Comment on "Effect of biofilm formation by clinical isolates of Helicobacter pylori on the efflux-mediated resistance to commonly used antibiotics".

Attaran et al[1] have recently shown that decreased susceptibility of established Helicobacter pylori (H. pylori) biofilms to specific antibiotics, was associated with the overtly enhanced transcription of two efflux pump genes, hp1165 and hefA, involved in specific resistance to tetracycline and multiple antibiotics, respectively. Apart from antibiotic exposure, secretion of multiple antimicrobial peptides, such as human ?-defensins (h?Ds), by the gastric epithelium upon Hp challenge, may act as early triggering events that positively impact biofilm formation and thus, antibiotic resistance. In this regard, we undertook genomic transcriptional studies using Hp 26695 strain following exposure to sublethal, similar to those present in the gastric niche, concentrations of h?Ds in an attempt to provide preliminary data regarding possible mechanisms of immune evasion and selective sensitivity of Hp. Our preliminary results indicate that h?D exposure ignites a rapid response that is largely due to the activation of several, possibly interconnected transcriptional regulatory networks - origons - that ultimately coordinate cellular processes needed to maintain homeostasis and successful adaptation of the bacterium in the gastric environment. In addition, we have shown that both antibiotic and h?D resistance are mediated by dedicated periplasmic transporters, including the aforementioned efflux pump genes hp1165 and hefA, involved in active export of antibiotics from the cell membrane and/or, as recently suggested, substrate sensing and signalling. Furthermore, it appears that sublethal doses of h?Ds may enhance biofilm formation by the sustained expression of, mainly, quorum sensing-related genes. In conclusion, we provide additional data regarding the role of specific innate immune molecules in antibiotic cross-resistance mechanisms that may deepen our understanding in the context of the development of novel eradication regimens

Scaling Egocentric Vision: The EPIC-KITCHENS Dataset

First-person vision is gaining interest as it offers a unique viewpoint on people's interaction with objects, their attention, and even intention. However, progress in this challenging domain has been relatively slow due to the lack of sufficiently large datasets. In this paper, we introduce EPIC-KITCHENS, a large-scale egocentric video benchmark recorded by 32 participants in their native kitchen environments. Our videos depict nonscripted daily activities: we simply asked each participant to start recording every time they entered their kitchen. Recording took place in 4 cities (in North America and Europe) by participants belonging to 10 different nationalities, resulting in highly diverse cooking styles. Our dataset features 55 hours of video consisting of 11.5M frames, which we densely labeled for a total of 39.6K action segments and 454.3K object bounding boxes. Our annotation is unique in that we had the participants narrate their own videos (after recording), thus reflecting true intention, and we crowd-sourced ground-truths based on these. We describe our object, action and anticipation challenges, and evaluate several baselines over two test splits, seen and unseen kitchens. Dataset and Project page: http://epic-kitchens.github.ioComment: European Conference on Computer Vision (ECCV) 2018 Dataset and Project page: http://epic-kitchens.github.i

Graph Guided Question Answer Generation for Procedural Question-Answering

In this paper, we focus on task-specific question answering (QA). To this end, we introduce a method for generating exhaustive and high-quality training data, which allows us to train compact (e.g., run on a mobile device), task-specific QA models that are competitive against GPT variants. The key technological enabler is a novel mechanism for automatic question-answer generation from procedural text which can ingest large amounts of textual instructions and produce exhaustive in-domain QA training data. While current QA data generation methods can produce well-formed and varied data, their non-exhaustive nature is sub-optimal for training a QA model. In contrast, we leverage the highly structured aspect of procedural text and represent each step and the overall flow of the procedure as graphs. We then condition on graph nodes to automatically generate QA pairs in an exhaustive and controllable manner. Comprehensive evaluations of our method show that: 1) small models trained with our data achieve excellent performance on the target QA task, even exceeding that of GPT3 and ChatGPT despite being several orders of magnitude smaller. 2) semantic coverage is the key indicator for downstream QA performance. Crucially, while large language models excel at syntactic diversity, this does not necessarily result in improvements on the end QA model. In contrast, the higher semantic coverage provided by our method is critical for QA performance.Comment: Accepted to EACL 2024 as long paper. 25 pages including appendi

Association between Helicobacter pylori Infection and Nasal Polyps: A Systematic Review and Meta-Analysis.

BACKGROUND Helicobacter pylori (H. pylori) has definite or possible associations with multiple local and distant manifestations. H. pylori has been isolated from multiple sites throughout the body, including the nose. Clinical non-randomized studies with H. pylori report discrepant data regarding the association between H. pylori infection and nasal polyps. The aim of this first systematic review and meta-analysis was the assessment of the strength of the association between H. pylori infection and incidence of nasal polyps. METHODS We performed an electronic search in the three major medical databases, namely PubMed, EMBASE and Cochrane, to extract and analyze data as per PRISMA guidelines. RESULTS Out of 57 articles, 12 studies were graded as good quality for analysis. Male-to-female ratio was 2:1, and age ranged between 17-78 years. The cumulative pooled rate of H. pylori infection in the nasal polyp group was 32.3% (controls 17.8%). The comparison between the two groups revealed a more significant incidence of H. pylori infection among the nasal polyp group (OR 4.12), though with high heterogeneity I$^{2}$ = 66%. Subgroup analysis demonstrated that in European studies, the prevalence of H. pylori infection among the nasal polyp group was significantly higher than in controls, yielding null heterogeneity. Subgroup analysis based on immunohistochemistry resulted in null heterogeneity with preserving a statistically significant difference in H. pylori infection prevalence between the groups. CONCLUSION The present study revealed a positive association between H. pylori infection and nasal polyps