Graph Analysis Research Articles

GraphCompass: spatial metrics for differential analyses of cell organization across conditions.

Spatial omics technologies are increasingly leveraged to characterize how disease disrupts tissue organization and cellular niches. While multiple methods to analyze spatial variation within a sample have been published, statistical and computational approaches to compare cell spatial organization across samples or conditions are mostly lacking. We present GraphCompass, a comprehensive set of omics-adapted graph analysis methods to quantitatively evaluate and compare the spatial arrangement of cells in samples representing diverse biological conditions. GraphCompass builds upon the Squidpy spatial omics toolbox and encompasses various statistical approaches to perform cross-condition analyses at the level of individual cell types, niches, and samples. Additionally, GraphCompass provides custom visualization functions that enable effective communication of results. We demonstrate how GraphCompass can be used to address key biological questions, such as how cellular organization and tissue architecture differ across various disease states and which spatial patterns correlate with a given pathological condition. GraphCompass can be applied to various popular omics techniques, including, but not limited to, spatial proteomics (e.g. MIBI-TOF), spot-based transcriptomics (e.g. 10× Genomics Visium), and single-cell resolved transcriptomics (e.g. Stereo-seq). In this work, we showcase the capabilities of GraphCompass through its application to three different studies that may also serve as benchmark datasets for further method development. With its easy-to-use implementation, extensive documentation, and comprehensive tutorials, GraphCompass is accessible to biologists with varying levels of computational expertise. By facilitating comparative analyses of cell spatial organization, GraphCompass promises to be a valuable asset in advancing our understanding of tissue function in health and disease.

Metric invariance in exploratory graph analysis via permutation testing

Metric invariance in exploratory graph analysis via permutation testing

Presurgical structural imaging and clinical outcome in combined bed nucleus of the stria terminalis–nucleus accumbens deep brain stimulation for treatment-resistant depression

BackgroundStructural imaging holds great potential for precise targeting and stimulation for deep brain stimulation (DBS). The anatomical information it provides may serve as potential biomarkers for predicting the efficacy of...

Membrane lateral organization from potential energy disconnectivity graph

Understanding the thermodynamic and kinetic properties of biomolecules requires elucidation of their complex energy landscape. A disconnectivity graph analysis of the energy landscape provides a framework for mapping the multi-dimensional landscape onto a two-dimensional representation while preserving the key features of the energy landscape. Several studies show that the structure or shape of the disconnectity graph is directly associated with the function of protein and nucleic acid molecules. In this review, we discuss how disconnectivity analysis of the potential energy surface can be extended to lipid molecules to glean important information about membrane organization. The shape of the disconnectivity graphs can be used to predict the lateral organization of multi-component lipid bilayer. We hope that this review encourages the use of disconnectivity graphs routinely by membrane biophysicists to predict the lateral organization of lipids.

Graph analysis uncovers an opposing impact of methylphenidate on connectivity patterns within default mode network sub-divisions

BackgroundThe Default Mode Network (DMN) is a central neural network, with recent evidence indicating that it is composed of functionally distinct sub-networks. Methylphenidate (MPH) administration has been shown before to modulate impulsive behavior, though it is not yet clear whether these effects relate to MPH-induced changes in DMN connectivity. To address this gap, we assessed the impact of MPH administration on functional connectivity patterns within and between distinct DMN sub-networks and tested putative relations to variability in sub-scales of impulsivity.MethodsFifty-five right-handed healthy adults underwent two resting-state functional MRI (rs-fMRI) scans, following acute administration of either MPH (20 mg) or placebo, via a randomized double-blind placebo-controlled design. Graph modularity analysis was implemented to fractionate the DMN into distinct sub-networks based on the impact of MPH (vs. placebo) on DMN connectivity patterns with other neural networks.ResultsMPH administration led to an overall decreased DMN connectivity, particularly with the auditory, cinguloopercular, and somatomotor networks, and increased connectivity with the parietomedial network. Graph analysis revealed that the DMN could be fractionated into two distinct sub-networks, with one exhibiting MPH-induced increased connectivity and the other decreased connectivity. Decreased connectivity of the DMN sub-network with the cinguloopercular network following MPH administration was associated with elevated impulsivity and non-planning impulsiveness.ConclusionCurrent findings highlight the intricate effects of MPH administration on DMN rs-fMRI connectivity, uncovering its opposing impact on distinct DMN sub-divisions. MPH-induced dynamics in DMN connectivity patterns with other neural networks may account for some of the effects of MPH administration on impulsive behavior.

Social network analysis of foreign research in the field of automation of cargo container transportation

The relevance of the topic is caused by the following. Improving automation and digitalization of technological processes of transshipment complexes is one of the priorities for development of maritime and river transport in the Russian Federation in the coming years. The importance of scientific research aimed at finding solutions to this problem, undoubtedly, increases already accumulated knowledge and the rate of emergence of new ones in this area. As a result, there is a need to update and systematize newly obtained theoretical and practical developments in review studies, which undoubtedly form the foundation of all academic research activities, as they are aimed at identifying current problems and links of future scientific developments with existing ones. The work analyzes the scientific area research in the field of automation of technological processes of container terminals regarding the dominant thematic areas of foreign scientific schools over the past ten years. The source of information flow for the analysis was secondary open scientific data posted in the GoogleScholar system. The objectives of the study included searching for publications corresponding to the stated topic, clustering the authors of these articles based on the principle of co-authorship, identifying scientists who contributed most to the new scientific developments, determining the scientific interests of researchers by analyzing the texts of their scientific works. The method of edge clustering, as well as structural and positional analyses were used to solve the tasks. As a result, a network graph was generated for the authorship of scientific works, a cross-citation graph of scientific publications, as well as a graph for comparing the research results of scientists with one of the thematic directions of the subject area of research. Graph construction and analysis were performed using Gephi software.

Education for Student with Cerebral palsy on Reducing Drooling through Oral Motor Exercise

This study aims to reduce drooling through oral motor exercises for cerebral palsy students in Special School in Padang, Indonesia. This study used quantitative research methods with a Single Subject Research (SSR) approach with A-B-A design from February to September 2021. The research data was collected by observing one child with cerebral palsy, recording events, and assessing oral motor exercise. All data was analyzed descriptively using visual graph analysis tools. Overall, the results showed that oral motor exercise effectively reduced drooling in cerebral palsy students. This was evidenced by the mean level obtained in the baseline-1 (A1) condition, which was 14.66; in the intervention condition (B), it decreased to 8.15; and in the baseline-2 (A2) condition, it decreased again to 3. Then, the results of data analysis in the conditions and between conditions also showed a tendency toward stability, an estimated directional tendency, and data trace and level changes that decreased positively. The percentage of overlap in the baseline-1 (A1) condition is 0%, while the percentage of overlap in the baseline-2 (A2) condition is 15% so the hypothesis can be accepted. These findings imply that the selection of oral motor exercises effectively reduces drooling in students with cerebral palsy

Beyond sound irritation: cross-cultural evidence on the robustness of the five aspects of misophonic experience measured by the S-Five in a Polish sample.

Misophonia is commonly associated with negative emotional or physiological responses to specific sounds. However, the consensus definition emphasizes that misophonia entails much more than that. Even in cases of subclinical misophonia, where individuals do not meet the disorder criteria, the experience can still be burdensome, despite not currently causing significant distress or impairment. The S-Five is a psychometric tool for comprehensive assessment of five aspects of misophonic experience: internalizing, externalizing, impact, threat, and outburst, and includes S-Five-T section to evaluate feelings evoked by triggering sounds and their intensity. We examined whether the five-factor structure developed in the UK could be replicated in a Polish sample, including individuals with and without self-identified misophonia. The Polish version of the S-Five was translated and tested on 288 Polish-speaking individuals. Comprehensive psychometric evaluation, including factor structure, measurement invariance, test-retest reliability, internal consistency, and concurrent validity evaluations, was conducted on the translated scale. Exploratory factor analysis suggested similar structure to the original English study, while bootstrap exploratory graph analysis showed the factor structure to be reproducible in other samples. The scale was found to be bias free with respect to gender, internally consistent and stable in time, and evidence of validity was provided using MisoQuest and Misophonia Questionnaire. These results offer support for the cross-cultural stability of the five factors and provide preliminary evidence for the suitability of the Polish version for clinical and research purposes. The study also investigated five facets of misophonia, triggering sounds, emotional responses, and their associations with symptoms of psychopathology across various cultures. It underscores the central role of anger, distress, and panic, while also highlighting the mixed role of irritation and disgust in misophonia across different cultural contexts. Mouth sounds evoked the most pronounced reactions compared to other repetitive sounds, although there were discernible cultural differences in the nature and intensity of reactions to various trigger sounds. These findings hold significant implications for future research and underscore the importance of considering cultural nuances in both research and the clinical management of misophonia.

Insights into wheat science: A bibliometric review using unsupervised machine learning techniques

Wheat (Triticum spp.) has been one of the most important cereal crops, serving as a source of protein and energy in the human diet. It remains a vital component of global food security, with extensive scientific literature dedicated to its study, although the large volume of literature often hinders global analysis. In this study, different unsupervised machine learning techniques, such as K-Nearest Neighbors (KNN) and Uniform Manifold Approximation and Projection (UMAP), text mining analyses, including word embeddings and statistical word analysis, and graph analysis methodologies, were applied to gain a deeper understanding of the wheat literature. The proposed bibliometric analysis was conducted and integrated with the Journal Citation Reports (JCR) to identify major wheat research trends in the PubMed literature. This analysis examined the evolution of these trends over time, evaluated the geographical distribution, impact, and research domains, and assessed author collaboration networks and the evolving relevance of different countries. Research on disease resistance, genetic modification, and dietary impact demonstrates a consistent increase in output, while interest in topics related to overcoming salt stress and enhancing animal feed appears to be diminishing. Interestingly, research on wheat germ agglutinin saw a surge in interest during the late 2000s, stabilizing thereafter. These trends underscore the dynamic nature of wheat research, driven by evolving priorities and technological advancements, particularly in genetics and omics tools. Moreover, the increasing significance of China in wheat research, including its size, impact, and networking, alongside longstanding leaders such as the United States, signals a shifting landscape in global wheat research.

Graph analysis using a GPU-based parallel algorithm: quantum clustering

Graph analysis using a GPU-based parallel algorithm: quantum clustering

The mediating role of psychological well-being in the relationship between the light triad of personality and sense of concordance with treatment adherence in patients with type 2 diabetes: A network analysis and structural equation modeling study

BackgroundThis study aimed to investigate the intricate relationship among treatment adherence, the light triad of personality, self-coherence, and psychological well-being in individuals diagnosed with Type 2 Diabetes Mellitus (T2DM). Structural equation modeling (SEM) was employed to elucidate the direct and mediated pathways linking these variables, while network analysis sought to identify and characterize the underlying factors of the light triad of personality within the context of T2DM management. MethodA path analysis-network analysis study using convenience sampling was conducted, recruiting 412 T2DM patients from ten private practices and general hospitals in Gilan province, Iran. Data collection utilized Antonovsky's Self of Coherence scale (SOC), The Light Triad Rating Scale, and The Reef's Psychological Well-being Questionnaire. Structural equation modeling assessed model fitness and determined direct and indirect links between variables. Analysis was conducted using R-Studio software (Version 4.2.1), SPSS (V.26), and AMOS software (V.24). ResultsConfirmatory factor analysis and network analysis confirmed the three-factor structure of the Light Triad of Personality scale. Direct impacts of Light Triad of Personality (β = 0.34, p < .001) and self-coherence (β = 0.32, p < .001) on treatment adherence were observed. Psychological well-being played an indirect role in this relationship, with significant effects from Light Triad of Personality (β = 0.25, p < .001) and self-coherence (β = 0.08, p < .001) on treatment adherence. Bootstrapped exploratory graph analysis revealed an average of 3 dimensions within the network, indicating community structures. ConclusionSEM analysis demonstrated good model fit, suggesting the importance of designing interventional programs incorporating self-coherence and psychological well-being frameworks to enhance treatment adherence in T2DM patients.

Factor Structure and Reliability of the Persian Version of Body Esteem Scale Among Iranian Adults: Exploratory Graph Analysis Approach.

Background and Purpose: The present study aimed to examine the psychometric properties of the Persian version of the Mendelson and White Body Esteem Scale in Iranian adults. Methods: This cross-sectional study design was used and carried out in 2023. Following the inclusion criteria, 500 adults were gathered from Tehran (Tehran, Iran) with an accessible sampling method. After translation of Body Esteem Scale to Persian language, construct validity (with factor analysis and exploratory graph analysis) and reliability were assessed. Results: The mean age of the participants was 30.66 (standard deviation = 7.40) years. The results of Maximum Likelihood Exploratory Factor Analysis (MLEFA) with Promax with Kaiser normalization rotation extracted three factors accounting for 43.4% of the variance comprising 21 items. Also, after necessary modifications during confirmatory factor analysis, the final model was approved. As for construct reliability, the Cronbach's alpha, Composite Reliability, and Maximal Reliability for all constructs were greater than 0.7, demonstrating good internal consistency and construct reliability. Conclusions: According to results, the Persian version of Body Esteem Scale has a valid structure and acceptable reliability. This scale can be used by health professionals in many ways.

Evaluating the Structure of the Aesthetic Responsiveness Assessment (AReA) with Bootstrap Exploratory Graph Analysis

The Aesthetic Responsiveness Assessment (AReA) is a self-report scale for measuring individual differences in the strength of responses to art objects and events. Its 14 items sort into three subscales: aesthetic appreciation (AA), intense aesthetic experience (IAE), and creative behaviour. The present research evaluated the dimensionality of the AReA using tools from network psychometrics, particularly bootstrap exploratory graph analysis. Using a sample of English-speaking adults ( n = 1071), the network analyses closely replicated the number and item composition of the AReA subscales, but one of the items—a cross-loaded item proposed to be in both the AA and IAE subscales—was not replicated. Using the bootstrap sampling distributions, we suggest item assignments that avoid awkward dual-loadings and provide a simpler dimensional structure. Taken together, the results reveal clear strengths of the AReA and illustrate how emerging network tools can illuminate and guide psychometric decisions.

Removal of Multi-heavy Metals from Simulated Wastewater using Hybrid Modified Carbonized Palm Shell and Rice Husk Adsorbents

It necessary to remove heavy metals from wastewater in order to comply with environmental regulations and for sake of human health and safety. The purposes of the present study was to prepare hybrid modified adsorbent from the carbonized palm shell and rice husk by physical treatment for the removal of 13 multi heavy metal component from simulated wastewater by single bed adsorption column. The Metals being studied are Cadmium, Chromium, Copper, Iron, Magnesium, Manganese, Lead, Lithium, Molybdenum, Nickel, Antimony, Vanadium and zinc. Six types of adsorbents were used for metal removal which are (100% BRH) adsorbent; (100% CPS) adsorbent , and four hybrids adsorbent prepared by mixing the blended rice husk and carbonized palm kernel shell with mixing ratios 20% , 40% , 60% , 80% wt Blended Rice Husk . The obtained results of the individual area under the graph analysis showed that cadmium, copper, lithium; vanadium elements were strongly adsorbed by hybrid adsorbents with achieved removal efficiency of 99.95%, 99.97%, 31.23%, and 89.58% with least area under the graph values of 3294.65, 2015.52, 118.231, and 115.18 respectively. As a conclusion, the mixing of blended rice husk and carbonized palm shell as hybrid adsorbent contributed to enhance the adsorption performance of cadmium, copper, lithium, vanadium, elements which demonstrated by less area under the graph values compared with pure carbonized palm shell and pure rice husk adsorbents.

Level Polynomials of Rooted Trees

Level index was introduced in 2017 for rooted trees which is a component of Gini index. In the origin, Gini index is a tool for economical investigations but Balaji and Mahmoud defined the graph theoretical applications of this index for statistical analysis of graphs. Level index is an important component of Gini index. In this paper we define a new graph polynomial which is called level polynomial and calculate the level polynomial of some classes of trees. We obtain some interesting relations between the level polynomials and some integer sequences.

Oscillation-Specific Nodal Differences in Parkinson's Disease Patients with Anxiety.

Parkinson's disease (PD) is a common neurodegenerative disorder that is predominantly known for its motor symptoms but is also accompanied by non-motor symptoms, including anxiety. The underlying neurobiological substrates and brain network changes associated with comorbid anxiety in PD require further exploration. An analysis of oscillation-specific nodal properties in patients with and without anxiety was conducted using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory. We used a band-pass filtering approach to differentiate oscillatory frequency bands for subsequent functional connectivity (FC) and graph analyses. The study included 68 non-anxiety PD (naPD) patients, 62 anxiety PD (aPD) patients, and 64 healthy controls (NC). Analyses of nodal betweenness centrality (BC), degree centrality (DC), and efficiency were conducted across multiple frequency bands. The findings indicated no significant differences in BC among naPD, aPD, and NC within the 0.01-0.08 Hz frequency range. However, we observed a specific reduction in BC at narrower frequency ranges in aPD patients, as well as differing patterns of change in DC and efficiency, which are believed to reflect the neurophysiological bases of anxiety symptoms in PD. Differential oscillation-specific nodal characteristics have been identified in PD patients with anxiety, suggesting potential dysregulations in brain network dynamics. These findings emphasize the complexity of brain network alterations in anxiety-associated PD and identify oscillatory frequencies as potential biomarkers. The study highlights the importance of considering oscillatory frequency bands in the analysis of brain network changes.

Trends in acupuncture for infertility: a scoping review with bibliometric and visual analysis.

Unexplained recurrent implantation failure and the high cost of assisted reproductive techniques for those experiencing infertility have increasingly resulted in the use of acupuncture. However, the trends and research status of acupuncture on infertility resulting in natural conception have not been systematically summarized. This scoping review and knowledge graph analysis aimed to summarize existing clinical studies on acupuncture for infertility that resulted in natural conception. Seven databases, namely, PubMed, Embase, the Cochrane Library, CNKI, VIP, Wanfang Data, and SinoMed, were searched up to August 2023 (updated on 1 April). Two authors independently identified related clinical studies and systematic reviews, and extracted data from included studies on acupuncture for infertility; any discrepancies were resolved by discussion or judged by a third author. A meta-analysis was conducted based on randomized controlled trials (RCTs), and data were synthesized using risk ratios with 95% confidence intervals. Of the 310 articles meeting the inclusion criteria, 274 were primary studies, 7 were systematic reviews, and 29 were case reports. Reported adverse events included mild ovarian irritation and early signs of miscarriage. Out of the 274 primary studies, there were 40 (14.60%) cases of male infertility and 234 (85.40%) cases of female infertility. Current research highlights on acupuncture for infertility focused on female infertility caused by polycystic ovary syndrome, ovulation disorder, and luteinized unruptured follicle syndrome (LUFS), while acupuncture for male infertility was a hotspot in the early research stage. The meta-analysis also suggested that acupuncture was more effective than human chorionic gonadotropin (HCG) [RR = 1.89, 95% CI (1.47, 2.42), 11 RCTs, 662 participants]. Acupuncture combined with HCG was comparable to HCG [RR = 2.33, 95% CI (1.53, 3.55), four RCTs, 259 participants]. Compared with no treatment, acupuncture resulted in a higher pregnancy rate [RR = 22.12, 95% CI (1.39, 353.09), one RCT, 47 participants]. There was no statistical difference between acupuncture combined with HCG plus letrozole and HCG plus letrozole [RR = 1.56, 95% CI (0.84, 2.89), one RCT, 84 participants]. Current research highlights on acupuncture for infertility resulting in natural conception focused on female infertility caused by polycystic ovary syndrome, ovulation disorder, and LUFS, while studies on male infertility and female infertility caused by blockage in the fallopian tube, thin endometrium, and other factors were insufficient. Well-designed confirmatory clinical studies are still needed as the research hypotheses of most studies were unclear.

Global Trends in mHealth and Medical Education Research: Bibliometrics and Knowledge Graph Analysis.

Mobile health (mHealth) is an emerging mobile communication and networking technology for health care systems. The integration of mHealth in medical education is growing extremely rapidly, bringing new changes to the field. However, no study has analyzed the publication and research trends occurring in both mHealth and medical education. The aim of this study was to summarize the current application and development trends of mHealth in medical education by searching and analyzing published articles related to both mHealth and medical education. The literature related to mHealth and medical education published from 2003 to 2023 was searched in the Web of Science core database, and 790 articles were screened according to the search strategy. The HistCite Pro 2.0 tool was used to analyze bibliometric indicators. VOSviewer, Pajek64, and SCImago Graphica software were used to visualize research trends and identify hot spots in the field. In the past two decades, the number of published papers on mHealth in medical education has gradually increased, from only 3 papers in 2003 to 130 in 2022; this increase became particularly evident in 2007. The global citation score was determined to be 10,600, with an average of 13.42 citations per article. The local citation score was 96. The United States is the country with the most widespread application of mHealth in medical education, and most of the institutions conducting in-depth research in this field are also located in the United States, closely followed by China and the United Kingdom. Based on current trends, global coauthorship and research exchange will likely continue to expand. Among the research journals publishing in this joint field, journals published by JMIR Publications have an absolute advantage. A total of 105 keywords were identified, which were divided into five categories pointing to different research directions. Under the influence of COVID-19, along with the popularization of smartphones and modern communication technology, the field of combining mHealth and medical education has become a more popular research direction. The concept and application of digital health will be promoted in future developments of medical education.

The Network Structure of Cognitive Impairment: From Subjective Cognitive Decline to Alzheimer's Disease.

It was proposed that a reorganization of the relationships between cognitive functions occurs in dementia, a vision that surpasses the idea of a mere decline of specific domains. The complexity of cognitive structure, as assessed by neuropsychological tests, can be captured by exploratory graph analysis (EGA). EGA was applied to the neuropsychological assessment of people (humans) with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD; total N = 638). Both sexes were included. In AD, memory scores detach from the other cognitive functions, and memory subdomains reduce their reciprocal relation. SCD showed a pattern of segregated neuropsychological domains, and MCI showed a noisy and less stable pattern. Results suggest that AD drives a reorganization of cognitive functions toward a less-fractionated architecture compared with preclinical conditions. Cognitive functions show a reorganization that goes beyond the performance decline. Results also have clinical implications in test interpretations and usage.

Improved sensitivity and ambient light stability of radiochromic plastic dosimeters through composite azo compounds

The aim of this study is to evaluate and compare the dose sensitivity and ambient light resistance of radiochromic plastic dosimeters (RPDs) incorporating mixed azo compound with those incorporating individual azo compounds.RPDs were fabricated using a mixture of polyurethane, leuco dye, initiator, and solvent.In this study, three azo compounds (tartrazine, sunset yellow, and allura red) were incorporated into RPDs either individually or in combination. Thus, we produced five dosimeter types: one original RPD (A) without azo compounds, three RPDs (B, C, D) with individual azo compounds, and one RPD (E) with mixed azo compounds. Initially, to compare dose response and sensitivity, one group of each sample was delivered to doses ranging from 0.2 Gy to 3 Gy with 6 MV photon beams at 600 cGy/min. To assess ambient light resistance, another group was exposed to light for varying durations. Following irradiation and light exposure, optical density (OD) was obtained using a cone-beam optical CT scanner for each group. Wavelength spectra for each sample were acquired using a spectrometer. This study encompassed analysis and comparison of dose response curves, sensitivity, and netOD-time graphs among samples. Additionally, the absorption wavelength spectra of the samples were compared with the light spectrum emitted by a light bulb.The dose response curves were represented by linear functions, with the slope indicating the sensitivity of each sample. The sensitivity for samples A-E were 0.0759, 0.0988, 0.0902, 0.0809, and 0.1013 ΔOD/Gy, respectively. Samples B-E demonstrated increases in sensitivity of 30.1%, 18.8%, 6.5%, and 33.4%, respectively, compared to sample A. Sample E, which incorporated mixed azo compounds, demonstrated the highest sensitivity and remarkable resistance to ambient light. The results suggested that all azo compounds influenced the sensitivity of the RPDs, and that mixed azo compounds does not reduce the sensitivity of the RPDs. The ambient light resistance was dictated by the overlap between the light bulb's wavelength and the azo dyes' absorption range, which for mixed azo compounds spanned widely from 300 nm to 600 nm. The mixed azo compounds, as opposed to a single azo compound, allowed for the absorption of a wider range of light wavelengths, leading to an increased resistance to ambient light.Our study demonstrated that the inclusion of azo compounds enhances the sensitivity of RPDs. Specifically, the use of mixed azo compounds provided the highest sensitivity and exhibited superior resistance to ambient light. This improved performance can be attributed to the broader absorption wavelength spectrum achievable with mixed azo compounds, enabling absorption across a wider range of light wavelengths. These findings highlight the potential utility of mixed azo compounds in the fabrication of RPDs, enhancing their function as highly sensitive and resistant dosimeters to ambient light.