Identification of Potential Molecular Determinants of Murine Embryonic Stem Cell Differentiation by a Transposon-Based Approach

Embryonic stem cells (ESCs) are self-renewing pluripotent cells, capable of differentiating into all somatic cell types. The molecular control of self-renewal is relatively well-characterized, whereas how ESCs exit pluripotent state to differentiate is poorly understood. Here we identify two genes are required for differentiation and dozens of intergenic regions that potentially regulate ESC differentiation. We used PiggyBac (PB) transposon-based approach to randomly mutate the genome of ESCs, and generated hundreds of clones that resisted differentiation signals. Each clone was sequenced to determine genomic regions mutated by PB insertion. Intriguingly, many mutations were localized among intergenic regions and we identified two genes are required for differentiation. This study should facilitate further exploration of novel molecular determinants of embryonic stem cell differentiation.     

The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning

Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study.     

The Role of Personalised Choice in Decision Support: A Randomized Controlled Trial of an Online Decision Aid for Prostate Cancer Screening

ImportanceDecision support tools can assist people to apply population-based evidence on benefits and harms to individual health decisions. A key question is whether “personalising” choice within decisions aids leads to better decision quality.ObjectiveTo assess the effect of personalising the content of a decision aid for prostate cancer screening using the Prostate Specific Antigen (PSA) test.DesignRandomized controlled trial.SettingAustralia.Participants1,970 men aged 40–69 years were approached to participate in the trial.Intervention1,447 men were randomly allocated to either a standard decision aid with a fixed set of five attributes or a personalised decision aid with choice over the inclusion of up to 10 attributes.Results5% of men in the fixed attribute group scored ‘Have a PSA test’ as the opinion generated by the aid, as compared to 62% of men in the personalised choice group (χ² = 569.38, 2df, p< 0001). Those men who used the personalised decision aid had slightly higher decision quality (t = 2.157, df = 1444, p = 0.031). The men in the personalised choice group made extensive use of the additional decision attributes. There was no difference between the two groups in terms of their stated intention to undergo screening in the next 12 months.ConclusionsTogether, these findings suggest that personalised decision support systems could be an important development in shared decision-making and patient-centered care.

Trial Registration

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12612000723886     

A Clinical Decision Support System for Integrating Tuberculosis and HIV Care in Kenya: A Human-Centered Design Approach

With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.     

基于模糊支持向量机的膜蛋白折叠类型预测

现有的基于支持向量机（support vector machine,SVM）来预测膜蛋白折叠类型的方法．利用的蛋白质序列特征并不充分．并且在处理多类蛋白质分类问题时存在不可分区域,针对这两类问题．提取蛋白质序列的氨基酸和二肽组成特征,并计算加权的多阶氨基酸残基指数相关系数特征,将3类特征融和作为分类器的输入特征矢量．并采用模糊SVM（fuzzy SVM,FSVM）算法解决对传统SVM不可分数据的分类．在无冗余的数据集上测试结果显示．改进的特征提取方法在相同分类算法下预测性能优于已有的特征提取方法：FSVM在相同特征提取方法下性能优于传统的SVM．二者相结合的分类策略在独立性数据集测试下的预测精度达到96．6％．优于现有的多种预测方法．能够作为预测膜蛋白和其它蛋白质折叠类型的有效工具．     

Development of a Simple Reliable Radiographic Scoring System to Aid the Diagnosis of Pulmonary Tuberculosis

Rationale

Chest radiography is sometimes the only method available for investigating patients with possible pulmonary tuberculosis (PTB) with negative sputum smears. However, interpretation of chest radiographs in this context lacks specificity for PTB, is subjective and is neither standardized nor reproducible. Efforts to improve the interpretation of chest radiography are warranted.

Objectives

To develop a scoring system to aid the diagnosis of PTB, using features recorded with the Chest Radiograph Reading and Recording System (CRRS).

Methods

Chest radiographs of outpatients with possible PTB, recruited over 3 years at clinics in South Africa were read by two independent readers using the CRRS method. Multivariate analysis was used to identify features significantly associated with culture-positive PTB. These were weighted and used to generate a score.

Results

473 patients were included in the analysis. Large upper lobe opacities, cavities, unilateral pleural effusion and adenopathy were significantly associated with PTB, had high inter-reader reliability, and received 2, 2, 1 and 2 points, respectively in the final score. Using a cut-off of 2, scores below this threshold had a high negative predictive value (91.5%, 95%CI 87.1,94.7), but low positive predictive value (49.4%, 95%CI 42.9,55.9). Among the 382 TB suspects with negative sputum smears, 229 patients had scores <2; the score correctly ruled out active PTB in 214 of these patients (NPV 93.4%; 95%CI 89.4,96.3). The score had a suboptimal negative predictive value in HIV-infected patients (NPV 86.4, 95% CI 75,94).

Conclusions

The proposed scoring system is simple, and reliably ruled out active PTB in smear-negative HIV-uninfected patients, thus potentially reducing the need for further tests in high burden settings. Validation studies are now required.     

Identification of Infected B-Cell Populations by Using a Recombinant Murine Gammaherpesvirus 68 Expressing a Fluorescent Protein

Infection of inbred mice with murine gammaherpesvirus 68 (MHV68) has proven to be a powerful tool to study gammaherpesvirus pathogenesis. However, one of the limitations of this system has been the inability to directly detect infected cells harvested from infected animals. To address this issue, we generated a transgenic virus that expresses the enhanced yellow fluorescent protein (YFP), driven by the human cytomegalovirus immediate-early promoter and enhancer, from a neutral locus within the viral genome. This virus, MHV68-YFP, replicated and established latency as efficiently as did the wild-type virus. During the early phase of viral latency, MHV68-YFP efficiently marked latently infected cells in the spleen after intranasal inoculation. Staining splenocytes for expression of various surface markers demonstrated the presence of MHV68 in distinct populations of splenic B cells harboring MHV68. Notably, these analyses also revealed that markers used to discriminate between newly formed, follicular and marginal zone B cells may not be reliable for phenotyping B cells harboring MHV68 since virus infection appears to modulate cell surface expression levels of CD21 and CD23. However, as expected, we observed that the overwhelming majority of latently infected B cells at the peak of latency exhibited a germinal center phenotype. These analyses also demonstrated that a significant percentage of MHV68-infected splenocytes at the peak of viral latency are plasma cells (ca. 15% at day 14 and ca. 8% at day 18). Notably, the frequency of virus-infected plasma cells correlated well with the frequency of splenocytes that spontaneously reactivate virus upon explant. Finally, we observed that the efficiency of marking latently infected B cells with the MHV68-YFP recombinant virus declined at later times postinfection, likely due to shut down of transgene expression, and indicating that the utility of this marking strategy is currently limited to the early stages of virus infection.Gammaherpesviruses are characterized by their ability to establish life-long infection in lymphocytes of their host as well as their oncogenic potential. The human gammaherpesviruses, Epstein-Barr virus (EBV) and human herpesvirus 8 (HHV-8; also known as Kaposi''s sarcoma-associated herpesvirus [KSHV]), are associated with a variety of neoplasms. EBV has been implicated in Burkitt''s lymphoma, nasopharyngeal carcinoma, and non-Hodgkin''s lymphoma (15, 27, 33). HHV-8 has been associated with Kaposi''s sarcoma, primary effusion lymphoma, and multicentric Castleman''s disease (4, 5, 7, 24).Research on the human gammaherpesvirus is hindered by their strict species specificity, and thus has been limited mostly to in vitro analyses. Murine gammaherpesvirus 68 (MHV68) is a closely related gammaherpesvirus that naturally infects rodents and provides a useful small animal model to study aspects of gammaherpesvirus pathogenesis that cannot be addressed for the human herpesviruses (3, 22, 25). In addition, the viral genome has been cloned as a bacterial artificial chromosome (BAC) and can readily be manipulated in Escherichia coli (1) and, coupled with the availability of numerous transgenic and knockout strains of mice, MHV68 infection of laboratory mice has provided a powerful small animal model for characterizing basic aspects of gammaherpesvirus pathogenesis in vivo.Like the human gammaherpesviruses, MHV68 establishes long-term latency in B cells, although at early time points after infection latency can also be detected in macrophages and dendritic cells (11, 26, 30). Acute infection is cleared around 2 to 3 weeks postinfection, and by days 16 to 18 postinfection the frequency of viral genome-positive cells in the spleen is ca. 1 in 100 splenocytes (19, 31). This is the peak of splenic latency, and the frequency of infected cells begins to decline significantly until it reaches a steady-state level of ca. 1 in 10,000 splenocytes by 3 months postinfection. Previous analyses have shown that latency is mainly established in germinal center (GC) and memory B cells (12, 19, 31). At early time points during the establishment of latency, the GC fraction has been shown to have the highest percentage of infected cells (ca. 60 to 80% of MHV68-infected B cells) (12). However, even in this population, only around 10% of total GC cells are infected (12). This low frequency limits detailed molecular analyses that can be performed on infected cells (e.g., analysis of virus-induced changes in cellular gene expression).Until now, there has not been an efficient way to directly detect or purify/enrich for MHV68-infected cells harvested from the spleens of infected mice. Because of these issues, we sought to develop a method to efficiently mark infected cells that would allow easy detection, as well as isolation, of infected cells. To this end, we created a transgenic virus that expresses the enhanced yellow fluorescent protein (YFP) from a neutral locus in the viral genome located between open reading frames (ORFs) 27 and 29b. We have previously used this locus to introduce other transgenes (Cre-recombinase and IκBαM expression cassettes) and have shown that this locus tolerates the insertion of transgene expression cassettes (14, 20). We show here that the MHV68-YFP recombinant virus is capable of efficiently marking infected cells, that highly enriched populations of infected cells can easily be isolated based of YFP expression, and that direct detection of infected cells provides a powerful tool for phenotypic analysis of infected cell populations.     

Assessment of Trading Partners for China's Rare Earth Exports Using a Decision Analytic Approach

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China''s rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.     

Binding Site Identification and Flexible Docking of Single Stranded RNA to Proteins Using a Fragment-Based Approach

Protein-RNA docking is hampered by the high flexibility of RNA, and particularly single-stranded RNA (ssRNA). Yet, ssRNA regions typically carry the specificity of protein recognition. The lack of methodology for modeling such regions limits the accuracy of current protein-RNA docking methods. We developed a fragment-based approach to model protein-bound ssRNA, based on the structure of the protein and the sequence of the RNA, without any prior knowledge of the RNA binding site or the RNA structure. The conformational diversity of each fragment is sampled by an exhaustive RNA fragment library that was created from all the existing experimental structures of protein-ssRNA complexes. A systematic and detailed analysis of fragment-based ssRNA docking was performed which constitutes a proof-of-principle for the fragment-based approach. The method was tested on two 8-homo-nucleotide ssRNA-protein complexes and was able to identify the binding site on the protein within 10 Å. Moreover, a structure of each bound ssRNA could be generated in close agreement with the crystal structure with a mean deviation of ~1.5 Å except for a terminal nucleotide. This is the first time a bound ssRNA could be modeled from sequence with high precision.     

L1 Cell Adhesion Molecule as a Potential Therapeutic Target in Murine Models of Endometriosis Using a Monoclonal Antibody Approach

Background/Aims

The neural cell adhesion molecule L1CAM is a transmembrane glycoprotein abnormally expressed in tumors and previously associated with cell proliferation, adhesion and invasion, as well as neurite outgrowth in endometriosis. Being an attractive target molecule for antibody-based therapy, the present study assessed the ability of the monoclonal anti-L1 antibody (anti-L1 mAb) to impair the development of endometriotic lesions in vivo and endometriosis-associated nerve fiber growth.

Methods and Results

Endometriosis was experimentally induced in sexually mature B6C3F1 (n=34) and CD-1 nude (n=21) mice by autologous and heterologous transplantation, respectively, of endometrial fragments into the peritoneal cavity. Transplantation was confirmed four weeks post-surgery by in vivo magnetic resonance imaging and laparotomy, respectively. Mice were then intraperitoneally injected with anti-L1 mAb or an IgG isotype control antibody twice weekly, over a period of four weeks. Upon treatment completion, mice were sacrificed and endometrial implants were excised, measured and fixed. Endometriosis was histologically confirmed and L1CAM was detected by immunohistochemistry. Endometriotic lesion size was significantly reduced in anti-L1-treated B6C3F1 and CD-1 nude mice compared to mice treated with control antibody (P<0.05). Accordingly, a decreased number of PCNA positive epithelial and stromal cells was detected in autologously and heterologously induced endometriotic lesions exposed to anti-L1 mAb treatment. Anti-L1-treated mice also presented a diminished number of intraperitoneal adhesions at implantation sites compared with controls. Furthermore, a double-blind counting of anti-neurofilament L stained nerves revealed significantly reduced nerve density within peritoneal lesions in anti-L1 treated B6C3F1 mice (P=0.0039).

Conclusions

Local anti-L1 mAb treatment suppressed endometriosis growth in B6C3F1 and CD-1 nude mice and exerted a potent anti-neurogenic effect on induced endometriotic lesions in vivo. The findings of this preliminary study in mice provide a strong basis for further testing in in vivo models.     

A New Stage in the Performance of a Human Immunogram: A Visual Streptavidin-Biotin Approach

The production of a reagent kit has been recently organized by DAKO, Immunotekh and other companies, for phenotyping of lymphocytes by the streptavidin–biotin method. The method needs no sophisticated equipment, is highly sensitive, and allows rapid staining of different lymphocyte subpopulations in capillary blood smears and subsequent observation of them under a light microscope. We have modified this method for staining leukocytes in the monolayer prepared with a plate cytorotor. Not decreasing the above-mentioned advantages of the method, this modification significantly cheapens and simplifies the staining procedure; the blood cells of 16 subjects can be stained concurrently, and the staining can be performed by a technician. The streptavidin–biotin method of lymphocyte phenotyping can be mastered in every immunological laboratory, thus improving its technical level.     

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein–protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.     

Cost-Effectiveness of Clinical Decision Support System in Improving Maternal Health Care in Ghana

ObjectiveThis paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS) in the identification of maternal complications in Ghana.MethodsA cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider’s perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out.ResultsComputer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC) in the intervention health centres (before-intervention= 9 /1,000 ANC attendance; after-intervention= 12/1,000 ANC attendance; P-value=0.010). In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention= 96/1,000 labour clients; P-value=0.305). Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost –effectiveness ratio) decreased from US$17,017.58 (before-intervention) to US$15,207.5 (after-intervention). Incremental cost –effectiveness ratio (ICER) was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS), cost per pregnancy complication detected was US$285.ConclusionsComputer –assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether the additional benefit is worth the additional cost.     

Identification of New Oligodendrocyte- and Myelin-Specific Genes by a Differential Screening Approach

Abstract: We have isolated several new genes that are specifically expressed by oligodendrocytes in the CNS. This was achieved by differential screening of a rat spinal cord cDNA library with probes derived from normal and from oligodendrocyte-free spinal cord mRNAs. Four of these genes are exclusively expressed by oligodendrocytes: Three of these are not related to known genes, whereas one encodes the myelin oligodendrocyte glycoprotein (MOG). Four other genes are expressed by oligodendrocytes as well as by Schwann cells. One gene codes for apolipoprotein D, which is thought to be involved in lipid metabolism. A second cDNA sequence codes for the recently identified galactosylceramide-synthesizing enzyme UDP-galactose:ceramide galactosyl-transferase. The third gene encodes a small protein with four putative transmembrane domains that is related to a T-lymphocyte-specific membrane protein, MAL. The fourth gene encodes the rat homologue of the stearyl-CoA-desaturase 2 (SCD2) gene, which is specifically expressed in the nervous system and involved in the synthesis and regulation of long-chain unsaturated fatty acids essential for myelination. Finally, we found that a member of the β-tubulin family is highly expressed in oligodendrocytes as well as neurons. The identification of several new proteins that may play a role in myelin synthesis and sheath formation will lead to new insight into this complex mechanism.     

Characterization of X-ray Dose in Murine Animals Using microCT,a New Low-Dose Detector and nanoDot Dosimeters

Background

Dose continues to be an area of concern in preclinical imaging studies, especially for those imaging disease progression in longitudinal studies. To our knowledge, this work is the first to characterize and assess dose from the Inveon CT imaging platform using nanoDot dosimeters. This work is also the first to characterize a new low-dose configuration available for this platform.

Methodology/Principal Findings

nanoDot dosimeters from Landauer, Inc. were surgically implanted into 15 wild type mice. Two nanoDots were placed in each animal: one just under the skin behind the spine and the other located centrally within the abdomen. A manufacturer-recommended CT protocol was created with 1 projection per degree of rotation acquired over 360 degrees. For best comparison of the low dose and standard configurations, noise characteristics of the reconstructed images were used to match the acquisition protocol parameters. Results for all dose measurements showed the average dose delivered to the abdomen to be 13.8 cGy±0.74 and 0.97 cGy±0.05 for standard and low dose configurations respectively. Skin measurements of dose averaged 15.99 cGy±0.72 and 1.18 cGy±0.06. For both groups, the standard deviation to mean was less than 5.6%. The maximum dose received for the abdomen was 15.12 cGy and 0.97 cGy while the maximum dose for the skin was 17.3 cGy and 1.32 cGy. Control dosimeters were used for each group to validate that no unwanted additional radiation was present to bias the results.

Conclusions/Significance

This study shows that the Inveon CT platform is suitable for imaging mice both for single and longitudinal studies. Use of low-dose detector hardware results in significant reductions in dose to subjects with a >12x (90%) reduction in delivered dose. Installation of this hardware on another in vivo microCT platform resulted in dose reductions of over 9x (89%).