Temperature-dependent intracellular crystallization of firefly luciferase in mammalian cells is suppressed by D-luciferin and stabilizing inhibitors.

Firefly luciferase (Fluc) from Photinus pyralis is one of the most widely used reporter proteins in biomedical research. Despite its widespread use, Fluc's protein phase transition behaviors and phase separation characteristics have not received much attention. Current research uncovers Fluc's intrinsic property to phase separate in mammalian cells upon a simple cell culture temperature change. Specifically, Fluc spontaneously produced needle-shaped crystal-like inclusion bodies upon temperature shift to the hypothermic temperatures ranging from 25 °C to 31 °C. The crystal-like inclusion bodies were not associated with or surrounded by membranous organelles and were likely built from the cytosolic pool of Fluc. Furthermore, the crystal-like inclusion formation was suppressed when cells were cultured in the presence of D-luciferin and its synthetic analog, as well as the benzothiazole family of so-called stabilizing inhibitors. These two classes of compounds inhibited intracellular Fluc crystallization by different modes of action as they had contrasting effects on steady-state luciferase protein accumulation levels. This study suggests that, under substrate insufficient conditions, the excess Fluc phase separates into a crystal-like state that can modulate intracellular soluble enzyme availability and protein turnover rate.

Bioluminescence - The Vibrant Glow of Nature and its Chemical Mechanisms.

Bioluminescence, the mesmerizing natural phenomenon where living organisms produce light through chemical reactions, has long captivated scientists and laypersons alike, offering a rich tapestry of insights into biological function, ecology, evolution as well as the underlying chemistry. This comprehensive introductory review systematically explores the phenomenon of bioluminescence, addressing its historical context, geographic dispersion, and ecological significance with a focus on their chemical mechanisms. Our examination begins with terrestrial bioluminescence, discussing organisms from different habitats. We analyze thefireflies of Central Europe's meadows and the fungi in the Atlantic rainforest of Brazil. Additionally, we inspect bioluminescent species in New Zealand, specifically river-dwelling snails and mosquito larvae found in Waitomo Caves. Our exploration concludes in the Siberian Steppes, highlighting the area's luminescent insects and annelids. Transitioning to the marine realm, the second part of this review examines marine bioluminescent organisms. We explore this phenomenon in deep-sea jellyfish and their role in the ecosystem. We then move to Toyama Bay, Japan, where seasonal bioluminescence of dinoflagellates and ostracods present a unique case study. We also delve into the bacterial world, discussing how bioluminescent bacteria contribute to symbiotic relationships. For each organism, we contextualize its bioluminescence, providing details about its discovery, ecological function, and geographical distribution. A special focus lies on the examination of the underlying chemical mechanisms that enables these biological light displays. Concluding this review, we present a series of practical bioluminescence and chemiluminescence experiments, providing a resource for educational demonstrations and student research projects. Our goal with this review is to provide a summary of bioluminescence across the diverse ecological contexts, contributing to the broader understanding of this unique biological phenomenon and its chemical mechanisms serving researchers new to the field, educators and students alike.

A reproducible and affordable method of conducting luciferase assay.

Commercially available glow luciferase assay kits are widely popular and convenient to use. However, concerning high-throughput screening, commercial kits are limited by huge running costs. As an alternative to commercial luciferase assay kits, this study presents a cost-effective and efficient methodology of performing a simple and rapid laboratory flash luciferase assay. The proposed luciferase assay method has a versatile use ranging from screening lysates in a microplate reader for quantitative assay as well as screening live cells qualitatively or quantitatively under an imaging system.

Function of snail shell hairs in anti-predator defense.

The function and evolutionary background of the hairs on the shells of terrestrial gastropods is largely unknown. Many hypotheses proposed by malacologists have never been proven, and the long-held hypothesis of mechanical stability in wet environments has been rejected by recent studies. It would therefore be worthwhile to reexamine other hypotheses regarding the adaptive significance of shell hairs. We investigated the defense function of shell hairs against a specialist predator, the snail-eating firefly, in the long-haired snail Moellendorffia diminuta. The firefly larvae, which hunt snails using abdominal suckers, were unable to attach to the shell because of the shell hairs but were able to attach to the shells that had lost their hairs. About half of the hairy snails successfully defended themselves by swinging their shells and dropping firefly larvae, but most of the snails without hair failed to defend. The hairs reduce the ability of the larva to attach to the shell and increase the effectiveness of the shell-swinging defense behavior in removing the larva from the shell. As shell hairs grow longer with shell development, they may confer an advantage based on the predator's growth stage. Our findings highlight the anti-predator defense role of shell hairs in land snails, introducing a hypothesis previously overlooked in the evolutionary context of hairy snails.

Intelligent Path Planning with an Improved Sparrow Search Algorithm for Workshop UAV Inspection.

Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The sparrow search algorithm (SSA), as a novel swarm intelligence optimization algorithm, has been proven to have good optimization performance. However, the reduction in the SSA's search capability in the middle or late stage of iterations reduces population diversity, leading to shortcomings of the algorithm, including low convergence speed, low solution accuracy and an increased risk of falling into local optima. To overcome these difficulties, an improved sparrow search algorithm (namely the chaotic mapping-firefly sparrow search algorithm (CFSSA)) is proposed by integrating chaotic cube mapping initialization, firefly algorithm disturbance search and tent chaos mapping perturbation search. First, chaotic cube mapping was used to initialize the population to improve the distribution quality and diversity of the population. Then, after the sparrow search, the firefly algorithm disturbance and tent chaos mapping perturbation were employed to update the positions of all individuals in the population to enable a full search of the algorithm in the solution space. This technique can effectively avoid falling into local optima and improve the convergence speed and solution accuracy. The simulation results showed that, compared with the traditional intelligent bionic algorithms, the optimized algorithm provided a greatly improved convergence capability. The feasibility of the proposed algorithm was validated with a final simulation test. Compared with other SSA optimization algorithms, the results show that the CFSSA has the best efficiency. In an inspection path planning problem, the CFSSA has its advantages and applicability and is an applicable algorithm compared to SSA optimization algorithms.

Emerging Synthetic Bioluminescent Reactions for Non-Invasive Imaging of Freely Moving Animals.

Bioluminescence imaging (BLI) is an indispensable technique for visualizing the dynamics of diverse biological processes in mammalian animal models, including cancer, viral infections, and immune responses. However, a critical scientific challenge remains: non-invasively visualizing homeostatic and disease mechanisms in freely moving animals to understand the molecular basis of exercises, social behavior, and other phenomena. Classical BLI relies on prolonged camera exposure to accumulate the limited number of photons that traveled from deep tissues in anesthetized or constrained animals. Recent advancements in synthetic bioluminescence reactions, utilizing artificial luciferin-luciferase pairs, have considerably increased the number of detectable photons from deep tissues, facilitating high-speed BLI to capture moving objects. In this review, I provide an overview of emerging synthetic bioluminescence reactions that enable the non-invasive imaging of freely moving animals. This approach holds the potential to uncover unique physiological processes that are inaccessible with current methodologies.

Forecasting medical waste in Istanbul using a novel nonlinear grey Bernoulli model optimized by firefly algorithm.

Waste management has gained global importance, aligning with the escalating impact of the COVID-19 pandemic and the associated concerns regarding medical waste, which poses threats to public health and environmental sustainability. In Istanbul, medical waste is considered a significant concern due to the rising volume of this waste, along with challenges in collection, incineration and storage. At this juncture, precise estimation of the waste volume is crucial for resource planning and allocation. This study, thus, aims to estimate the volume of medical waste in Istanbul using the nonlinear grey Bernoulli model (NGBM(1,1)) and the firefly algorithm (FA). In other words, this study introduces a novel hybrid model, termed as FA-NGBM(1,1), for predicting waste amount in Istanbul. Within this model, prediction accuracy is enhanced through a rolling mechanism and parameter optimization. The effectiveness of this model is compared with the classical GM(1,1) model, the GM(1,1) model optimized with the FA (FA-GM(1,1)), the fractional grey model optimized with the FA (FA-FGM(1,1)) and linear regression. Numerical results indicate that the proposed FA-NGBM(1,1) hybrid model yields lower prediction error with a mean absolute percentage error value 3.47% and 2.57%, respectively, for both testing and validation data compared to other prediction algorithms. The uniqueness of this study is rooted in the process of initially optimizing the parameters for the NGBM(1,1) algorithm using the FA for medical waste estimation in Istanbul. This study also forecasts the amount of medical waste in Istanbul for the next 3 years, indicating a dramatic increase. This suggests that new policies should be promptly considered by decision-makers and practitioners.

Collective synchrony of mating signals modulated by ecological cues and social signals in bioluminescent sea fireflies.

Individuals often employ simple rules that can emergently synchronize behaviour. Some collective behaviours are intuitively beneficial, but others like mate signalling in leks occur across taxa despite theoretical individual costs. Whether disparate instances of synchronous signalling are similarly organized is unknown, largely due to challenges observing many individuals simultaneously. Recording field collectives and ex situ playback experiments, we describe principles of synchronous bioluminescent signals produced by marine ostracods (Crustacea; Luxorina) that seem behaviorally convergent with terrestrial fireflies, and with whom they last shared a common ancestor over 500 Mya. Like synchronous fireflies, groups of signalling males use visual cues (intensity and duration of light) to decide when to signal. Individual ostracods also modulate their signal based on the distance to nearest neighbours. During peak darkness, luminescent 'waves' of synchronous displays emerge and ripple across the sea floor approximately every 60 s, but such periodicity decays within and between nights after the full moon. Our data reveal these bioluminescent aggregations are sensitive to both ecological and social light sources. Because the function of collective signals is difficult to dissect, evolutionary convergence, like in the synchronous visual displays of diverse arthropods, provides natural replicates to understand the generalities that produce emergent group behaviour.

Dramatic dietary shift maintains sequestered toxins in chemically defended snakes.

Unlike other snakes, most species of Rhabdophis possess glands in their dorsal skin, sometimes limited to the neck, known as nucho-dorsal and nuchal glands, respectively. Those glands contain powerful cardiotonic steroids known as bufadienolides, which can be deployed as a defense against predators. Bufadienolides otherwise occur only in toads (Bufonidae) and some fireflies (Lampyrinae), which are known or believed to synthesize the toxins. The ancestral diet of Rhabdophis consists of anuran amphibians, and we have shown previously that the bufadienolide toxins of frog-eating species are sequestered from toads consumed as prey. However, one derived clade, the Rhabdophis nuchalis Group, has shifted its primary diet from frogs to earthworms. Here we confirm that the worm-eating snakes possess bufadienolides in their nucho-dorsal glands, although the worms themselves lack such toxins. In addition, we show that the bufadienolides of R. nuchalis Group species are obtained primarily from fireflies. Although few snakes feed on insects, we document through feeding experiments, chemosensory preference tests, and gut contents that lampyrine firefly larvae are regularly consumed by these snakes. Furthermore, members of the R. nuchalis Group contain compounds that resemble the distinctive bufadienolides of fireflies, but not those of toads, in stereochemistry, glycosylation, acetylation, and molecular weight. Thus, the evolutionary shift in primary prey among members of the R. nuchalis Group has been accompanied by a dramatic shift in the source of the species' sequestered defensive toxins.

Exploring the Applications of Indocyanine Green in Robot-Assisted Urological Surgery: A Comprehensive Review of Fluorescence-Guided Techniques.

This comprehensive review aims to explore the applications of indocyanine green (ICG) in robot-assisted urological surgery through a detailed examination of fluorescence-guided techniques. An extensive literature search was conducted in PubMed/MEDLINE, EMBASE and Scopus, using keywords such as "indocyanine green," "ICG", "NIRF", "Near Infrared Fluorescence", "robot-assisted", and "urology". Additional suitable articles were collected by manually cross-referencing the bibliography of previously selected papers. The integration of the Firefly® technology in the Da Vinci® robotic system has opened new avenues for the advancement and exploration of different urological procedures. ICG is a fluorophore widely used in near-infrared fluorescence-guided techniques. The synergistic combination of intraoperative support, safety profiles and widespread availability comprises an additional asset that empowers ICG-guided robotic surgery. This overview of the current state of the art illustrates the potential advantages and broad applications of combining ICG-fluorescence guidance with robotic-assisted urological surgery.

An Intelligent System to Enhance the Performance of Brain Tumor Diagnosis from MR Images.

In the human body, cancer is caused by aberrant cell proliferation. Brain tumors are created when cells in the human brain proliferate out of control. Brain tumors consist of two types: benign and malignant. The aberrant parts of benign tumors, which contain dormant tumor cells, can be cured with the appropriate medication. On the other hand, malignant tumors are tumors that contain abnormal cells and an unorganized area of these abnormal cells that cannot be treated with medication. Therefore, surgery is required to remove these brain tumors. Brain cancers are manually identified and diagnosed by a skilled radiologist using traditional procedures. It's a lengthy and error-prone procedure. As a result, it is unsuitable for emerging countries with large populations. So computer-assisted automatic identification and diagnosis of brain tumors are recommended. This work proposes and implements a CAD system for the diagnosis of brain cancers using magnetic resonance imaging (MRI). Preprocessing, segmentation, feature extraction, and classification are the stages of automatic brain MRI processing that necessitate software based on a sophisticated algorithm. Image normalization with contourlet transform (INCT) is used in the preprocessing step to remove undesirable or noisy data. The performance metrics such as PSNR, MSE, and RMSE are computed. Then, the modified hierarchical k-means with firefly clustering (MHKFC) technique is used in the segmentation step to precisely recover the afflicted (tumor) area from the preprocessed image. The enhanced monarch butterfly optimization (EMBO) is used to select and then extract the most important gray-level co-occurrence matrix feature from the segmented image. The classification task was finally completed using the adaptive neuro-fuzzy inference system (ANFIS). The overall classification accuracy is 95.4% ( BRATS 2015), 96.6% ( BRATS 2021), and 93.7% (clinical data) is obtained.

Sentinel lymph node mapping in endometrial cancer - robotic vs. laparoscopic detection system.

OBJECTIVE: Comparison of systems to detect sentinel lymph node in endometrial carcinoma using indocyanine green. Robotic Firefly Da Vinci fluorescence imaging system (Intuitive Surgical Inc., Sunnyvale, CA, USA) vs. laparoscopic Novadaq Pinpoint near-infrared imaging system (Novadaq, Ontario, Canada). MATERIAL AND METHOD: Fifteen patients with stage I endometrial cancer underwent sentinel lymph node biopsy after intracervical application of indocyanine green. For all of them, the detection was performed sequentially using both evaluated devices. The detection rate, identification match and extent of imaging of the lymphatic system were evaluated. RESULTS: The detection rate of both systems verified on a set of patients was identical, the detected sentinel nodes were identical, and the lymphatic system was shown to the same extent. The quality of the display and overall user-friendliness is different due to the applied technologies. CONCLUSION: Both systems used in minimally invasive surgery provide excelent perioperative imaging of the lymphatic system.

Fuzzy C-Means Clustering: A Review of Applications in Breast Cancer Detection.

This paper reviews the potential use of fuzzy c-means clustering (FCM) and explores modifications to the distance function and centroid initialization methods to enhance image segmentation. The application of interest in the paper is the segmentation of breast tumours in mammograms. Breast cancer is the second leading cause of cancer deaths in Canadian women. Early detection reduces treatment costs and offers a favourable prognosis for patients. Classical methods, like mammograms, rely on radiologists to detect cancerous tumours, which introduces the potential for human error in cancer detection. Classical methods are labour-intensive, and, hence, expensive in terms of healthcare resources. Recent research supplements classical methods with automated mammogram analysis. The basic FCM method relies upon the Euclidean distance, which is not optimal for measuring non-spherical structures. To address these limitations, we review the implementation of a Mahalanobis-distance-based FCM (FCM-M). The three objectives of the paper are: (1) review FCM, FCM-M, and three centroid initialization algorithms in the literature, (2) illustrate the effectiveness of these algorithms in image segmentation, and (3) develop a Python package with the optimized algorithms to upload onto GitHub. Image analysis of the algorithms shows that using one of the three centroid initialization algorithms enhances the performance of FCM. FCM-M produced higher clustering accuracy and outlined the tumour structure better than basic FCM.

A novel firefly algorithm approach for efficient feature selection with COVID-19 dataset.

Feature selection is one of the most important challenges in machine learning and data science. This process is usually performed in the data preprocessing phase, where the data is transformed to a proper format for further operations by machine learning algorithm. Many real-world datasets are highly dimensional with many irrelevant, even redundant features. These kinds of features do not improve classification accuracy and can even shrink down performance of a classifier. The goal of feature selection is to find optimal (or sub-optimal) subset of features that contain relevant information about the dataset from which machine learning algorithms can derive useful conclusions. In this manuscript, a novel version of firefly algorithm (FA) is proposed and adapted for feature selection challenge. Proposed method significantly improves performance of the basic FA, and also outperforms other state-of-the-art metaheuristics for both, benchmark bound-constrained and practical feature selection tasks. Method was first validated on standard unconstrained benchmarks and later it was applied for feature selection by using 21 standard University of California, Irvine (UCL) datasets. Moreover, presented approach was also tested for relatively novel COVID-19 dataset for predicting patients health, and one microcontroller microarray dataset. Results obtained in all practical simulations attest robustness and efficiency of proposed algorithm in terms of convergence, solutions' quality and classification accuracy. More precisely, the proposed approach obtained the best classification accuracy on 13 out of 21 total datasets, significantly outperforming other competitor methods.

Rhythmic adenosine triphosphate release from the cyanobacterial circadian clock protein KaiC revealed by real-time monitoring of bioluminescence using firefly luciferase.

The cyanobacterial circadian clock is composed of three clock proteins, KaiA, KaiB and KaiC. This KaiABC clock system can be reconstituted in vitro in the presence of adenosine triphosphate (ATP) and Mg2+ , and shows circadian rhythms in the phosphorylation level and ATPase activity of KaiC. Previously, we found that ATP regulates a complex formation between KaiB and KaiC, and KaiC releases ATP from KaiC itself (PLoS One, 8, 2013, e80200). In this study, we examined whether the ATP release from KaiC shows any rhythms in vitro. We monitored the release of ATP from wild-type and ATPase motif mutants of KaiC as a bioluminescence in real time using a firefly luciferase assay in vitro and obtained the following results: (a) ATP release from KaiC oscillated even without KaiA and KaiB although period of the oscillation was not 24 hr; (b) ATP was mainly released from the N-terminal domain of KaiC; and (c) the ATP release was enhanced and suppressed by KaiB and KaiA, respectively. These results suggest that KaiC can generate basal oscillation as a core clock without KaiA and KaiB, whereas these two proteins contribute to adjusting and stabilizing the oscillation.

Cloning and molecular properties of a novel luciferase from the Brazilian Bicellonycha lividipennis (Lampyridae: Photurinae) firefly: comparison with other firefly luciferases.

Several firefly luciferases eliciting light emission in the yellow-green range of the spectrum and with distinct kinetic properties have been already cloned, sequenced, and characterized. Some of them are currently being applied as analytical reagents and reporter genes for bioimaging and biosensors, and more recently as potential color tuning indicators of intracellular pH and toxic metals. They were cloned from the subfamilies Lampyrinae (Photinini: Photinus pyralis, Macrolampis sp2; Cratomorphini: Cratomorphus distinctus), Photurinae (Photuris pennsylvanica), Luciolinae (Luciola cruciata, L. lateralis, L. mingrelica, L. italica, Hotaria parvula), and Amydetinae (Amydetes vivianii) occurring in different parts of the world. The largest number has been cloned from fireflies occurring in Brazilian biomes. Taking advantage of the large biodiversity of fireflies occurring in the Brazilian Atlantic rainforest, here we report the cloning and characterization of a novel luciferase cDNA from the Photurinae subfamily, Bicellonycha lividipennis, which is a very common firefly in marshlands in Brazil. As expected, multialignements and phylogenetic analysis show that this luciferase clusters with Photuris pennsylvanica adult isozyme, and with other adult lantern firefly luciferases, in reasonable agreement with traditional phylogenetic analysis. The luciferase elicits light emission in the yellow-green region, has kinetics properties similar to other adult lantern firefly luciferases, including pH- and metal sensitivities, but displays a lower sensitivity to nickel, which is suggested to be caused by the natural substitution of H310Y.

Variance in translational fidelity of different bacterial species is affected by pseudouridines in the tRNA anticodon stem-loop.

Delicate variances in the translational machinery affect how efficiently different organisms approach protein synthesis. Determining the scale of this effect, however, requires knowledge on the differences of mistranslation levels. Here, we used a dual-luciferase reporter assay cloned into a broad host range plasmid to reveal the translational fidelity profiles of Pseudomonas putida, Pseudomonas aeruginosa and Escherichia coli. We observed that these profiles are surprisingly different, whereas species more prone to translational frameshifting are not necessarily more prone to stop codon readthrough. As tRNA modifications are among the factors that have been implicated to affect translation accuracy, we also show that translational fidelity is context-specifically influenced by pseudouridines in the anticodon stem-loop of tRNA, but the effect is not uniform between species.

Recent applications of CBT-Cys click reaction in biological systems.

Click chemistry is a hot topic in many research fields. A biocompatible reaction from fireflies has attracted increasing attention since 2009. Herein, we focus on the firefly-sourced click reaction between cysteine (Cys) and 2-cyanobenzothiazole (2-CBT). This reaction has many excellent properties, such as rapidity, simplicity and high selectivity, which make it successfully applied in protein labeling, molecular imaging, drug discovery and other fields. Meanwhile, its unique ability to form nanoparticles expands its applications in biological systems. We review its principle, development, and latest applications in the past 5 years and hope this review provides more profound and comprehensive insights to its further application.

How to avoid misinterpretation of dual reporter gene assay data affected by cell damage.

The activity of nuclear receptors (e.g., pregnane x receptor, PXR) can be assessed by luminescence-based dual reporter gene assays. Under most conditions, receptor-activated firefly luminescence is normalized to Renilla luminescence, which is triggered by a constitutively active promoter. Simultaneous damage to the cells can however disrupt these signals and thus impair the interpretation of the data. Consequently, this study addressed three important aspects: First, idealized models were described, each highlighting crucial characteristics and important pitfalls of dual PXR reporter gene assays used to evaluate PXR activation or inhibition. Second, these models were supported by experimental data obtained with a strong PXR activator (rifampicin) with low cytotoxicity, a PXR activator with high cytotoxicity (dovitinib), a proposed PXR inhibitor that reportedly has no toxic effects (triptolide), and a cytotoxic control (oxaliplatin). Data were evaluated for relative PXR activity data, individual firefly or Renilla luminescence, and anti-proliferative effects of the compounds (assessed by crystal violet staining). Finally, a step-by-step guide is proposed to avoid misleading set-up of the assay or misinterpretation of the data obtained. Key considerations here include (1) omission of drug concentrations beyond 10-20% proliferation inhibition; (2) observation of Renilla luminescence, because this tends to indicate 'false PXR activation' when it inexplicably decreases; (3) parallel decrease of relative PXR activity and proliferation below baseline levels in conjunction with a sharp decrease in Renilla luminescence indicates 'false PXR antagonism'; (4) non-sigmoidal relationships suggest the absence of concentration dependency.

Impact of the indocyanine green fluorescence method for anastomotic blood flow in robotic distal gastrectomy.

PURPOSE: To evaluate the blood flow at the site of delta-shaped anastomosis during robotic distal gastrectomy and determine surgical outcomes and risk factors for ischemia at the anastomotic site from the perspective of clinical characteristics, surgical outcomes and perigastric vascular anatomy. METHODS: We included 55 patients who underwent robotic distal gastrectomy with a blood flow evaluation in the duodenal walls using intravenous indocyanine green injection with the da Vinci Xi-equipped Firefly system. Additional resection was performed in patients with a poor blood flow. Clinical characteristics, surgical outcomes and perigastric vascular anatomy were compared between the 45 patients with sufficient blood flow (group S) and the 10 patients with insufficient blood flow (group I). Vascular anatomy was assessed by preoperative contrast-enhanced computed tomography according to Hiatt's classification. RESULTS: The patient characteristics and surgical outcomes were not significantly different. No patient developed anastomotic complications requiring intervention; more patients in group I had aberrant branching of the left hepatic artery than those in group S (p = 0.047). CONCLUSIONS: An indocyanine green-based blood flow evaluation might be an effective method of preventing anastomotic complications of delta-shaped anastomosis. Anatomical branching variations of the left hepatic artery might be a risk factor for impaired vascular perfusion of the anastomotic site.