F-18 FDG PET/CT Imaging in Normal Variants, Pitfalls and Artifacts in the Abdomen and Pelvis

Since its introduction into clinical practice, multimodality imaging has revolutionized diagnostic imaging for both oncologic and non-oncologic pathologies. 18F-fluorodeoxyglucose (18F-FDG) PET/CT imaging which takes advantage of increased anaerobic glycolysis that occurs in tumor cells (Warburg effect) has gained significant clinical relevance in the management of most, if not all oncologic conditions. Because FDG is taken by both normal and abnormal tissues, PET/CT imaging may demonstrate several normal variants and imaging pitfalls. These may ultimately impact disease detection and diagnostic accuracy. Imaging specialists (nuclear medicine physicians and radiologists) must demonstrate a thorough understanding of normal and physiologic variants in the distribution of 18F-FDG; including potential imaging pitfalls and technical artifacts to minimize misinterpretation of images. The normal physiologic course of 18F-FDG results in a variable degree of uptake in the stomach, liver, spleen, small and large bowel. Urinary excretion results in renal, ureteric, and urinary bladder uptake. Technical artifacts can occur due to motion, truncation as well as the effects of contrast agents and metallic hardware. Using pictorial illustrations, this paper aims to describe the variants of physiologic 18F-FDG uptake that may mimic pathology as well as potential benign conditions that may result in misinterpretation of PET/CT images in common oncologic conditions of the abdomen and pelvis.

‘SRS’ R Package and ‘q2-srs’ QIIME 2 Plugin: Normalization of Microbiome Data Using Scaling with Ranked Subsampling (SRS)

Several ecological data types, especially microbiome count data, are commonly sample-wise normalized before analysis to correct for sampling bias and other technical artifacts. Recently, we developed an algorithm for the normalization of ecological count data called ‘scaling with ranked subsampling (SRS)’, which surpasses the widely adopted ‘rarefying’ (random subsampling without replacement) in reproducibility and in safeguarding the original community structure. Here, we describe an implementation of the SRS algorithm in the ‘SRS’ R package and the ‘q2-srs’ QIIME 2 plugin. We also provide accessory functions for dataset exploration to guide the choice of parameters for SRS.

Shaping the World

This article explores the biography of a network of Soviet telescopic cameras stationed across the African Sahel during the Cold War. Through joint Soviet-African cooperative programs, scientists used these advanced cameras in Egypt, Somalia, Mali, the Sudan, and Chad to photograph satellites flying overhead to gather data to produce a new model of the Earth, one that Soviet scientists hoped would be an alternative to Western models. I argue that these technical artifacts in Africa, connected into a single global network, represented examples of “infrastructural irruptions” of Cold War technopolitics into African geography, wherein the superpowers placed networked technologies inside postcolonial spaces for the collection of data. Although these technologies were nominally Soviet in origin, the story could also be read as one of Africans who invested their geography with agency in the production of scientific knowledge. Like the socialist moment in Africa and indeed the Soviet Union itself, this camera network no longer exists, its data compromised and its material imprint disappeared. But this “failure” should not blind us to the immanent power of possibility embedded in this incomplete project. I argue that this combination of unbounded aspiration and incomplete materiality was a powerful manifestation of the African-Soviet Modern.

Technologizing the Transcendental, not Discarding it

In this reply I further defend my claim that the transcendental should always remain a primary concern for philosophy of technology as a philosophical enterprise, contra the empirical turn’s rejection of it. Yet, instead of emphasizing the non-technological conditions of technology, as ‘classic’ thinkers of technology such as Heidegger did, it should recognize technology itself as the transcendental operator par excellence. Starting from Heidegger’s ontological understanding of transcendence I show that while technical artifacts may indeed always conform to a certain horizon of understanding, they also constitute this horizon in specific ways. Following Stiegler I show that concrete technologies (technology with a small ‘t’) are not just empirical effects of an overarching movement of transcendence (Technology with a capital ‘T’) but are originally constitutive of it. In response to Romele’s critique that the social, language, images, imaginaries, symbols, etc. are also transcendentals, I argue that all these phenomena are always already conditioned by technical milieus. As for Besmer’s contention that I offer a reductive interpretation of postphenomenology’s notion of multistability, I argue that there are decisive systemic and organological limits to multistability offered by technical artefacts and that all variation in use and implementation is always constrained by inherent technical tendencies and processes of concretization. Agreeing with Besmer that the transcendental and the empirical should be understood not oppositional but compositional I argue that technology may be that which constantly ‘mediates’ between the two.

Thinking Technology Big Again. Reconsidering the Question of the Transcendental and ‘Technology with a Capital T’ in the Light of the Anthropocene

This article has two general aims. It first of all critically reconsiders the empirical turn’s dismissal of transcendentalism in the philosophy of technology, in particular through the work of Ihde and Verbeek, and defends the continuing relevance of the notion of the transcencental in thinking about technology today, illustrating this mainly through a reading of Stiegler’s understanding of the human condition as a technical condition and his view of human (noetic) evolution as proceeding from a process of technical exteriorization. The crucial issue that is missed by postphenomenology and the empirical turn is that technology itself in its empiricity occupies the (periodically changing) place of the transcendental. It thus fails to consider the transcendental operativity of technical artifacts within its own empiricist stance. Secondly, it argues for the continuing importance and usefulness of the idea of Technology with a capital T, equally discarded by the representatives of the empirical turn, in particular against the emerging backdrop of the Anthropocene as the age of decisive anthropogenic forcing of the planet and the growing dominance of what has recently been called the technosphere in Earth system science. With Stiegler I show that a proper, inherent dynamic of technology must be acknowledged historically, anthropologically, techno-evolutionarily as well as (techno)phenomenologically. I conclude by demonstrating that our time of planetary crisis summons us to redirect our attention to technology from the empirical to the transcendental, and from the micro-level to the macro-level again.

Differential dropout analysis captures biological variation in single-cell RNA sequencing data

Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological rather than technical artifacts. We propose differential dropout analysis (DDA), as an alternative to differential expression analysis (DEA), to identify the effects of biological variation in single-cell RNA sequencing data. Using 16 publicly available datasets, we show that dropout patterns are biological in nature and can assess the relative abundance of transcripts more robustly than counts.

No detectable alloreactive transcriptional responses under standard sample preparation conditions during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

Background Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures. Results Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets. Conclusions We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.