Cellular Communication - Science topic
Any of several ways in which living cells of an organism communicate with one another, whether by direct contact between cells or by means of chemical signals carried by neurotransmitter substances, hormones, and cyclic AMP.
Questions related to Cellular Communication
I have a single cell data on mouse lung at homeostasis and at 4 different time points after injury. I've read a couple of review papers on different packages available for cell-cell interaction- cellphonedb and cellchat being the most popular ones. Others being SingeCellSignalR, iTALK and NicheNet. All have their pros and cons and I'm confused about which one would be the right one to choose and how to visually represent the cell-cell communication in the time series data
I am doing research on T cell interactions with epithelial cells and am looking to see if the interaction is MHC mediated. There was another post on research gate but it is from 2014 https://www.researchgate.net/post/What-is-the-best-way-to-block-MHC-class-I-and-II-in-in-vitro-assays-of-T-cell-function.
I think this is the pan Class II blocker ( https://www.bdbiosciences.com/en-us/products/reagents/flow-cytometry-reagents/research-reagents/single-color-antibodies-ruo/buv496-mouse-anti-human-hla-dr-dp-dq.741157) mentioned in the above post, but is any antibody clone that is Tu39 with/without a flurophore able to block binding?
- alternative Tu39 clone for blocking https://www.biolegend.com/en-us/products/purified-anti-human-hla-dr-dp-dq-antibody-9337?Clone=T%c3%bc39
This antibody I found was cited in literature as a CD4 blocking antibody https://www.biolegend.com/en-us/products/pacific-blue-anti-human-cd4-antibody-3662?GroupID=BLG5901 so similarly would any OKT4 clone for anti-CD4 work for blocking?
Thank you for your assistance!
I am currently working on a study to estimate the traffic volume distribution of urban areas by utilizing mobile phone location records. Please, can anyone help me to find an open access dataset for the desired task? Your contribution in this regard is highly appreciated!
For my simulations I get a sum rate of X b/s. If my total energy consumption is Y mW, how should i calculate energy efficiency(EE). Is the following formula correct?
I am going through some digital communication literature, where some research papers have used the following formula to calculate the sum rate
Sum_rate=Summation (log2(1+SINR(i)) eq.1
My confusion is as follows:
1. Why is bandwidth(B) not included i.e. B.log2(1+SINR)
2. What will be the units (e.g. bps/Kbps/Mbps etc) if eq.1 is used.
I want to parse signals coming from 4G/5G towers to extract only the ID of the tower and the transmission time (on simplex communication: only downlink). Are these packets (or frames) sent on a regular time interval ?
Please guide me about the difference between SINR threshold and Minimum discernable signal.
From my search I have come across the following.
1) A signal can be decoded if the SINR of the received signal is higher than the SINR threshold. Does it mean that we should not be concerned about the minimum required power, and that if the received signal satisfies the SINR threshold, it will be successfully decoded?
2) I also have come across the idea of minimum discernable level. For instance -70 db is considered acceptable for some types of communication.
Which of the two I should follow. As in the first case, I get very low transmit powers and still satisfy the SINR threshold, while the transmit powers in the 2nd case are way too high compared to the first case.
Please help me with the following formulation.
I want to calculate transmit power that can satisfy a given SINR threshold on the receiver side.
My formulation is as follows:
SINR=Received_Power/(Interference+Noise) Eq. 1
If SINR Threshold (SINR_th) is known, we can get the Required_Received_Power and thus the "Required_Transmit_Power" power as follows:
SINR_th=Required_Received_Power/(Interference+Noise) Eq. 2
We know that
Received_Power=Transmit_Power/Pathloss; Eq. 3
Required_Received_Power=Required_Transmit_Power/Pathloss; Eq. 4
Substituing "Required_Received_Power" in Eq.2 with the right hand side of Eq.4, we get
SINR_th=(Required_Transmit_Power/Pathloss)/(Interference+Noise) Eq. 5
Required_Transmit_Power=SINR_th x (Interference+Noise) x Pathloss Eq. 6
Please advise whether this formulation is correct or not as I am getting wrong results.
How do we represent zero interference on db scale?
I am using the following formula for calculating the Received_Power_TH (TH stands for threshold). Received_Power_TH is the power of the received signal required for successful decoding. I am using the following formulation.
SINR=Received_Power - Interference - Noise Or
The Recieved_Power that satisfies the SINR_TH (or in other words the minimum Received_Power required for successful decoding) is given as follows
SINR_TH=Received_Power_TH - Interference - Noise Or
Received_Power_TH =SINR_TH + Interference + Noise
However, i get the following results which seem counter intuitive.
Assuming SINR=25, Interference=-50, Noise= -95
Now if we do not have any interference e.g. in a case when there is only one node transmitting, we get the following
This result seems counter intuitive as Received_Power_TH for successful reception in case of no interference should drop below the value we get when we have interference whereas in this case the Received_Power_TH is equal to -120 in case of interference and it increases to -70 when there is no interference.
Does anyone know a way to block cell:cell communication during innate immune signalling (IIS) in cell culture? Possibly by blocking release of IIS-induced signalling factors, eg IFNs, ISGs, proinflammatory cytokines etc, or by blocking their binding and recognition to surrounding cells?
As an overview, detection of intracellular pathogens stimulates innate immune paths within the cell, which ultimately leads to release of IIS signalling molecules to warn surrounding cells of infection. This stimulates innate immune paths in the surrounding cells, making it difficult to differentiate between the infected and warned cells.
I'm attempting to break this link so I can study the pathway at the single cell level. All of the cells in the culture will be infected with the pathogen, and I will be screening compounds that modulate the intracellular paths, so I can't just remove uninfected cells. The actual cell type is flexible, but importantly the assay cannot kill the cell as it needs to survive for multiple screening rounds.
Intelligent reflecting surface (IRS) is deemed as the promising and revolutionizing technology for future wireless communication systems.
As the kind of impedance metasurface, each element of IRS is composed of configurable electromagnetic (EM) internals and can reflect the incident EM wave with the desired phase shift. Thus, the IRS is able to intelligently change the propagation environment and significantly enhance the quality and coverage of wireless communications. So, do you see any chance that network operators will deploy the IRS in their networks?
IRS can create higher beamforming gain with the help of an “intelligent” reflector. But, this brings other practical issues.
How does BS/AP synchronize with the reflector about the amplitude and phase?
where IRS is the intelligent reflective surfaces, BS is the base station and AP is the access point.
where IRS is intelligent reflective surfaces, ISI is inter symbol interference which is a main cause that can reduce efficiency of the system due to multi
Is it possible to mention the areas in which IRS have been used? And how much benefit have you achieved or will be achieved when using it?
The researcher, scientist, or engineer who uses mathematical optimization, or more generally, computational mathematics. This includes, naturally, those working directly in optimization and operations research, and also many others who use optimization, in fields like computer science, economics, finance, statistics, data mining, and many fields of science and engineering. The primary focus is on the latter group, the potential users of convex optimization, and not the (less numerous) experts in the field of convex optimization.
An intelligent reflecting surface (IRS) comprises an array of IRS units, each of which can independently incur some change to the incident signal. The change, in general, may be about the phase, amplitude, frequency, or even polarization.
To date, in most studies, the change is considered as a phase shift only to the incident signal, so that an IRS consumes no transmit power. In essence, an IRS intelligently configures the wireless environment to help the transmissions between the sender and receiver, when direct communications have bad qualities. Example places to put IRSs are walls, building facades, and ceilings,
Therefore, the optimization algorithm solves the achievable problems by optimizing the phase shifts by considering both continuous phase shifts (CPSs) and discrete phase shifts (DPSs).
How can benefit from Convex Optimization when using intelligent reflective surfaces in wireless communications?
In essence, Intelligent Reflecting Surfaces (IRS) intelligently configures the wireless environment to help the transmissions between the sender and receiver, when direct communications have bad qualities. Example places to put IRSs are walls, building facades, and ceilings. But, is it possible to benefit from the use of the Intelligent Reflecting Surfaces (IRS) for satellite communications?
The intelligent reflecting surface (IRS) aided wireless communication system, where the IRS has emerged as the revolutionizing solution to enhance wireless communications by intelligently changing the propagation environment.
One of the aims of the wireless communication system with IRS is to minimize the transmit power while guaranteeing the qualities of both primary and secondary transmissions. As in communication between a multiple antenna Base Station (BS) and a single antenna user, assisted by an Intelligent Reflecting Surface (IRS); and Due to the large number of elements in IRS, acquiring Channel State Information (CSI) requires many radio-frequency chains and considerable training overhead.
Therefore, what is a new method based on the Optimization to optimize the problem of beamforming at the BS and IRS without CSI, by minimizing the transmit power, subject to a minimum signal-to-noise ratio (SNR)?
The Fifth Generation (5G) mobile communication standard promises to provide enhanced mobile broadband, massive connectivity and ultra-low latency through various technological advances, including massive multiple-input multiple-output (MIMO), millimeter wave (mmWave) communications, and network densification. However, these technologies consume a lot of power and struggle to provide the users with guaranteed quality of service (QoS) in harsh propagation environments.
For example, the network’s total energy consumption scales linearly with the numbers of base stations (BS)s and the active antennas at each BS, while communication at mmWave bands suffers from high path/penetration losses. These limitations have resulted in the need for green and sustainable future cellular networks with control over the propagation environment.
Therefore, can Intelligent Reflecting Surface (IRS) be designed for 1 to 6 GHz bands as well? Or is it only suitable for high-frequency bands such as millimeter waves?
There is a set of problems found in smart reflective surfaces, including:
1. the secrecy rate maximization (SRM) problem is formulated, which is a non-convex problem with multiple coupled variables.
2. The nonconvexity problem of maximizing the weighted sum rate (WSR) of all users when the BSs and the users are equipped with multiple antennas, which enhances the spectral efficiency by exploiting the spatial multiplexing gain.
3. The optimization problem of maximizing the weighted sum rate (WSR) of information receivers (IRs), the transmit precoding (TPC) matrices of the base station (BS) and the passive phase shift matrix of the IRS jointly.
4. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays.
5. properly altering the signal propagation via tuning a large number of passive reflecting units.
6. the secrecy rate of the intelligent reflecting surface (IRS) assisted Guassian multiple-input multiple-output (MIMO) wiretap channel
7. maximize the spectral efficiency of an IRS-assisted point-to-point multi-input multi-output (MIMO) system
8. enhancing its secrecy rate for an intelligent reflecting surface (IRS) assisted Guassian multiple-input multiple-output (MIMO) wiretap channel (WTC).
What parameters can be used when improving the performance of intelligent reflecting surface (IRS) by optimization algorithms?
One of the most important modern systems used in wireless communications is the intelligence reflective surfaces. Are there filters used with these surfaces?
Can new optimization algorithms be designed to work infinitely to get the best results, they search the entire search area in a spherical manner and are concerned with all static and dynamic particles and possess all physical and topological properties to achieve the best possible solution?
I am able to generate Rayleigh coefficients as per the following code (function) in python using H=(1/sqrt(2))*(randn(N)+randn(N)*1i)
def RAYLEIGH(d, etaa, num_symbols):
// Input arguments (Distance, pathloss exponent and samples required (depends on data if fast fading)//
h1 = np.sqrt(c); //(Pathloss is multiplied with Rayleigh coefficient)
h = h1*((np.random.randn(num_symbols)+1j*np.random.randn(num_symbols))/np.sqrt(2));
g = (np.absolute(h))**2; // Magnitude
return h.tolist(), g.tolist(); // Return as a list
How to generate the Rician Coefficients given d (distance), etaa (path loss exponent) on the same lines.
If not then how hypothetically or in theory MItochondrial Exchange between organisms that are taxonomically separated as far as kingdoms will go in terms of their physiological and biochemical interactions?
Say we transfer a mitochondrion from a fungal cell/plant cell to a Mamillian cell line will it still be functional in the new cytoplasm? How the different host cells interact with it?
Basically, This project I have started few months ago and planned to coculture 3T3 cells so that I can understand the cell - cell communication. If they is another way to find out how mutant and wild types cells are communicating each other it would be really helpful for giving my project a good start.
Could you please suggest me some papers, textbooks and basic tools for learning in silico methods? Primarily, I want to research about cancer metabolism, drug resistance, and epigenetics. For example, how can I work on and understand "possible" protein-protein interactions, non-coding RNA targets and cell to cell communication?
Thank you in advance
Small cell networks are a promising approach to meet the higher data rate demands of cellular users. How many small cell base stations would be required to provide coverage in the typical urban areas of say 4000x4000?
In thinking about stem cell interactions with tissues as a possible cause of cancer, the basic idea of DNA damage is relevant on the opposite side of the metabolism. DNA is involved in producing the molecules that interact in the tissue system, and regulating the cells in the tissue, but it is interesting to wonder which side of the metabolism causes cancer. Is it the DNA or the cell interactions?
The UAVs used in the military services can stay aloft for almost 45 hours based on the payload. What about the UAV used in cellular communications? For instance, the UAVs used in emergency services (earthquake) for cellular communications.
I want to know if there is any noise in the estimation of a cell (especially cancer cell) about number and type of neighbor cells. I also want to know what factors are involved in the amount of noise? Does the phenotypic behavior of cells (i.e., being quiscent, prolifertive, apoptotic, and necrotic) influence the amount of noise?
I want to co-culture cancer cells and transfected Jurkat cells, and want to examine their interaction. I wonder what is the best way to culture them. Should I plate cancer cells a day before and then add Jurkat on top of cancer cells, or I should plate both cells together at the same time when I trypsinize cancer cells? After mixing the cells, how long do I need to spin down the culture to force interaction of the cells?
Thank you for your comments and suggestions!
A possible answer in A. Tugui, D. Danciulescu, M.-S. Subtirelu (2019, The Biological as a Double Limit for Artificial Intelligence: Review and Futuristic Debate. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 14(2), 253-271, April 2019 https://doi.org/10.15837/ijccc.2019.2.3536).
Biocomputing—The invisible hand of AI?
"Fascinated by the secrets of medicine, in an informal discussion in 2014, we asked the famous surgeon I. Lascar, a professor at the University of Medicine and Pharmacy in Bucharest, what the secret was to a successful operation. Among the syntheses and content-related explanations, Professor Lascar pointed out that surgery is assisted, besides a number of strictly scientific factors, by a so-called invisible hand that contributes to the success of an operation and which all physicians rely on. In this context, the success of biocomputing research and development as part of the bio computer could be the catalyst for leaping to a level of AI that surprises us in terms of intelligent performance and behavior. Current achievements, such as the design of the biological transducer; the monitoring, programming, and behavioral control of the live cell (via logical operations AND, OR, and NOT); and technological challenges such as the decoding of live cell communication and the future development of a natural language of living cells (N2LC) used in biocomputing could turn biocomputing into the invisible hand of biological systems stretched towards artificial systems, especially AI."
I'd like to know if hypoxic cells communicate with the surroundings cells (that are also hypoxic or not hypoxic). I mean I assume they release signals that could lead to angiogenesis or other mechanisms but I'd like to know if there is a cooperative effect with the other cells of the region to sayto them : "let's all reduce our metabolism so that we all burn off less oxygen and nutrients, so that we will live longer".
And would you know if that behavior changes for tumor cells ?
And if you know articles about that topic, could you please give me the reference ?
Or even if they don't emit signals, do cells release molecules that can have an effect on the sourrounding cells metabolism ?
Is there any computational method or data base with the help of which one could predict if two interacting cell surface proteins are located on separate cells or are located on the same cell surface?
I have a idea to reduce call drops in busy state. To implement my idea in real time process what i need t do. I attached current using call transition state.
1) How to Reduce the mobile radiation without affecting the effective mobile communication ??
2) How to Reduce the specific absorption rate (SAR) of bio-tissue of electromagnetic radiation found in cellular communication ??
** I want to start in this field but I do not know how to start and I want help. I want to participate with researchers in this field .
1) How can I Reduce the mobile radiation without affecting the effective mobile communication ? .
2)How can I Reduce the specific absorption rate (SAR) of bio-tissue of electromagnetic radiation found in cellular communication ?
**I want to start in this field but I do not know how to start and I want help
**I want to participate with researchers in this field
I would like to stain EVs and see whether, once stained, they are captured by cells or they interact with cell surface.
I was looking to the manifacturer's instructions and I wasn't able to find any information on how to stain EVs.
Does anyone have experience on these kind of staining or articles to suggest in order I can have an idea on the workflow?
Thank you all!
Have a nice day.
We are supplementing RPMI meida with human plasma instead of serum for culture of human breast cancer cells.
When PRMI is supplemented with 10% human plasma, the media looks fine, however once cells are added into this media a gel forms.
This seems to be a reproducible phenomenon with plasma from different donors.
Do you think its concentration dependent? or are the coagulation factors somehow clumping our cells?
What is the simplest, quickest, and/or cheapest way of finding out whether a molecule is involved in a novel quorum sensing / cell-cell signaling / signal transduction pathway?
Most literature explains assays that build on systems that have already been established, involving AHLs, AI-2, DKPs, DSFs, HAQs, etc., but our suspected signal molecule is not similar to those. It might be involved in cessation of cell growth, and we sort of have growth curves at different concentrations of the compound.
Outside of forward and reverse genetics, which would be especially difficult for our organism, an Archaeal methanogen, I’ve seen the most plausible options in this paper:
Affinity chromatography and photo-affinity labeling don’t seem simple or quick or cheap, though.
I’d appreciate any suggestions.
I‘m investigating the epithiel cell interaction with bacteria. So I co-cultured the gram + ,gram - with epithiel cell. The bacteria were stained with SYTO9 or hexidium iodide separately. The staining time were 15 minutes and wash with PBS for 3 times to remove remaining dye. After co-culture, I utilized 4% PFA for fixation.The final step was mounting. However, can’t observe the fluorescent light of of bacteria under confocal microscope and phase contrast microscope. While I can see the bacter is under bright light field. And the stained bacteria also can be found and emit fluorescents.
I‘m wondering is there any step I made wrong?
Can anyone help me this question?
Normally, in cell culture, we add FBS in RPMI media. However, in case that we add our materials containing electrostatic or hydrophobic interactions into the cell solution. There is possibility that proteins in medium will be absorbed. How can we know that the ONLY nanoparticles were taken up or as a clusters (nanomaterials + proteins absorbed)
Thank you very much
I have suspension cells. I incubate cells with my fluorescence tagged nanoparticles, and then I will run the flow. The problem is that it seems impossible to separate nanoparticles that haven't been taken up into the cells with the suspension cells. Also, some of my nanoparticles can bind to the cell surface receptors, and some of them will be taken up by the cells. How can I only get the information of the fluorescence tagged nanoparticles interacted with the cells instead of the free fluorescence tagged nanoparticles. Thank you!
hello everybody,I have a question about FACs assay.
I am working on cell-cell interaction, I have some modifies cells which can interact together in presence of co factor, but the problem is that the co factor itself make the peak kinda shifted!?
foe example I have a two cell population and stained them with different dye(DiO and DiI) on FACs results we should see three population the green one the red one and the mix population (yellow) but after the co factor every peak shifted ( for a blank or control sample), then I can not say my cells interacted or not?
I will be thankful if anybody has or had experience before share with me.
how to predict homophilic and heterophilic interactions for cell adhesion molecule. Is there a software that predict homophilic or heterophilic interaction from protein sequence ?
there is a lot of data, opinions and the like available about Biophotons. Many papers reveal, that organic matter may emit photons and it is argued that cells communicate by this.
If this is so, than there should be evidence that cells also ABSORB biophotons which other cells emitted.
How has this been proved?
I am trying to establish the interaction between two proteins using immunoprecipitation. I always use an asynchronous population to transfect my protein of interest. I want to clarify if the interaction is cell cycle phase specific.
My question regards the real necessity to have subframe (3GPP Rel. 12) or slot (3GPP Rel. 13) aligned transmissions in the unlicensed band.
According to TR 36.889: "Channel reservation refers to the transmission of signals, by an LAA node, after gaining channel access via a successful LBT operation, so that other nodes that receive the transmitted signal with energy above a certain threshold sense the channel to be occupied." This signal is transmitted until the next subframe or slot boundary is reached so that transmissions are aligned.
The channel reservation signal defined by the 3GPP standard adds an overhead to LTE-LAA transmissions that impact on its performance. If there were no necessity for any kind of time alignment to the PCell the SCell performance could be increased.
Therefore, my question is, what would be the possible implications to all LTE layers if the transmissions were not aligned at all?
Wish somebody help me to understand the following situation: Consider the MD simulation of two interacting molecule (first one on the left and the second one on the right) in a unit cell: The second molecule is interacting with the right side of the first one. Then, the second molecule start to get far from the first one and to get out of the unit cell, lets say the right-hand face of unit cell. Under the PBCs it has to enter from the the left-hand face and it interacts with the first molecule from the left side of the first molecule, while before getting out the cell it was interacting with the right side of the first molecule. I wonder if such simulation is correct...? I mean before getting out of cell the second one was interacting with the first one from its left side and if it interfaces the cell wall, it interact with the first molecule from its right side. There is a jump and I don't know how to deal with that during the simulation..
In-order for my system to calculate the outage probability, I have to get the number/probability of those SNRs that are below the SNRthreshold. So I am asking if there is a formula to calculate the SNRthreshold or I just have to assume a value?
I am working to reduce the inter-cell interference in the cell edge users. So i need to include an efficient approach for co-variance matrix estimation in IRC receiver. Most of the existing works seem to be working on assumptions at some point.
Which one is more promising, network-assisted D2D or without network D2D communication? It's generally said that in D2D communication the two devices communicate directly using highly directional antennas keeping the out-of-band emission very low. Finally, is it related to cooperative diversity in any way?
Taking into consideration :
-properties of doubly terminated filters, to help minimise factors such as group delay.
-derivation of two port parameters as well as the input impedance to aid in synthesizing of the transfer function and analysis of the filter response.
-the realization of a power transfer function of an elliptic filter given filter specifications.
And lastly with the use of a relevant frequency transformation, a new power transfer function is to be attained that is suitable for waveguide transmissions and has a pair of transmission zeros at infinity and reflection zeros at the origin.
In some articles (e.g: Spotfi Localization), I found that they extracted the time of arrival using MUSIC algorithm. What is the process.
Say I got a 1 D vectors samples received in 5 arrays at 2.437 MHz with half-wavelength spacing. How can I find the ToA.
1 D Vector = 42.03 + 131.44i, -17.13 - 37.40i, 71.78 + 119.89i, -23.83 - 31.39i, 97.39 + 102.58i
A signal is transmitted by the transmitter and multiple rays arrive at the receiver as a result of reflections (from the flat obstacles), diffraction (from the edges of obstacles) and scattering.
How do I find the number of clusters in this condition?
I have modeled proportional fair (PF), round robin (RR) and best CQI (BCQI) scheduler. I have calculated the fairness of the schedulers using the users throughput. Now, I want to compute the latency of the schedulers.
How can I calculate the latency?
Small cells are the only means of communication in areas where terrestrial media cannot be engineered however, different means of backhaul communication can be made available aggt a communication node which becomes the hub for the EPC. Ahead of the hub small cells are created with mutually exclusive zones in such a manner that they allow intercell communication of the UE and with negligible interference from neighbouring cells
Is there any mathematical demonstration for advantage of the chaotic spreading sequence compared with the gold or other spreading sequences?
For example, between neurones there are electrical signals, but these electrical signals there are in all type of cells, like the smooth muscle cells. In tissue engineering, the scaffold is use to make a support for the celular proliferation, normally this material is insulating. But, what would happen if the scaffold is make with a conductive material? the cellular comunication will be better? (without electrical stimulation in vitro, that's another topic).
I am a PhD student in computer science . The object of my thesis is "solving optimization problems in cellular networks". It consists of resolving optimization problems that exist in radio mobile networks using bio-inspired algorithm called "metheuristics". Any comments regarding this?
Dear experts, I am a computer scientist and I know that there is some schemes to perform location-updates/page of mobile users within a cellular network. I would like to know if these schemes are standard (i.e. in all generations) or are specific to each generation ?
What are the possible ways of basolateral-to-apical signal transitions for polarized epithelial cells in culture?
I suppose, cytoskeleton is one of the sensing mechanisms, with basolateral anchoring influencing cell shape and behaviour at the apical side.
However, I am now looking for the mechanism regulating protein phosphorylation, which is probably different from the cytoskeleton arrangement.
Particularly, in my experiment changing basolateral conditions result in variations of apical protein activity, which is most likely regulated by phosphorylation. What are the possible basolateral signals and/or sensors, influencing protein kinase activity towards apical proteins and mechanisms underlying these effects? How is protein kinase targeted to the apical cell side?