Cartilage-derived morphogenetic protein-1 (CDMP1) belongs to the TGF-beta superfamily, a large group of signaling molecules that are secreted as biologically active dimers with a carboxyl-terminal domain containing seven highly conserved cysteines. On the other hand,  FGF23 is overproduced by some types of tumors, such as the benign mesenchymal neoplasm Phosphaturic mesenchymal tumor causing tumor-induced osteomalacia, a paraneoplastic syndrome. Whether or not CDMP1 causes the transcriptional promoting function of FGF23 depends on the cell context, which is deeply influenced by the surrounding environment. One possibility is that co-activator or co-suppressor of CDMP1 exists in the different manner between in vitro and in vivo.

Thank you.

All living beings are structured following a hierarchical scale of "levels of complexity". Within one given level, you can distinguish "components" (elements) working in such a way that you can call the whole team a "unit". Example: within the "cell" level of complexity there are lots of different organelles, working in such a way that you can call the whole company "a cell". The description of the system as a special arrangement of matter is called the "structure" of the system. The way the team works following always the same rules of behavior is called the "organization" of it.

The striking aspect of the structural organization of all living beings is that you can always study  "units" into which there are lots of "components" working following always the same rules. But you can also realize, if you do the necessary research, that your studied "unit" is, at the same time, a "component" of a more complex team, which is also, of course, working following always the same (general) rules. Example: Teams of cells (units) of different types may work following a higher level of organization, as "components" of a new, more complex "unit", i.e. the "tissue" level. And so on.

It can be said that you trespass a level of organization every time you find that your studied "units" are really working following some particular rules, in such a way that the function of the whole team of "units" is more complex than the sum of the separate functions of everyone as a single element.

All living beings (no exception) are organized respecting the same growing scale of "levels of complexity", namely, molecular, macro-molecular, subcellular, cellular, tissue, organic, systemic, individual, population, communitary, ecosystemic.

Also in all living beings, when something happens into a given level of complexity (say, a cell), there are always some evoked reaction manifested or expressed at a higher level (say, tissue, organic, systemic levels) that tends to neutralize the change that took place at the lower (cellular) level, with different degrees of cuccess, depending on the magnitude of the initial change and the ability of the "system" to react against it.

Therefore, if you restrict the scope of your investigation by delimiting your model within just one of the lowest levels of complexity (say, cellular), artificially blocking any possibility to affect the organization of the components of units structured at higher levels of complexity (say, tissues, organs, systems) by the natural amplification of the changes you are inducing, then you are forcing your "system" to work following a totally different "organization" compared with the natural behavior of the same elements when they are integrated into a "whole" living being.

 The natural consequence of that kind of "reductionist" experimentyal modeling is that you can find lots of changes of your "system" that would be visible only when it is "protected" against the reactions of the higher levels, i.e. quite differently with respect to the way they proceed when things work naturally.

Example: Yo can find that cultured osteoblasts respond ot a drug producing mineralized bone within the culture capsule. So, you publoish a paper proposing that your finding is an "evidence" of the "potential" efficacy of the assayed drug to treat osteoporosis. On the other hand, the same drug administered to a living dog does not induce any change in its bone mass. The explanation is that the natural deformations of the bone tissue induced during life by the mechanical usage of the skeleton (absent in your model) is sensed by osteocytes (absent in your model), and, according to the results (not present in your model), osteocytes send messages to neighbor osteoblasts (present in your model, by "incommunicated") or osteoclasts (absent in your model) to build or destruct local bone tissue, just in order to keep its structural stiffness (impossible to be measured in your system) within its natural limits, as sensed by the osteocytes (again, absent in your model).

Now, if you translate this example to your matters concerning cDMP1 / Fgf23 relatonships, either in different conditions in vitro and/or when comparing in vitro and in vivo findings, you can easily understand the reason of the apparent paradox.

The "big question" involved here is the classical fight between "reductionists" who try to discover the "first causes" of natural phenomena, and the "holists" who prefer to investigate the "real" behavior of integrated living beings. Theoretical Phyhsicists are adding lots of pepper to this salad currently.

Thank you for the answer. It was of great help. For the sake of my calarity, I would like to ask something to you. How can invitro results be manipulated vivo? There are lot of published papers reporting the same results in vivo and invitro.  If i want to publish my contradictory result, how can I take it forward. Iam not able to convince my PI

It is also possible that the cell line (I am assuming this is what you use in vitro) is not representative of the cells in which FGF23 is regulated in vivo. If your cell line is missing an inhibitory factor, the results could be opposite to what you expected. You could try using other cell lines or primary cultures for your in vitro studies

Thank you.

I had answered to you this second question some days ago but I don't see my message in this list. Thus, I am doing it again now.

From the biological point of view, there are a lot of reasons for which your results could be interpreted quite differently from the way you do, or directly rejected with some compelling reasons (as correctly pointed out by Lilian).

I have nothing to tell about this kind of risk your investigation could be run into. However, in general terms, and just from the methodological point of view, when you have to discuss your research plan or to publish your results in situations like this, you should define which are

1. the justifications of the restrictions involved in the delimitation of your experimental model/design and the relationships they may have with the scientific and biological support of your working hypothesis (i.e. which are the advantages of having selected that model/design), and

2. the limitations of your model/design at the time of interpreting the results obtained as a function of that hypothyesis (i.e. the disadvantages of having selected that model/design).

In doing this, you could not avoid making reference to the upper or lower levels of complexity of the studied biologial structures that are or were disregarded in your investigation. This must be done in parallel and correlatively in all the Introduction, Material & Methods, Results, Discussion, and Conclusions Sections of your paper.

This way yo can conclude anything within the real methodological possibilities of your approach. Also you should (not must) extend your explanation or previsions in this concern in the Introduction, and analyze the pro- and con- arguments derived from others' investigations that could or not not be either profitted or neutralized by your findings.

This applies to both a research project or a report of the results of that, and should be the strongest way to present the problem to the persons (your boss, the referees, etc) who are to be convinced by your arguments.

Thank you. I will think on these lines.

One key thing to remember about musculoskeletal cells (whether bone, muscle or cartilage) is that in vivo they are subject to loading forces.  You might consider a cell-culture loading model such as fluid-flow shear stress or cell stretching to see if that makes a difference.

Donna's opportune warning concerns just one of the components of the sets of what I had regarded as factors acting at higher levels of complexity with respect to cultures. Specially for bones there exist just two sources of "high-level" interactions: those coming from the mechanical and from the metabolic environments (and virtually no others). Mechanical stimuli (loads) "teach" bones about how to conform their structure to cope with their mechanical functions. Metaboilic stimuli just disturb that learning by inducing bones to build or destroy  themselves as a function of the homeostatic needs of the organism concerning mineral balance (what are far a higher biological priority than bone strength, of course).

thank you for your responses.

The in vitro and in vivo results vary. Besides, the hype generated by present models of Warburg effect, and TCA cyce as the central hub of nutrient catabolism to CO2 and energy production are primary cause of aberrations in experimental science. These two models reduced rspiration as catabolic process and suggested that fermentation of carbohydrates converges in the production of lactic acid. Fermentation processes and lactic acid and mitochondrial metabolism are two separate entities. In fact lactic acid production from glycerol/ alcohol produced in anaerobic metabolism contributes a shift rfrom anaerobic metabolism to oxidative metabolism. O2 consumption and mitochondrial respiration are independently controlled by nano iron materials, and cyanide resistant and cyanide susciptible respiration. Unless people come out of these two models, which created several aberrations, we would not be able to understand properly the basic metabolic chemistry and waste millions of tax payers dollars on putative imaginery targets.

My advise is to look to some research articles in the direction i suggested:

García-Contreras R, et al. FEBS J. 2012. PMID: 22978366. and for cyanide glycosides24278641; 12475032; 12199497

Can I assume that unregulated proliferation of cells always produces an acidic extra cellular micro environment?

• Lactic acid entering the cells through MCT1 will be first oxidized to pyruvate by LDHB, which along with glutamine will be entering mitochondria and activates reductive carboxylation to promote citrate synthesis, Citrate lyase (ACLY) will be producing oxaloacetate, which will be reduced to malate. Malic enzyme decarboxylates malate to pyruvate. LDHA reduces pyruvate to lactic acid, which exits the cells through MCT4 into microenvironment and creates acidity. Metformin inhibits both MCT1 and MCT4 and creates acidity and oxidative stress within the tissues, by disturbing the NAD/NADH ratio. I discussed this model in my article (PMID: 33520860, available as PMC text.) The problem is with the present models is the dogmas of aerobic glycolysis and TCA cycle. Both the models hijacked science of pathology for nearly a century, despite demonstration that neither pyruvate kinase is active in cancer, nor pyruvate is decarboxylated in mitochondria. In fact two amino acids Cysteine in G1 phase of cell cycle, and Glutamine in G2 phase of cell cycle produce citrate. Cysteine G1 phase has a role in activating the ferredoxin pathway, which inserts iron-Sulphur clusters into respiratory chain to activate mitochondrial respiration. The most unfortunate aspect is people, who worked extensively on pyruvate carrier proteins and pyruvate kinase fall back into these two dogmas and adopt the classical TCA cycle as the standard model.

This figure gives you the dynamics of lactic acid shuttles and the aberrations created by TCA cycle.

The differences in results between in vitro (outside a living organism, often in a lab dish) and in vivo (inside a living organism) studies are due to several fundamental differences in the experimental conditions and biological complexity:

Understanding these differences is crucial for interpreting the results of both types of studies. Often, a combination of in vitro and in vivo studies is necessary to fully understand biological processes or the effects of a treatment. In vitro studies are valuable for initial screenings and understanding mechanisms at a cellular or molecular level, while in vivo studies are essential for understanding the actual effects in a living organism.

l With this protocol list, we might find more ways to solve this problem.