Monitoring Alzheimer's disease via ultraweak photon emission.

In an innovative experiment, we detected ultraweak photon emission (UPE) from the hippocampus of male rat brains and found significant correlations between Alzheimer's disease (AD), memory decline, oxidative stress, and UPE intensity. These findings may open up novel methods for screening, detecting, diagnosing, and classifying neurodegenerative diseases, particularly AD. The study suggests that UPE from the brain's neural tissue can serve as a valuable indicator. It also proposes the development of a minimally invasive brain-computer interface (BCI) photonic chip for monitoring and diagnosing AD, offering high spatiotemporal resolution of brain activity. The study used a rodent model of sporadic AD, demonstrating that STZ-induced sAD resulted in increased hippocampal UPE, which was associated with oxidative stress. Treatment with donepezil reduced UPE and improved oxidative stress. These findings support the potential utility of UPE as a screening and diagnostic tool for AD and other neurodegenerative diseases.

Effects of optogenetic and visual stimulation on gamma activity in the visual cortex.

Studying brain functions and activity during gamma oscillations can be a challenge because it requires careful planning to create the necessary conditions for a controlled experiment. Such an experiment consists of placing the brain into a gamma state and investigating cognitive processing with a careful design. Cortical oscillations in the gamma frequency range (30-80 Hz) play an essential role in a variety of cognitive processes, including visual processing and cognition. The present study aims to investigate the effects of a visual stimulus on the primary visual cortex under gamma oscillations. Specifically, we sought to explore the behavior of gamma oscillations triggered by optogenetic stimulation in the II and IV layers of the visual cortex, both with and without concurrent visual stimulation. Our results show that optogenetic stimulation increases the power of gamma oscillation in both layers of the visual cortex. However, the combined stimuli resulted in a reduction of gamma power in layer II and an increase and reinforcement in gamma power in layer IV. Modelling the results with the Wilson-Cowan model suggests changes in the input of the excitatory population due to the combined stimuli. In addition, our analysis of the data using the Lempel-Ziv complexity method supports our interpretations from the modeling. Thus, our results suggest that optogenetic stimulation enhances low gamma power in both layers of the visual cortex, while simultaneous visual stimulation has differing effects on the two layers, reducing gamma power in layer II and increasing it in layer IV.

Effect of methamphetamine on ultraweak photon emission and level of reactive oxygen species in male rat brain.

All living cells, including neurons, generate ultra-weak photon emission (UPE) during biological activity, and in particular, in the brain, it has been shown that UPE is correlated with neuronal activity and associated metabolic processes. Various intracellular factors, as well as external factors, can reduce or increase the intensity of UPE. In this study, we have used Methamphetamine (METH) as one potentially effective external factor, which is a substance that has the property of stimulating the central nervous system. METH can impair mitochondrial function by causing toxicity via various pathways, including an increase in the number of mitochondria, hyperthermia, the increased metabolic activity of the brain, and the production of glutamate and excess calcium. In addition to mitochondrial dysfunction, METH alters cellular homeostasis, leading to cell damage and the production of excess ROS. The aim of this study is to measure and compare the UPE intensity and reactive oxygen species (ROS) levels of the prefrontal, motor, and visual cortex before and after METH administration. Twenty male rats were randomly assigned to two groups, the control, and METH groups. In the control group, 2 h after injection of normal saline and without any intervention, and in the experimental group 2 h after IP injection of 20 mg/kg METH, sections were prepared from three areas: prefrontal, motor, and V1-V2 cortex, which were used to evaluate the emission of UPE using a photomultiplier tube (PMT) device and to evaluate the amount of ROS. The results showed that the amount of ROS and UPE in the experimental group in all three areas significantly increased compared to the control group. So, METH increases UPE and ROS in the prefrontal, motor, and visual regions, and there is a direct relationship between UPE intensity and ROS production. Therefore, UPE may be used as a dynamic reading tool to monitor oxidative metabolism in physiological processes related to ROS and METH research. Also, the results of this experiment may create a new avenue to test the hypothesis that the excess in UPE generation may lead to the phenomenon of phosphene and visual hallucinations.

Quantum face recognition protocol with ghost imaging.

Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, with numerous applications in security, access control, and law enforcement, among many others. Pattern recognition with classical algorithms requires significant computational resources, especially when dealing with high-resolution images in an extensive database. Quantum algorithms have been shown to improve the efficiency and speed of many computational tasks, and as such, they could also potentially improve the complexity of the face recognition process. Here, we propose a quantum machine learning algorithm for pattern recognition based on quantum principal component analysis, and quantum independent component analysis. A novel quantum algorithm for finding dissimilarity in the faces based on the computation of trace and determinant of a matrix (image) is also proposed. The overall complexity of our pattern recognition algorithm is [Formula: see text]-N is the image dimension. As an input to these pattern recognition algorithms, we consider experimental images obtained from quantum imaging techniques with correlated photons, e.g. "interaction-free" imaging or "ghost" imaging. Interfacing these imaging techniques with our quantum pattern recognition processor provides input images that possess a better signal-to-noise ratio, lower exposures, and higher resolution, thus speeding up the machine learning process further. Our fully quantum pattern recognition system with quantum algorithm and quantum inputs promises a much-improved image acquisition and identification system with potential applications extending beyond face recognition, e.g., in medical imaging for diagnosing sensitive tissues or biology for protein identification.

An optimizing method for performance and resource utilization in quantum machine learning circuits.

Quantum computing is a new and advanced topic that refers to calculations based on the principles of quantum mechanics. It makes certain kinds of problems be solved easier compared to classical computers. This advantage of quantum computing can be used to implement many existing problems in different fields incredibly effectively. One important field that quantum computing has shown great results in machine learning. Until now, many different quantum algorithms have been presented to perform different machine learning approaches. In some special cases, the execution time of these quantum algorithms will be reduced exponentially compared to the classical ones. But at the same time, with increasing data volume and computation time, taking care of systems to prevent unwanted interactions with the environment can be a daunting task and since these algorithms work on machine learning problems, which usually includes big data, their implementation is very costly in terms of quantum resources. Here, in this paper, we have proposed an approach to reduce the cost of quantum circuits and to optimize quantum machine learning circuits in particular. To reduce the number of resources used, in this paper an approach including different optimization algorithms is considered. Our approach is used to optimize quantum machine learning algorithms for big data. In this case, the optimized circuits run quantum machine learning algorithms in less time than the original ones and by preserving the original functionality. Our approach improves the number of quantum gates by 10.7% and 14.9% in different circuits respectively. This is the amount of reduction for one iteration of a given sub-circuit U in the main circuit. For cases where this sub-circuit is repeated more times in the main circuit, the optimization rate is increased. Therefore, by applying the proposed method to circuits with big data, both cost and performance are improved.

Are Brain-Computer Interfaces Feasible With Integrated Photonic Chips?

The present paper examines the viability of a radically novel idea for brain-computer interface (BCI), which could lead to novel technological, experimental, and clinical applications. BCIs are computer-based systems that enable either one-way or two-way communication between a living brain and an external machine. BCIs read-out brain signals and transduce them into task commands, which are performed by a machine. In closed loop, the machine can stimulate the brain with appropriate signals. In recent years, it has been shown that there is some ultraweak light emission from neurons within or close to the visible and near-infrared parts of the optical spectrum. Such ultraweak photon emission (UPE) reflects the cellular (and body) oxidative status, and compelling pieces of evidence are beginning to emerge that UPE may well play an informational role in neuronal functions. In fact, several experiments point to a direct correlation between UPE intensity and neural activity, oxidative reactions, EEG activity, cerebral blood flow, cerebral energy metabolism, and release of glutamate. Therefore, we propose a novel skull implant BCI that uses UPE. We suggest that a photonic integrated chip installed on the interior surface of the skull may enable a new form of extraction of the relevant features from the UPE signals. In the current technology landscape, photonic technologies are advancing rapidly and poised to overtake many electrical technologies, due to their unique advantages, such as miniaturization, high speed, low thermal effects, and large integration capacity that allow for high yield, volume manufacturing, and lower cost. For our proposed BCI, we are making some very major conjectures, which need to be experimentally verified, and therefore we discuss the controversial parts, feasibility of technology and limitations, and potential impact of this envisaged technology if successfully implemented in the future.

Toxicity assessment of total petroleum hydrocarbons in aquatic environments using the bioluminescent bacterium Aliivibrio fischeri.

Toxicity monitoring of environmental pollutants especially petroleum hydrocarbons as priority pollutants is an important environmental issue. This study addresses a rapid, sensitive and cost effective method for the detection of total petroleum hydrocarbons (TPHs) using Aliivibrio fischeri bioluminescence inhibition bioassay. At the first step, the optimum conditions including time, pH and temperature for growth of A. fischeri were determined. Then, two methods were used to evaluate the toxicity of petroleum compounds. In the first method, short-term (15 min) and long-term (16 h) toxicity assays were performed. In the second method luminescence kinetics of A. fischeri was investigated during 24 h. The results demonstrated the most appropriate time for the bacterial growth occurred 16 h after inoculation and optimum temperature and pH were found 25 °C and 7, respectively. Short-term and long-term toxicity did not indicate any toxicity for various concentrations of TPHs (30, 50, 110, 160, 220 mg/L). Considering the luminescence kinetics of A. fischeri the long-term assay was introduced as 6 h. The half maximal effective concentration (EC50) was achieved 1.77 mg/L of TPHs. It is concluded that the luminescence kinetics of A. fischeri can be a valuable approach for assessing toxicity of TPHs in aquatic environments.

An Experimental Investigation of Ultraweak Photon Emission from Adult Murine Neural Stem Cells.

Neurons like other living cells may have ultraweak photon emission (UPE) during neuronal activity. This study is aimed to evaluate UPE from neural stem cells (NSC) during their serial passaging and differentiation. We also investigate whether the addition of silver nanoparticles (AgNPs) or enhancement of UPE (by AgNPs or mirror) affect the differentiation of NSC. In our method, neural stem and progenitor cells of subventricular zone (SVZ) are isolated and expanded using the neurosphere assay. The obtained dissociated cells allocated and cultivated into three groups: groups: I: cell (control), II: cell + mirror, and III: cell + AgNPs. After seven days, the primary neurospheres were counted and their mean number was obtained. Serial passages continuous up to sixth passages in the control group. Differentiation capacity of the resulting neurospheres were evaluated in vitro by immunocytochemistry techniques. Measurement of UPE was carried out by photomultiplier tube (PMT) in the following steps: at the end of primary culture, six serial cell passages of the control group, before and after of the differentiation for 5 minutes. The results show that neither mirror nor AgNPs affect on the neurosphere number. The UPE of the NSC in the sixth subculturing passage was significantly higher than in the primary passage (P < 0.05). AgNPs significantly increased the UPE of the NSC compared to the control group before and after the differentiation (P < 0.05). Also, the treatment with AgNPs increased 44% neuronal differentiation of the harvested NSCs. UPE of NSC after the differentiation was significantly lower than that before the differentiation in each groups, which is in appropriate to the cell numbers (P < 0.0001). The mirror did not significantly increase UPE, neither before nor after the differentiation of NSC. As a conclusion, NSC have UPE-properties and the intensity is increased by serial passaging that are significant in the sixth passage. The AgNPs increases the UPE intensity of NSC that pushes more differentiation of NSC to the neurons. The mirror was not effective in enhancement of UPE. As a result, UPE measurement may be suitable for assessing and studying the effects of nanoparticles in living cells and neurons.

Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network.

Background: Convolutional neural networks (CNN) have enabled significant progress in speech recognition, image classification, automotive software engineering, and neuroscience. This impressive progress is largely due to a combination of algorithmic breakthroughs, computation resource improvements, and access to a large amount of data. Method: In this paper, we focus on the automated detection of autism spectrum disorder (ASD) using CNN with a brain imaging dataset. We detected ASD patients using most common resting-state functional magnetic resonance imaging (fMRI) data from a multi-site dataset named the Autism Brain Imaging Exchange (ABIDE). The proposed approach was able to classify ASD and control subjects based on the patterns of functional connectivity. Results: Our experimental outcomes indicate that the proposed model is able to detect ASD correctly with an accuracy of 70.22% using the ABIDE I dataset and the CC400 functional parcellation atlas of the brain. Also, the CNN model developed used fewer parameters than the state-of-art techniques and is hence computationally less intensive. Our developed model is ready to be tested with more data and can be used to prescreen ASD patients.

Excitation energy transport with noise and disorder in a model of the selectivity filter of an ion channel.

A selectivity filter is a gate in ion channels that is responsible for the selection and fast conduction of particular ions across the membrane (with high throughput rates of 108 ions s-1 and a high 1:104 discrimination rate between ions). It is made of four strands as the backbone, and each strand is composed of sequences of five amino acids connected by peptide units H-N-C=O in which the main molecules in the backbone that interact with ions in the filter are carbonyl (C=O) groups that mimic the transient interactions of ion with binding sites during ion conduction. It has been suggested that quantum coherence and possible emergence of resonances in the backbone carbonyl groups may play a role in mediating ion conduction and selectivity in the filter. Here, we investigate the influence of noise and disorder on the efficiency of excitation energy transfer (EET) in a linear harmonic chain of N = 5 sites with dipole-dipole couplings as a simple model for one P-loop strand of the selectivity filter backbone in biological ion channels. We include noise and disorder inherent in real biological systems by including spatial disorder in the chain, and random noise within a weak coupling quantum master equation approach. Our results show that disorder in the backbone considerably reduces EET, but the addition of noise helps to recover high EET for a wide range of system parameters. Our analysis may help for better understanding of the coordination of ions in the filter as well as the fast and efficient functioning of the selectivity filters in ion channels.

Electromagnetic fields and optomechanics in cancer diagnostics and treatment.

In this paper, we discuss biological effects of electromagnetic (EM) fields in the context of cancer biology. In particular, we review the nanomechanical properties of microtubules (MTs), the latter being one of the most successful targets for cancer therapy. We propose an investigation on the coupling of electromagnetic radiation to mechanical vibrations of MTs as an important basis for biological and medical applications. In our opinion, optomechanical methods can accurately monitor and control the mechanical properties of isolated MTs in a liquid environment. Consequently, studying nanomechanical properties of MTs may give useful information for future applications to diagnostic and therapeutic technologies involving non-invasive externally applied physical fields. For example, electromagnetic fields or high intensity ultrasound can be used therapeutically avoiding harmful side effects of chemotherapeutic agents or classical radiation therapy.

Validity Examination of the Dissipative Quantum Model of Olfaction.

Despite some inconclusive experimental evidences for the vibrational model of olfaction, the validity of the model has not been examined yet and therefore it suffers from the lack of conclusive experimental support. Here, we generalize the model and propose a numerical analysis of the dissipative odorant-mediated inelastic electron tunneling mechanism of olfaction, to be used as a potential examination in experiments. Our analysis gives several predictions on the model such as efficiency of elastic and inelastic tunneling of electrons through odorants, sensitivity thresholds in terms of temperature and pressure, isotopic effect on sensitivity, and the chiral recognition for discrimination between the similar and different scents. Our predictions should yield new knowledge to design new experimental protocols for testing the validity of the model.

Phosphenes, retinal discrete dark noise, negative afterimages and retinogeniculate projections: A new explanatory framework based on endogenous ocular luminescence.

Cellular luminescence is the emission of photons by living cells due to various biophysical and biochemical processes, mostly associated with cellular metabolism. In this review paper we summarize today's understanding of four luminescence-dependent phenomena in the eye, i.e., phosphenes, retinal discrete dark noise, negative afterimages and the development of retinogeniculate projections in the brain. We review the phenomena above in the context of knowledge gained from experimental and theoretical works. Finally, we discuss this knowledge in terms of its physiological significance.

Quantum Interference and Selectivity through Biological Ion Channels.

The mechanism of selectivity in ion channels is still an open question in biology for more than half a century. Here, we suggest that quantum interference can be a solution to explain the selectivity mechanism in ion channels since interference happens between similar ions through the same size of ion channels. In this paper, we simulate two neighboring ion channels on a cell membrane with the famous double-slit experiment in physics to investigate whether there is any possibility of matter-wave interference of ions via movement through ion channels. Our obtained decoherence timescales indicate that the quantum states of ions can only survive for short times, i.e. ≈100 picoseconds in each channel and ≈17-53 picoseconds outside the channels, giving the result that the quantum interference of ions seems unlikely due to environmental decoherence. However, we discuss our results and raise few points, which increase the possibility of interference.

Possible role of biochemiluminescent photons for lysergic acid diethylamide (LSD)-induced phosphenes and visual hallucinations.

Today, there is an increased interest in research on lysergic acid diethylamide (LSD) because it may offer new opportunities in psychotherapy under controlled settings. The more we know about how a drug works in the brain, the more opportunities there will be to exploit it in medicine. Here, based on our previously published papers and investigations, we suggest that LSD-induced visual hallucinations/phosphenes may be due to the transient enhancement of bioluminescent photons in the early retinotopic visual system in blind as well as healthy people.

The Physical Mechanism for Retinal Discrete Dark Noise: Thermal Activation or Cellular Ultraweak Photon Emission?

For several decades the physical mechanism underlying discrete dark noise of photoreceptors in the eye has remained highly controversial and poorly understood. It is known that the Arrhenius equation, which is based on the Boltzmann distribution for thermal activation, can model only a part (e.g. half of the activation energy) of the retinal dark noise experimentally observed for vertebrate rod and cone pigments. Using the Hinshelwood distribution instead of the Boltzmann distribution in the Arrhenius equation has been proposed as a solution to the problem. Here, we show that the using the Hinshelwood distribution does not solve the problem completely. As the discrete components of noise are indistinguishable in shape and duration from those produced by real photon induced photo-isomerization, the retinal discrete dark noise is most likely due to 'internal photons' inside cells and not due to thermal activation of visual pigments. Indeed, all living cells exhibit spontaneous ultraweak photon emission (UPE), mainly in the optical wavelength range, i.e., 350-700 nm. We show here that the retinal discrete dark noise has a similar rate as UPE and therefore dark noise is most likely due to spontaneous cellular UPE and not due to thermal activation.

Phosphene perception is due to the ultra-weak photon emission produced in various parts of the visual system: glutamate in the focus.

Phosphenes are experienced sensations of light, when there is no light causing them. The physiological processes underlying this phenomenon are still not well understood. Previously, we proposed a novel biopsychophysical approach concerning the cause of phosphenes based on the assumption that cellular endogenous ultra-weak photon emission (UPE) is the biophysical cause leading to the sensation of phosphenes. Briefly summarized, the visual sensation of light (phosphenes) is likely to be due to the inherent perception of UPE of cells in the visual system. If the intensity of spontaneous or induced photon emission of cells in the visual system exceeds a distinct threshold, it is hypothesized that it can become a conscious light sensation. Discussing several new and previous experiments, we point out that the UPE theory of phosphenes should be really considered as a scientifically appropriate and provable mechanism to explain the physiological basis of phosphenes. In the present paper, we also present our idea that some experiments may support that the cortical phosphene lights are due to the glutamate-related excess UPE in the occipital cortex.

Endogenous spontaneous ultraweak photon emission in the formation of eye-specific retinogeniculate projections before birth.

In 1963, it was suggested [Sperry, R.W. (1963). Chemoaffinity in the orderly growth of nerve fiber patterns and connections. Proc. Natl. Acad. Sci. USA 50, 703-710.] that molecular cues can direct the development of orderly connections between the eye and the brain (the "chemoaffinity hypothesis"). In the same year, the amazing degree of functional accuracy of the visual pathway in the absence of any external light/photon perception prior to birth [Wiesel, T.N and Hubel, D.H. (1963). Single-cell responses in striate cortex of kittens deprived of vision in one eye. J. Neurophysiol. 26, 1003-1017.] was discovered. These recognitions revealed that the wiring of the visual system relies on innate cues. However, how the eye-specific retinogeniculate pathway can be developed before birth without any visual experience is still an unresolved issue. In the present paper, we suggest that Müller cells (functioning as optical fibers), Müller cell cone (i.e. the inner half of the foveola that is created of an inverted cone-shaped zone of Müller cells), discrete retinal noise of rods, and intrinsically photosensitive retinal ganglion cells might have key functions by means of retinal spontaneous ultraweak photon emission in the development of eye-specific retinogeniculate pathways prior to birth.

Noise assisted excitation energy transfer in a linear model of a selectivity filter backbone strand.

In this paper, we investigate the effect of noise and disorder on the efficiency of excitation energy transfer (EET) in a N = 5 sites linear chain with 'static' dipole-dipole couplings. In fact, here, the disordered chain is a toy model for one strand of the selectivity filter backbone in ion channels. It has recently been discussed that the presence of quantum coherence in the selectivity filter is possible and can play a role in mediating ion-conduction and ion-selectivity in the selectivity filter. The question is 'how a quantum coherence can be effective in such structures while the environment of the channel is dephasing (i.e. noisy)?' Basically, we expect that the presence of the noise should have a destructive effect in the quantum transport. In fact, we show that such expectation is valid for ordered chains. However, our results indicate that introducing the dephasing in the disordered chains leads to the weakening of the localization effects, arising from the multiple back-scatterings due to the randomness, and then increases the efficiency of quantum energy transfer. Thus, the presence of noise is crucial for the enhancement of EET efficiency in disordered chains. We also show that the contribution of both classical and quantum mechanical effects are required to improve the speed of energy transfer along the chain. Our analysis may help for better understanding of fast and efficient functioning of the selectivity filters in ion channels.