Loss-of-function studies are a central approach to understanding gene/protein function. In mice, this often relies upon heritable recombination at the DNA level. This approach is slow and nonreversible, which limits both spatial and temporal resolution of analysis. Recently, degron techniques that directly target proteins for degradation have been successfully used to quickly and reversibly knock down proteins. Currently, these systems have been limited by lack of tissue/cell type specificity. Here, we generated mice that allow spatial and temporal control of GFP-tagged protein degradation. This DegronGFP line leads to degradation of GFP-tagged proteins in different cellular compartments and in distinct cell types. Further, it is rapid and reversible. We used DegronGFP to probe the function of the glucocorticoid receptor in the epidermis and demonstrate that it has distinct functions in proliferative and differentiated cells-an analysis that would not have been possible with traditional recombination approaches. We propose that the ability to use GFP knock-in lines for loss-of-function analysis will provide additional motivation for generation of these useful tools.

Forensic estimation of the postmortem interval (PMI) becomes increasingly challenging when decomposition progresses beyond the initial weeks, as traditional medicolegal indicators lose their temporal precision. Here, we demonstrate that dual-kingdom microbial communities associated with decomposing remains form robust molecular clocks that maintain predictive power for PMI estimation well into skeletonization. Using full-length amplicon sequencing, we tracked the succession of bacteria and fungi in host-associated oral samples and the underlying gravesoil from decomposing pigs (N = 6) over nearly five months (2170.0 accumulated degree days; ADD). Microbial communities exhibited consistent three-phase succession patterns - initial disruption, intermediate colonization, and late-stage stabilization - that aligned with morphological decomposition scoring. Necrobiome succession dynamics continued long after morphological decomposition metrics reached a plateau, demonstrating the extended temporal resolution provided by microbial markers. Machine-learning models integrating microbial features with morphological data achieved robust predictive accuracy for both PMI in days and ADD, with performance varying systematically across decomposition stages. Bacterial models dominated early decomposition, dual-kingdom approaches optimized intermediate phases, and fungal models excelled during late-stage decomposition when conventional indicators fail. We identified specific microbial taxa that serve as reliable temporal indicators across sample types. These findings demonstrate that necrobiome succession extends capabilities to estimate time since death by months, offering a molecular framework for advanced decomposition cases where traditional methods lose precision.

EEG-based epileptic seizure prediction with patient-tailored spectral-spatial-temporal feature learning.

Numerous factors interfere with the successful transmission of messages during verbal conversations leading speakers to use different speech modes, i.e., specific prototypes of speech with unique phonatory and articulatory characteristics. Despite their omnipresence in verbal exchanges, no theoretical model in the speech production literature has provided a mechanistical account of the encoding processes underpinning speech in different modes. The present study thus aims to investigate how speech modes are planned/programmed relative to standard speech using the high temporal resolution provided by electroencephalography (EEG). 20 Participants uttered pseudowords in three different conditions-standard speech, speaking louder than usual and faking an English accent in French-during a delayed production task. Event-related potential (ERP) of standard speech was contrasted separately with the two others speech modes. Results indicate that speaking by adopting speech modes varying in articulatory and phonatory properties entails increased neural activity of the brain networks that are already involved in standard speech production. Especially, electrophysiological signatures of loud speech and faking an accent were both associated to differences in ERP responses relative to standard speech in a time period covering the last 200 msec preceding the vocal onset. This observation was coherent across waveform analysis (more extended differences in time and space for faking an accent), topographical dissimilarity analysis and microstates analysis (more extended for loud speech). The present findings highlight that different speech modes are encoded in the last 200 msec preceding their vocal production, possibly in a mode-specific way which will need further investigation.

A dense recurrent unrolling network leveraging spatio-temporal priors for highly-accelerated dynamic MRI.

High-resolution data and continuous monitoring of water quality parameters enable a more accurate characterisation of stormwater pollutants dynamics. This article presents a unique dataset combining real-time online monitoring of turbidity and discharge data with event-based, size-fractionated chemical characterisation of stormwater. Turbidity and discharge were measured with a high temporal resolution at the stormwater outlet of a small urban catchment in Dresden, Germany. Additionally, for selected rainfall-runoff events, the following data were produced: total suspended solids concentrations and their particle-size distribution (<63 µm: fine particles; >63 µm: coarse fraction), elemental composition, and organic content. The online monitoring data covers the period from January 2018 to August 2022, whereas the sampled data were collected from September 2018 to 2021. Turbidity serves as a proxy for particles, organic, and elemental composition of stormwater. Therefore, our dataset is suitable for exploring flush dynamics, particle transport patterns, particle-bound pollutants, as well as for developing and validating particle transport formulations in urban drainage models. This will enable a more effective identification of stormwater treatment and management strategies to address different pollutant flushes, support regulatory decision-making, and minimise the impact of stormwater discharges on receiving water bodies. Hence, intended users of this dataset include, but are not limited to, the urban drainage/urban hydrology/stormwater research community and practitioners, students, decision-makers, policymakers, urban planners, engineers, and other stakeholders interested in water-related issues at the city or urban catchment scale.

To evaluate Frequency Alternation at Low duty cycle for Single Offset (FALSO) as a novel Magnetization Transfer (MT) preparation scheme to increase speed and/or spatial resolution of inhomogeneous MT (ihMT) MRI by reducing the number of volumes required. We compared FALSO MT to standard single frequency MT preparations using signal simulations and ihMT data acquired in a rat brain at 9.4 T and human brains at 3 T. Using FALSO MT preparations, combined with optimized Variable Flip Angle (VFA) MPRAGE readouts, we also acquired ihMT data at high resolution (down to 1.4 mm isotropic) to demonstrate the reduction in acquisitions required for ihMT images of sufficient SNR. We found no statistically significant difference between ihMT ratios from data acquired using FALSO MT preparations versus averaging data following separate positive and negative frequency offset MT acquisitions (as in regular ihMT to account for MT asymmetry). Use of VFA (relative to constant flip angle) readouts allowed high-resolution ihMT images with a minimal number of volumes to be acquired and reduced variance in ihMT ratios within ROIs. FALSO MT preparations allow for a reduction in the number of acquisitions required for ihMT while still controlling for MT asymmetry. IhMT data acquired with VFA readouts allow for higher resolution acquisitions in the same scan time. The combination of FALSO MT and VFA readouts can be used to increase the spatial and/or temporal resolution of ihMT experiments, allowing for easier clinical translation and improving the utility of ihMT in neurological studies of myelin.

The Eocene-Oligocene transition was the crucial turning point when Earth's climate shifted to its current icehouse state. Understanding how the marine biosphere responded during this transition is not well-constrained, appearing as a simple extinction pulse in low temporal resolution global compendia. Here we design an artificial-intelligence-inspired metaheuristics algorithm to construct a high-resolution global species richness history across the Eocene-Oligocene transition for the rich foraminifera fossil record with an imputed ~29,000-year resolution. The revealed diversity dynamics are complex and differ for each foraminiferal group with distinct ecology. Planktonic and shallow-water larger benthic foraminifera show steady diversity levels in the early phases of the transition in the latest Eocene after a long-term reduction, while the deeper-water small benthic foraminifera radiate notably and then decline over the same interval. In the earliest Oligocene, the planktonic and larger foraminifera suffer major species losses coincident with the first continental-scale ice sheet formed on Antarctica, while small benthic foraminifera diversity holds steady, followed by an accelerating lowering as the early Oligocene proceeds. These findings reveal complicated and ecologically differentiated environment-life processes, indicating the importance of high-resolution temporal data for dissecting out ecological responses to major environmental changes.

Manipulating light at the nanoscale with minimal loss remains a central challenge for nanophotonic technologies that can be tackled by using the direction-dependent polariton modes supported by anisotropic materials. Although best known for their highly confined polaritons, hyperbolic materials can also host long-range directional polaritons, whose direct observation has remained challenging as it requires experimental techniques that combine nanometer and femtosecond spatial and temporal resolution, respectively. Here, we use time-resolved photoemission electron microscopy for direct nanoscale visualization of long-range anisotropic plasmon polariton (LRAPP) dynamics on a flake of the van der Waals hyperbolic material molybdenum oxydichloride. We directly image plasmon polaritons with propagation lengths larger than 10 μm, exhibiting an approximately three times longer propagation length and intrinsically lower optical loss than short-range polaritons previously reported on the same material. By tracking the spatiotemporal evolution of LRAPPs, we determine their phase and group velocities at the nanoscale and directly observe their reflections at flake edges. These results establish molybdenum oxydichloride as a versatile platform for integrated nanophotonics, supporting both low-loss directional transport and deeply subwavelength field confinement within a single natural material in the visible spectral range.

Recent advances in functional PET (fPET) enable modeling of metabolic processes with second-level temporal resolution, opening applications such as imaging molecular connectivity comparable to fMRI. However, high-temporal fPET is more noise-sensitive, making meaningful signal extraction challenging. We developed a component-based preprocessing method adapted from fMRI, which models structured noise with tissue-specific regressors and removes low-frequency uptake trends (CompCor). This approach was applied to 20 high-temporal [18F]FDG-fPET scans from a long-axial PET/CT system (1 s frames) and 16 scans from a PET/MR scanner (3 s frames). Filtering methods were compared across frequency bands, and their effects on metabolic connectivity (M-MC) assessed. Connectivity was strongly influenced by filter strategy and scanner type. CompCor produced more consistent, structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) gave the most reliable connectivity across PET/CT and PET/MR (r = 0.89), while high-sensitivity PET/CT also revealed structured patterns at 0.1-0.2 Hz. Compared to fMRI, fPET networks appeared more spatially cohesive but less differentiated. In sum, high-temporal [18F]FDG-fPET enables high within-scan reliability estimation of resting-state M-MC when paired with appropriate denoising, opening a new avenue in molecular imaging. Scanner characteristics and preprocessing critically affect signal quality, while our physiologically informed pipeline improves comparability across systems and studies.

Liver transplantation remains the only curative treatment for end-stage liver failure, yet its impact is constrained by organ shortages and graft non-utilization. Machine perfusion (MP) enables exvivo liver assessment; however, current viability criteria rely on intermittent sampling, limiting temporal resolution and accuracy. Indocyanine green (ICG), a clinically validated dye cleared exclusively by hepatocytes, provides a continuous index of hepatic function beyond initial injury. We present a non-invasive, clamp-on optical sensor that demonstrates the first continuous, real-time quantification of ICG clearance during MP. The sensor consists of a clamp-on module with an 808 nm laser and phototransistor connected to a microcontroller and computer for real-time plotting. The raw phototransistor signal was linearised to a unitless absorbance signal proportional to perfusate ICG; bi-exponential fitting yielded plasma disappearance rate (PDRbi, %/min) and the 15-min residual fraction (R15). Across 10 whole and 3 split human livers (45 boluses; 13 paired with spectrophotometry), the sensor closely matched spectrophotometric measurements (pooled R2 = 0.994; range 0.983-0.999). The sensor resolved expected physiological trends: ICG clearance rate increased from subnormothermic to normothermic temperatures (ΔPDRbi + 14.41% ± 9.53%/min, ΔR15 -22.35 ± 9.97 percentage points; n = 4). The continuous sensor signal also revealed early mixing dynamics and medication-related effects missed by intermittent sampling. This optical sensor enables accurate, real-time monitoring of ICG clearance during exvivo perfusion. The exvivo setting is uniquely positioned to validate ICG clearance models, enhance clinical interpretation, and support informed graft assessment during perfusion.

This study aimed to evaluate the real-time performance of an Electrostatic Mass Monitor (EDM) against the reference-grade Tapered Element Oscillating Microbalance (TEOM) for measuring PM2.5 mass concentrations emitted from a simulated oil/gas furnace. PM2.5 was sampled from the furnace exhaust using a dilution system under varying operating conditions, including a wide range of Air-to-Fuel Ratios (AFR) (2.5, 5.0, 7.5) and flue gas temperature setpoints (75 °C–150 °C). Experimental results confirmed that PM2.5 emission rates were overwhelmingly controlled by the AFR, with the fuel-rich condition (AFR = 2.5) generating concentrations up to 1400 g/m3 and exhibiting high temporal volatility. A linear regression analysis performed on the paired real-time data established a strong positive correlation between the two instruments (Pearson’s r = 0.962; Adj. R2= 0.963). The resulting regression slope of 0.909 suggests the EDM systematically reports mass concentrations approximately 9% lower than the TEOM for these combustion aerosols. However, the EDM demonstrated superior temporal resolution, capturing greater short-term fluctuations in the PM2.5 concentration compared to the TEOM. The high level of correlation validates the EDM as a reliable and cost-effective instrument for continuous, real-time PM2.5 emission monitoring in combustion source applications, contingent upon the application of a site-specific calibration factor derived from the TEOM.

Optical imaging is playing an increasingly critical role in modern biomedical research. In particular, the second near-infrared window (NIR-II, 1000-1700 nm) has attracted widespread attention due to its significant advantages in tissue penetration depth, spatial resolution, and temporal resolution. In this cutting-edge field, silver nanoclusters (AgNCs) have emerged as highly promising NIR-II luminescent probes owing to their unique physicochemical properties. These intrinsic properties position AgNCs as a highly promising platform for engineering advanced NIR-II luminescent nanoprobes. This review aims to systematically summarize the research progress in AgNCs with NIR-II emission. Firstly, we will outline the main types of AgNCs with NIR-II emission, their synthesis strategies, and the theoretical foundations of their luminescence mechanisms. Secondly, we will focus on summarizing specific application examples of these materials in in vivo fluorescence imaging. Furthermore, the review will provide an in-depth analysis of the key challenges currently faced by these probes in practical biomedical applications, such as the need for further improvement in brightness, optimization of targeted functionalization strategies, and further clarification of in vivo metabolic behavior and long-term biosafety. The corresponding strategies for performance enhancement and novel material design approaches will also be discussed. Finally, we will prospect future development directions of NIR-II luminescent AgNCs, with the aim of promoting their broader application breakthroughs in areas such as deep-tissue imaging, multimodal theranostics, and precision medicine.

The eukaryotic cell cycle is one of the most fundamental biological processes, ensuring the accurate duplication and segregation of the genome during mitosis. Decades of research across model systems have shown that this process is orchestrated by a family of protein kinases known as cyclin-dependent kinases (Cdks). Together with their cyclin partners, Cdks act as master regulators of cell division, coordinating DNA replication, chromosome segregation, and cytokinesis with remarkable precision. The discovery of Cdks and cyclins in yeast and sea urchins, celebrated with the Nobel Prize of Hartwell, Hunt, and Nurse (awarded in 2001), established the conceptual framework for understanding how oscillations in kinase activities drive cell cycle progression in a unidirectional and irreversible manner. Over the past thirty years, a central question has been whether cell cycle control relies primarily on the quantitative level of Cdk1 activity or whether distinct qualitative functions of cyclin-Cdk1 complexes ensure the correct ordering of events. Addressing this question required new genetic and biochemical tools capable of controlling Cdk1 activity with high temporal resolution and specificity. A turning point came in 2000 with the development of the analogue-sensitive Cdk1 allele by the Shokat laboratory. This approach replaced classical temperature-sensitive alleles with a version of Cdk1 that can be selectively inhibited by bulky ATP analogues. Beyond specific inhibition, the system was soon adapted to directly label and identify Cdk1 substrates, coupling chemical genetics with the emerging power of mass spectrometry. This review outlines the conceptual frameworks of quantitative and qualitative models of Cdk1 control. It also highlights how these ideas have been experimentally dissected, tracing the development of the Cdk1 Shokat system and advances from synthetic biology and phosphoproteomics in decoding phosphorylation logic, and how these concepts apply to meiosis. These studies draw primarily on budding yeast and fission yeast which have a single Cdk, making them convenient models for studying core principles of cell cycle regulation. Key insights from vertebrates are also integrated to illustrate principles that extend to other eukaryotes.

Abstract. This paper reports on the instrumental design of a new cryogenically cooled middle-atmosphere water vapor radiometer developed by the University of Bern at the Institute of Applied Physics (IAP). Here, we present the instrument design for the breadboard stage. The key innovation of this new instrument is its cryogenically cooled front-end, which is designed to keep its size compact, reducing the required cooling power compared to existing cryogenically cooled radiometers. The advantage compared to uncooled instruments is the reduced receiver noise temperature and the possibility to extend the altitude coverage of the retrieval of water vapor profiles to even higher altitudes with better temporal resolution. The new radiometer is part of the Swiss H2O Hub and is supposed to replace the existing 22 GHz radiometer, MIAWARA, which has been in operation at the University of Bern for over 20 years at the Zimmerwald observatory. The calibration of the new instrument includes tipping curve calibration to determine tropospheric opacity, using the sky as a cold target. An ambient load serves as the hot target for the Hot-Cold calibration, and we also explore the possibility of using frequency-switch calibration to reduce the impact of non-linearities in the receiver chain, allowing for a higher integration time of the line observation compared to other calibration techniques. The combination of a cryogenic front-end and frequency switch microwave radiometers at 22 GHz has not been previously implemented in a single instrument. In addition to detailing the instrumental design and calibration techniques, we present preliminary results of atmospheric spectra obtained with the breadboard setup.

Although large field-of-view two-photon microscopy (LF-TPM) is a powerful neuroimaging tool, low signal-to-noise (SNR) poses challenges for high-speed imaging. Increasing the average laser power improves the SNR, but the thermal effect of high laser power on the cortex is not well studied. Further, capturing the curvature of the cortex requires creating an image stack, which also reduces the temporal resolution. Solving these problems would enable mesoscopic mapping with LF-TPM. We aim to study the temperature dynamic of the mouse cortex as a function of the field of view and the average laser power and demonstrate the feasibility of relatively high illumination power. Combining the higher illumination intensity and the curved scanning, we aim to showcase the capability of the LF-TPM system in both stimulated and spontaneous mesoscopic mapping. We developed a combined thermal imaging and LF-TPM system to measure the spatial-temporal dynamics of heat during TPM imaging. We used an electrically tunable lens to vary the focusing depth and track the cortical curvature as a function of the medial distance. We then used the optimized system to image functional activations and resting-state functional connectivity patterns across both hemispheres. The steady-state maximum cortical temperature declines as the FOV increases. For a FOV and 388mW average laser power on the cortical surface, the cortical temperature stayed below 40°C. Using 360mW average power and a curved imaging surface, the custom LF-TPM system can map bilateral hind paw stimulation responses with a single trial and spontaneous bilateral functional connectivity. Concurrent thermal and LF-TPM imaging enables a quantitative optimization of laser power and SNR in LF-TPM systems. We demonstrated the feasibility of bilateral brain mapping using LF-TPM. These findings will help expand the utility of LF-TPMs for mesoscopic brain mapping applications.

Abstract This work presents an experimental analysis of the powder flow from a continuous coaxial nozzle for Laser Metal Deposition (LMD), demonstrating the ability to identify the transients and high-speed process flow dynamics. High-speed video tracking of individual particles enabled detailed analysis of size, spatial distribution, and velocities, revealing significant flowrate variations over time of up to $$20\%$$ , which may compromise deposition quality. These oscillations emerge from the large number of interactions among particles, carrier gas, and nozzle walls, reflecting complex, self-excited flow dynamics not captured by time-averaged measurements. The standoff distance, defined as the optimal distance between the nozzle and the workpiece, was determined with unprecedented temporal resolution. In the most representative case, the average standoff distance was found to be approximately $$16.0~\textrm{mm}$$ , with oscillations over time of up to $$19\%$$ , due to variations in both particle trajectories and quantity over time. The particle size distribution was consistent with the manufacturer’s specifications, a good indication of the method’s accuracy, and an error estimation is performed to determine the expected precision of the measurements. A key aspect of this work, and its main contribution, is the development of a workflow capable of tracking individual particles to determine the instantaneous powder mass flowrate, providing a reliable approach to monitor and optimize powder delivery in the LMD process.

The liquid-solid interface plays a fundamental role in a wide range of phenomena, including reaction kinetics, charge transfer, and fluid behavior. However, the underlying physicochemical mechanisms governing these interfacial interactions remain a topic of ongoing debate. Recently, the concept of the triboelectric nanogenerator probe (TENG probe) has been introduced to investigate the charge transfer at liquid-solid interfaces by recording the triboelectrification of liquid droplets sliding on insulating surfaces with both spatial and temporal resolution. Variations in interfacial properties directly influence charge transfer dynamics, such as ion concentration, chemical composition, flow rate, and structure of electric double layer (EDL), making the TENG probe a powerful and sensitive tool for quantitative studying charge transfer at liquid-solid interfaces. This review summarizes the fundamental principles and key features of TENG probes and highlights their applications in liquid-solid charge transfer studies, in situ chemical analysis, fluid status monitoring, and sensing systems. The perceived challenges and opportunities that face this multidisciplinary research field are also outlined, with special attention on experimental efforts linking chemical, physical, and mechanical factors in liquid-solid interfacial charge transfer dynamics.

Acinetobacter baumannii is a Gram-negative nosocomial pathogen that is notorious for its rapid development of antibiotic resistance. However, its ecology and evolution outside hospital settings remain poorly defined. Here, we demonstrate that the natural lifestyle of A. baumannii includes soil-dwelling and airborne dissemination, which helps explaining its adaptability and tolerance to desiccation, radiation and antibiotics, and thus its predisposition to establish within hospitals. Starting from white stork nestlings previously discovered as a reservoir, we studied food chains and associated environments and identified soil and decaying plants as habitats. We demonstrate that sterilized plant material is rapidly colonized by airborne A. baumannii. A set of 401 genomes were sequenced and compared to publicly available genomes, revealing numerous links between wildlife isolates and hospital strains, and disclosing intercontinental dispersal. Our pan-genome estimate of the species (~51,000 gene families) more than doubles that of previous studies. Our data further suggest massive radiation of the species early after its emergence, possibly fostered by human activity since the Neolithic. Now, it is possible to study the ecology and evolution of A. baumannii in nature at an unprecedented temporal and spatial resolution and to elucidate the adaptive evolution of environmental bacteria towards multidrug-resistant opportunistic pathogens.

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1-13C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker's yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1-13C]pyruvate into oxidative decarboxylation products CO2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1-13C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.