A Systematic Review of the Perforated Duodenal Diverticula: Lessons Learned from the Last Decade

Background: The perforated duodenal diverticulum remains a rare clinical entity, the optimal management of which has not been well established. Historically, primary surgery has been the preferred treatment modality. This was called into question during the last decade, with the successful application of non-operative therapy in selected patients. The aim of this systematic review is to identify cases of perforated duodenal diverticula published over the past decade and to assess any subsequent evolution in treatment. Methods: A systematic review of English and non-English articles reporting on perforated duodenal diverticula using MEDLINE (2008-2020) was performed. Only cases of perforated duodenal diverticula in adults (> 18 years) that reported on diagnosis and treatment were included. Results: Some 328 studies were identified, of which 31 articles met the inclusion criteria. These studies included a total of 47 patients with perforated duodenal diverticula. This series suggests a trend towards conservative management with 34% (16/47) of patients managed non-operatively. In 31% (5/16) patients initially managed conservatively, a step-up approach to surgical intervention was required. Conclusion: Conservative treatment of perforated duodenal diverticula appears to be an acceptable and safe treatment strategy in stable patients without signs of peritonitis under careful observation. For patients who fail to respond to conservative treatment, a step-up approach to percutaneous drainage or surgery can be applied. If surgery is required, competence in techniques ranging from simple diverticulectomy to Roux-en-Y gastric diversion or even Whipple's procedure may be required depending on tissue friability and diverticular collar size. Keywords: Duodenal diverticulum; Duodenum; Management; Perforation

Pre-Emptive Endoluminal Negative Pressure Therapy at the Anastomotic Site in Minimally Invasive Transthoracic Esophagectomy (the preSPONGE Trial): Study Protocol for a Multicenter Randomized Controlled Trial

Introduction: Anastomotic leakage (AL) accounts for a significant proportion of morbidity following oesophagectomy. Endoluminal negative pressure (ENP) therapy via a specifically designed polyurethane foam (EsoSponge®, B.Braun Medical, Melsungen, Germany) has become the standard of care for AL in many specialized centres. The prophylactic (pENP) application of this technique aims to reduce postoperative morbidity and is a novel approach which has not yet been investigated in a prospective study. The aim of this study is therefore to assess the effect of pENP at the anastomotic site in high-risk patients undergoing minimally invasive transthoracic Ivor Lewis oesophagectomy. Methods and analysis: The study design is a prospective, multi-centre, two-arm, parallel-group, randomised controlled trial and will be conducted in two phases. Phase one is a randomised feasibility and safety pilot trial involving 40 consecutive patients. After definitive sample size calculation, additional patients will be included accordingly during phase two. The primary outcome of the study will be the postoperative length of hospitalization until reaching previously defined “fit for discharge criteria”. Secondary outcomes will include postoperative morbidity, mortality and postoperative AL-rates based on 90-day follow-up. A confirmatory analysis based on intention-to-treat will be performed. Ethics and dissemination: The ethics committee of the University of Zurich approved this study (2019-00562), which has been registered with ClinicalTrials.gov on 14.11.2019 (NCT04162860) and the Swiss National Clinical Trials Portal (SNCTP000003524). The results of the study will be published and presented at appropriate conferences

Variation in pre-PCR processing of FFPE samples leads to discrepancies in BRAF and EGFR mutation detection: a diagnostic RING trial.

Aims Mutation detection accuracy has been described extensively; however, it is surprising that pre-PCR processing of formalin-fixed paraffin-embedded (FFPE) samples has not been systematically assessed in clinical context. We designed a RING trial to (i) investigate pre-PCR variability, (ii) correlate pre-PCR variation with EGFR/BRAF mutation testing accuracy and (iii) investigate causes for observed variation. Methods 13 molecular pathology laboratories were recruited. 104 blinded FFPE curls including engineered FFPE curls, cell-negative FFPE curls and control FFPE tissue samples were distributed to participants for pre-PCR processing and mutation detection. Follow-up analysis was performed to assess sample purity, DNA integrity and DNA quantitation. Results Rate of mutation detection failure was 11.9%. Of these failures, 80% were attributed to pre-PCR error. Significant differences in DNA yields across all samples were seen using analysis of variance (p<0.0001), and yield variation from engineered samples was not significant (p=0.3782). Two laboratories failed DNA extraction from samples that may be attributed to operator error. DNA extraction protocols themselves were not found to contribute significant variation. 10/13 labs reported yields averaging 235.8ng (95% CI 90.7 to 380.9) from cell-negative samples, which was attributed to issues with spectrophotometry. DNA measurements using Qubit Fluorometry demonstrated a median fivefold overestimation of DNA quantity by Nanodrop Spectrophotometry. DNA integrity and PCR inhibition were factors not found to contribute significant variation. Conclusions In this study, we provide evidence demonstrating that variation in pre-PCR steps is prevalent and may detrimentally affect the patient's ability to receive critical therapy. We provide recommendations for preanalytical workflow optimisation that may reduce errors in down-stream sequencing and for next-generation sequencing library generation

Sediment Cores from White Pond, South Carolina, contain a Platinum Anomaly, Pyrogenic Carbon Peak, and Coprophilous Spore Decline at 12.8 ka

A widespread platinum (Pt) anomaly was recently documented in Greenland ice and 11 North American sedimentary sequences at the onset of the Younger Dryas (YD) event (~12,800 cal yr BP), consistent with the YD Impact Hypothesis. We report high-resolution analyses of a 1-meter section of a lake core from White Pond, South Carolina, USA. After developing a Bayesian age-depth model that brackets the late Pleistocene through early Holocene, we analyzed and quantified the following: (1) Pt and palladium (Pd) abundance, (2) geochemistry of 58 elements, (3) coprophilous spores, (4) sedimentary organic matter (OC and sedaDNA), (5) stable isotopes of C (δ13C) and N (δ15N), (6) soot, (7) aciniform carbon, (8) cryptotephra, (9) mercury (Hg), and (10) magnetic susceptibility. We identified large Pt and Pt/Pd anomalies within a 2-cm section dated to the YD onset (12,785 ± 58 cal yr BP). These anomalies precede a decline in coprophilous spores and correlate with an abrupt peak in soot and C/OC ratios, indicative of large-scale regional biomass burning. We also observed a relatively large excursion in δ15N values, indicating rapid climatic and environmental/hydrological changes at the YD onset. Our results are consistent with the YD Impact Hypothesis and impact-related environmental and ecological changes

The Future is Big Graphs! A Community View on Graph Processing Systems

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?Comment: 12 pages, 3 figures, collaboration between the large-scale systems and data management communities, work started at the Dagstuhl Seminar 19491 on Big Graph Processing Systems, to be published in the Communications of the AC

Common Gamma Chain Cytokines Promote Rapid In Vitro Expansion of Allo-Specific Human CD8+ Suppressor T Cells

Human CD8+ regulatory T cells, particularly the CD8+CD28− T suppressor cells, have emerged as an important modulator of alloimmunity. Understanding the conditions under which these cells are induced and/or expanded would greatly facilitate their application in future clinical trials. In the current study, we develop a novel strategy that combines common gamma chain (γc) cytokines IL-2, IL-7 and IL-15 and donor antigen presenting cells (APCs) to stimulate full HLA-mismatched allogeneic human CD8+ T cells which results in significant expansions of donor-specific CD8+CD28− T suppressor cells in vitro. The expanded CD8+CD28− T cells exhibit increased expressions of CTLA-4, FoxP3, and CD25, while down-regulate expressions of CD56, CD57, CD127, and perforin. Furthermore, these cells suppress proliferation of CD4+ T cells in a contact-dependent and cytokine-independent manner. Interestingly, the specificity of suppression is restricted by the donor HLA class I antigens but promiscuous to HLA class II antigens, providing a potential mechanism for linked suppression. Taken together, our results demonstrate a novel role for common γc cytokines in combination with donor APCs in the expansion of donor-specific CD8+CD28− T suppressor cells, and represent a robust strategy for in vitro generation of such cells for adoptive cellular immunotherapy in transplantation

Signatures of Environmental Genetic Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human Evolution

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes

Review of Intrinsic Motivation in Simulation-based Game Testing

This paper presents a review of intrinsic motivation in player modeling, with a focus on simulation-based game testing. Modern AI agents can learn to win many games; from a game testing perspective, a remaining research problem is how to model the aspects of human player behavior not explained by purely rational and goal-driven decision making. A major piece of this puzzle is constituted by intrinsic motivations, i.e., psychological needs that drive behavior without extrinsic reinforcement such as game score. We first review the common intrinsic motivations discussed in player psychology research and artificial intelligence, and then proceed to systematically review how the various motivations have been implemented in simulated player agents. Our work reveals that although motivations such as competence and curiosity have been studied in AI, work on utilizing them in simulation-based game testing is sparse, and other motivations such as social relatedness, immersion, and domination appear particularly underexplored

Genomic evidence of widespread admixture from polar bears into brown bears during the last ice age

Recent genomic analyses have provided substantial evidence for past periods of gene flow from polar bears (Ursus maritimus) into Alaskan brown bears (Ursus arctos), with some analyses suggesting a link between climate change and genomic introgression. However, because it has mainly been possible to sample bears from the present day, the timing, frequency, and evolutionary significance of this admixture remains unknown. Here, we analyze genomic DNA from three additional and geographically distinct brown bear populations, including two that lived temporally close to the peak of the last ice age. We find evidence of admixture in all three populations, suggesting that admixture between these species has been common in their recent evolutionary history. In addition, analyses of ten fossil bears from the now-extinct Irish population indicate that admixture peaked during the last ice age, when brown bear and polar bear ranges overlapped. Following this peak, the proportion of polar bear ancestry in Irish brown bears declined rapidly until their extinction. Our results support a model in which ice age climate change created geographically widespread conditions conducive to admixture between polar bears and brown bears, as is again occurring today. We postulate that this model will be informative for many admixing species pairs impacted by climate change. Our results highlight the power of paleogenomics to reveal patterns of evolutionary change that are otherwise masked in contemporary data