Objective-specific pollen count thresholds for robust and relevant assemblages in boreal and northern temperate forests of eastern Canada - Jonathan A. Lesven; Dorian M. Gaboriau; Pierre J.H. Richard; Adam A. Ali; Hugo Asselin; Marion Blache; Martin P. Girardin; Mathis Jean-Sépet; Noé Moroy; Yves Bergeron (Palaeogeography, Palaeoclimatology, Palaeoecology, 2026)

KPC-producing Klebsiella pneumoniae in Switzerland from 2024 to 2025: comparative genomics and cefiderocol resistance mechanisms analyses - Jacqueline Findlay; Patrice Nordmann; R Lienhard; L Vonallmen; C Schilt; A Scherler; K Lucke; M Jutzi; M Reichmuth; U Schibli; C Fricker; S Pranghofer; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2026)

Vegetation Increases CH 4 Emissions and Methanotroph Diversity in Marine Sediments - Marion Dolivet‐Maréchal; Carlos Palacin‐Lizarbe; Henri M. P. Siljanen; Dhiraj Paul; Abigaïl Delort; Jonathan Gervaix; Charline Creuzé des Châtelliers; Sabine Schmidt; Mathis Cognat; David Sebag; Olivier Taugourdeau; Clara Schübert; et al. (Global Change Biology, 2026)
Seagrass meadows are key blue carbon (C) ecosystems, storing large amounts of organic C over centuries. Their climate benefits may be reduced by methane (CH 4 ) emissions, whose microbial and environmental descriptors in Zostera noltii meadows, dominant seagrass in North‐Western Europe, remain poorly understood. We studied CH 4 fluxes, CH 4 ‐producing and consuming microbial communities and sediment physicochemical parameters in Z. noltii meadows and adjacent bare sediments across seven sites in Arcachon Bay, France. In situ CH 4 fluxes were measured at low tide during daytime conditions, providing standardized estimates of peak emissions. Microbial communities were characterized using targeted metagenomics of three functional genes ( mcrA , mmoX , pmoA ) and quantitative PCR. CH 4 fluxes were higher in vegetated than bare sediments (24.4 ± 2.6 vs. 9.4 ± 0.7 μmol m −2 day −1 ). Mixed linear models and random forest analyses identified C accumulation rate and CO 2 flux as the strongest positive descriptors of CH 4 fluxes. Vegetated sediments hosted more diverse methanotrophs, while methanogens showed no habitat differences. Four genera ( mcrA–Methanolobus , mmoX–Methylocella , pmoA–Methylococcus , Methyloglobulus ) emerged as abundant, seagrass‐associated, correlated with CH 4 fluxes, and highlighted by models. Functional diversity, especially pmoA richness, was a stronger microbial descriptor of CH 4 fluxes than gene abundance or a specific genus. Findings indicate Z. noltii meadows enhance C burial and CH 4 emission, with methanotroph diversity potentially mitigating CH 4 emissions. Our results provide the first integrated assessment of CH 4 fluxes and their descriptors in Z. noltii meadows, based on limited temporal coverage capturing the daytime peak emission conditions, highlighting the intertwined nature of C burial and CH 4 emissions and the need to account for both in blue C climate assessments.

In vitro activity of β-lactamase inhibitors avibactam, relebactam and vaborbactam in combination with aztreonam against metallo-β-lactamase producing Escherichia coli clinical isolates - Clément Viguier; Samanta Freire; Maxime Bouvier; Christophe Le Terrier; Laurent Poirel; A. Westers; M. Imperiali; L. Pozzi; D. Balzari; G. Vaninetti; C. Cirillo; V. Gaia; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2026)

Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Silicification in the ocean: from molecular pathways to silicifiers' ecology and biogeochemical cycles - Ivia Closset; J. Jotautas Baronas; Fiorenza Torricella; Félix de Tombeur; Bianca T. P. Liguori; Alessandra Petrucciani; Natasha Bryan; María López-Acosta; Yelena Churakova; Antonia U. Thielecke; Zhouling Zhang; Natalia Llopis Monferrer; et al. (Ocean Science, 2025)
The oceanic silicon (Si) cycle has undergone a profound transformation from an abiotic system in the Precambrian to a biologically regulated cycle driven by siliceous organisms such as diatoms, Rhizaria, and sponges. These organisms actively uptake Si using specialized proteins to transport and polymerize it into amorphous silica through the process of biosilicification. This biological control varies depending on environmental conditions, influencing both the rate of silicification and its ecological function, including structural support, defence, and stress mitigation. Evidence suggests that silicification has evolved multiple times independently across different taxa, each developing distinct molecular mechanisms for Si handling. This review identifies major gaps in our understanding of biosilicification, particularly among lesser-known silicifiers beyond traditional model organisms like diatoms. It emphasizes the ecological significance of these underexplored taxa and synthesizes current knowledge of molecular pathways involved in Si uptake and polymerization. By comparing biosilicification strategies across taxa, this review calls for expanding the repertoire of model organisms and leveraging new advanced tools to uncover Si transport mechanisms, efflux regulation, and environmental responses. It also emphasizes the need to integrate biological and geological perspectives, both to refine palaeoceanographic proxies and to improve the interpretation of microfossil records and present-day biogeochemical models. On a global scale, Si enters the ocean primarily via terrestrial weathering and is removed through burial in sediments and/or authigenic clay formation. While open-ocean processes are relatively well studied, dynamic boundary zones – where land, sediments, and ice interact with seawater – are increasingly recognized as key interfaces regulating global Si fluxes, though they remain poorly understood. Therefore, special attention is given to the role of dynamic boundary zones such as the interfaces between land and ocean, the benthic zone, and the cryosphere, which are often overlooked yet play critical roles in controlling Si cycling. By bringing together cross-discipline insights, this review proposes a new integrated framework for understanding the complex biological and biogeochemical dimensions of the oceanic Si cycle. This integrated perspective is essential for improving global Si budget estimates, predicting climate-driven changes in marine productivity, and assessing the role of Si in modulating Earth's long-term carbon balance.

Interactive electrical behaviour in mormyrid weakly electric fish: jamming avoidance response or social interaction? - Nils Weimar; Moritz Maxeiner; Emily M. Wong; Ingolf P. Rick; Mathis Hocke; Tim Landgraf; Gerhard von der Emde (Animal Behaviour, 2025)

Surface-based morphometry reveals divergent aging trajectories in veterans with and without traumatic brain injury - Michelle C. Eliason; Amrutha Bindu Nagella; Cristian Cuadra; David S. Wack; Ghazala T. Saleem; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowki; Arthur W. Toga; et al. (GeroScience, 2025)

Combined resistance mechanisms leading to high-level of cefiderocol resistance among NDM-like producing E. coli ST167 clinical isolates - Mustafa Sadek; Juan Bosch Duran; Trinad Chakraborty; Laurent Poirel; R. Lienhard; L. Vonallmen; C. Schilt; A. Scherler; K. Lucke; M. Jutzi; M. Reichmuth; V. Slutter; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2025)
Summary Purpose A series of NDM-producing Escherichia coli ST167 clinical isolates exhibiting resistance to cefiderocol (FDC), with no previous exposure to this antibiotic, were analyzed in this study. Methods The antimicrobial susceptibility testing and phenotypic detection of resistance patterns (Rapid Cefiderocol NP test and MIC determination) were performed for all tested isolates. Their entire genomes were sequenced by using the Illumina MiSeq platform and high-quality reads were de-novo assembled using the CLC Genomic Workbench. Genome-sequence based characteristics were analyzed using bioinformatics tools. Results All NDM-producing E. coli ST167 isolates showed a high level of resistance to FDC (MICs being 64 or > 64 mg/L). The chromosomally located cirA gene, encoding a catecholate siderophore receptor in E. coli , was truncated in all FDC-resistant isolates due to a frameshift mutation (S90Y), leading to CirA-deficient isolates. A four amino acid insertion (YRIN) was also identified after residue 333 in the PBP3 protein sequence of all E. coli isolates. Among them, a single FDC-resistant NDM-5-producing E. coli isolate (1006) was additionally resistant to aztreonam/avibactam (AZA MIC of 8 mg/L). When analyzed against the genome of another FDC resistant NDM-5 producing E. coli ST167 containing a YRIN insertion in the PBP3, and exhibiting decreased susceptibility to AZA, the broad-spectrum ß-lactamase CMY-42 was identified. Conclusion We identified a variety of NDM-producing E. coli isolates exhibiting high level of resistance to FDC as a result of the combined effect of CirA deficiency, along with production of NDM-type enzymes. The spread of such resistance phenotype across Europe poses great concern on the clinical efficacy of this novel drug. Additionally, the identification of an FDC- and AZA-resistant NDM-5 producing E. coli isolate represents one of the ultimate evolutions with a possible step towards pan-resistance.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Voxel-wise insights into early Alzheimer’s disease pathology progression: the association with APOE and memory decline - Maha Wybitul; Nicolas Langer; Christoph Hock; Anton Gietl; Valerie Treyer; Michael Weiner; Paul Aisen; Ronald-Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; et al. (GeroScience, 2025)
Longitudinal investigation of the Apolipoprotein E (APOE) genotype’s impact on Alzheimer’s disease (AD) biomarker progression, focusing on amyloid beta (Aβ) accumulation and gray matter (GM) atrophy, integrating cognitive decline and baseline levels. Longitudinal florbetapir-PET and T1-weighted MRI data from 100 cognitively normal (CN) and mild cognitive impaired (MCI) participants both with considerable global Aβ accumulation (“high Aβ accumulators”) were analyzed using a voxel-wise approach. Associations of APOE genotype and memory decline with Aβ accumulation and GM atrophy were examined separately for each neuroimaging modality, controlling for baseline Aβ levels and diagnosis. Alternatively, the effect of baseline diagnosis, while controlling for memory decline, was investigated. A multimodal analysis evaluated interactions between genotype, memory decline, and GM atrophy on Aβ accumulation. High Aβ accumulators displayed extensive Aβ pathology predominantly in the medial orbito-frontal cortex, cingulate cortex, and precuneus, along with GM atrophy in temporal, occipital, orbito-frontal, and parietal areas. ɛ4 carriers with memory decline exhibited greater Aβ accumulation and GM atrophy in selective regions compared to non-carriers with memory decline, while no genotype difference was observed in individuals without decline. No interaction effect was observed for MCI diagnosis. Regional associations between the two biomarkers were similarly dependent on genotype and memory decline. ɛ4 carriers exhibiting memory decline present an accelerated neurobiological pattern at predementia stages, supporting early ɛ4 carrier monitoring and interventions in this at-risk group. Importantly, memory decline might be more informative than MCI regarding AD pathology progression emphasizing the importance of repeated cognitive assessments.

Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts - Luyao Wang; Wenjing Hu; Fan Dong; Can Sheng; Jinglong Wu; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2025)

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction - Andreas Engvig; Karl Trygve Kalleberg; Lars T. Westlye; Esten Høyland Leonardsen; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; et al. (GeroScience, 2024)
DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both β s 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-driven health deficit selection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA’s impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA’s limited contribution suggests caution in their use for individual risk assessment of dementia.

Local molecular and connectomic contributions of tau-related neurodegeneration - Fardin Nabizadeh; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; Robert C. Green; Andrew J. Saykin; John Morris; et al. (GeroScience, 2024)

Sex differences in interacting genetic and functional connectivity biomarkers in Alzheimer’s disease - Jordan N. Williamson; Shirley A. James; Sean P. Mullen; Bradley P. Sutton; Tracey Wszalek; Beni Mulyana; Peter Mukli; Andriy Yabluchanskiy; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2024)

Molecular analysis of metallo-beta-lactamase-producing Pseudomonas aeruginosa in Switzerland 2022–2023 - Jacqueline Findlay; Otavio Hallal Ferreira Raro; Laurent Poirel; Patrice Nordmann; R. Lienhard; L. Vonallmen; C. Schilt; A. Scherler; K. Lucke; M. Jutzi; M. Reichmuth; U. Schibli; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2024)
Objectives The occurrence of metallo-beta-lactamase-producing Pseudomonas aeruginosa (MBL-PA) isolates is increasing globally, including in Switzerland. The aim of this study was to characterise, phenotypically and genotypically, the MBL-PA isolates submitted to the Swiss National Reference Center for Emerging Antibiotic Resistance (NARA) reference laboratory over a 12-month period from July 2022 to July 2023. Methods Thirty-nine non-duplicate MBL-PA Isolates were submitted to NARA over the study period from across Switzerland. Susceptibility was determined by broth microdilution according to EUCAST methodology. Whole-genome sequencing was performed on 34 isolates. Sequence types (STs) and resistance genes were ascertained using the Centre for Genomic Epidemiology platform. MBL genes, bla NDM-1 , bla IMP-1 , and bla VIM-2 , were cloned into vector pUCP24 and transformed into P. aeruginosa PA14. Results The most prevalent MBL types identified in this study were VIM (21/39; 53.8%) followed by NDM (11/39; 28.2%), IMP (6/39; 15.4%), and a single isolate produced both VIM and NDM enzymes. WGS identified 13 different STs types among the 39 isolates. They all exhibited resistance to cephalosporins, carbapenems, and the beta-lactam-beta-lactamase inhibitor combinations, ceftolozane-tazobactam, ceftazidime-avibactam, imipenem-relebactam, and meropenem-vaborbactam, and 8 isolates were cefiderocol (FDC) resistant. Recombinant P. aeruginosa strains producing bla NDM-1 , bla IMP-1 , and bla VIM-2 exhibited FDC MICs of 16, 8, and 1 mg/L, respectively. Conclusions This study showed that the MBL-PA in Switzerland could be attributed to the wide dissemination of high-risk clones that accounted for most isolates in this study. Although FDC resistance was only found in 8 isolates, MBL carriage was shown to be a major contributor to this phenotype.

Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer’s disease: an exploratory study of 18F-FDG-PET - Qi Zhang; Chunqiu Fan; Luyao Wang; Taoran Li; Min Wang; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2023)

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment - Jiehui Jiang; Can Sheng; Guanqun Chen; Chunhua Liu; Shichen Jin; Lanlan Li; Xueyan Jiang; Ying Han; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2022)

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

The Mean Single Molecule Rate (mSMR) in the Analysis of Fluorescence Fluctuations: Measurements on DNA Mixtures of Defined Composition - Lorenz T. Sparrenberg; Benjamin Greiner; Harald P. Mathis (Journal of Fluorescence, 2021)
We present a method for the evaluation of fluorescence fluctuations on the basis of Mandel’s Q parameter, using sampling time-dependent factorial cumulants. By relating the Q parameter to the sampling time, we obtain the mean single molecule rate (mSMR), an easy to interpret expression that provides both brightness and diffusion information. The model is suitable for the widely used confocal setups with single photon excitation and a single detection channel. We present a way to correct the mSMR for afterpulsing, dead time and background noise. To account for photokinetic effects at short sampling times, we expand the model by a simple on/off isomerization term, which is similar to the well-known triplet model. The functionality of the mSMR is shown using Monte Carlo simulations. The correction mechanisms and the experimental applicability of the model are then demonstrated by DNA measurements of defined composition. By systematically analyzing DNA mixtures, we can show that at large sampling times, the mSMR correctly describes the single molecule brightness rates and the diffusive properties of DNA molecules. At short sampling times, the photokinetic effects of isomerization are accurately described by the mSMR model. Since additionally the mSMR can easily be corrected for measurement artefacts such as detector dead time, afterpulsing and background noise, this is a valuable advantage over the standard method of fluorescence correlation spectroscopy.

Erratum to: Surface expression and channel function of TRPM8 are cooperatively controlled by transmembrane segments S3 and S4 - Frank J. P. Kühn; Mathis Winking; Cornelia Kühn; Daniel C. Hoffmann; Andreas Lückhoff (Pflügers Archiv - European Journal of Physiology, 2013)

Surface expression and channel function of TRPM8 are cooperatively controlled by transmembrane segments S3 and S4 - Frank J. P. Kühn; Mathis Winking; Cornelia Kühn; Daniel C. Hoffmann; Andreas Lückhoff (Pflügers Archiv - European Journal of Physiology, 2013)

Yeast communities associated with artisanal mezcal fermentations from Agave salmiana - A. Verdugo Valdez; L. Segura Garcia; M. Kirchmayr; P. Ramírez Rodríguez; A. González Esquinca; R. Coria; A. Gschaedler Mathis (Antonie van Leeuwenhoek, 2011)

Effect of adenoviral mediated overexpression of fibromodulin on human dermal fibroblasts and scar formation in full-thickness incisional wounds - Alexander Stoff; Angel A. Rivera; J. Michael Mathis; Steven T. Moore; N. S. Banerjee; Maaike Everts; Antonio Espinosa-de-los-Monteros; Zdenek Novak; Luis O. Vasconez; Thomas R. Broker; Dirk F. Richter; Dale Feldman; et al. (Journal of Molecular Medicine, 2007)

A Cell Fractionation Approach for the Quantitative Analysis of Subcellular Drug Disposition - Muralikrishna Duvvuri; Wenhong Feng; Amanda Mathis; Jeffrey P. Krise (Pharmaceutical Research, 2004)

Synthesis and evaluation of 2-(3′-lodo-4′-aminophenyl)-6-hydroxybenzothiazole for in vivo quantitation of amyloid deposits in alzheimer’s disease - Yanming Wang; William E. Klunk; Guo-Feng Huang; Manik L. Debnath; Daniel P. Holt; Chester A. Mathis (Journal of Molecular Neuroscience, 2002)

Scratching the Skin of Predator—prey Interactions in Fishes: A Tribute to R. Jan F. Smith (1940–1998) - Douglas P. Chivers; Alicia Mathis; Grant E. Brown; Reehan S. Mirza; Brian D. Wisenden (Environmental Biology of Fishes, 1999)

Symposia lectures - F. Parak; A. Ostermann; G. U. Nienhaus; Nobuo Niimura; William A. Eaton; Stephen J. Hagen; Eric R. Henry; James Hofrichter; Gouri Jas; Lisa Lapidus; Victor Muñoz; Chih-chen Wang; et al. (Journal of Biosciences, 1999)

Kinetics of electron transfer between the tetrahemic cytochrome and the special pair in isolated reaction centers of Roseobacter denitrificans - D. Garcia; P. Mathis; A. Verméglio (Photosynthesis Research, 1998)