Multiplexed tandem PCR: gene profiling from small amounts of RNA using SYBR Green detection

Multiplexed tandem PCR (MT-PCR) is a process for highly multiplexed gene expression profiling. In the first step, multiple primer pairs are added to the RNA to be analysed together with reverse transcriptase and Taq DNA polymerase. Following reverse transcription, the multiplexed amplicons are simultaneously amplified for a small number of cycles so as to avoid competition between amplicons. The reaction product is then diluted and analysed in multiple individual PCRs using primers nested inside the primers used for the multiplexed amplification. As the second PCR uses a template enriched in the amplicons of interest, the conditions can be optimized to significantly reduce ‘primer dimer’ formation allowing SYBR Green chemistry to be used for quantification. MT-PCR can be configured for as little as 10 pg RNA (equivalent to a single mammalian cell) and works well with RNA extracted from archival formalin-fixed paraffin-embedded sections. We illustrate MT-PCR with gene expression profiles of breast cancer cell lines

Control of p62 binding to TGN38/41 by phosphorylation

AbstractTGN38/41 cycles between the trans-Golgi network (TGN) and plasma membrane, traversing three sorting compartments: the TGN, plasma membrane and early endosome. The targeting signals responsible for this complex itinerary reside in a short cytoplasmic domain of 33 amino acid residues. We show that phosphorylation of the cytoplasmic domain of TGN38 prevents binding of p62 — a cytoplasmic protein essential for exocytic vesicle formation. Thus the cycle of TGN38/41 traffic, and by implication the pathway of exocytosis, could be controlled by phosphorylation of the TGN38 cytoplasmic domain

Improving Automatic Melanoma Diagnosis using Deep Learning-Based Segmentation of Irregular Networks

Deep Learning Has Achieved Significant Success in Malignant Melanoma Diagnosis. These Diagnostic Models Are Undergoing a Transition into Clinical Use. However, with Melanoma Diagnostic Accuracy in the Range of Ninety Percent, a Significant Minority of Melanomas Are Missed by Deep Learning. Many of the Melanomas Missed Have Irregular Pigment Networks Visible using Dermoscopy. This Research Presents an Annotated Irregular Network Database and Develops a Classification Pipeline that Fuses Deep Learning Image-Level Results with Conventional Hand-Crafted Features from Irregular Pigment Networks. We Identified and Annotated 487 Unique Dermoscopic Melanoma Lesions from Images in the ISIC 2019 Dermoscopic Dataset to Create a Ground-Truth Irregular Pigment Network Dataset. We Trained Multiple Transfer Learned Segmentation Models to Detect Irregular Networks in This Training Set. a Separate, Mutually Exclusive Subset of the International Skin Imaging Collaboration (ISIC) 2019 Dataset with 500 Melanomas and 500 Benign Lesions Was Used for Training and Testing Deep Learning Models for the Binary Classification of Melanoma Versus Benign. the Best Segmentation Model, U-Net++, Generated Irregular Network Masks on the 1000-Image Dataset. Other Classical Color, Texture, and Shape Features Were Calculated for the Irregular Network Areas. We Achieved an Increase in the Recall of Melanoma Versus Benign of 11% and in Accuracy of 2% over DL-Only Models using Conventional Classifiers in a Sequential Pipeline based on the Cascade Generalization Framework, with the Highest Increase in Recall Accompanying the Use of the Random Forest Algorithm. the Proposed Approach Facilitates Leveraging the Strengths of Both Deep Learning and Conventional Image Processing Techniques to Improve the Accuracy of Melanoma Diagnosis. Further Research Combining Deep Learning with Conventional Image Processing on Automatically Detected Dermoscopic Features is Warranted

Rapid semi-automated quantitative multiplex tandem PCR (MT-PCR) assays for the differential diagnosis of influenza-like illness

<p>Abstract</p> <p>Background</p> <p>Influenza A, including avian influenza, is a major public health threat in developed and developing countries. Rapid and accurate detection is a key component of strategies to contain spread of infection, and the efficient diagnosis of influenza-like-illness is essential to protect health infrastructure in the event of a major influenza outbreak.</p> <p>Methods</p> <p>We developed a multiplexed PCR (MT-PCR) assay for the simultaneous diagnosis of respiratory viruses causing influenza-like illness, including the specific recognition of influenza A haemagglutinin subtypes H1, H3, and H5. We tested several hundred clinical specimens in two diagnostic reference laboratories and compared the results with standard techniques.</p> <p>Results</p> <p>The sensitivity and specificity of these assays was higher than individual assays based on direct antigen detection and standard PCR against a range of control templates and in several hundred clinical specimens. The MT-PCR assays provided differential diagnoses as well as potentially useful quantitation of virus in clinical samples.</p> <p>Conclusions</p> <p>MT-PCR is a potentially powerful tool for the differential diagnosis of influenza-like illness in the clinical diagnostic laboratory.</p

Digitizing a Face-to-Face Group Fatigue Management Program: Exploring the Views of People With Multiple Sclerosis and Health Care Professionals Via Consultation Groups and Interviews.

BACKGROUND: Fatigue is one of the most common and debilitating symptoms of multiple sclerosis (MS) and is the main reason why people with MS stop working early. The MS Society in the United Kingdom funded a randomized controlled trial of FACETS-a face-to-face group-based fatigue management program for people with multiple sclerosis (pwMS)-developed by members of the research team. Given the favorable trial results and to help with implementation, the MS Society supported the design and printing of the FACETS manual and materials and the national delivery of FACETS training courses (designed by the research team) for health care professionals (HCPs). By 2015 more than 1500 pwMS had received the FACETS program, but it is not available in all areas and a face-to-face format may not be suitable for, or appeal to, everyone. For these reasons, the MS Society funded a consultation to explore an alternative Web-based model of service delivery. OBJECTIVE: The aim of this study was to gather views about a Web-based model of service delivery from HCPs who had delivered FACETS and from pwMS who had attended FACETS. METHODS: Telephone consultations were undertaken with FACETS-trained HCPs who had experience of delivering FACETS (n=8). Three face-to-face consultation groups were held with pwMS who had attended the FACETS program: London (n=4), Liverpool (n=4), and Bristol (n=7). The interviews and consultation groups were digitally recorded and transcribed. A thematic analysis was undertaken to identify key themes. Toward the end of the study, a roundtable meeting was held to discuss outcomes from the consultation with representatives from the MS Society, HCPs, and pwMS. RESULTS: Key challenges and opportunities of designing and delivering an integrated Web-based version of FACETS and maintaining user engagement were identified across 7 themes (delivery, online delivery, design, group, engagement, interactivity, and HCP relationships). Particularly of interest were themes related to replicating the group dynamics and the lack of high-quality solutions that would support the FACETS' weekly homework tasks and symptom monitoring and management. CONCLUSIONS: A minimum viable Web-based version of FACETS was suggested as the best starting point for a phased implementation, enabling a solution that could then be added to over time. It was also proposed that a separate study should look to create a free stand-alone digital toolkit focusing on the homework elements of FACETS. This study has commenced with a first version of the toolkit in development involving pwMS throughout the design and build stages to ensure a user-centered solution

Epidermal Growth Factor Receptor Activation in Glioblastoma through Novel Missense Mutations in the Extracellular Domain

Background: Protein tyrosine kinases are important regulators of cellular homeostasis with tightly controlled catalytic activity. Mutations in kinase-encoding genes can relieve the autoinhibitory constraints on kinase activity, can promote malignant transformation, and appear to be a major determinant of response to kinase inhibitor therapy. Missense mutations in the EGFR kinase domain, for example, have recently been identified in patients who showed clinical responses to EGFR kinase inhibitor therapy. Methods and Findings: Encouraged by the promising clinical activity of epidermal growth factor receptor (EGFR) kinase inhibitors in treating glioblastoma in humans, we have sequenced the complete EGFR coding sequence in glioma tumor samples and cell lines. We identified novel missense mutations in the extracellular domain of EGFR in 13.6% (18/132) of glioblastomas and 12.5% (1/ 8) of glioblastoma cell lines. These EGFR mutations were associated with increased EGFR gene dosage and conferred anchorage-independent growth and tumorigenicity to NIH-3T3 cells. Cells transformed by expression of these EGFR mutants were sensitive to small-molecule EGFR kinase inhibitors. Conclusions: Our results suggest extracellular missense mutations as a novel mechanism for oncogenic EGFR activation and may help identify patients who can benefit from EGFR kinase inhibitors for treatment of glioblastoma

A meta-analysis of the investment-uncertainty relationship

In this article we use meta-analysis to investigate the investment-uncertainty relationship. We focus on the direction and statistical significance of empirical estimates. Specifically, we estimate an ordered probit model and transform the estimated coefficients into marginal effects to reflect the changes in the probability of finding a significantly negative estimate, an insignificant estimate, or a significantly positive estimate. Exploratory data analysis shows that there is little empirical evidence for a positive relationship. The regression results suggest that the source of uncertainty, the level of data aggregation, the underlying model specification, and differences between short- and long-run effects are important sources of variation in study outcomes. These findings are, by and large, robust to the introduction of a trend variable to capture publication trends in the literature. The probability of finding a significantly negative relationship is higher in more recently published studies. JEL Classification: D21, D80, E22 1

Epidermal Growth Factor Receptor Activation in Glioblastoma through Novel Missense Mutations in the Extracellular Domain

BACKGROUND: Protein tyrosine kinases are important regulators of cellular homeostasis with tightly controlled catalytic activity. Mutations in kinase-encoding genes can relieve the autoinhibitory constraints on kinase activity, can promote malignant transformation, and appear to be a major determinant of response to kinase inhibitor therapy. Missense mutations in the EGFR kinase domain, for example, have recently been identified in patients who showed clinical responses to EGFR kinase inhibitor therapy. METHODS AND FINDINGS: Encouraged by the promising clinical activity of epidermal growth factor receptor (EGFR) kinase inhibitors in treating glioblastoma in humans, we have sequenced the complete EGFR coding sequence in glioma tumor samples and cell lines. We identified novel missense mutations in the extracellular domain of EGFR in 13.6% (18/132) of glioblastomas and 12.5% (1/8) of glioblastoma cell lines. These EGFR mutations were associated with increased EGFR gene dosage and conferred anchorage-independent growth and tumorigenicity to NIH-3T3 cells. Cells transformed by expression of these EGFR mutants were sensitive to small-molecule EGFR kinase inhibitors. CONCLUSIONS: Our results suggest extracellular missense mutations as a novel mechanism for oncogenic EGFR activation and may help identify patients who can benefit from EGFR kinase inhibitors for treatment of glioblastoma

The Arabidopsis thaliana Homeobox Gene ATHB12 Is Involved in Symptom Development Caused by Geminivirus Infection

BACKGROUND: Geminiviruses are single-stranded DNA viruses that infect a number of monocotyledonous and dicotyledonous plants. Arabidopsis is susceptible to infection with the Curtovirus, Beet severe curly top virus (BSCTV). Infection of Arabidopsis with BSCTV causes severe symptoms characterized by stunting, leaf curling, and the development of abnormal inflorescence and root structures. BSCTV-induced symptom development requires the virus-encoded C4 protein which is thought to interact with specific plant-host proteins and disrupt signaling pathways important for controlling cell division and development. Very little is known about the specific plant regulatory factors that participate in BSCTV-induced symptom development. This study was conducted to identify specific transcription factors that are induced by BSCTV infection. METHODOLOGY/PRINCIPAL FINDINGS: Arabidopsis plants were inoculated with BSCTV and the induction of specific transcription factors was monitored using quantitative real-time polymerase chain reaction assays. We found that the ATHB12 and ATHB7 genes, members of the homeodomain-leucine zipper family of transcription factors previously shown to be induced by abscisic acid and water stress, are induced in symptomatic tissues of Arabidopsis inoculated with BSCTV. ATHB12 expression is correlated with an array of morphological abnormalities including leaf curling, stunting, and callus-like structures in infected Arabidopsis. Inoculation of plants with a BSCTV mutant with a defective c4 gene failed to induce ATHB12. Transgenic plants expressing the BSCTV C4 gene exhibited increased ATHB12 expression whereas BSCTV-infected ATHB12 knock-down plants developed milder symptoms and had lower ATHB12 expression compared to the wild-type plants. Reporter gene studies demonstrated that the ATHB12 promoter was responsive to BSCTV infection and the highest expression levels were observed in symptomatic tissues where cell cycle genes also were induced. CONCLUSIONS/SIGNIFICANCE: These results suggest that ATHB7 and ATHB12 may play an important role in the activation of the abnormal cell division associated with symptom development during geminivirus infection