumor grades. Further, ovarian cancer cells with high expression of cyclooxygenase 2 exhibit enhanced proliferation and invasion abilities. Specifically, cyclooxygenase 2 promoted the release of prostaglandin E2 upregulated the phosphorylation levels of phospho-nuclear factor-kappa B p65. Celecoxib, AH6809, and BAY11-7082 all can inhibit the promoting effect of cyclooxygenase 2 on SKOV3 and OVCAR3 cell proliferation and invasion. Besides, celecoxib inhibited SKOV3 cell growth in the xenograft tumor model. These data suggest that high expression of cyclooxygenase 2 promotes the proliferation and invasion of ovarian cancer cells through the prostaglandin E2/nuclear factor-kappa B signaling pathway. Cyclooxygenase 2 may be a potential therapeutic target for the treatment of ovarian cancer.
Preparation of low-density polyethylene–silver ion antimicrobial film with and without ethylene-vinyl acetate
Authors: Sahai RSN , Gaval VR , Bhat B
Published: December 2019

The incorporation of antimicrobial agents into packaging materials is an effective method to inhibit the microbial population and aimed at specific microorganisms to provide better and safe products. The present study aims at developing an effective antimicrobial film with silver ions as an antimicrobial agent with and without ethylene-vinyl acetate (EVA). In the present work, two different masterbatches (MBs) were prepared. In the first case MB of 90%, linear low-density polyethylene (LLDPE) and 10% silver ions as an antimicrobial agent were prepared. In the second case MB of 80%, LLDPE, 10% silver ion, and 10% EVA were prepared. An antimicrobial film with low-density polyethylene and different percentages of the MB (0–30%) was prepared and tested under Japanese Industrial Standard (JIS Z 2801:2000) for Escherichia coli bacteria and Staphylococcus aureus bacteria. With the increase in the percentage loading of MB, the living amount of bacteria decreases. The decrease in the living amount of bacteria was greater when EVA was incorporated.
Health-related Quality of Life and Its Predictors in Korean Patients with Myocardial Infarction in the Acute Phase
Authors: Kang Kyoungrim , Gholizadeh Leila , Han Hae-Ra
Published: December 2019

This study aims to investigate health-related quality of life (HRQoL) of Korean patients in the acute phase of myocardial infarction (MI) and correlates of this important patient outcome. A total of 150 patients with recent MI were recruited. The Korean version of the MacNew Quality of Life after Myocardial Infarction Questionnaire was used to assess their HRQoL. Demographic, behavioural and disease-related factors were also assessed and the Depression, Anxiety and Stress Scale (DASS 21) was used for psychological well-being. Participants who had a higher education level and better financial status had better HRQoL. Diabetes, history of stroke, other heart disease and a higher score of the DASS 21 were adversely associated with HRQoL. The findings of this study help identify risk factors that are related to lower HRQoL after MI. Early psychological and financial support may help reduce the impact of MI on patients’ overall health and quality of life.
Remote Ischemic Conditioning in Acute Myocardial Infarction and Shock States
Authors: Kloner Robert A. , Shi Jianru , Dai Wangde , Carreno Juan , Zhao Lifu
Published: December 2019

Remote ischemic conditioning is the phenomenon whereby brief, nonlethal episodes of ischemia in one organ (such as a limb) protect a remote organ from ischemic necrosis induced by a longer duration of severe ischemia followed by reperfusion. This phenomenon has been reproduced by dozens of experimental laboratories and was shown to reduce the size of myocardial infarction in many but not all clinical studies. In one recent large clinical trial, remote ischemic conditioning induced by repetitive blood pressure cuff inflations on the arm did not reduce infarct size or improve clinical outcomes. This negative result may have been related in part to the overall success of early reperfusion and current adjunctive therapies, such as antiplatelet therapy, antiremodeling therapies, and low-risk patients, that may make it difficult to show any advantage of newer adjunctive therapies on top of existing therapies. One relevant area in which current outcomes are not as positive as in the treatment of heart attack is the treatment of shock, where mortality rates remain high. Recent experimental studies show that remote ischemic conditioning may improve survival and organ function in shock states, especially hemorrhagic shock and septic shock. In this study, we review the preclinical studies that have explored the potential benefit of this therapy for shock states and describe an ongoing clinical study.
Single Ventricle Physiology Patients and Coagulation Abnormalities: Is There a Relationship With Hemodynamic Data and Postoperative Course? A Pilot Study
Authors: Callegari Alessia , Christmann Martin , Albisetti Manuela , Kretschmar Oliver , Quandt Daniel
Published: December 2019

This study evaluates coagulation profiles of single ventricle (SV) patients in relationship to liver function, hemodynamic variables and outcome. Twenty-six children with SV anatomy were included. Advanced coagulation profiles, invasive preoperative hemodynamic parameters and clinical course were retrospectively analyzed. Median (interquartile range) age and weight at the time of blood sampling was 25.5 (31) months and 10.5 (6.9) kg. Sixteen patients (16/26; 62%) showed decreased antithrombin and/or protein C (PC) and/or free protein S (PS) function and/or free PS antigen. Two patients showed abnormal activated PC resistance ratio due to heterozygous factor V Leiden mutation and 1 heterozygous prothrombin G20210A mutation. Group comparison (abnormal coagulation profile [group 1; n = 16] versus normal coagulation profile [group 2; n = 10]) showed longer postoperative hospitalization time ( p = .04), longer postoperative catecholamine support ( p = .01), a higher incidence of thromboembolic events ( p = .04), and chylothoraxes ( p = .007) in group 1. In 5 (31%) of 16 group 1 patients, thromboembolic complications occurred: cerebral stroke (n = 1), intestinal ischemia (n = 2), thrombus formation in inferior caval vein (n = 1), and pulmonary vein (n = 1). Abnormalities in coagulation parameters are common in SV patients. Coagulation abnormalities constitute a preoperative risk factor and affect postoperative course.
Outcomes and survivorship after conversion of failed hip hemiarthroplasty to total hip arthroplasty
Authors: Sarpong Nana O , Grosso Matthew J , Lakra Akshay , Herndon Carl L , Jennings Emma , Shah Roshan P , Geller Jeffrey A , Cooper H John
Published: December 2019

Background:

Arthroplasty is the treatment of choice for elderly patients with displaced femoral neck fractures. When compared to total hip arthroplasty (THA), higher revision rates have been reported for hemiarthroplasty (HA). Conversion of failed HA to THA can be complex, especially in the elderly population at risk for revision surgery complications. We report a single institution’s experience with conversion of failed HA to THA at mid-term follow-up.

Methods:

We identified patients converted from failed HA to THA from 2006 to 2016. Clinical data including indication for index and conversion surgery, maintenance or revision of femoral component during conversion, operative time, estimated blood loss, postoperative complications, and need for revision surgery were collected. Descriptive statistics were analysed in SPSS.

Results:

The cohort included 21 men and 39 women (mean age of 74.5 years). The mean follow-up after conversion HA to THA was 2.8 years. During conversion surgery, the femoral component was revised in 75.0% and retained in 25.0% of cases. After conversion HA to THA, the rate of major complications and re-revision at 2 years was 11.7% and 10.0%, respectively. Femoral revision versus retention did not affect complication rates (11.1% vs. 6.7%; p = 0.31) or re-revision rates (8.9% vs. 13.3%; p = 1.0).

Conclusions:

In this high-risk population, mid-term follow-up demonstrated tolerable complication and re-revision rates, the majority of which were for instability. We observed high rates of femoral component revision during conversion THA, although this did not increase the likelihood of postoperative complications or need for future surgery.
Pleomorphic Adenoma of the Ala Nasi: A Case Report
Authors: Mouzali Amina , Lameche Samia , Slimani Assia , Zemirli Omar
Published: December 2019

Objectives:

Pleomorphic adenomas are benign tumors that rarely involve nonsalivary glands. We report an uncommon case of ala nasi pleomorphic adenoma. We discuss the clinical and histopathologic characteristics, and review the literature on nasal pleomorphic adenoma.

Method:

A 20-year-old man presented with a painless slow growing lobulated mass located on the right ala nasi extending into the nasal vestibule.

Results:

Complete surgical excision was performed. Histologic examination found a mixed cellular component: epithelial and myoepithelial cells with chondromyxoid stroma. This was consistent with the diagnosis of a typical pleomorphic adenoma. There was no evidence of recurrence at 18 months after the surgery.

Conclusions:

Pleomorphic adenomas located in the external nose are extremely rare. In such case, pleomorphic adenoma could originate from ectopic minor salivary gland. Complete surgical excision with long-term follow-up is recommended due to the potential risk of recurrence and malignant transformation.
Pneumatic stability analysis of single-pad aerostatic thrust bearing with pocketed orifice
Authors: Zheng Yueqing , Yang Guangwei , Cui Hailong , Hou Yu
Published: December 2019

The pneumatic hammer phenomenon and pneumatic stability of a single-pad aerostatic thrust bearing with pocked orifice were investigated numerically. A time-dependent dynamic model for pneumatic stability analysis of the bearing was established with taking the pocket volume and the mass flow difference between the pocket inlet and outlet into account. The numerical prediction indicates that the delay effect is an important reason for the pneumatic hammer phenomenon. With considering the delay effect, an in-depth explanation for the pneumatic hammer phenomenon is proposed in this paper. The air compressibility combined with the volume effect in the aerostatic bearing could lead to the delay of pocket pressure change, then resulting in the delay of bearing force change at larger film thickness region. The delay of the bearing force change at larger film thickness region causes the bearing damping to become negative at larger film thickness. The negative damping provides some energy into the aerostatic bearing system at larger film thickness and maintains vibration, which leads to the pneumatic hammer phenomenon.
Industry Funding and Cholesterol Research: A Systematic Review
Authors: Barnard Neal D. , Long M. Blaire , Ferguson Jennifer M. , Flores Rosendo , Kahleova Hana
Published: December 2019

The effect of diet on blood cholesterol concentrations has become controversial. We assessed whether industry-funded studies were more likely than non–industry-funded studies to report conclusions that were not supported by their objective findings. PubMed and Cochrane Central Register of Controlled Trials searches through March 8, 2019, yielded 211 relevant articles. The percentage of industry-funded studies increased from 0% in the 1950s to 60% for 2010 tp 2019 ( P < .001). Of 94 non–industry-funded intervention studies for which the effect of egg ingestion on cholesterol concentrations could be determined, net cholesterol increases were reported in 88 (93%) studies (51% statistically significant, 21% not significant, 21% significance not reported). Among 59 industry-funded intervention studies, net cholesterol increases were reported in 51 (86%) studies (34% statistically significant, 39% not significant, and 14% significance not reported). No studies reported significant cholesterol decreases. Nonsignificant net cholesterol decreases were reported by 6 (6%) non–industry-funded and 8 (14%) industry-funded studies. However, 49% of industry-funded intervention studies reported conclusions that were discordant with study results (ie, net cholesterol increases were described as favorable in the articles’ stated conclusions), compared with 13% of non–industry-funded studies. Readers, editors, and the public should remain alert to funding sources in interpreting study findings and conclusions.
Evaluation of clinical and anatomical outcome of staged stenting after acute coiling of ruptured intracranial aneurysms
Authors: Mine Benjamin , Bonnet Thomas , Vazquez-Suarez Juan Carlos , Ligot Noémie , Lubicz Boris
Published: December 2019

Introduction

Stent-assisted coiling has widened indications and improved stability of endovascular treatment of intracranial aneurysms. However, stent-assisted coiling is usually not used to treat acutely ruptured intracranial aneurysms to avoid antiplatelet therapy. The objective of this study is to evaluate a strategy of staged endovascular treatment of ruptured intracranial aneurysms including coiling at the acute phase with complementary stenting with or without coiling at the subacute phase.

Material and methods

Between 2012 and 2017, we retrospectively identified, in our prospectively maintained database, all patients treated for a ruptured intracranial aneurysm based on this staged stenting strategy. Clinical charts and imaging follow-up were analyzed to assess the procedural safety and feasibility as well as clinical and anatomical outcome.

Results

We identified 23 patients with 23 intracranial aneurysms including 15 (65.2%) women with a mean age of 50 years (range 24–69 years). No rebleeding occurred during the mean delay of 24.3 days between initial coiling and stenting. All procedures were successful and additional coiling was performed in 5/23 procedures (21.7%). Clinical status was unchanged in all patients. At follow-up, the modified Rankin scale was graded 0 in 19/23 (82.6%), 1 in 2/23 (8.7%), and 2 in 2/23 (8.7%) patients, respectively. The rate of complete occlusion rose from 30.4% before the stenting procedure to 52.2% immediately after and 72.7% at follow-up.

Conclusion

This strategy of early staged stenting in selected patients is safe and improves immediate intracranial aneurysm occlusion and long-term stability in this population at high risk of intracranial aneurysm recurrence with coiling alone.
When Social Inequalities Produce “Difficult Patients”: A Qualitative Exploration of Physicians’ Views
Authors: Carde Estelle
Published: December 2019

“Difficult patients” are most often characterized by their personality, behavior, or pathology. Little research has been done to understand how some patients, because of their disadvantaged social position, are perceived as “difficult” by their physicians. Our qualitative, exploratory study was conducted to understand how social inequalities contribute to this perception of a “difficult patient.” It was based on 12 semi-structured interviews with physicians, in Montréal, Canada. Participants identified three main challenging factors: a perception of excessive time required to manage these patients; a feeling of ineffectiveness, despite this additional time spent; and the pressure to “do something” about needs they perceive as serious, despite this feeling of ineffectiveness. To adjust their practice to the specific circumstances of these disadvantaged patients, they feel it is important to establish good relationships with them, to set realistic objectives, and to increase interprofessional interactions. We discuss these findings in relation to three issues that contribute to this sense of difficulty: the social distance between physicians and patients, the social determinants affecting patients’ health, and certain aspects of the health care system that impede the above-mentioned adjustments in medical practice. By exploring, social inequalities in health care access not through the experience of patients, but rather through the perspectives of the physicians who feel unable to protect them, this analysis highlights that the scope of action required to address such inequalities far exceeds physicians’ practice.
Endoscopic ultrasound guided biliary drainage: a multicenter retrospective experience of a technique slowly gaining acceptance in Egypt
Authors: Altonbary Ahmed Youssef , Galal Ahmed , El-Nady Mohamed , Hakim Hazem
Published: December 2019

Background and aim:

Endoscopic ultrasound-guided biliary drainage is an alternative to failed endoscopic retrograde cholangiopancreatography. Unfortunately, this procedure remains relatively less explored in Egypt due to its high cost, lack of adequate training, and the perception of increased risk. This study is the first multicenter Egyptian experience of an endoscopic ultrasound-guided biliary drainage in patients with malignant biliary obstruction.

Patients and methods:

We retrospectively reviewed 15 patients (10 men and five women) with malignant biliary obstruction who from October 2013 to May 2019, following a failed or inaccessible endoscopic retrograde cholangiopancreatography, underwent an endoscopic ultrasound-guided choledochoduodenostomy, endoscopic ultrasound-guided hepaticogastrostomy, or endoscopic ultrasound-guided rendezvous. Their mean age was 57.4 years and mean bilirubin was 18.2 mg/dL. The outcome parameters included technical and clinical success. Technical success was defined as the successful placement of a stent in the biliary system, while clinical success was defined as a greater than 50% decrease in the bilirubin levels 2 weeks after the procedure. Patients were monitored for complications during and after the procedure.

Results:

In total, 15 patients underwent endoscopic ultrasound-guided biliary drainage (eight underwent endoscopic ultrasound-guided choledochoduodenostomy, five underwent endoscopic ultrasound-guided hepaticogastrostomy, and two underwent endoscopic ultrasound-guided rendezvous). The technical and clinical success rates were 100% (15/15 patients) and 93.3% (14/15 patients), respectively. The complication rate was 26.6% (4/15 patients). All complications were mild and self-limited, and included fever, mild biliary peritonitis, pneumoperitoneum, and a slight migration of one plastic stent during insertion.

Conclusion:

Although slowly gaining acceptance in Egypt, endoscopic ultrasound-guided biliary drainage is an effective and safe procedure in patients with a malignant biliary obstruction after a failed or inaccessible endoscopic retrograde cholangiopancreatography.
Gradual transition from mosaic to global DNA methylation patterns during deuterostome evolution
Authors: Okamura Kohji , Matsumoto Kazuaki A , Nakai Kenta
Published: December 2019

Background

DNA methylation by the Dnmt family occurs in vertebrates and invertebrates, including ascidians, and is thought to play important roles in gene regulation and genome stability, especially in vertebrates. However, the global methylation patterns of vertebrates and invertebrates are distinctive. Whereas almost all CpG sites are methylated in vertebrates, with the exception of those in CpG islands, the ascidian genome contains approximately equal amounts of methylated and unmethylated regions. Curiously, methylation status can be reliably estimated from the local frequency of CpG dinucleotides in the ascidian genome. Methylated and unmethylated regions tend to have few and many CpG sites, respectively, consistent with our knowledge of the methylation status of CpG islands and other regions in mammals. However, DNA methylation patterns and levels in vertebrates and invertebrates have not been analyzed in the same way.

Results

Using a new computational methodology based on the decomposition of the bimodal distributions of methylated and unmethylated regions, we estimated the extent of the global methylation patterns in a wide range of animals. We then examined the epigenetic changes in silico along the phylogenetic tree. We observed a gradual transition from fractional to global patterns of methylation in deuterostomes, rather than a clear demarcation between vertebrates and invertebrates. When we applied this methodology to six piscine genomes, some of which showed features similar to those of invertebrates.

Conclusions

The mammalian global DNA methylation pattern was probably not acquired at an early stage of vertebrate evolution, but gradually expanded from that of a more ancient organism.
Robust and accurate prediction of noncoding RNAs from aligned sequences
Authors: Saito Yutaka , Sato Kengo , Sakakibara Yasubumi
Published: December 2019

Background

Computational prediction of noncoding RNAs (ncRNAs) is an important task in the post-genomic era. One common approach is to utilize the profile information contained in alignment data rather than single sequences. However, this strategy involves the possibility that the quality of input alignments can influence the performance of prediction methods. Therefore, the evaluation of the robustness against alignment errors is necessary as well as the development of accurate prediction methods.

Results

We describe a new method, called Profile BPLA kernel, which predicts ncRNAs from alignment data in combination with support vector machines (SVMs). Profile BPLA kernel is an extension of base-pairing profile local alignment (BPLA) kernel which we previously developed for the prediction from single sequences. By utilizing the profile information of alignment data, the proposed kernel can achieve better accuracy than the original BPLA kernel. We show that Profile BPLA kernel outperforms the existing prediction methods which also utilize the profile information using the high-quality structural alignment dataset. In addition to these standard benchmark tests, we extensively evaluate the robustness of Profile BPLA kernel against errors in input alignments. We consider two different types of error: first, that all sequences in an alignment are actually ncRNAs but are aligned ignoring their secondary structures; second, that an alignment contains unrelated sequences which are not ncRNAs but still aligned. In both cases, the effects on the performance of Profile BPLA kernel are surprisingly small. Especially for the latter case, we demonstrate that Profile BPLA kernel is more robust compared to the existing prediction methods.

Conclusions

Profile BPLA kernel provides a promising way for identifying ncRNAs from alignment data. It is more accurate than the existing prediction methods, and can keep its performance under the practical situations in which the quality of input alignments is not necessarily high.
DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection
Authors: Chen Ting-wen , Wu Timothy H , Ng Wailap V , Lin Wen-chang
Published: December 2019

Background

Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired.

Results

An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases.

Conclusions

DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from http://140.109.42.19:16080/dodo_web/home.htm
Integrating diverse biological and computational sources for reliable protein-protein interactions
Authors: Wu Min , Li Xiaoli , Chua Hon Nian , Kwoh Chee-Keong , Ng See-Kiong
Published: December 2019

Background

Protein-protein interactions (PPIs) play important roles in various cellular processes. However, the low quality of current PPI data detected from high-throughput screening techniques has diminished the potential usefulness of the data. We need to develop a method to address the high data noise and incompleteness of PPI data, namely, to filter out inaccurate protein interactions (false positives) and predict putative protein interactions (false negatives).

Results

In this paper, we proposed a novel two-step method to integrate diverse biological and computational sources of supporting evidence for reliable PPIs. The first step, interaction binning or InterBIN, groups PPIs together to more accurately estimate the likelihood (Bin-Confidence score) that the protein pairs interact for each biological or computational evidence source. The second step, interaction classification or InterCLASS, integrates the collected Bin-Confidence scores to build classifiers and identify reliable interactions.

Conclusions

We performed comprehensive experiments on two benchmark yeast PPI datasets. The experimental results showed that our proposed method can effectively eliminate false positives in detected PPIs and identify false negatives by predicting novel yet reliable PPIs. Our proposed method also performed significantly better than merely using each of individual evidence sources, illustrating the importance of integrating various biological and computational sources of data and evidence.
CFMDS: CUDA-based fast multidimensional scaling for genome-scale data
Authors: Park Sungin , Shin Soo-Yong , Hwang Kyu-Baek
Published: December 2019

Background

Multidimensional scaling (MDS) is a widely used approach to dimensionality reduction. It has been applied to feature selection and visualization in various areas. Among diverse MDS methods, the classical MDS is a simple and theoretically sound solution for projecting data objects onto a low dimensional space while preserving the original distances among them as much as possible. However, it is not trivial to apply it to genome-scale data (e.g., microarray gene expression profiles) on regular desktop computers, because of its high computational complexity.

Results

We implemented a highly-efficient software application, called CFMDS (CUDA-based Fast MultiDimensional Scaling), which produces an approximate solution of the classical MDS based on CUDA (compute unified device architecture) and the divide-and-conquer principle. CUDA is a parallel computing architecture exploiting the power of the GPU (graphics processing unit). The principle of divide-and-conquer was adopted for circumventing the small memory problem of usual graphics cards. Our application software has been tested on various benchmark datasets including microarrays and compared with the classical MDS algorithms implemented using C# and MATLAB. In our experiments, CFMDS was more than a hundred times faster for large data than such general solutions. Regarding the quality of dimensionality reduction, our approximate solutions were as good as those from the general solutions, as the Pearson's correlation coefficients between them were larger than 0.9.

Conclusions

CFMDS is an expeditious solution for the data dimensionality reduction problem. It is especially useful for efficient processing of genome-scale data consisting of several thousands of objects in several minutes.
Linearization of ancestral multichromosomal genomes
Authors: Maňuch Ján , Patterson Murray , Wittler Roland , Chauve Cedric , Tannier Eric
Published: December 2019

Background

Recovering the structure of ancestral genomes can be formalized in terms of properties of binary matrices such as the Consecutive-Ones Property (C1P). The Linearization Problem asks to extract, from a given binary matrix, a maximum weight subset of rows that satisfies such a property. This problem is in general intractable, and in particular if the ancestral genome is expected to contain only linear chromosomes or a unique circular chromosome. In the present work, we consider a relaxation of this problem, which allows ancestral genomes that can contain several chromosomes, each either linear or circular.

Result

We show that, when restricted to binary matrices of degree two, which correspond to adjacencies, the genomic characters used in most ancestral genome reconstruction methods, this relaxed version of the Linearization Problem is polynomially solvable using a reduction to a matching problem. This result holds in the more general case where columns have bounded multiplicity, which models possibly duplicated ancestral genes. We also prove that for matrices with rows of degrees 2 and 3, without multiplicity and without weights on the rows, the problem is NP-complete, thus tracing sharp tractability boundaries.

Conclusion

As it happened for the breakpoint median problem, also used in ancestral genome reconstruction, relaxing the definition of a genome turns an intractable problem into a tractable one. The relaxation is adapted to some biological contexts, such as bacterial genomes with several replicons, possibly partially assembled. Algorithms can also be used as heuristics for hard variants. More generally, this work opens a way to better understand linearization results for ancestral genome structure inference.
A consolidation algorithm for genomes fractionated after higher order polyploidization
Authors: Jahn Katharina , Zheng Chunfang , Kováč Jakub , Sankoff David
Published: December 2019

Background

It has recently been shown that fractionation, the random loss of excess gene copies after a whole genome duplication event, is a major cause of gene order disruption. When estimating evolutionary distances between genomes based on chromosomal rearrangement, fractionation inevitably leads to significant overestimation of classic rearrangement distances. This bias can be largely avoided when genomes are preprocessed by "consolidation", a procedure that identifies and accounts for regions of fractionation.

Results

In this paper, we present a new consolidation algorithm that extends and improves previous work in several directions. We extend the notion of the fractionation region to use information provided by regions where this process is still ongoing. The new algorithm can optionally work with this new definition of fractionation region and is able to process not only tetraploids but also genomes that have undergone hexaploidization and polyploidization events of higher order. Finally, this algorithm reduces the asymptotic time complexity of consolidation from quadratic to linear dependence on the genome size. The new algorithm is applied both to plant genomes and to simulated data to study the effect of fractionation in ancient hexaploids.
Interpolative multidimensional scaling techniques for the identification of clusters in very large sequence sets
Authors: Hughes Adam , Ruan Yang , Ekanayake Saliya , Bae Seung-Hee , Dong Qunfeng , Rho Mina , Qiu Judy , Fox Geoffrey
Published: December 2019

Background

Modern pyrosequencing techniques make it possible to study complex bacterial populations, such as 16S rRNA, directly from environmental or clinical samples without the need for laboratory purification. Alignment of sequences across the resultant large data sets (100,000+ sequences) is of particular interest for the purpose of identifying potential gene clusters and families, but such analysis represents a daunting computational task. The aim of this work is the development of an efficient pipeline for the clustering of large sequence read sets.

Methods

Pairwise alignment techniques are used here to calculate genetic distances between sequence pairs. These methods are pleasingly parallel and have been shown to more accurately reflect accurate genetic distances in highly variable regions of rRNA genes than do traditional multiple sequence alignment (MSA) approaches. By utilizing Needleman-Wunsch (NW) pairwise alignment in conjunction with novel implementations of interpolative multidimensional scaling (MDS), we have developed an effective method for visualizing massive biosequence data sets and quickly identifying potential gene clusters.

Results

This study demonstrates the use of interpolative MDS to obtain clustering results that are qualitatively similar to those obtained through full MDS, but with substantial cost savings. In particular, the wall clock time required to cluster a set of 100,000 sequences has been reduced from seven hours to less than one hour through the use of interpolative MDS.

Conclusions

Although work remains to be done in selecting the optimal training set size for interpolative MDS, substantial computational cost savings will allow us to cluster much larger sequence sets in the future.
KIS SPLICE: de-novo calling alternative splicing events from RNA-seq data
Authors: Sacomoto Gustavo AT , Kielbassa Janice , Chikhi Rayan , Uricaru Raluca , Antoniou Pavlos , Sagot Marie-France , Peterlongo Pierre , Lacroix Vincent
Published: December 2019

Background

In this paper, we address the problem of identifying and quantifying polymorphisms in RNA-seq data when no reference genome is available, without assembling the full transcripts. Based on the fundamental idea that each polymorphism corresponds to a recognisable pattern in a De Bruijn graph constructed from the RNA-seq reads, we propose a general model for all polymorphisms in such graphs. We then introduce an exact algorithm, called KIS SPLICE, to extract alternative splicing events.

Results

We show that KIS SPLICE enables to identify more correct events than general purpose transcriptome assemblers. Additionally, on a 71 M reads dataset from human brain and liver tissues, KIS SPLICE identified 3497 alternative splicing events, out of which 56% are not present in the annotations, which confirms recent estimates showing that the complexity of alternative splicing has been largely underestimated so far.

Conclusions

We propose new models and algorithms for the detection of polymorphism in RNA-seq data. This opens the way to a new kind of studies on large HTS RNA-seq datasets, where the focus is not the global reconstruction of full-length transcripts, but local assembly of polymorphic regions. KIS SPLICE is available for download at http://alcovna.genouest.org/kissplice/.
Pattern-driven neighborhood search for biclustering of microarray data
Authors: Ayadi Wassim , Elloumi Mourad , Hao Jin-Kao
Published: December 2019

Background

Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications. From a computational point of view, biclustering is a highly combinatorial search problem and can be solved with optimization methods.

Results

We describe a stochastic pattern-driven neighborhood search algorithm for the biclustering problem. Starting from an initial bicluster, the proposed method improves progressively the quality of the bicluster by adjusting some genes and conditions. The adjustments are based on the quality of each gene and condition with respect to the bicluster and the initial data matrix. The performance of the method was evaluated on two well-known microarray datasets (Yeast cell cycle and Saccharomyces cerevisiae), showing that it is able to obtain statistically and biologically significant biclusters. The proposed method was also compared with six reference methods from the literature.

Conclusions

The proposed method is computationally fast and can be applied to discover significant biclusters. It can also used to effectively improve the quality of existing biclusters provided by other biclustering methods.
Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations
Authors: Savojardo Castrense , Fariselli Piero , Martelli Pier Luigi , Casadio Rita
Published: December 2019

Background

Recently, information derived by correlated mutations in proteins has regained relevance for predicting protein contacts. This is due to new forms of mutual information analysis that have been proven to be more suitable to highlight direct coupling between pairs of residues in protein structures and to the large number of protein chains that are currently available for statistical validation. It was previously discussed that disulfide bond topology in proteins is also constrained by correlated mutations.

Results

In this paper we exploit information derived from a corrected mutual information analysis and from the inverse of the covariance matrix to address the problem of the prediction of the topology of disulfide bonds in Eukaryotes. Recently, we have shown that Support Vector Regression (SVR) can improve the prediction for the disulfide connectivity patterns. Here we show that the inclusion of the correlated mutation information increases of 5 percentage points the SVR performance (from 54% to 59%). When this approach is used in combination with a method previously developed by us and scoring at the state of art in predicting both location and topology of disulfide bonds in Eukaryotes (DisLocate), the per-protein accuracy is 38%, 2 percentage points higher than that previously obtained.

Conclusions

In this paper we show that the inclusion of information derived from correlated mutations can improve the performance of the state of the art methods for predicting disulfide connectivity patterns in Eukaryotic proteins. Our analysis also provides support to the notion that improving methods to extract evolutionary information from multiple sequence alignments greatly contributes to the scoring performance of predictors suited to detect relevant features from protein chains.
MS-k NN: protein function prediction by integrating multiple data sources
Authors: Lan Liang , Djuric Nemanja , Guo Yuhong , Vucetic Slobodan
Published: December 2019

Background

Protein function determination is a key challenge in the post-genomic era. Experimental determination of protein functions is accurate, but time-consuming and resource-intensive. A cost-effective alternative is to use the known information about sequence, structure, and functional properties of genes and proteins to predict functions using statistical methods. In this paper, we describe the Multi-Source k-Nearest Neighbor (MS-k NN) algorithm for function prediction, which finds k-nearest neighbors of a query protein based on different types of similarity measures and predicts its function by weighted averaging of its neighbors' functions. Specifically, we used 3 data sources to calculate the similarity scores: sequence similarity, protein-protein interactions, and gene expressions.

Results

We report the results in the context of 2011 Critical Assessment of Function Annotation (CAFA). Prior to CAFA submission deadline, we evaluated our algorithm on 1,302 human test proteins that were represented in all 3 data sources. Using only the sequence similarity information, MS-k NN had term-based Area Under the Curve (AUC) accuracy of Gene Ontology (GO) molecular function predictions of 0.728 when 7,412 human training proteins were used, and 0.819 when 35,622 training proteins from multiple eukaryotic and prokaryotic organisms were used. By aggregating predictions from all three sources, the AUC was further improved to 0.848. Similar result was observed on prediction of GO biological processes. Testing on 595 proteins that were annotated after the CAFA submission deadline showed that overall MS-k NN accuracy was higher than that of baseline algorithms Gotcha and BLAST, which were based solely on sequence similarity information. Since only 10 of the 595 proteins were represented by all 3 data sources, and 66 by two data sources, the difference between 3-source and one-source MS-k NN was rather small.

Conclusions

Based on our results, we have several useful insights: (1) the k-nearest neighbor algorithm is an efficient and effective model for protein function prediction; (2) it is beneficial to transfer functions across a wide range of organisms; (3) it is helpful to integrate multiple sources of protein information.
Discovering and mapping chromatin states using a tree hidden Markov model
Authors: Biesinger Jacob , Wang Yuanfeng , Xie Xiaohui
Published: December 2019

New biological techniques and technological advances in high-throughput sequencing are paving the way for systematic, comprehensive annotation of many genomes, allowing differences between cell types or between disease/normal tissues to be determined with unprecedented breadth. Epigenetic modifications have been shown to exhibit rich diversity between cell types, correlate tightly with cell-type specific gene expression, and changes in epigenetic modifications have been implicated in several diseases. Previous attempts to understand chromatin state have focused on identifying combinations of epigenetic modification, but in cases of multiple cell types, have not considered the lineage of the cells in question.

We present a Bayesian network that uses epigenetic modifications to simultaneously model 1) chromatin mark combinations that give rise to different chromatin states and 2) propensities for transitions between chromatin states through differentiation or disease progression. We apply our model to a recent dataset of histone modifications, covering nine human cell types with nine epigenetic modifications measured for each. Since exact inference in this model is intractable for all the scale of the datasets, we develop several variational approximations and explore their accuracy. Our method exhibits several desirable features including improved accuracy of inferring chromatin states, improved handling of missing data, and linear scaling with dataset size. The source code for our model is available at http://github.com/uci-cbcl/tree-hmm