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Interfaith controversies and disputes regarding the role of reason in interpreting the Scriptures characterised scholarly discussion in the Low Countries between the seventeenth and eighteenth centuries. The Jewish author Abraham Gómez Silveira contributed to this discussion with an eclectic body of literature. This article focuses on his Libro Mudo (Mute Book), which embodies his efforts to present the Jewish religion as the only rational one and the Christian dogma as irrational. In order to corroborate his reading, Silveira mostly bases his argumentation on non-Jewish texts. By selecting passages from the New Testaments, Christian religious commentaries as well as Qur'anic excerpts, Silveira aims to demonstrate that even non-Jewish sources prove the rationality of the Jewish theological system. The novelty of Silveira's approach consists in confuting Christian dogma by accepting the Gospels as reliable historical sources. In this argumentative structure, the Qur'an has a similar although not identical function.
The Jewish population of early modern Italy was characterised by its inner diversity, which found its expression in the coexistence of various linguistic, cultural and liturgical traditions, as well as social and economic patterns. The contributions in this volume aim to explore crucial questions concerning the self-perception and identity of early modern Italian Jews from new perspectives and angles.
Multijunction solar cells can overcome the fundamental efficiency limits of single-junction devices. The bandgap tunability of metal halide perovskite solar cells renders them attractive for multijunction architectures(1). Combinations with silicon and copper indium gallium selenide (CIGS), as well as all-perovskite tandem cells, have been reported(2-5). Meanwhile, narrow-gap non-fullerene acceptors have unlocked skyrocketing efficiencies for organic solar cells(6,7). Organic and perovskite semiconductors are an attractive combination, sharing similar processing technologies. Currently, perovskite-organic tandems show subpar efficiencies and are limited by the low open-circuit voltage (V-oc) of wide-gap perovskite cells(8) and losses introduced by the interconnect between the subcells(9,10). Here we demonstrate perovskite-organic tandem cells with an efficiency of 24.0 per cent (certified 23.1 per cent) and a high V-oc of 2.15 volts. Optimized charge extraction layers afford perovskite subcells with an outstanding combination of high V-oc and fill factor. The organic subcells provide a high external quantum efficiency in the near-infrared and, in contrast to paradigmatic concerns about limited photostability of non-fullerene cells(11), show an outstanding operational stability if excitons are predominantly generated on the non-fullerene acceptor, which is the case in our tandems. The subcells are connected by an ultrathin (approximately 1.5 nanometres) metal-like indium oxide layer with unprecedented low optical/electrical losses. This work sets a milestone for perovskite-organic tandems, which outperform the best p-i-n perovskite single junctions(12) and are on a par with perovskite-CIGS and all-perovskite multijunctions(13).
A combinatorial study of the effect of in-mixing of various guests on the thermoelectric properties of the host workhorse polymer poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT) is presented. Specifically, the composition and thickness for doped films of PBTTT blended with different polymers are varied. Some blends at guest weight fractions around 10-15% exhibit up to a fivefold increase in power factor compared to the reference material, leading to zT values around 0.1. Spectroscopic analysis of the charge-transfer species, structural characterization using grazing-incidence wide-angle X-ray scattering, differential scanning calorimetry, Raman, and atomic force microscopy, and Monte Carlo simulations are employed to determine that the key to improved performance is for the guest to promote long-range electrical connectivity and low disorder, together with similar highest occupied molecular orbital levels for both materials in order to ensure electronic connectivity are combined.
We present proper motion (PM) measurements within the central region of the Large Magellanic Cloud (LMC), using near-infrared data from the VISTA survey of the Magellanic Cloud system (VMC). This work encompasses 18 VMC tiles covering a total sky area of similar to 28 deg(2). We computed absolute stellar PMs from multiepoch observations in the K-s filter over time baselines between similar to 12 and 47 months. Our final catalogue contains similar to 6322 000 likely LMC member stars with derived PMs. We employed a simple flat-rotating disc model to analyse and interpret the PM data. We found a stellar centre of rotation (alpha(0) = 79.95 degrees(+0.22)(-0.23), delta(0) = -69.31 degrees(+0.12)(-0.11)) that is in agreement with that resulting from Hubble Space Telescope data. The inferred viewing angles of the LMC disc (i = 33.5 degrees(+1.2)(-1.3), Theta = 129.8 degrees(+1.9)(-1.9)) are in good agreement with values from the literature but suggest a higher inclination of the central parts of the LMC. Our data confirm a higher rotation amplitude for the young (less than or similar to 0.5 Gyr) stars compared to the intermediate-age/old (greater than or similar to 1 Gyr) population, which can be explained by asymmetric drift. We constructed spatially resolved velocity maps of the intermediate-age/old and young populations. Intermediate-age/old stars follow elongated orbits parallel to the bar's major axis, providing first observational evidence for x(1) orbits within the LMC bar. In the innermost regions, the motions show more chaotic structures. Young stars show motions along a central filamentary bar structure.
Solid organ transplant (SOT) recipients receive therapeutic immunosuppression that compromises their immune response to infections and vaccines. For this reason, SOT patients have a high risk of developing severe coronavirus disease 2019 (COVID-19) and an increased risk of death from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Moreover, the efficiency of immunotherapies and vaccines is reduced due to the constant immunosuppression in this patient group. Here, we propose adoptive transfer of SARS-CoV-2-specific T cells made resistant to a common immunosuppressant, tacrolimus, for optimized performance in the immunosuppressed patient. Using a ribonucleoprotein approach of CRISPR-Cas9 technology, we have generated tacrolimus-resistant SARS-CoV-2-specific T cell products from convalescent donors and demonstrate their specificity and function through characterizations at the single-cell level, including flow cytometry, single-cell RNA (scRNA) Cellular Indexing of Transcriptomes and Epitopes (CITE), and T cell receptor (TCR) sequencing analyses. Based on the promising results, we aim for clinical validation of this approach in transplant recipients. Additionally, we propose a combinatory approach with tacrolimus, to prevent an overshooting immune response manifested as bystander T cell activation in the setting of severe COVID-19 immunopathology, and tacrolimus-resistant SARS-CoV-2-specific T cell products, allowing for efficient clearance of viral infection. Our strategy has the potential to prevent severe COVID-19 courses in SOT or autoimmunity settings and to prevent immunopathology while providing viral clearance in severe non-transplant COVID-19 cases.
Background and aims: Accurate and user-friendly assessment tools quantifying alcohol consumption are a prerequisite to effective prevention and treatment programmes, including Screening and Brief Intervention. Digital tools offer new potential in this field. We developed the ‘Animated Alcohol Assessment Tool’ (AAA-Tool), a mobile app providing an interactive version of the World Health Organization's Alcohol Use Disorders Identification Test (AUDIT) that facilitates the description of individual alcohol consumption via culturally informed animation features. This pilot study evaluated the Russia-specific version of the Animated Alcohol Assessment Tool with regard to (1) its usability and acceptability in a primary healthcare setting, (2) the plausibility of its alcohol consumption assessment results and (3) the adequacy of its Russia-specific vessel and beverage selection. Methods: Convenience samples of 55 patients (47% female) and 15 healthcare practitioners (80% female) in 2 Russian primary healthcare facilities self-administered the Animated Alcohol Assessment Tool and rated their experience on the Mobile Application Rating Scale – User Version. Usage data was automatically collected during app usage, and additional feedback on regional content was elicited in semi-structured interviews. Results: On average, patients completed the Animated Alcohol Assessment Tool in 6:38 min (SD = 2.49, range = 3.00–17.16). User satisfaction was good, with all subscale Mobile Application Rating Scale – User Version scores averaging >3 out of 5 points. A majority of patients (53%) and practitioners (93%) would recommend the tool to ‘many people’ or ‘everyone’. Assessed alcohol consumption was plausible, with a low number (14%) of logically impossible entries. Most patients reported the Animated Alcohol Assessment Tool to reflect all vessels (78%) and all beverages (71%) they typically used. Conclusion: High acceptability ratings by patients and healthcare practitioners, acceptable completion time, plausible alcohol usage assessment results and perceived adequacy of region-specific content underline the Animated Alcohol Assessment Tool's potential to provide a novel approach to alcohol assessment in primary healthcare. After its validation, the Animated Alcohol Assessment Tool might contribute to reducing alcohol-related harm by facilitating Screening and Brief Intervention implementation in Russia and beyond.
Simulating the space weather in the AU Mic system: stellar winds and extreme coronal mass ejections
(2022)
Two close-in planets have been recently found around the M-dwarf flare star AU Microscopii (AU Mic). These Neptune-sized planets (AU Mic b and c) seem to be located very close to the so-called "evaporation valley" in the exoplanet population, making this system an important target for studying atmospheric loss on exoplanets. This process, while mainly driven by high-energy stellar radiation, will be strongly mediated by the space environment surrounding the planets. Here we present an investigation of this last area, performing 3D numerical modeling of the quiescent stellar wind from AU Mic, as well as time-dependent simulations describing the evolution of a highly energetic coronal mass ejection (CME) event in this system. Observational constraints on the stellar magnetic field and properties of the eruption are incorporated in our models. We carry out qualitative and quantitative characterizations of the stellar wind, the emerging CMEs, as well as the expected steady and transient conditions along the orbit of both exoplanets. Our results predict extreme space weather for AU Mic and its planets. This includes sub-Alfvenic regions for the large majority of the exoplanet orbits, very high dynamic and magnetic pressure values in quiescence (varying within 10(2)-10(5) times the dynamic pressure experienced by Earth), and an even harsher environment during the passage of any escaping CME associated with the frequent flaring observed in AU Mic. These space weather conditions alone pose an immense challenge for the survival of exoplanetary atmospheres (if any) in this system.
Introduction
Attempts to improve cognitive abilities via transcranial direct current stimulation (tDCS) have led to ambiguous results, likely due to the method's susceptibility to methodological and inter-individual factors. Conventional tDCS, i.e., using an active electrode over brain areas associated with the targeted cognitive function and a supposedly passive reference, neglects stimulation effects on entire neural networks.
Methods
We investigated the advantage of frontoparietal network stimulation (right prefrontal anode, left posterior parietal cathode) against conventional and sham tDCS in modulating working memory (WM) capacity dependent transfer effects of a single-session distractor inhibition (DIIN) training. Since previous results did not clarify whether electrode montage drives this individual transfer, we here compared conventional to frontoparietal and sham tDCS and reanalyzed data of 124 young, healthy participants in a more robust way using linear mixed effect modeling.
Results
The interaction of electrode montage and WM capacity resulted in systematic differences in transfer effects. While higher performance gains were observed with increasing WM capacity in the frontoparietal stimulation group, low WM capacity individuals benefited more in the sham condition. The conventional stimulation group showed subtle performance gains independent of WM capacity.
Discussion
Our results confirm our previous findings of WM capacity dependent transfer effects on WM by a single-session DIIN training combined with tDCS and additionally highlight the pivotal role of the specific electrode montage. WM capacity dependent differences in frontoparietal network recruitment, especially regarding the parietal involvement, are assumed to underlie this observation.
Background
There is consistent evidence that the COVID-19 pandemic is associated with an increased psychosocial burden on children and adolescents and their parents. Relatively little is known about its particular impact on high-risk groups with chronic physical health conditions (CCs). Therefore, the primary aim of the study is to analyze the multiple impacts on health care and psychosocial well-being on these children and adolescents and their parents.
Methods
We will implement a two-stage approach. In the first step, parents and their underage children from three German patient registries for diabetes, obesity, and rheumatic diseases, are invited to fill out short questionnaires including questions about corona-specific stressors, the health care situation, and psychosocial well-being. In the next step, a more comprehensive, in-depth online survey is carried out in a smaller subsample.
Discussion
The study will provide insights into the multiple longer-term stressors during the COVID-19 pandemic in families with a child with a CC. The simultaneous consideration of medical and psycho-social endpoints will help to gain a deeper understanding of the complex interactions affecting family functioning, psychological well-being, and health care delivery.
Introduction General and particularly sport-specific testing is an integral aspect of performance optimization in artistic gymnastics. In artistic gymnastics, however, only non-specific field tests have been used to assess endurance performance (e.g., Multistage Shuttle Run Test; Cooper's Test).
Methods This study aimed to examine the validity of a new sport-specific endurance test in artistic gymnastics. Fourteen elite-level gymnasts (i.e., eight males and six females) participated in this study. The newly developed artistic gymnastics-specific endurance test (AGSET) was conducted on two different occasions seven days apart to determine its reliability. To assess the concurrent validity of AGSET, participants performed the multistage shuttle run test (MSRT). Maximum oxygen uptake (VO2max) and respiratory exchange ratio (RER) were directly assessed using a portable gas analyzer system during both protocols. Additionally, the total time maintained (TTM) during the AGSET, maximum heart rate (HRmax), maximal aerobic speed (MAS), and blood lactate concentration (BLa) during the two protocols were collected.
Results The main findings indicated that all variables derived from the AGSET (i.e., VO2max, MAS, HRmax, BLa, and RER) displayed very good relative (all intraclass correlation coefficients [ICC] > 0.90) and absolute (all typical errors of measurement [TEM] < 5%) reliability. Further, results showed that the ability of the AGSET to detect small changes in VO2max, MAS, BLa, and RER was good (smallest worthwhile change [SWC0.2] > TEM), except HRmax (SWC0.2 < TEM). Additionally, results showed a nearly perfect association between the VO2max values derived from the AGSET and MSRT (r = 0.985; coefficient of determination [R-2] = 97%) with no statistically significant differences (p>0.05). The mean (bias) +/- 95% limits of agreement between the two protocols were 0.28 +/- 0.55 mlminkg-1.
Discussion AGSET seems to present very good reliability and concurrent validity for assessing endurance performance in elite artistic gymnastics. In addition, the newly developed protocol presents a good ability to detect small changes in performance.
Background Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders.
Methods Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP).
Results The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: & beta; = -0.35; NVS: & beta; = 0.39; CS: & beta; = -0.12; SP: & beta; = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.
Limitations The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.
Conclusion Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
How to not induce SNAs
(2023)
People respond faster to smaller numbers in their left space and to larger numbers in their right space. Here we argue that movements in space contribute to the formation of spatial-numerical associations (SNAs). We studied the impact of continuous isometric forces along the horizontal or vertical cardinal axes on SNAs while participants performed random number production and arithmetic verification tasks. Our results suggest that such isometric directional force do not suffice to induce SNAs.
Background
Machine learning models promise to support diagnostic predictions, but may not perform well in new settings. Selecting the best model for a new setting without available data is challenging. We aimed to investigate the transportability by calibration and discrimination of prediction models for cognitive impairment in simulated external settings with different distributions of demographic and clinical characteristics.
Methods
We mapped and quantified relationships between variables associated with cognitive impairment using causal graphs, structural equation models, and data from the ADNI study. These estimates were then used to generate datasets and evaluate prediction models with different sets of predictors. We measured transportability to external settings under guided interventions on age, APOE & epsilon;4, and tau-protein, using performance differences between internal and external settings measured by calibration metrics and area under the receiver operating curve (AUC).
Results
Calibration differences indicated that models predicting with causes of the outcome were more transportable than those predicting with consequences. AUC differences indicated inconsistent trends of transportability between the different external settings. Models predicting with consequences tended to show higher AUC in the external settings compared to internal settings, while models predicting with parents or all variables showed similar AUC.
Conclusions
We demonstrated with a practical prediction task example that predicting with causes of the outcome results in better transportability compared to anti-causal predictions when considering calibration differences. We conclude that calibration performance is crucial when assessing model transportability to external settings.
BackgroundIn spring of 2020, the Sars-CoV-2 incidence rate increased rapidly in Germany and around the world. Throughout the next 2 years, schools were temporarily closed and social distancing measures were put in place to slow the spread of the Covid-19 virus. Did these social restrictions and temporary school lockdowns affect children's physical fitness? The EMOTIKON project annually tests the physical fitness of all third-graders in the Federal State of Brandenburg, Germany. The tests assess cardiorespiratory endurance (6-min-run test), coordination (star-run test), speed (20-m sprint test), lower (powerLOW, standing long jump test), and upper (powerUP, ball-push test) limbs muscle power, and static balance (one-legged stance test with eyes closed). A total of 125,893 children were tested in the falls from 2016 to 2022. Primary analyses focused on 98,510 keyage third-graders (i.e., school enrollment according to the legal key date, aged 8 to 9 years) from 515 schools. Secondary analyses included 27,383 older-than-keyage third-graders (i.e., OTK, delayed school enrollment or repetition of a grade, aged 9 to 10 years), who have been shown to exhibit lower physical fitness than expected for their age. Linear mixed models fitted pre-pandemic quadratic secular trends, and took into account differences between children and schools.ResultsThird-graders exhibited lower cardiorespiratory endurance, coordination, speed and powerUP in the Covid pandemic cohorts (2020-2022) compared to the pre-pandemic cohorts (2016-2019). Children's powerLOW and static balance were higher in the pandemic cohorts compared to the pre-pandemic cohorts. From 2020 to 2021, coordination, powerLOW and powerUP further declined. Evidence for some post-pandemic physical fitness catch-up was restricted to powerUP. Cohen's |ds| for comparisons of the pandemic cohorts 2020-2022 with pre-pandemic cohorts 2016-2019 ranged from 0.02 for powerLOW to 0.15 for coordination. Within the pandemic cohorts, keyage children exhibited developmental losses ranging from approximately 1 month for speed to 5 months for cardiorespiratory endurance. For powerLOW and static balance, the positive pandemic effects translate to developmental gains of 1 and 7 months, respectively. Pre-pandemic secular trends may account for some of the observed differences between pandemic and pre-pandemic cohorts, especially in powerLOW, powerUP and static balance. The pandemic further increased developmental delays of OTK children in cardiorespiratory endurance, powerUP and balance.ConclusionsThe Covid-19 pandemic was associated with declines in several physical fitness components in German third-graders. Pandemic effects are still visible in 2022. Health-related interventions should specifically target those physical fitness components that were negatively affected by the pandemic (cardiorespiratory endurance, coordination, speed).
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.
The detection of communities in graph datasets provides insight about a graph's underlying structure and is an important tool for various domains such as social sciences, marketing, traffic forecast, and drug discovery. While most existing algorithms provide fast approaches for community detection, their results usually contain strictly separated communities. However, most datasets would semantically allow for or even require overlapping communities that can only be determined at much higher computational cost. We build on an efficient algorithm, FOX, that detects such overlapping communities. FOX measures the closeness of a node to a community by approximating the count of triangles which that node forms with that community. We propose LAZYFOX, a multi-threaded adaptation of the FOX algorithm, which provides even faster detection without an impact on community quality. This allows for the analyses of significantly larger and more complex datasets. LAZYFOX enables overlapping community detection on complex graph datasets with millions of nodes and billions of edges in days instead of weeks. As part of this work, LAZYFOX's implementation was published and is available as a tool under an MIT licence at https://github.com/TimGarrels/LazyFox.
Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N & B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.