Fisher information matrix for single molecules with stochastic trajectories

Tracking of objects in cellular environments has become a vital tool in molecular cell biology. A particularly important example is single molecule tracking which enables the study of the motion of a molecule in cellular environments and provides quantitative information on the behavior of individual molecules in cellular environments, which were not available before through bulk studies. Here, we consider a dynamical system where the motion of an object is modeled by stochastic differential equations (SDEs), and measurements are the detected photons emitted by the moving fluorescently labeled object, which occur at discrete time points, corresponding to the arrival times of a Poisson process, in contrast to uniform time points which have been commonly used in similar dynamical systems. The measurements are distributed according to optical diffraction theory, and therefore, they would be modeled by different distributions, e.g., a Born and Wolf profile for an out-of-focus molecule. For some special circumstances, Gaussian image models have been proposed. In this paper, we introduce a stochastic framework in which we calculate the maximum likelihood estimates of the biophysical parameters of the molecular interactions, e.g., diffusion and drift coefficients. More importantly, we develop a general framework to calculate the Cram\'er-Rao lower bound (CRLB), given by the inverse of the Fisher information matrix, for the estimation of unknown parameters and use it as a benchmark in the evaluation of the standard deviation of the estimates. There exists no established method, even for Gaussian measurements, to systematically calculate the CRLB for the general motion model that we consider in this paper. We apply the developed methodology to simulated data of a molecule with linear trajectories and show that the standard deviation of the estimates matches well with the square root of the CRLB

Sex differences, gonadal hormones and the fear extinction network: implications for anxiety disorders

Convergent data from rodents and human studies have led to the development of models describing the neural mechanisms of fear extinction. Key components of the now well-characterized fear extinction network include the amygdala, hippocampus, and medial prefrontal cortical regions. These models are fueling novel hypotheses that are currently being tested with much refined experimental tools to examine the interactions within this network. Lagging far behind, however, is the examination of sex differences in this network and how sex hormones influence the functional activity and reactivity of these brain regions in the context of fear inhibition. Indeed, there is a large body of literature suggesting that sex hormones, such as estrogen, do modulate neural plasticity within the fear extinction network, especially in the hippocampus

Mechanisms of estradiol in fear circuitry: implications for sex differences in psychopathology

Over the past two decades, substantial knowledge has been attained about the mechanisms underlying the acquisition and subsequent extinction of conditioned fear. Knowledge gained on the biological basis of Pavlovian conditioning has led to the general acceptance that fear extinction may be a useful model in understanding the underlying mechanisms in the pathophysiology of anxiety disorders and may also be a good model for current therapies treating these disorders. Lacking in the current knowledge is how men and women may or may not differ in the biology of fear and its extinction. It is also unclear how the neural correlates of fear extinction may mediate sex differences in the etiology, maintenance, and prevalence of psychiatric disorders. In this review, we begin by highlighting the epidemiological differences in incidence rate. We then discuss how estradiol (E2), a primary gonadal hormone, may modulate the mechanisms of fear extinction and mediate some of the sex differences observed in psychiatric disorders

The relationship between extravascular lung water and oxygenation in three patients with influenza A (H1N1)-induced respiratory failure

Zusammenfassung: Diese Fallsammlung berichtet über die Korrelation zwischen extravaskulärem Lungenwasser (EVLW) und dem arteriellen Sauerstoffpartialdruck/fraktionierten inspiratorischen Sauerstoffkonzentration (PaO2/FiO2) Quotienten bei drei Patienten mit schwerem Influenza A (H1N1)-induziertem Lungenversagen. Alle Patienten erlitten eine ausgeprägte Hypoxie (PaO2, 26-42 mmHg), mussten mit dem Biphasic Airway Pressure Mode (PEEP, 12-15 mmHg; FiO2, 0,8-1) mechanisch beatmet werden und wurden in 12 stündlichen Intervallen in die Bauchlage gedreht. Alle Patienten waren während 8-11 Tagen mit dem PICCO® System monitorisiert. Während der mechanischen Beatmung wurden ingesamt 62 simultane Bestimmungen des PaO2/FiO2 Quotienten und des EVLW durchgeführt. Es zeigte sich ein signifikanter Zusammenhang zwischen dem EVLW und dem PaO2/FiO2 Quotienten (Spearman-rho Korrelationskoeffizient, -0,852; p < 0,001). Bei allen Patienten war eine Abnahme des EVLW von einer Verbesserung der Oxygenation begleitet. Die Serumkonzentrationen der Laktatdehydrogenase waren bei allen Patienten erhöht und korrelierten signifikant mit dem EVLW während des Intensivaufenthaltes (Spearman-rho Korrelationskoeffizient, 0,786; p < 0,001). Zusammenfassend erscheint es, dass das EVLW bei Patienten mit schwerem H1N1-induziertem Lungenversagen erhöht ist und dabei eng mit Einschränkungen der Oxygenationsfunktion korrelier

Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models

With the advent of sophisticated artificial intelligence (AI) technologies, the proliferation of deepfakes and the spread of m/disinformation have emerged as formidable threats to the integrity of information ecosystems worldwide. This paper provides an overview of the current literature. Within the frontier AI's crucial application in developing defense mechanisms for detecting deepfakes, we highlight the mechanisms through which generative AI based on large models (LM-based GenAI) craft seemingly convincing yet fabricated contents. We explore the multifaceted implications of LM-based GenAI on society, politics, and individual privacy violations, underscoring the urgent need for robust defense strategies. To address these challenges, in this study, we introduce an integrated framework that combines advanced detection algorithms, cross-platform collaboration, and policy-driven initiatives to mitigate the risks associated with AI-Generated Content (AIGC). By leveraging multi-modal analysis, digital watermarking, and machine learning-based authentication techniques, we propose a defense mechanism adaptable to AI capabilities of ever-evolving nature. Furthermore, the paper advocates for a global consensus on the ethical usage of GenAI and implementing cyber-wellness educational programs to enhance public awareness and resilience against m/disinformation. Our findings suggest that a proactive and collaborative approach involving technological innovation and regulatory oversight is essential for safeguarding netizens while interacting with cyberspace against the insidious effects of deepfakes and GenAI-enabled m/disinformation campaigns.Comment: This paper appears in IEEE International Conference on Computer and Applications (ICCA) 202

Near-unity light-matter interaction in mid-infrared van der Waals nanocavities

Accessing mid-infrared radiation is of great importance for a range of applications, including thermal imaging, sensing, and radiative cooling. Here, we study light interaction with hexagonal boron nitride nanocavities and reveal strong and tunable resonances across its hyperbolic transition. In addition to conventional phonon-polariton excitations, we demonstrate that the high refractive index of hexagonal boron nitride outside the Reststrahlen band allows enhanced light-matter interactions in deep subwavelength (<{\lambda}/15) nanostructures across a broad 7-8 {\mu}m range. Near-unity absorption and high quality (Q>80) resonance interaction in the vicinity of the transverse optical phonon is observed. Our study provides new avenues to design highly efficient and ultracompact structures for controlling mid-infrared radiation and accessing strong light-matter interaction.Comment: 14 pages, 4 figure