Expression and role of the universal stress protein, UspA, of Escherichia coli during growth arrest

The synthesis of the small, cytoplasmic protein UspA universal stress protein A) of Escherichia coli is induced as soon as the cell growth rate falls below the maximal growth rate supported by the medium, regardless of the condition inhibiting growth. The increase in UspA synthesis appears to be the result of Induction of the monocistronic uspA gene. Induction of this gene during a heat-shock treatment is demonstrated to be the result of transcriptional activation of Σ 70 -dependent promoter which has previously been shown to be activated also during carbon starvation-induced growth arrest. Mutant cells lacking UspA grow at rates indistinguisible from the isogenic parent at different temperatures and in the presence of different growth inhibitors but are impaired in their ability to survive prolonged periods of complete growth inhibition caused by a variety of diverse stresses, including CdCl 2 , H 2 O 2 , DNP, CCCP exposure, and osmotic shock. Moreover, the uspA mutation results in an increased sensitivity of cells to carbon-source starvation (i.e. glucose, glycerol or succinate depletion). Also, the mutation causes a marked alteration in the timing of starvation protein expression but protein expression during steady-state growth appears to be normal. The results presented have prompted us to postulate that UspA may have a general protective function related to the growth arrest state.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73757/1/j.1365-2958.1994.tb00334.x.pd

The new man and the new world the influence of Renaissance humanism on the explorers of the Italian era of discovery

In contemporary research, microsaccade detection is typically performed using the calibrated gaze-velocity signal acquired from a video-based eye tracker. To generate this signal, the pupil and corneal reflection (CR) signals are subtracted from each other and a differentiation filter is applied, both of which may prevent small microsaccades from being detected due to signal distortion and noise amplification. We propose a new algorithm where microsaccades are detected directly from uncalibrated pupil-, and CR signals. It is based on detrending followed by windowed correlation between pupil and CR signals. The proposed algorithm outperforms the most commonly used algorithm in the field (Engbert & Kliegl, 2003), in particular for small amplitude microsaccades that are difficult to see in the velocity signal even with the naked eye. We argue that it is advantageous to consider the most basic output of the eye tracker, i.e. pupil-, and CR signals, when detecting small microsaccades

The declining spadefoot toad Pelobates fuscus: calling site choice and conservation

We investigated whether local biotic and abiotic conditions could explain the occurrence of calling males of the declining spadefoot toad Pelobates fuscus in 72 ponds in southern Sweden. The ponds covered the entire distribution range of P. fuscus and were monitored during the breeding season in 2000. Calling males were found in 33 ponds. representing ca 50% of all known ponds for the species ill Sweden. They had a non-random distribution and a discriminant analysis including 19 environmental variables successfully classified 86% of the ponds as with or without calling males A stepwise discriminant analysis selected eight of these variables and classified 85% of the ponds correctly. ponds with calling males were classified mainly on characteristics of the ponds, whereas composition of the terrestrial habitat close to the ponds and traffic load within 500 in had little influence on the distribution of calling males. Ponds with P. fuscus were large, permanent and eutrophic with high concentrations of oxygen and high spring temperatures. They also had a high proportion of shoreline with steep banks. Permanent ponds with calling males typically had a low abundance of predatory fish and crayfish: only two of the ponds with P. fuscus contained predatory fish. The results of this study indicate that interactions between physical factors (e.g. pond drying) and predation determine the presence of P. fuscus. Because P. fuscus has specific habitat requirements necessary for its survival and high site fidelity, it is particularly vulnerable to local changes in the condition of its natural breeding ponds. The situation is particularly serious for this species because the majority of the ponds that are within its dispersal range do not seem to be suitable for P. fuscus because of physical constraints

Secretory leukocyte protease inhibitor in punch biopsies from human colonic mucosa.

Secretory leukocyte protease inhibitor (SLPI) is a well-known protease inhibitor. Its function is thought to be protease/protease-inhibitor balance. Free proteolytic activity, mainly pancreatic elastase, anionic trypsin and granulocytic elastase, has been demonstrated in faecal extracts from patients with ulcerative colitis. We wanted to verify that SLPI is actually secreted from normal human colonic mucosa. Also, we wanted to ascertain whether studies of SLPI secretion based on punch biopsies were dependent on biopsy area or on biopsy circumference. Normal colonic mucosa was sampled during surgery for colonic cancer. A total of 36 samples from four patients were used. Mucosa preparation was carried out using a punch biopsy technique, and samples of 3, 4 and 6 mm diameter were used. All media contained SLPI at varying concentrations. When expressed in terms of the sample area, the secretion per millimetre-squared seemed to decrease with increasing area. When calculated as secretion per circumference, secretion seemed to be constant. In conclusion, SLPI was secreted from normal human colonic mucosa. The SLPI secretion seemed dependent on the circumference of the biopsy rather than on the area of the biopsy

Role of the \u3ci\u3eEscherichia coli\u3c/i\u3e FadR Regulator in Stasis Survival and Growth Phase-Dependent Expression of the \u3ci\u3euspA, fad\u3c/i\u3e, and \u3ci\u3efab\u3c/i\u3e Genes

The increased expression of the uspA gene of Escherichia coli is an essential part of the cell’s response to growth arrest. We demonstrate that stationary-phase activation of the uspA promoter is in part dependent on growth phase-dependent inactivation or repression of the FadR regulator. Transcription of uspA is derepressed during exponential growth in fadR null mutants or by including the fatty acid oleate in the growth medium of FadR1 cells. The results of DNA footprinting analysis show that FadR binds downstream of the uspA promoter in the noncoding region. Thus, uspA is a member of the fadR regulon. All the fad-lacZ fusions examined (fadBA, fadL, and fadD) are increasingly expressed in stationary phase with kinetics similar to that of the increased expression of uspA. In contrast, b-galactosidase levels decrease during stationary phase in a fabA-lacZ lysogen, consistent with the role of FadR as an activator of fabA. The growth phase-dependent increased and decreased transcription of fad genes and fabA, respectively, is dependent on the status of the fadR gene. Cells carrying a mutation in the FadR gene (fadRS219N) that makes it nonderepressible exhibit a weak stationary-phase induction of uspA and fad genes. In addition, cells carrying fadRS219N survive long-term stasis poorly, indicating that FadR-dependent alterations in fatty acid metabolism are an integral and important part of the adaptation to stationary phase

Role of the \u3ci\u3eEscherichia coli\u3c/i\u3e FadR Regulator in Stasis Survival and Growth Phase-Dependent Expression of the \u3ci\u3euspA, fad\u3c/i\u3e, and \u3ci\u3efab\u3c/i\u3e Genes

The increased expression of the uspA gene of Escherichia coli is an essential part of the cell’s response to growth arrest. We demonstrate that stationary-phase activation of the uspA promoter is in part dependent on growth phase-dependent inactivation or repression of the FadR regulator. Transcription of uspA is derepressed during exponential growth in fadR null mutants or by including the fatty acid oleate in the growth medium of FadR1 cells. The results of DNA footprinting analysis show that FadR binds downstream of the uspA promoter in the noncoding region. Thus, uspA is a member of the fadR regulon. All the fad-lacZ fusions examined (fadBA, fadL, and fadD) are increasingly expressed in stationary phase with kinetics similar to that of the increased expression of uspA. In contrast, b-galactosidase levels decrease during stationary phase in a fabA-lacZ lysogen, consistent with the role of FadR as an activator of fabA. The growth phase-dependent increased and decreased transcription of fad genes and fabA, respectively, is dependent on the status of the fadR gene. Cells carrying a mutation in the FadR gene (fadRS219N) that makes it nonderepressible exhibit a weak stationary-phase induction of uspA and fad genes. In addition, cells carrying fadRS219N survive long-term stasis poorly, indicating that FadR-dependent alterations in fatty acid metabolism are an integral and important part of the adaptation to stationary phase

Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)

The advent of foundation models signals a new era in artificial intelligence. The Segment Anything Model (SAM) is the first foundation model for image segmentation. In this study, we evaluate SAM's ability to segment features from eye images recorded in virtual reality setups. The increasing requirement for annotated eye-image datasets presents a significant opportunity for SAM to redefine the landscape of data annotation in gaze estimation. Our investigation centers on SAM's zero-shot learning abilities and the effectiveness of prompts like bounding boxes or point clicks. Our results are consistent with studies in other domains, demonstrating that SAM's segmentation effectiveness can be on-par with specialized models depending on the feature, with prompts improving its performance, evidenced by an IoU of 93.34% for pupil segmentation in one dataset. Foundation models like SAM could revolutionize gaze estimation by enabling quick and easy image segmentation, reducing reliance on specialized models and extensive manual annotation.Comment: 14 pages, 8 figures, 1 table, submitted to ETRA 2024: ACM Symposium on Eye Tracking Research & Application

Chapter 04: Ecological resilience, climate change and the Great Barrier Reef

The vulnerability assessments in this volume frequently refer to the resilience of various ecosystem elements in the face of climate change. This chapter provides an introduction to the concept of ecological resilience, and its application as part of a management response to climate change threats. As defined in the glossary, resilience refers to the capacity of a system to absorb shocks, resist dramatic changes in condition, and maintain or recover key functions and processes, without undergoing “phase shifts” to a qualitatively different state. For example, people who are physically and mentally fit and strong will have good prospect of recovery from disease, injury or trauma: they are resilient.This is Chapter 4 of Climate change and the Great Barrier Reef: a vulnerability assessment. The entire book can be found at http://hdl.handle.net/11017/13

LEyes: A Lightweight Framework for Deep Learning-Based Eye Tracking using Synthetic Eye Images

Deep learning has bolstered gaze estimation techniques, but real-world deployment has been impeded by inadequate training datasets. This problem is exacerbated by both hardware-induced variations in eye images and inherent biological differences across the recorded participants, leading to both feature and pixel-level variance that hinders the generalizability of models trained on specific datasets. While synthetic datasets can be a solution, their creation is both time and resource-intensive. To address this problem, we present a framework called Light Eyes or "LEyes" which, unlike conventional photorealistic methods, only models key image features required for video-based eye tracking using simple light distributions. LEyes facilitates easy configuration for training neural networks across diverse gaze-estimation tasks. We demonstrate that models trained using LEyes are consistently on-par or outperform other state-of-the-art algorithms in terms of pupil and CR localization across well-known datasets. In addition, a LEyes trained model outperforms the industry standard eye tracker using significantly more cost-effective hardware. Going forward, we are confident that LEyes will revolutionize synthetic data generation for gaze estimation models, and lead to significant improvements of the next generation video-based eye trackers.Comment: 32 pages, 8 figure