Responses Of Complex Cells Research Articles

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

Detection of inflammatory biomarkers in saliva and urine: Potential in diagnosis, prevention, and treatment for chronic diseases.

Inflammation is a part of the complex biological response ofinflammatory cells to harmful stimuli, such aspathogens, irritants, or damaged cells. This inflammation has been linked to several chronic diseases including cancer, atherosclerosis, rheumatoid arthritis, and multiple sclerosis. Major biomarkers of inflammation include tumor necrosis factor, interleukins (IL)-1, IL-6, IL-8, chemokines, cyclooxygenase, 5-lipooxygenase, and C-reactive protein, all of which are regulated by the transcription factor nuclear factor-kappaB. Although examining inflammatory biomarkers in blood is a standard practice, its identification in saliva and/or urine is more convenient and non-invasive. In this review, we aim to (1) discuss the detection of these inflammatory biomarkers in urine and saliva; (2) advantages of using salivary and urinary inflammatory biomarkers over blood, while also weighing on the challenges and/or limitations of their use; (3) examine their role(s) in connection with diagnosis, prevention, treatment, and drug development for several chronic diseases with inflammatory consequences, including cancer; and (4) explore the use of innovative salivary and urine based biosensor strategies that may permit the testing of biomarkers quickly, reliably, and cost-effectively, in a decentralized setting.

Irradiation of primary human gliomas triggers dynamic and aggressive survival responses involving microvesicle signaling.

Malignant gliomas are heterogeneous populations of dynamically interacting cells. Genomic and transcriptional changes define this cellular hierarchy and allow certain tumor cells to co-opt metabolic machinery and adopt gene expression profiles that promote cellular reprogramming. Resultant expansion of privileged subpopulations can then rapidly adapt to microenvironmental stress that ultimately influence tumor response to therapeutic intervention. In this study, primary gliomas were subjected to acute or chronic irradiation and analyzed for changes in survival parameters, oxidative stress, gene expression, and cell invasion before and after treatment with secreted microvesicles isolated from irradiated and nonirradiated glioma cells. We found that primary gliomas exposed to ionizing radiation undergo metabolic changes that increase oxidative stress, alter gene expression, and affect the contents of and response to cellular secreted microvesicles. Radiation-induced changes were exacerbated under chronic as compared to acute irradiation paradigms and promoted cellular reprogramming through enhanced expression of key transcription factors and regulators involved in differentiation and pluripotency (SOX2, POU3F2, SALL2, OLIG2, NANOG, POU5F1v1, MSI1). Irradiation also affected changes in paracrine signaling mediated by cellular secreted microvesicles that significantly altered target cell phenotype. Primary gliomas treated with microvesicles exhibited increased radioresistance and treatment with microvesicles from chronically irradiated gliomas promoted invasion via induction of increased matrix metalloproteinase II activity. Together, our data describe a complex radiation response of primary glioma cells involving metabolic and transcriptional changes that alter radiation sensitivity and induce invasive behavior. These important changes can contribute to tumor growth and recurrence, and confound interventions designed to forestall disease progression. Environ. Mol. Mutagen. 57:405-415, 2016. © 2015 Wiley Periodicals, Inc.

Perturbations of PIP3 signalling trigger a global remodelling of mRNA landscape and reveal a transcriptional feedback loop.

PIP3 is synthesized by the Class I PI3Ks and regulates complex cell responses, such as growth and migration. Signals that drive long-term reshaping of cell phenotypes are difficult to resolve because of complex feedback networks that operate over extended times. PIP3-dependent modulation of mRNA accumulation is clearly important in this process but is poorly understood. We have quantified the genome-wide mRNA-landscape of non-transformed, breast epithelium-derived MCF10a cells and its response to acute regulation by EGF, in the presence or absence of a PI3Kα inhibitor, compare it to chronic activation of PI3K signalling by cancer-relevant mutations (isogenic cells expressing an oncomutant PI3Kα allele or lacking the PIP3-phosphatase/tumour-suppressor, PTEN). Our results show that whilst many mRNAs are changed by long-term genetic perturbation of PIP3 signalling (‘butterfly effect’), a much smaller number do so in a coherent fashion with the different PIP3 perturbations. This suggests a subset of more directly regulated mRNAs. We show that mRNAs respond differently to given aspects of PIP3 regulation. Some PIP3-sensitive mRNAs encode PI3K pathway components, thus suggesting a transcriptional feedback loop. We identify the transcription factor binding motifs SRF and PRDM1 as important regulators of PIP3-sensitive mRNAs involved in cell movement.

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model.

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas.

Equation of motion and general solution for the one-dimensional complex cell response in the signal-tuned approach.

A signal-tuned approach has been recently introduced for modeling stimulus-dependent cortical receptive fields. The approach is based on signal-tuned Gabor functions, which are Gaussian-modulated sinusoids whose parameters are obtained from a "tuning" signal. Given a stimulus to a cell, it is taken as the tuning signal for the Gabor function modeling the cell's receptive field, and the inner product of the stimulus and the stimulus-dependent field produces the cell's response. Here, we derive and solve the equation of motion for the signal-tuned complex cell response r(x,τ), where x and τ are receptive-field parameters: its center, and the delay with which it adapts to a change in input. The motion equation can be mapped onto the Schrödinger equation for a system with time-dependent imaginary mass and time-dependent complex potential, and yields a plane-wave solution and an Airy-packet solution. The plane-wave solution replicates responses previously obtained for temporally modulated and translating signals, and yields responses which seem compatible with apparent-motion effects, when the stimulus is a pair of alternating pulses. The Airy-packet solution can lead to long-range propagating responses.

The chronic challenge-new vistas on long-term multisite contacts to the central nervous system.

The chronic challenge-new vistas on long-term multisite contacts to the central nervous system.

Kinetics effects and modeling of mRNA turnover.

Broader comprehension of gene expression regulatory mechanisms can be gained from a global analysis of how transcription and degradation are coordinated to orchestrate complex cell responses. The role of messenger RNA (mRNA) turnover modulation in gene expression levels has become increasingly recognized. From such perspective, in this review we briefly illustrate how a simple but effective mathematical model of mRNA turnover and some experimental findings, may together shed light on the molecular mechanisms underpinning the major role of mRNA decay rates in shaping the kinetics of gene activation and repression.

BIMP: A real-time biological model of multi-scale keypoint detection in V1

We present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation.

Primate area V1: largest response gain for receptive fields in the straight-ahead direction.

Although neuronal responses in behaving monkeys are typically studied while the monkey fixates straight ahead, it is known that eye position modulates responses of visual neurons. The modulation has been found to enhance neuronal responses when the receptive field is placed in the straight-ahead position for neurons receiving input from the peripheral but not the central retina. We studied the effect of eye position on the responses of V1 complex cells receiving input from the central retina (1.1-5.7° eccentricity) while minimizing the effect of fixational eye movements. Contrast response functions were obtained separately with drifting light and dark bars. Data were fit with the Naka-Rushton equation: r(c)=Rmax×c/(c+c50)+s, where r(c) is mean spike rate at contrast c, Rmax is the maximum response, c50 is the contrast that elicits half of Rmax, and s is the spontaneous activity. Contrast sensitivity as measured by c50 was not affected by eye position. For dark bars, there was a statistically significant decline in the normalized Rmax with increasing deviation from straight ahead. Data for bright bars showed a similar trend with a less rapid decline. Our results indicate that neurons representing the central retina show a bias for the straight-ahead position resulting from modulation of the response gain without an accompanying modulation of contrast sensitivity. The modulation is especially obvious for dark stimuli, which might be useful for directing attention to hazardous situations such as dark holes or shadows concealing important objects (Supplement 1: Video Abstract, Supplemental digital content 1, http://links.lww.com/WNR/A295).

Complex cells decrease errors for the Müller-Lyer illusion in a model of the visual ventral stream.

To improve robustness in object recognition, many artificial visual systems imitate the way in which the human visual cortex encodes object information as a hierarchical set of features. These systems are usually evaluated in terms of their ability to accurately categorize well-defined, unambiguous objects and scenes. In the real world, however, not all objects and scenes are presented clearly, with well-defined labels and interpretations. Visual illusions demonstrate a disparity between perception and objective reality, allowing psychophysicists to methodically manipulate stimuli and study our interpretation of the environment. One prominent effect, the Müller-Lyer illusion, is demonstrated when the perceived length of a line is contracted (or expanded) by the addition of arrowheads (or arrow-tails) to its ends. HMAX, a benchmark object recognition system, consistently produces a bias when classifying Müller-Lyer images. HMAX is a hierarchical, artificial neural network that imitates the “simple” and “complex” cell layers found in the visual ventral stream. In this study, we perform two experiments to explore the Müller-Lyer illusion in HMAX, asking: (1) How do simple vs. complex cell operations within HMAX affect illusory bias and precision? (2) How does varying the position of the figures in the input image affect classification using HMAX? In our first experiment, we assessed classification after traversing each layer of HMAX and found that in general, kernel operations performed by simple cells increase bias and uncertainty while max-pooling operations executed by complex cells decrease bias and uncertainty. In our second experiment, we increased variation in the positions of figures in the input images that reduced bias and uncertainty in HMAX. Our findings suggest that the Müller-Lyer illusion is exacerbated by the vulnerability of simple cell operations to positional fluctuations, but ameliorated by the robustness of complex cell responses to such variance.

Antioedematous and Analgesic Properties of Fertile Fronds of Drynaria quercifolia

Inflammation is a complex biological response of tissue cells to harmful stimuli including trauma, tissue necrosis, and infections which plays a key role in the pathophysiology of many deadly diseases. In ethnomedicine Drynaria quercifolia fronds are used to treat inflammation as poultice on swellings and as antibacterial, hepatoprotective, and antipyretic agent. Herein, we have evaluated the antioedematous, antiproliferative, and analgesic properties of the ethanolic extract of fertile fronds of D. quercifolia (FF) by standard procedures. Oral administration of FF produced significant inhibition of carrageenan and histamine induced paw oedema in Wistar rats. FF significantly reduced both wet weight and dry weight of granuloma tissue which shows the inhibitory effect on exudative and proliferative phases of inflammation. FF significantly attenuated acute and delayed phases of formalin induced pain, acetic acid-induced writhing, capsaicin-induced nociception, and hot plate test in mice. Phytochemical analysis revealed the presence of coumarins, flavonoids, glycosides, phenolics, saponins, steroids, tannins, and terpenoids. Total phenolic content was 186 mg/g equivalent of gallic acid. The HPLC estimation showed flavanone glycoside naringin (1.2%) and its aglycone naringenin (0.02%). The presence of potent anti-inflammatory and analgesic principles in FF and their synergistic action may be the reason for the proposed therapeutic effects.

Determining Omics spatiotemporal dimensions using exciting new nanoscopy techniques to assess complex cell responses to DNA damage: part B--structuromics.

Recent groundbreaking developments in Omics and bioinformatics have generated new hope for overcoming the complexity and variability of (radio)biological systems while simultaneously shedding more light on fundamental radiobiological questions that have remained unanswered for decades. In the era of Omics, our knowledge of how genes and dozens of proteins interact in the frame of complex signaling and repair pathways (or, rather, networks) to preserve the integrity of the genome has been rapidly expanding. Nevertheless, these functional networks must be observed with strong correspondence to the cell nucleus, which is the main target of ionizing radiation. Information regarding these intricate processes cannot be achieved using high-throughput Omics approaches alone; it requires sophisticated structural probing and imaging. In the first part of this review, the article "Giving Omics Spatiotemporal Dimensions Using Exciting New Nanoscopy Techniques to Assess Complex Cell Responses to DNA Damage: Part A--Radiomics," we showed the development of different Omics solutions and how they are contributing to a better understanding of cellular radiation response. In this Part B we show how high-resolution confocal microscopy as well as novel approaches of molecular localization nanoscopy fill the gaps to successfully place Omics data in the context of space and time. The dynamics of double-strand breaks during repair processes and chromosomal rearrangements at the microscale correlated to aberration induction are explained. For the first time we visualize pan-nuclear nucleosomal rearrangements and clustering at the nanoscale during repair processes. Finally, we introduce a novel method of specific chromatin nanotargeting based on a computer database search of uniquely binding oligonucleotide combinations (COMBO-FISH). With these challenging techniques on hand, we speculate future perspectives that may combine specific COMBO-FISH nanoprobing and structural nanoscopy to observe structure-function correlations in living cells in real-time. Thus, the Omics networks obtained from function analyses may be enriched by real-time visualization of Structuromics.

Determining Omics spatiotemporal dimensions using exciting new nanoscopy techniques to assess complex cell responses to DNA damage: part A--radiomics.

Recent ground-breaking developments in Omics have generated new hope for overcoming the complexity and variability of biological systems while simultaneously shedding more light on fundamental radiobiological questions that have remained unanswered for decades. In the era of Omics, our knowledge of how genes and proteins interact in the frame of complex networks to preserve genome integrity has been rapidly expanding. Nevertheless, these functional networks must be observed with strong correspondence to the cell nucleus, which is the main target of ionizing radiation. Nuclear architecture and nuclear processes, including DNA damage responses, are precisely organized in space and time. Information regarding these intricate processes cannot be achieved using high-throughput Omics approaches alone, but requires sophisticated structural probing and imaging. Based on the results obtained from studying the relationship between higher-order chromatin structure, DNA double-strand break induction and repair, and the formation of chromosomal translocations, we show the development of Omics solutions especially for radiation research (radiomics) (discussed in this article) and how confocal microscopy as well as novel approaches of molecular localization nanoscopy fill the gaps to successfully place the Omics data in the context of space and time (discussed in our other article in this issue, "Determining Omics Spatiotemporal Dimensions Using Exciting New Nanoscopy Techniques to Assess Complex Cell Responses to DNA Damage: Part B--Structuromics"). Finally, we introduce a novel method of specific chromatin nanotargeting and speculate future perspectives, which may combine nanoprobing and structural nanoscopy to observe structure-function correlations in living cells in real time. Thus, the Omics networks obtained from function analyses may be enriched by real-time visualization of Structuromics.

Giving OMICS spatiotemporal dimensions using exciting new nanoscopy techniques to assess complex cell responses to DNA damage – PART B (Structuromics)

Giving OMICS spatiotemporal dimensions using exciting new nanoscopy techniques to assess complex cell responses to DNA damage – PART B (Structuromics)

Stereoscopic Depth Perception Using a Model Based on the Primary Visual Cortex

This work describes an approach inspired by the primary visual cortex using the stimulus response of the receptive field profiles of binocular cells for disparity computation. Using the energy model based on the mechanism of log-Gabor filters for disparity encodings, we propose a suitable model to consistently represent the complex cells by computing the wide bandwidths of the cortical cells. This way, the model ensures the general neurophysiological findings in the visual cortex (V1), emphasizing the physical disparities and providing a simple selection method for the complex cell response. The results suggest that our proposed approach can achieve better results than a hybrid model with phase-shift and position-shift using position disparity alone.

Epigenetic deregulation of the anaplastic lymphoma kinase gene modulates mesenchymal characteristics of oral squamous cell carcinomas

DNA hypermethylation of promoter CpG islands is associated with epigenetic silencing of tumor suppressor genes in oral squamous cell carcinomas (OSCCs). We used a methyl-CpG-binding domain protein capture method coupled with next-generation sequencing (MBDCap-seq) to survey global DNA methylation patterns in OSCCs with and without nodal metastasis and normal mucosa (total n = 58). Of 1462 differentially methylated CpG islands identified in OSCCs relative to normal controls, MBDCap-seq profiling uncovered 359 loci linked to lymph node metastasis. Interactive network analysis revealed a subset of these loci (n = 23), including the anaplastic lymphoma kinase (ALK) gene, are potential regulators and effectors of invasiveness and metastatic progression. Promoter methylation of ALK was preferentially observed in OSCCs without node metastasis, whereas relatively lower methylation levels were present in metastatic tumors, implicating an active state of ALK transcription in the latter group. The OSCC cell line, SCC4, displayed reduced ALK expression that corresponded to extensive promoter CpG island methylation. SCC4 treatment with demethylating agents induced ALK expression and increased invasion and migration characteristics. Inhibition of ALK activity in OSCC cells with high ALK expression (CAL27, HSC3 and SCC25), decreased cell growth and resulted in changes in invasive potential and mesenchymal marker expression that were cell-line dependent. Although ALK is susceptible to epigenetic silencing during oral tumorigenesis, overwriting this default state may be necessary for modulating invasive processes involved in nodal metastases. Given the complex response of OSCC cells to ALK inhibition, future studies are required to assess the feasibility of targeting ALK to treat invasive OSCCs.

Pulp Responses After CO2Laser Irradiation of Rat Dentin

The purpose of this study was to investigate pulp responses after CO(2) laser irradiation of rat molars using reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemical methods. Many kinds of lasers have been used for the treatment of dentin hypersensitivity. However, the immunohistochemical details of the responses of dentin-pulp complex cells after CO(2) laser irradiation through the dentin are still not clear. Adult male Sprague-Dawley rats were used in this study. A CO(2) laser (wavelength of 10.6 μm, 2 W in the super pulse mode, pulse 0.6 ms) and total laser energy of 4 J (density, 203.84 J/cm(2)) was used. The temperature change in the pulp was measured using a super fine sheath thermocouple. The temperature at the pulp side after the CO(2) laser irradiation increased 22.5°C. The expression of tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-1-α mRNAs was significantly higher at 6, 12, and 24 h after laser irradiation than in the control group (p<0.05). Histologically, a slight degeneration of the pulp tissue was observed immediately after the laser irradiation. Immunohistochemically, heat shock protein (HSP)-70-positive cells in the pulp horn were observed immediately after irradiation and cells positive for vascular endothelial growth factor (VEGF) in the subodontoblast layer were observed after 5 days. There were no nestin-positive cells immediately, but after 5 days nestin-positive cells were recognized in the deeper pulp cells. Immediately after irradiation, neurofilament protein (NFP)-positive nerve fibers were observed but they disappeared in the pulp horn after 5 days. These results suggest that 203.84 J/cm(2) CO(2) laser irradiation of pulp tissue through the dentin, such as is used in the clinic, induces inflammatory and pathological cytokine pathways to repair the damaged pulp tissue.

Inflammatory Cytokines of Cystic Fibrosis Airway Cells Are Reduced with Exposure to Interleukin-10

Interleukin (IL) 10 deficiency is notable in cystic fibrosis (CF) bronchoalveolar lavage (BAL) fluid. Similar airway neutrophils did not inhibit IL-8 production with IL-10 exposure. This study describes the complex response of CF airway immune cells to recombinant IL-10 exposure when compared to non-CF patients. BAL fluid was obtained from 11 CF and 3 non-CF pediatric subjects and immediately centrifuged at 1,000 rpm for 10 min. The cells were resuspended to a final concentration of 1×106 cells/mL. Aliquots of the cells were incubated with 0, 10, 100, and 1,000 ng/mL of recombinant human IL-10 for 24 h. Supernatants were obtained and enzyme-linked immunosorbent assay performed for levels of IL-8, IL-1β, and tumor necrosis factor alpha (TNFα) cytokines. CF patients (n=11) showed statistically significant percent inhibition of IL-8 at IL-10 level at 10 ng/mL (34.7%, P<0.001) and 100 ng/mL (45.9%, P=0.001), though no statistically significant inhibition noted at 1,000 ng/mL. IL-1β did not show statistically significant percent inhibition at any concentration. TNFα revealed a percent inhibition at IL-10 level of 10 ng/mL (52.4%, P=0.002) and 100 ng/mL (61.0%, P<0.001) and no statistically significant inhibition at 1,000 ng/mL. CF and controls (n=3) were marginally different for IL-1β, but showed no statistically significant difference in percent inhibition for IL-8 and TNFα. CF airway immune cell cytokines demonstrate a similar response to IL-10 as non-CF controls with notable differential suppression of IL-8 and TNFα, though not IL-1β. IL-10 resistant airway cells are less likely to be the cause of CF pulmonary hyperinflammation.

Characterizing responses of translation-invariant neurons to natural stimuli: maximally informative invariant dimensions.

The human visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization is finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation-invariant models based on one template compared with position-specific models with several relevant features.