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CDK1 activity and protein abundance are different observables. A total-CDK1 Western blot estimates protein amount under its calibration and loading assumptions. A phosphosite-specific Western blot asks about a particular CDK1 phosphorylation state. A histone H1 kinase assay asks how much substrate modification occurs under specified assay conditions. Any conversion between them needs a model and suitable controls.

An original counting example stipulates $100$ CDK1 molecules, with $60$ bound to cyclin B in each of two hypothetical samples. In sample A, $10$ bound molecules are activity-permissive and $50$ are inhibited; in sample B, $40$ are activity-permissive and $20$ are inhibited. The other $40$ are unbound in both samples. Total CDK1 and bound CDK1 agree, but activity-permissive counts differ fourfold. These are invented counts for bookkeeping, not measured biological populations.

If each activity-permissive molecule contributes the same reaction rate, substrate and ATP remain available, and the assay stays linear in time, a simple illustrative readout isHere $R$ is the recorded signal, $R_0$ is a matched blank signal, $N_{\mathrm{active}}$ is the activity-permissive count, $t$ the reaction interval, and $\alpha$ a common signal contribution per active molecule per unit time. The corrected signals in the stipulated samples have ratio $40/10=4$, although their total protein amounts agree. This is an assay accounting assumption, not an ordinary differential equation for the cell cycle. The no-added-cyclin B baseline in the inspected experiment can itself contain catalytic activity; it need not equal an enzyme-free blank $R_0$.

Substrate depletion, differing inhibitory conditions or a saturated detector can break the simple proportionality. Comparing samples therefore requires matched reaction intervals, substrate supply, loading and detector response, rather than assuming that brighter histone H1 labeling automatically means more total CDK1.

The chemotaxis FRET assay uses Förster resonance energy transfer between fluorescent tags on CheY and CheZ to report their association. Interpreting this emission ratio as CheA activity requires the coupling between CheY phosphorylation and CheZ binding described in the experimental sources above.

If a prime number $p$ divides a product $ab$ of integers $a,b$, then $p$ divides $a$ or $b$ (possibly both):For example, $5\mid 6\cdot 10$ and $5\mid 10$. The hypothesis that $p$ is a prime number matters: $6\mid 2\cdot 3$, although six divides neither factor. When $p$ does not divide $a$, the greatest common divisor of $p$ and $a$ is one; multiply Bézout's identity $up+va=1$ by $b$ to see that $p\mid b$. Repeated application makes this the uniqueness step in the fundamental theorem of arithmetic. ^[ref].

For a completely computed example, $7\mid 20\cdot 21$ because $20\cdot 21=420=7\cdot 60$, while $20=7\cdot 2+6$ shows that seven does not divide twenty. Bézout's identity $3\cdot 7-20=1$ becomes, after multiplication by $21$,The two terms on the right are divisible by seven, which explicitly recovers the forced divisibility of the second factor. Both alternatives can hold: $7\mid 14\cdot 21$, and seven divides both $14$ and $21$.

In fact the property characterizes prime numbers among the integers greater than one. If $c$ is a composite number, choose $c=ab$ with $1<a,b<c$; then $c\mid ab$, but $c$ divides neither $a$ nor $b$. For several factors, repeated application of Euclid's lemma says that a prime number dividing their product divides at least one factor. In a product of prime numbers, that factor must equal it, because a prime number has no other prime factor. This is what prevents a different collection of prime factors from representing the same positive integer in the fundamental theorem of arithmetic.

Book VII, Proposition 30 of Euclid's Elements states the result in terms of a prime number measuring a product; its proof uses coprimality and ratios. The calculation using Bézout's identity above is a modern way to explain the same divisibility statement. ^[ref]

The Förster distance is the separation giving FRET efficiency $E=1/2$ for the specified pair and conditions. It is a property of the optical pair and its environment, rather than a universal length. In the usual pair model,where ${\kappa }^2$ is the FRET dipole orientation factor, $Q_D$ the FRET donor quantum yield, $J$ the FRET spectral overlap integral, and $n$ the medium's refractive index. The omitted proportionality constant depends on the unit convention for $J$.^[ref]

If FRET efficiency is known and those assumptions hold, inversion givesThe derivative explains why errors become troublesome near $E=0$ or $E=1$. An illustrative pair with $R_0=4$ nanometres and another with $R_0=6$ nanometres both give $E=1/2$ at their different Förster distances: knowing FRET efficiency alone does not determine $r$.

A heterogeneous population adds another ambiguity. In a synthetic example with equal weights per FRET donor excitation, efficiencies $0.1$ and $0.9$ average to $0.5$, but their separations are $9^{1/6}{R}_0$ and $9^{-1/6}{R}_0$. Their average separation is approximately $1.068R_0$, whereas inverting the average FRET efficiency gives $R_0$. A measured emission ratio has additional detection weights; it need not equal even this excitation-weighted average. The transferable lesson is that an average readout does not uniquely specify a distribution of molecular separations.

In Receptor sensitivity in bacterial chemotaxis by Victor Sourjik and others, Victor Sourjik and Howard C. Berg used a cyan fluorescent tag on CheZ as FRET donor and a yellow tag on CheY as FRET acceptor. Escherichia coli biological cells adhered to a polylysine-coated coverslip in a continuously perfused chamber. A fluorescence microscope excited them with a $442$-nanometre laser; split emission bands fed two photon-counting detectors. The yellow/cyan emission ratio fell when attractant was added and rose when it was removed.^[ref]

Saturating attractant increased cyan emission by an amount matching selective bleaching of the yellow tag: removing the FRET acceptor supported relief of FRET donor transfer. Strains carrying the tagged pair but lacking other chemotaxis machinery showed no stimulus-dependent emission ratio change. Weak illumination reduced bleaching drift.^[ref]

The inference is a change in the population of nearby tagged CheY/CheZ pairs associated with CheY phosphorylation. It neither measures each pair's separation nor directly observes motor motion. The readout also averages many biological cells, and perfusion takes finite time. The pathway interpretation belongs to the chemotaxis FRET assay; the general measurement lesson is that molecular association can alter FRET while the geometry of an individual associated pair stays the same.

FRET sensitized emission is FRET acceptor fluorescence caused by transfer from an excited FRET donor. Excite predominantly the FRET donor and collect both emission bands. Reduced FRET donor emission and increased FRET acceptor emission are useful together, but an acceptor-to-donor emission ratio is not automatically the FRET efficiency: brightness, label abundance and channel collection also enter.^[ref]

A geometric progression is a sequence obtained by repeatedly multiplying by one fixed common ratio $r$:Here $a$ and $r$ may be real numbers or complex numbers. The recurrence is meaningful even when $a=0$ or $r=0$; expressing $r$ as a ratio of successive terms requires a nonzero denominator. As a polynomial convention, $r^0=1$, including at $r=0$.

For example, quantities $100,80,64,51.2,\dots$ retain four fifths of their preceding value at every step. The decrement changes, but the retained fraction does not. With the same initial value and common ratio $2$, the terms are $100,200,400,800,\dots$. This multiplicative structure is useful whenever the same proportional rule repeats: it turns many updates into the single exponentiation $r^n$. An arithmetic progression instead repeats an additive increment.

For nonzero $a$, the modulus of $a_n$ tends to zero when $|r|<1$, stays fixed when $|r|=1$, and grows without bound when $|r|>1$. For a negative real common ratio, successive nonzero terms also alternate in sign. Thus the terms $1,-1/2,1/4,-1/8,\dots$ decay in size while crossing zero at every step. Adding the terms gives a geometric series; the individual terms and their accumulated partial sums are different sequences.

In an ideal aqueous chemical solution, set $h=[{\mathrm{H}}_3{\mathrm{O}}^{+}]/c^{\circ }=10^{-\mathrm{pH}}$, with $c^{\circ }=1\mathrm{mol}{\mathrm{L}}^{-1}$, and approximate activity coefficients by one. Put $K_1=10^{-2.35}$ and $K_2=10^{-9.78}$ for the stipulated dimensionless acid dissociation constants. The Henderson-Hasselbalch equation gives the adjacent-state ratiosWith analytical concentration $C_T=[G^{+}]+[G^0]+[G^{-}]$, normalization gives the three fractions and mean electric charge in units of the elementary charge:All three fractions are nonnegative and sum to one. At pH $7$, the model gives about $99.832\%$ zwitterion, $0.00224\%$ cation and $0.1657\%$ anion; $\bar{z}\approx -0.00163$. Predominantly zwitterionic therefore need not mean exactly at the isoelectric point.

Setting $\bar{z}=0$ requires $h^2=K_1{K}_2$. Taking the logarithm yieldsAt this model isoelectric point, ${\alpha }_{+}={\alpha }_{-}\approx 0.0001927$ and ${\alpha }_0\approx 0.9996146$: about $0.0193\%$ of each charged form remains. At either pKa, the relevant adjacent fractions are equal, but the third fraction is not mathematically zero. This three-state model neglects the minor uncharged form ${\mathrm{H}}_2\mathrm{N}-\mathrm{C}{\mathrm{H}}_2-\mathrm{COOH}$; macroscopic pKa values alone do not determine its fraction separately from the zwitterion.

For positive quantities measured at successive steps, the growth factor $g_i=Q_i/Q_{i-1}$ is a dimensionless ratio. It can be below one when the quantity shrinks. Repeated multiplication gives $Q_n=Q_0{\prod }_{i=1}^n{g}_i$, so the common factor that reproduces the endpoint after $n$ identical steps is their geometric mean. A factor $g$ corresponds to a relative change $g-1$; factors must be averaged before subtracting one when summarizing compounded change.

Insulin is a protein hormone. Its mature form has two polypeptide chains; identifying their sequences and protein disulfide bonds provided the motivating example in Sanger's insulin sequencing experiment. See Cooper: insulin as a two-chain hormone, figure 2.16.

A meal illustrates the insulin side of blood glucose homeostasis: rising glucose stimulates beta cells in the pancreatic islets, and released insulin favors uptake and storage of fuel. Alpha cells produce glucagon, while delta cells produce somatostatin, which inhibits release of both insulin and glucagon. The pancreas therefore contains interacting sensor and secretory biological cells, rather than one undifferentiated source of hormones. ^[ref]

Insulin and glucagon are peptide hormones, built from amino acid residues joined by peptide bonds; glucose is a small carbohydrate molecule. A hormone changes signal transduction, not the identity of the fuel it regulates. Human mature insulin has 51 amino acid residues in two polypeptide chains. Beta cells process proinsulin to insulin and C-peptide, storing the products in secretory granules for exocytosis. Increased glucose metabolism raises the ATP-to-ADP ratio, tending to close ATP-sensitive potassium channels; depolarization and entry of calcium ions then trigger exocytosis. This is an important triggering pathway, with additional amplification and modulatory inputs.^[ref]

Binding to the insulin receptor, a receptor tyrosine kinase, starts phosphorylation of the receptor and insulin receptor substrates. Recruitment of phosphoinositide 3-kinase and activation of Akt transmit a major metabolic branch. In skeletal muscle and adipose tissue, that branch helps move GLUT4 to the cell membrane, increasing glucose uptake by facilitated diffusion. GLUT4 is a membrane transport protein, not an insulin receptor. Insulin also favors glycogenesis in skeletal muscle and the liver, and inhibits lipolysis in adipose tissue. In the liver, suppression of glucose output involves enzyme regulation, gene expression, and indirect changes in substrate supply. Its relative direct and indirect contributions are more complex than a single Akt arrow. ^[ref]

Insulin is not a universal permission slip for glucose entry: red blood cells and much of the nervous system use uptake mechanisms that are not acutely dependent on insulin. Nor does the liver use the same GLUT4 switch as skeletal muscle. This is why reduced insulin action can change blood glucose dramatically without stopping all glucose uptake. ^[ref]

Diabetes can disrupt production, response, and counterregulation. Type 1 diabetes usually involves destruction of beta cells and severe loss of endogenous insulin; type 2 diabetes combines insulin resistance with insufficient beta cell compensation. High circulating insulin can therefore coexist with impaired insulin action. Inappropriate glucagon release can add to excessive liver glucose output, and the response to low blood glucose can also be impaired: "more glucagon" is not a complete description of diabetes. These distinctions explain mechanisms, rather than prescribe treatment. ^{[ref] [ref]}

Negative feedback closes a causal loop whose net effect opposes an initiating change. In signal transduction, activation followed by a downstream inhibition of the earlier activating stage is one example of negative feedback. Loop sign alone does not establish asymptotic stability or complete signaling adaptation; see the worked signaling feedback example.

A useful biological example is chemotaxis feedback regulation: an Escherichia coli biological cell adjusts its response to a sustained attractant instead of remaining at its immediate response. Increased CheA activity promotes CheB phosphorylation; CheB reverses receptor methylation, opposing their activation. After attractant addition, reduced activity instead favors receptor methylation by CheR, restoring activity. This is a return from receptor activity to the machinery regulating that activity. The response need not return exactly at every dose. ^[ref]

A motivating measurement is the chemotaxis FRET assay. CheY and CheZ carrying yellow and cyan fluorescent tags were observed in immobilized Escherichia coli biological cells on a coverslip in a flow chamber. Adding and removing attractant changed the yellow-to-cyan emission ratio, reporting the association of phosphorylated CheY with CheZ. This measures a molecular readout upstream of motor behavior. Comparisons with biological cells lacking CheR, CheB, or both tested the dependence on receptor modification; these perturbations also change starting activity and sensitivity, so they are not pure changes of one feedback gain. ^[ref]

The later chemotaxis feedback regulation experiment used only the Tar receptor and nonmetabolizable methylaspartate, supplied and removed by flow. Long recordings separated slow recovery from incomplete signaling adaptation; correction for bleaching addressed drift in the optical readout. Activity recovered incompletely after sufficiently large additions, with detectable imprecision already at $10\mu \mathrm{M}$ in that preparation. Restricting the receptor type and preventing consumption of the stimulus help interpret the perturbation, but limit transfer to other receptors and conditions. The readout infers CheA activity through CheY-CheZ association, rather than directly measuring every molecular step. ^[ref]

Negative feedback can also overshoot or sustain oscillations if its return arrives too late. The worked signaling feedback example gives the contrasting instantaneous case; the delayed negative feedback model below isolates the effect of timing. Loop sign describes causation, while asymptotic stability describes what happens to displacements over time.

A ratio compares two quantities $a,b$, written $a:b$ and corresponding to division $a/b$ when $b\ne 0$. Equal ratios of corresponding lengths characterize the scaling of similar triangles.

For example, $6:4$ and $3:2$ specify the same ratio because $6/4=3/2$. Multiplying both entries by the same nonzero scale preserves the quotient: $(ca)/(cb)=a/b$. This is useful when comparing mixtures or scaling a recipe; doubling both ingredient amounts preserves their ratio, while adding the same amount to both generally does not. For quantities with the same physical units, their ratio is dimensionless, connecting this elementary calculation with dimensional analysis.

A receptor phosphorylation assay asks whether, and how much, a specified receptor is modified by phosphorylation under defined conditions. It is distinct from a binding assay for receptor binding occupancy, a test of protein kinase activity on a supplied substrate, and a test of downstream signal transduction. Those measurements answer related but different questions.

For a Western blot implementation, compare matched samples with ligand omitted or added, detect a specified phosphorylated epitope, and separately detect total receptor abundance. Preserve the sampled state by stopping further enzyme reactions during sample preparation; otherwise protein kinase or protein phosphatase activity after sampling can change the result. A general anti-phosphotyrosine residue antibody recognizes many modified proteins; a site-selective antibody gives a narrower readout, but still needs Western blot antibody specificity controls.

Reason through the controls before interpreting the difference. Loss of the proposed signal after receptor-specific gene deletion supports protein identity. Treatment with a protein phosphatase, alongside preservation of the total-receptor signal, tests phosphate-dependent recognition. Western blot loading controls and Western blot transfer controls address sample recovery; a usable detection range addresses Western blot response saturation. Lower signal after perturbing protein kinase activity supports dependence on that perturbation, but alternative targets and altered receptor abundance can complicate the inference. These are proposed assay comparisons, not outcomes attributed to the historical membrane experiment.

An original idealized measurement model explains the normalization. Let $N$ be the retained number of receptor molecules, $f$ the fraction carrying the selected modified epitope, and $c_p,c_t>0$ fixed detection gains. After subtracting their respective backgrounds, suppose the phosphorylated and total-receptor signals lie in a linear response range:Dividing by total receptor cancels $N$ under these assumptions. It differs from total-protein Western blot normalization, whose denominator includes many other proteins. For invented values $c_p=c_t=1$, samples with $(N,f)=(100,0.2)$ and $(200,0.2)$ give $A=20$ and $40$, but both give $A/B=0.2$. Twice the phospho signal here means twice the retained receptor amount, with no change in fractional modification. Unequal recovery, changed epitope accessibility, nonzero uncorrected background or Western blot response saturation invalidates the cancellation. Unknown relative gains prevent reading an absolute modified fraction directly from the ratio.

Signal amplification is an increase in a specified downstream response relative to an initiating signal. In a molecular-count description, one activated component can generate or activate many downstream molecules. Repeated catalysis by an enzyme supplies a mechanism: the enzyme remains available for another chemical reaction. Successive stages can multiply the response. For a biological example, Cooper describes the epinephrine-to-glycogen phosphorylase pathway, where production of many cAMP molecules and repeated downstream protein phosphorylation provide opportunities for signal amplification. This is an example, not a claim that every signal transduction pathway has the same stages or gain. ^[ref]

Here is a counting toy extending the example under signal transduction. Suppose $N_0$ activated receptors each activate $a=5$ distinct relay proteins during a first interval. During a subsequent interval, each relay activates $b=20$ distinct target proteins. Assume enough inactive relays and targets, no shared targets, and no loss of activity during the count. ThenFor $N_0=1$, this gives $N_1=5$ and $N_2=100$: the target-to-receptor count ratio is $100$. These are assumed integer counts, not measured rates or a universal physiological amplification factor. The intervals are sequential; the equations do not specify a time course.

Availability limits the multiplication. As a second toy assumption, let there be only $T=250$ initially inactive target proteins shared by all branches, and suppose the branches can activate distinct targets until this pool is exhausted. ThenTwo activated receptors give $200$ active targets, whereas three give $250$, not $300$. At three activated receptors, the total count ratio is $250/3\simeq 83.3$; adding a fourth activates no additional targets. Thus total output per input and the increment caused by an extra input are different notions of gain. This finite-pool rule is an illustrative bound, not an enzyme kinetics law.

Signal amplification makes a small initiating signal capable of a larger response, but it does not supply the material or energy for downstream chemical reactions. In the second messenger transfer experiment, both stages still required added ATP and magnesium ions. Counts, changes in concentration, and changes in enzyme activity are different readouts; an amplification claim should name its input, output and observation interval. ^[ref]

Two triangles are similar if a Euclidean similarity maps one onto the other. Their corresponding angles agree, and corresponding side lengths have a common positive ratio.

Specify the correspondence first: $A$ matches $A^{\prime }$, $B$ matches $B^{\prime }$ and $C$ matches $C^{\prime }$. For similar triangles, the common scale factor $k>0$ satisfiesThe ratios compare matching sides in the same order. A Euclidean similarity can also move, turn or reflect the triangle; its orientation on the page is irrelevant. In the Euclidean plane, matching just two interior angles is enough: their sums force the third to match, and equal corresponding angles force the side ratios to agree. This is the angle-angle (AA) criterion for similar triangles. Matching just one angle is insufficient.

Scale the right triangle with vertices $(0,0)$, $(4,0)$ and $(0,3)$ by $k=2$. Its new vertices are $(0,0)$, $(8,0)$ and $(0,6)$, and its side lengths are $6,8,10$. The matching side ratios are $6/3=8/4=10/5=2$. Both triangles have a right angle and the same two other interior angles, approximately $36.87^{\circ }$ and $53.13^{\circ }$. However, their areas are $3\cdot 4/2=6$ and $6\cdot 8/2=24$: doubling lengths multiplies area by four.

Generally, a Euclidean similarity multiplies both a base and its perpendicular height by $k$, so the area becomes $\frac{1}{2}(kb)(kh)=k^2\frac{1}{2}bh$. This explains why an enlarged drawing needs four times as much surface when each length doubles. It also enables indirect measurement: under assumptions of level ground, vertical objects and parallel light rays, an object of height $3$ casting a shadow of length $4$ provides a right triangle. Another object's shadow of length $8$ gives a similar triangle and height $3(8/4)=6$. The shared angles justify the inference; visual resemblance alone does not.

Euclid's Elements VI, Definition 1 describes similarity using corresponding angles and proportional sides. VI.4 establishes the implication from matching angles to matching side ratios, while VI.19 states the squared relation between side ratios and areas. These are documented ancient formulations of the principles used above, without establishing a first discoverer.^{[ref][ref][ref]}