Measuring gene transcription using real-time reverse transcription polymerase chain reaction (RT-qPCR) technology is a mainstay of molecular biology. Technologies now exist to measure the abundance ...of many transcripts in parallel. The selection of the optimal reference gene for the normalisation of this data is a recurring problem, and several algorithms have been developed in order to solve it. So far nothing in R exists to unite these methods, together with other functions to read in and normalise the data using the chosen reference gene(s).
We have developed two R/Bioconductor packages, ReadqPCR and NormqPCR, intended for a user with some experience with high-throughput data analysis using R, who wishes to use R to analyse RT-qPCR data. We illustrate their potential use in a workflow analysing a generic RT-qPCR experiment, and apply this to a real dataset. Packages are available from http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.htmland http://www.bioconductor.org/packages/release/bioc/html/NormqPCR.html
These packages increase the repetoire of RT-qPCR analysis tools available to the R user and allow them to (amongst other things) read their data into R, hold it in an ExpressionSet compatible R object, choose appropriate reference genes, normalise the data and look for differential expression between samples.
Transient interactions, which involve protein interactions that are formed and broken easily, are important in many aspects of cellular function. Here we describe structural and functional properties ...of transient interactions between globular domains and between globular domains, short peptides, and disordered regions. The importance of posttranslational modifications in transient interactions is also considered. We review techniques used in the detection of the different types of transient protein-protein interactions. We also look at the role of transient interactions within protein-protein interaction networks and consider their contribution to different aspects of these networks.
Background:
A spring ligament tear is commonly present in advanced stages of adult acquired flatfoot deformity (AAFD). Previous anatomic studies have demonstrated that the superficial deltoid ...ligament blends with the superomedial spring ligament, forming the tibiocalcaneonavicular ligament (TCNL). Adding allograft TCNL reconstruction to osseous correction has been suggested to augment medial peritalar stability in advanced AAFD with large spring ligament tears. We aimed to investigate the clinical and radiographic outcomes of TCNL reconstruction for flexible AAFD with medial peritalar instability.
Methods:
Fourteen feet in 12 patients who underwent osseous and TCNL reconstructions for advanced AAFD (stage IIB with large spring ligament tears or stage IV) were recruited for the study. The mean postoperative follow-up was 24 (range, 12-33) months. Pre- and postoperative clinical outcomes were assessed by the Foot and Ankle Ability Measure (FAAM), SF-36, and Patient-Reported Outcomes Measurement Information System (PROMIS). Correction of forefoot abduction and the sagittal arch were measured from pre- and postoperative weightbearing radiographs.
Results:
The FAAM Activities of Daily Living improved from 69.3 to 90.1 (P = .001). The SF-36 Physical Function (PF) and Pain subscales both improved significantly (39.4 to 87.8 and 44.6 to 93.1, respectively, P < .001 for each). The PROMIS PF improved from 38.2 to 46.8 (P = .002) and the PROMIS Pain Interference (PI) from 62.6 to 50.1 (P = .003). Radiographic measures showed an improved anterior-posterior (AP) talo–first metatarsal angle of 24.7 to 11.8 degrees (P < .001) and talonavicular coverage angle of 47.4 to 23.1 degrees (P < .01). An improved Meary’s angle of 29.7 to 12.5 degrees (P < .001) and a calcaneal pitch angle of 11.7 to 16.9 degrees (P = .14) were noted in the lateral view.
Conclusion:
Considering the anatomic characteristics of the deltoid-spring ligament complex, TCNL reconstruction may play a significant role in maintaining peritalar stability when performed with osseous correction. Deltoid-spring ligament (TCNL) reconstruction is a viable surgical option for those with advanced stage AAFD with medial peritalar instability that leads to improved functional and radiographic outcomes.
Level of Evidence:
Level IV, retrospective case series.
Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the leading causes of hypersensitivity reactions to drugs, and they are classified in two groups: those induced by nonspecific immunological ...mechanisms (non-allergic or cross-intolerance (CI) reactions), or by specific immunological mechanisms (allergic or selective reactions (SR)). The pathogenesis of CI is associated with their pharmacological activity (COX-1 inhibition), with symptoms due to an imbalance in the arachidonic acid pathway, independently of their chemical structure. SRs are mediated by specific IgE- or by a T-cell response and can be induced by a single NSAID or a class of chemically related NSAIDs, with patients tolerating chemically unrelated compounds. NSAIDs hypersensitivity reactions have been classified in five main groups: i) NSAIDs-exacerbated respiratory disease (NERD); ii) NSAIDs-exacerbated cutaneous disease (NECD); iii) NSAIDs-induced urticaria/angioedema (NIUA); iv) Single NSAID-induced urticaria/angioedema or anaphylaxis (SNIUAA); v) Single NSAID-induced delayed reactions (SNIDRs). Although this classification described above is widely accepted by most authors some phenotypes such as blended reactions do not fit. Therefore more research is needed in this topic.
If they could be easily exfoliated, layered materials would become a diverse source of two-dimensional crystals whose properties would be useful in applications ranging from electronics to energy ...storage. We show that layered compounds such as MoS₂, WS₂, MoSe₂, MoTe₂, TaSe₂, NbSe₂, NiTe₂, BN, and Bi₂Te₃ can be efficiently dispersed in common solvents and can be deposited as individual flakes or formed into films. Electron microscopy strongly suggests that the material is exfoliated into individual layers. By blending this material with suspensions of other nanomaterials or polymer solutions, we can prepare hybrid dispersions or composites, which can be cast into films. We show that WS₂ and MoS₂ effectively reinforce polymers, whereas WS₂/carbon nanotube hybrid films have high conductivity, leading to promising thermoelectric properties.
Genetic and molecular analysis of rare disease is made difficult by the small numbers of affected patients. Phenotypic comorbidity analysis can help rectify this by combining information from ...individuals with similar phenotypes and looking for overlap in terms of shared genes and underlying functional systems. However, few studies have combined comorbidity analysis with genomic data. We present a computational approach that connects patient phenotypes based on phenotypic co-occurence and uses genomic information related to the patient mutations to assign genes to the phenotypes, which are used to detect enriched functional systems. These phenotypes are clustered using network analysis to obtain functionally coherent phenotype clusters. We applied the approach to the DECIPHER database, containing phenotypic and genomic information for thousands of patients with heterogeneous rare disorders and copy number variants. Validity was demonstrated through overlap with known diseases, co-mention within the biomedical literature, semantic similarity measures, and patient cluster membership. These connected pairs formed multiple phenotype clusters, showing functional coherence, and mapped to genes and systems involved in similar pathological processes. Examples include claudin genes from the 22q11 genomic region associated with a cluster of phenotypes related to DiGeorge syndrome and genes related to the GO term anterior/posterior pattern specification associated with abnormal development. The clusters generated can help with the diagnosis of rare diseases, by suggesting additional phenotypes for a given patient and potential underlying functional systems. Other tools to find causal genes based on phenotype were also investigated. The approach has been implemented as a workflow, named PhenCo, which can be adapted to any set of patients for which phenomic and genomic data is available. Full details of the analysis, including the clusters formed, their constituent functional systems and underlying genes are given. Code to implement the workflow is available from GitHub.
The kidney donor risk index (KDRI) and percentile conversion, kidney donor profile index (KDPI), provide a continuous measure of donor quality. Kidneys with a KDPI >85% (KDPI85) are referred to as ...“high KDPI.” The KDPI85 cutoff changes every year, impacting which kidneys are labeled as KDPIHIGH. We examine kidney utilization around the KDPI85 cutoff and explore the “high KDPI” labeling effect. KDRI to KDPI Mapping Tables from 2012 to 2020 were used to determine the yearly KDRI85 value. Organ Procurement and Transplantation Network data was used to calculate discard rates and model organ use. KDRI85 varied between 1.768 and 1.888. In a multivariable analysis, kidney utilization was lower for KDPI 86% compared with KDPI 85% kidneys (p = .046). Kidneys with a KDRI between 1.785–1.849 were classified as KDPIHIGH in the years 2015–2017 and KDPILOW in the years 2018–2020. The discard rate was 44.9% when labeled as KDPIHIGH and 39.1% when labeled as KDPILOW (p < .01). For kidneys with the same KDRI, the high KDPI label is associated with increased discard. We should reconsider the appropriateness of the “high KDPI” label.
Deceased donor kidneys with the same kidney donor risk index are more frequently discarded when labelled as high kidney donor profile index.
Abstract
Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as ...enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin–chromatin and chromatin–protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution.
We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.
Kidney transplants from donors after circulatory death (DCD) make up an increasing proportion of all deceased donor kidney transplants in the United States (US). However, DCD grafts are considered to ...be of lower quality than kidneys from donors after brain death (DBD). It is unclear whether graft survival is different for these two types of donor kidneys.
We conducted a retrospective cohort study of US deceased donor kidney recipients using data from the United Network of Organ Sharing from 12/4/2014 to 6/30/2018. We employed a Cox proportional hazard model with mixed effects to compare all-cause graft loss and death-censored graft loss for DCD versus DBD deceased donor kidney transplant recipients. We used transplant center as the random effects term to account for cluster-specific random effects. In the multivariable analysis, we adjusted for recipient characteristics, donor factors, and transplant logistics.
Our cohort included 27,494 DBD and 7,770 DCD graft recipients transplanted from 2014 to 2018 who were followed over a median of 1.92 years (IQR 1.08-2.83). For DCD compared with DBD recipients, we did not find a significant difference in all-cause graft loss (hazard ratio HR 0.96, 95% confidence interval CI 0.87-1.05 in univariable and HR 1.03 95% CI 0.95-1.13 in multivariable analysis) or for death-censored graft loss (HR 0.97 (95% CI 0.91-1.06) in univariable and 1.05 (95% CI 0.99-1.11) in multivariable analysis).
For a contemporary cohort of deceased donor kidney transplant recipients, we did not find a difference in the likelihood of graft loss for DCD compared with DBD grafts. These findings signal a need for additional investigation into whether DCD status independently contributes to other important outcomes for current kidney transplant recipients and indices of graft quality.
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