very recently , the journal of medicinal chemistry embraced the qhnmr concept by including absolute qhnmr as an acceptable 
 and established scientific method for purity analysis . as a quantitative method , qhnmr continues to 
 gain popularity in the biopharmaceutical industry and acceptance by 
 the international conference on harmonization ( ich ) .
notably , qnmr 
 is a ( relative ) primary analytical method and is part of the general chapter < 761 > of the united 
 states pharmacopeia ( usp ) as well as an official method in 
 the japanese pharmacopoeia ( jp17 ) . with respect to the development of quantitative methodology for 
 botanical standardization , the application potential of qhnmr for 
 purity analysis , residual complexity studies , metabolomics , multimarker 
 standardization , and orthogonal quantitation has been demonstrated . due to the presence of very many components , 
 possible excipients , and the resulting intense signal overlap ,
thus , 
 while established qhnmr methods work well for a single component and 
 relatively simple mixtures , analysis of such complex samples demands 
 an expanded qhnmr tool box .
in general , the choice of appropriate 
 quantitative measures in qhnmr depends on the type of sample and the 
 required accuracy . in classical qnmr
, both relative and absolute quantitation 
 methods rely on signal integration ( int ) . as int - qhnmr
is by far the 
 most practiced form of qnmr , both accuracy and precision of most contemporary 
 qnmr methods depend on the means of the integral measurement .
presently , 
 three mechanistically different quantitative measures exist apart 
 from classical int - qhnmr ( figure 1 ) .
one entails peak height measurements , but due to 
 limitations related to resolution of resonances and signal multiplicity , 
 it was rendered impractical for this , given the complex peak overlap 
 in the rce qhnmr spectrum . before delving into the mechanistic differences 
 of the two spectral deconvolution ( sd)-based approaches used in this study , it is important 
 to differentiate the often interchangeably used terms  line  , 
  peak  , and  resonance  .
multiple lines 
 constitute an nmr resonance ( or a signal that is the digital visual 
 output of a resonance ) due to the presence of scalar couplings ( giving 
 rise to signal multiplicities ) .
the number of observable lines depends 
 on the digital resolution as well as the natural line width of the 
 signals .
peaks refer to only the visual  top  of each 
 line or resonance .
it involves sd of select 
 lines or entire spectra via mathematical peak fitting ( pf ) algorithms . 

pf - qhnmr methods take a one - by - one approach to the fitting of visible 
 peaks ( not spectral lines ) and do not involve quantum mechanical ( qm ) 
 calculations of the underlying spin systems .
the third alternative 
 to integration , builds on the method of h iterative full 
 spin analysis ( hifsa ) and consists of the qm - driven generation of a simulated 
 qhnmr spectrum .
this spectrum accumulates the subspectra of all individual 
 components , and the underlying qm simulation includes their individual 
 line shape characteristics as well as the relative intensities as 
 present in the mixture . intrinsically , the qm simulations yield precise 
 intensities for all resonances , including those belonging to non - first - order 
 ( i.e. , higher order ) spin systems .
the presence of non - first - order 
 situations is nearly inevitable in h nmr , even at very 
 high magnetic field strengths ( equivalent to 700 mhz h ) , and its impact on qhnmr quantitation continues to be underrated 
 despite the availability of well - established spin simulation tools . in qhnmr , 
 aside from peak height quantiation ( see text ) , three principal methods 
 with different characteristics ( yes / no ) exist for the extraction of quantitative measures 
 (  numbers  ) that reflect the molarity of the analytical 
 response to be used for the quantitative calculation .
( i ) classical 
 integration ( int - qhnmr ) calculates the areas - under - the - curve of discrete 
 regions of the spectra .
( ii ) spectral deconvolution ( sd ) that employs 
 peak fitting methods ( pf - qhnmr ) , such as global sd ( gsd ) , are limited 
 by line and peak assignment , especially in the case of non - first - order 
 effects .
qm - qhnmr derives 
 exact measures from the spin populations of all target analytes .
it 
 has the ability to account only for relevant individual line intensities , 
 thereby excluding  impurities  from the quantification . during the initial stage of this 
 study ,
it became evident that both sd methods ( qm - based and non - qm / pf ) 
 outperform the classical region - based integration ( int - qhnmr ) in terms 
 of achievable accuracy and precision , especially with complex samples 
 such as the rce or similar natural products .
with deconvolution processing 
 being the common denominator in sd , one major aim of the study was 
 a systematic comparison and exploration of the capabilities of the 
 two methods for covering a wide dynamic range of analytes .
additional 
 study goals related to the multidisciplinary study context , supporting 
 the continued biological studies of the rce , are the establishment 
 of an orthogonal analytical means of chemical standardization , as 
 a means of advancing the accuracy of standardization , and the need 
 to ( re)assess the stability of the extract , using these new methods . 

the recently developed hifsa fingerprinting and hifsa - qhnmr methodologies were enabling technologies for these aims : they could 
 be applied to the relatively complex rce sample and results could 
 be compared with those from previously published hplc - uv and lc - ms 
 standardization . moreover , to generate 
 an independent data set that is mechanistically congruent with the 
 studies performed some 10 years ago , a fast 10 min uhplc - uv method 
 was developed that allowed both chromatographic fingerprinting and 
 quantitation .
lc - uv / ms are the most commonly used analytical methods worldwide , 
 partly as a result of the widely abundant instrumentation and the 
 relatively high sensitivity of uv and ms detection . while often categorized 
 as a relatively insensitive method , qnmr analysis typically requires 
 only 1530 min of instrument time , especially when samples 
 are not mass limited and/or when the mass sensitivity of the instrumentation 
 is high ( cryoprobes , microprobes ) .
importantly , the identical and 
 costly reference materials required for any lc - based quantitation 
 are entirely dispensable in qnmr .
another intrinsic advantage is that 
 multitargeted analysis can be performed on a single nmr sample , using 
 standard qhnmr conditions , and can be repeated as needed .
furthermore , qhnmr provides valuable 
 spin parameter information simultaneously with quantitation , thereby 
 enabling a thorough structural characterization of the constituents . 

the use of well - established quantitative conditions assures that signal 
 intensities in qhnmr spectra are directly proportional to the molarity 
 of hydrogen atoms giving rise to them .
notably , qhnmr is unaffected 
 by response factors , which are inevitable in lc - based quantitation .
considering these main advantages of qhnmr , including its time 
 efficiency , simplicity of sample preparation , linearity of signal 
 response , independence of sample intrinsic factors , and even cost 
 considerations , qhnmr offers a unique set of attractive properties , 
 making it a standardization method that deserves broader consideration 
 in the botanical research community and industry .
furthermore , qhnmr 
 can recognize dynamic properties such as chemical exchange ( e.g. , 
 keto  enol tautomerism ) or rotational / conformational isomerism , 
 along with the identification of uv - transparent and/or poorly ionizable 
 molecules .
while such phenomena often evade lc / ms - based analysis , 
 they can be important for the explanation of biological outcomes . in light of the natural variation of phytoconstituents 
 in source plants and the potential overlap with ( chemo-)taxonomically 
 related and unrelated species ( both authentic species and adulterants ) , 
 the specificity of botanical standardization increases with the number 
 of markers used and their individual chemotaxonomic ( sub)species specificity . 

compared to the quantitation of a single marker , multimarker schemes 
 enhance the significance of the standardization method by capturing 
 a wider chemical window of the botanical metabolome .
accordingly , 
 over the years , the development of new standardization protocols at 
 the uic botanical center has progressed from oligo- to multimarker / metabolomic 
 schemes , in order to better capture the metabolic complexity of botanical 
 preparations .
the underlying hypothesis of this approach is that metabolomic 
 standardization enhances the measure of botanical integrity and is 
 the key to better reproducibility in botanical research .
as the number of targeted markers increases , the experimental effort 
 for lc - based methods increases overproportionally due to the requirement 
 of having high - quality ( purity ) reference materials available for 
 each of the target compounds .
as the chemotaxonomic significance and 
 abundance ( % content ) are often mutually exclusive properties , this 
 leads to substantial isolation efforts associated with the purification 
 of multi - milligram amounts of minor constituents .
this is often rendered 
 impractical and the main contributing factor why multimarker standardization 
 schemes are not used more widely despite their acknowledged significant 
 advantage .
while there might be 
 a need for the use of such compounds in the initial establishment 
 of a qhnmr method ( e.g. , for the confirmation of peak assignments 
 and assessment of method specificity , see discussion below ) , all subsequent 
 qhnmr analyses can be performed without these reference materials . 

in addition , qhnmr is fully capable of multitargeted quantitation , 
 as shown recently for preparations from ginkgo biloba and glycyrrhiza species .
achieving a targeted multimarker standardization of the rce using 
 qhnmr was one important methodological aim of this study .
the first 
 step toward a qhnmr - driven multimarker standardization is the identification 
 and unambiguous assignment of the signals of the target components 
 in the qhnmr spectrum of a mixture .
isoflavones 19 ( chart 1 ) 
 and the flavonols 10 and 11 were identified 
 in the rce spectrum .
the isoflavone signals 
 were divided into four key regions ( figure 3 ) : region 1 consisting of the 
 methoxy proton signals from the b - ring ( 3.54.0 ppm ) ; region 
 2 with the signals of the a - ring protons h-6/h-8 ( 6.06.7 ppm ) ; 
 region 3 with the signals of the b - ring aaxx or amx 
 spin systems ( 6.78.0 ppm ) ; and region 4 containing the c - ring 
 h-2 singlets ( 8.28.5 ppm ) .
signal assignment in region 3 was 
 the most challenging due to a combination of intense overlaps and 
 higher order effects .
the characteristic h-2 singlets in region 4 
 enabled the determination of the total isoflavone content of the extract . 

the h-2 resonances maintained their singlet property even after the 
 application of very strong lorentzian 
gaussian resolution enhancement 
 window functions , proving their  pure singlet  characteristics . 

this was in line with the predictable lack of observable long - range 
 couplings for these protons : the only potential coupling partners 
 are located in the b - ring , giving rise to j and j couplings that evidently are 
 well below the natural line width of the h-2 signal ( 1 hz ) 
 and even lower than the achievable signal splitting ( 0.4 hz ) .
non - qm 
 deconvolution of region 4 of the rce qhnmr spectrum using the global 
 spectral deconvolution approach .
the deconvoluted signals of the internal 
 calibrant ( ic : 3,5-dinitrobenzoic acid ) , the isoflavones 17 , and flavonoid 10 are labeled . 

the colored lines represent the sum ( blue ) , the fitted peaks ( green ) , 
 and the residual ( red ) of the deconvolution process .
stacked qhnmr spectra ( dmso - d6 ; 600 mhz ) 
 of the red clover extract and the isoflavones were divided into four 
 key regions representing different spin systems present in the isoflavones .
6 , prunetin ; 5 , calycosin ; 4 , daidzein ; 3 , genistein ; 2 , formononetin ; 1 , biochanin a ; rce , red clover extract . the nmr spin parameters for 
 ps , pb , and ir were obtained from metidb . depending on the type of 
 the spin system , the a - ring protons fall into either region 2 ( aaxx ) 
 or 3 ( amx ) .
the signals of biochanin 
 a ( 1 ) , formononetin ( 2 ) , irilone ( 7 ) , and quercetin ( 10 ) were assigned unambiguously 
 by stacking of reference spectra and , in the case of 7 , based on the data in the literature . to demonstrate the specificity of close resonances , the assignments 
 for genistein ( 3 ) , daidzein ( 2 ) ,
calycosin 
 ( 5 ) , and prunetin ( 6 ) were confirmed using 
 spiking experiments .
the resonances of the isoflavones pratensein 
 ( 8) and pseudobaptigenin ( 9 ) were initially 
 assigned based on previously published results . except for the methoxy protons ,
this naturally 
 gave rise to severe overlap in the spectrum of an extract sample .
for 
 example , the 7.36 to 7.40 ppm portion of region 3 of the rce spectrum 
 contained a set of two protons from an aaxx system 
 belonging to four minor isoflavones , which altogether represented 
 eight individual protons ( figure 4b , blue region ) .
such a high level of complexity precluded 
 the use of classical integration and posed a significant challenge 
 for an exact assignment .
moreover , field - dependence resulting from 
 the involvement of non - first - order spin particles intrinsically limits 
 the transmission of classical integration and non - qm linear sd outcomes 
 between laboratories .
even when considering a region with relatively 
 simple resonances , such as region 4 , the observed signal resolution 
 still does not allow sufficiently broad or even uniform integral ranges . 

for example , the h-2 singlet of genistein ( 3 ) at 8.3083 
 ppm overlapped with the corresponding h-2 singlet of pseudobaptigenin 
 ( 9 ) at 8.3132 ppm , and the signals of both the minor 
 components were riding on the feet of the h-2 singlet of the major 
 isoflavone formononetin ( 2 ) ( figure 4b , green region ) .
another close overlap occurred 
 between the h-2 singlets of daidzein ( 1 ) and calycosin 
 ( 5 ) at 8.2743 and 8.2770 ppm , respectively . in this case , 
 spiking experiments combined with hifsa were necessary to ensure unambiguous 
 assignment of the minor constituents .
regions 3 and 4 of the qhnmr spectrum 
 of rce were the most relevant for the qhnmr analyses .
panel a shows 
 the signal assignments of the two major isoflavones 1 and 2 .
magnified expansions of the colored regions 
 in panel b show the assignments of the seven minor isoflavones 39 and the flavonols 10 and 11 to demonstrate the importance of quantitative measures 
 derived from qm - based deconvolution in strongly overlapping spectra 
 ( ic , internal calibrant ; 3,5-dinitrobenzoic acid ) . whereas signal overlap can be resolved for the 
 purpose of analyte assignment
, the complexity of 
 the situation also shows that resolution of the underlying individual 
 peak areas is not straightforward and can not be achieved 
 by simple definition of ( integral ) ranges .
this underscores again 
 that classical integration is not a viable quantitative measure for 
 most complex mixtures .
some of the signals belonging to pratensein 
 ( 8) , pseudobaptigenin ( 9 ) , and kaempferol 
 ( 11 ) were completely masked by major isoflavone signals , 
 thus lowering the confidence with which the minor markers can be quantified 
 compared to other constituents .
for instance , five 
 out of the eight nmr signals for 9 were masked partially 
 or completely by those of the major constituents . despite the exclusion 
 of 8 , 9 , and 11 from full 
 quantitative analysis , their identification and assignment in the 
 rce nmr spectrum helped improve the overall match between the observed 
 and the calculated spectrum when using the qm - based approach ( hifsa ) , 
 especially for the 6.807.05 ppm portion of region 3 ( figure 4 , red region ) . 

the spin parameter set ( pms ) ( perch parameter file ) files for 8 and 9 were built based on data obtained from 
 the metidb .
as per the literature , the 
 h-2 singlets for both 8 and 9 in dmso - d6 appeared at 8.32 ppm . insufficient reporting of ( relative ) nmr chemical shifts in the 
 literature precludes the successful dereplication and accurate assignment 
 in a more complex sample , especially with regard to the frequently 
 relevant non - first - order effects .
this once more reinforces the importance 
 of reporting h nmr chemical shifts with at least four 
 decimal points ( 100 ppb level ) , as shown earlier . while concentration and sample matrix effects in complex samples 
 such as extracts typically necessitate adjustments of absolute  values ( accuracy ) , the relative frequencies 
 of the various resonances (  ) of a given analyte are 
 much more stable than generally considered .
in fact , reporting  or  values with 100 ppb precision is a 
 valuable means of identifying analytes and improving the specificity 
 of a qhnmr method .
this can be exemplified by pratensein ( 8) : the literature assignments of the chemical shifts of the two highly 
 coupled protons h-5 and h-6 in 8 as 6.95 
 and 6.96 ppm , respectively , resulted in a higher order effect that 
 transformed the h-2 signal into a pseudotriplet instead of 
 a doublet .
a side aspect of this observation is that it serves as 
 a reminder of the often forgotten fact that peak separation in h nmr spectra is not identical to coupling constants .
the 
 first - order doublet property of the h-2 signal without higher 
 order effect in the rce spectrum was contradictory and indicated that 
 the  between h-5 and h-6 must indeed 
 be larger than their coupling constant ( > 8 hz ) .
thus , the signal 
 assignments for 8 were refined through iterative optimization 
 ( figure 5a / b ) . however , 
 we speculate that there might be two reasons behind this observation . 
 one is the plausible matrix effect of the extract , and the second 
 could be misreporting ( incorrect or inadequate ) of the nmr spectroscopic 
 parameters in the literature , as indicated above .
chemical shifts 
 and/or line shapes of the signals of pure vs target compounds in the 
 extract can be affected by the temperature , sample matrix , ph , and/or 
 water content .
notably , the h nmr spectrum of rce without 
 3,5-dinitrobenzoic acid ( 3,5-dnb ) added also showed the signal for 
 h-2 in 8 as a doublet , ruling out the possibility 
 of a drastic chemical shift perturbation due to the addition of an 
 internal calibrant ( ic ) .
hifsa was capable of resolving the higher 
 order effects observed in the case of calycosin ( 5 , figure 5c / d ) , 
 as well as achieved assignments of the signals of 5 and 8 and in the spectral region with the most intense overlap . 

using an algorithm that sets strong probability distribution ( prior ) on metabolite resonance patterns , the recently developed 
 bayesian sd approach allows automated peak ( re)assignment under conditions 
 of sample - dependent resonance shifts (  ) , but by default can not overcome the intrinsic 
 limitations of non - qm - based methods .
representative portions of the qm - qhnmr spectra of rce 
 showing the high congruence of the experimental ( red ) and qm - simulated 
 ( blue ) spectra .
panels a and b show the assignments of the b - ring 
 amx system of the minor isoflavone pratensein ( 8) before 
 and after the qm - based optimization ( iteration ) , respectively .
panels 
 c and d demonstrate the higher order effect observed in the b - ring 
 amx system of calycosin ( 5 ) in the pure isoflavone ( c ) 
 and the signal assignments in the rce ( d ) ( * indicates the assignment 
 of h-6 of 5 in the rce ) .
along with the quantitation of individual components , qhnmr 
 also enabled the close approximation of the total isoflavone content 
 of the extract .
the presence of a deshielded c - ring h-2 singlet resonance 
 in the 8.20 to 8.55 ppm region is highly characteristic of all isoflavones 
 and leads to the formation of  chromatogram - like 
nine 
 of the ten isoflavone singlets observed in rce could be identified , 
 and seven could be quantified using the qm - based hifsa - qhnmr method . 
 in this way ,
integration of h-2 resonances in the entire region 4 
 against the calibrant signals was used to estimate the tifco of the 
 rce .
the inter - isoflavone signal overlap was not critical , as region 
 4 was well isolated from the signals of the other regions in the spectrum 
 ( figure 3 ) .
if interfering 
 signals were present , a more elaborate sd approach would be necessary . 

linear sd performed with the total line shape ( tls ) module of the 
 perch software was used as a second means of estimating the tifco . 

quantitation was done with reference to the ic signals , and a weighted 
 average of the individual molecular weights of the isoflavones was 
 used to determine the tifco as a total average isoflavone 
 content . using the integration and the tls methods ,
the tifco in the 
 rce was estimated to be 34.5% and 36.5% w / w , respectively ( table 2 ) . given preference to the deconvolution method , this outcome showed 
 that it is feasible to standardize an rce to its tifco , instead of , or in addition to , the individual isoflavone percentages , in a single - step 
 qhnmr analysis .
peak picking and deconvolution used the pac and tls modules 
 of the perch software tool , respectively .
the weight percentages of isoflavones obtained from the 
 qm - qhnmr analyses were used to calculate the weighted average of the 
 molecular weight of the isoflavones as a whole . the 100% normalization , internal calibrant ( ic ) , and external calibrant 
 ( ec ) methods are the three established 
 modes of quantitation in qhnmr , differing in the way calibration is 
 achieved .
additionally , an ec can be used to calibrate the ( residual ) 
 solvent signal , which can then be used as an ic for an extended series 
 of qhnmr analyses ( ecic method ) , provided 
 the same batch of solvent is used throughout and the exact volume 
 is known . traditionally , these quantitation modes have employed manual 
 integration of the nmr signals as a quantitative measure .
classical 
 integration is most commonly used for the purity evaluation of single 
 chemical entities such as isolated or synthesized compounds and can 
 be used successfully for slightly complex mixtures . however , the classical 
 integration approaches are limited or even inadequate for the analysis 
 of more complex samples such as plant extracts , foods , or biological 
 fluids .
this is a result of the discrepancy between the widths of 
 resonances and the chemical shift dispersion required for clean , nonoverlapped 
 signals for integration .
the former depends on the natural spectral 
 line width (  ; 1 hz or slightly below in well - shimmed 
 spectra ) and the total width of the individual resonances , which is 
 the sum of all j values plus 2 , but 
 notably only as long as first - order assumptions apply .
moreover , reliable 
 integration requires relatively wide integration ranges ( 510 ) 
 in order to capture the full resonance , depending on the accuracy 
 requirements .
another confining factor is the presence of c satellite signals , which limits the width of integral ranges and 
 produces an additional level of signal overlap with minor constituents . 

collectively , these challenges explain why advancement of quantitative 
 measures is required to make 1d qhnmr fit for the purpose of metabolomic 
 standardization.whereas chemometric approaches employing multivariate 
 analysis can be used for untargeted nmr metabolomics , some form of 
 deconvolution ( peak fitting ) is needed to achieve a targeted quantitative 
 analysis of known metabolites , but also of unknowns when assuming 
 molecular structures and weights .
moreover , generic software 
 tools exist for highly flexible curve fitting , such as fityk ( http://fityk.nieto.pl/ ) and general 
 commercial statistics tools .
one of the recent developments in this 
 area geared toward nmr spectra is the bayesian deconvolution and quantitation 
 of metabolites using the automated batman software .
this r package 
 enables automated peak assignment and quantitation based on a list 
 of chemical shifts of the metabolites entered by the user .
the present study entailed a targeted qhnmr multimarker standardization 
 using two methods : a qm - based approach , which utilized the previously 
 developed h full spin analysis to deconvolute the entire 
 qhnmr spectrum , and a non - qm sd method that used the gsd function 
 of the mestrenova nmr software tool .
the 
 qm - based method had previously been termed hifsa - qhnmr , in reference 
 to the use of the hifsa process for sd , and emphasizes the iterative 
 nature of the qm deconvolution process for h nmr spectra . 
 using
the same approach for deriving quantitation measures in qhnmr 
 has also been termed quantitative , quantum - mechanics - based spectral 
 analysis ( qqmsa ) . in this serum metabolomics 

study , qm - based stoichiometry of the target analytes required prior 
 knowledge about the sample via the use of multiterm baseline functions 
 to address extensive background , as well as optimizable and adjustable 
 lines , regular multiplets , or constructs composed of spectral lines 
 to account for unknown signals .
however , in order to consolidate the 
 nomenclature of the shared qm aspects , the present study used qm - qhnmr 
 ( quantum mechanical quantitative h nmr ) to highlight the 
 benefit of using quantum mechanical calculations to derive the quantitative 
 measures , while continuing to refer to hifsa for the actual sd process , 
 involving full spin analysis through iterative calculations . even under very careful 
 experimental conditions , the analysis of qhnmr spectra is limited 
 by a variety of factors such as incomplete signal assignments , extensive 
 signal overlap , and imperfect baselines .
these confounding factors 
 are encountered commonly in the spectra of complex natural product 
 samples such as rce .
collectively , they influence the choice of the 
 spectral window that is amenable to iteration or integration and , 
 thereby , impact the achievable quantitative results .
however , when 
 compared to non - qm deconvolution , qm - based hifsa sd yields a much 
 enhanced resolution of signal overlap by virtue of the qm - based calculation 
 of individual spectral lines .
this includes all interdependencies 
 of the individual lines , especially in non - first - order situations , 
 which are very common .
for instance , the h-2/6 signals 
 of irilone ( 7 ) and prunetin ( 8) almost perfectly 
 coincided with each other , as well as overlapped with those of the 
 aaxx spin systems of genistein ( 3 ) and 
 daidzein ( 4 ) ( figure 4b ) . the ability to assess the contribution of each 
 component in such highly overlapped resonances and correctly assign 
 peaks to individual components has to take into consideration the 
 system of all spin particles ( i.e. , atoms ) involved . thus , the resolution 
 of signals where multiple degenerated lines from both the individual 
 and one or several other species overlap inevitably requires a qm 
 approach ( figure 1 ) . 
 in contrast , non - qm , linear sd based approaches fail at this level 
 of complexity , leaving the selection of the cleanest region with the 
 least overlap as the only and predictably error - prone option for quantitation . 

collectively , this explains the intrinsic limitation of non - qm - based 
 deconvolution as a quantitative measure in qhnmr . despite its advantage 
 over classical integration , sd
is flawed systematically and , thus , 
 less rigorous for building comprehensive analyses of multiple components 
 in complex mixtures .
analogous to chromophores 
 in uv- and molecular / fragment masses in ms - detected quantitation , 
 qm is key to the definition of the spin parameters of the target compounds 
 and ultimately guides the prerequisites of qm - qhnmr analyses .
additionally , non - qm , peak - fitted lines of unknown components can be added to improve 
 the overall fit , their quantitation requires the assignment of partial 
 structures and amu values .
while any assumptions made in this process 
 become part of the systematic error of the initial quantitation , additional 
 knowledge gained afterward can be used to eliminate such errors due 
 to the inherent calibration characteristics of qhnmr .
qm - qhnmr 
 does not face this limitation for the development of multimarker standardization 
 approaches . using the hifsa deconvolution mechanism ,
in contrast , other non - qm sd methods are  nmr - blind  
 and limited to modeling certain peak shape assumptions such as lorentzian or gaussian line shapes . as couplings and higher 
 order effects involve multiple individual spins , non - first - order effects 
 encode spectral information into the nmr resonances of coupled spin 
 particles in other regions of the spectrum that might be subject to 
 less overlap .
as qm assures the integrity of these interdependencies , 
 the degree of freedom and the number of iterative solutions that are 
 consistent with the qm rules are reduced considerably , because only 
 chemical shifts and coupling constants need to be optimized rather 
 than frequencies and intensities for each single line .
thus , an important thing 
 to note is that application of any qm method does require at least 
 partial characterization of an analyte of interest in order to enable 
 the use of accurately predicted and simulated spin parameters . while 
 fully defined spin systems of target compounds with known molecular 
 weight are desirable , the qm definition of partial spin systems (  spin 
 cages  ; e.g. , sugars , amino acids ) still enables targeted quantification 
 of full or partial structures .
qm - qhnmr utilizes the quantum mechanically 
 simulated spectra , which represent the most accurate achievable replicas 
 of the experimental spectra of the target analytes and can be derived 
 from predicted initial spin parameters via an iterative qm calculation .
importantly , because it employs the same mechanisms as hifsa profiling 
 does for pure compounds , qm - qnmr performs a qm - based sd of all spectral lines , not just of the ( visible ) peaks , 
 of a given species in a mixture .
considering that individual peaks 
 often consist of more than one line and that multiple peaks constitute 
 the composite h signals ( i.e. , resonances ) of a given 
 proton , this has far reaching consequences for both the qualitative 
 and quantitative interpretation of hnmr spectra : the distinction of lines and consideration of their intensities is fundamental 
 to the accurate interpretation of all hnmr signals .
the quantum mechanical description of a spin system correlates 
 frequencies and intensities of the corresponding lines not only for 
 each spin particle but via spin 
these constraints dramatically reduce the 
 number of variables and allow the complete sd of even completely overlapping 
 lines also in the presence of higher order effects . in the relatively 
 rare case of a pure first - order spin system these constraints degenerate 
 to the simple first - order rules . in practice , significant proportions 
 of the intensity of hnmr signals can reside outside the 
   peak range  assigned to the respective 
 proton ( regardless of its assigned multiplicity ) , explaining at least 
 in part the widely experienced relative weakness of int - qhnmr . taking 
 into account the observed and/or achievable natural line width and 
 signal - to - noise of the experimental spectra ,
it becomes evident that 
 these effects can add considerable error to the accuracy and precision 
 of sd methods in pf - qhnmr and , even more so , to classical int - qhnmr .
in contrast , qm - based sd is less limited when analyzing the same 
 experimental data . due to the ability to correlate spin particles 
 through the underlying qm rules ,
the intensity information on individual 
 lines is encoded in the intensity of other lines as well . as a result
, 
 qm - qhnmr has the ability to automatically exclude line(s ) ( intensity ) 
 that can not be explained by the given spin system(s ) of the target 
 analyte(s ) from the quantification . in other words , qm - based sd methods 

have superior accuracy by virtue of their inherent capability to account 
 only for the intensity of those lines ( consequently also peaks and 
 signals ) that truly belong to the analyte .
in addition to its 
 higher intrinsic accuracy , the hifsa deconvolution process imparted 
 in qm - qhnmr enabled a thorough qualitative analysis 
 of the spectra and validated the identity of the target compounds 
 simultaneously with their quantitation .
once a library 
 of hifsa spin parameter sets has been created for the individual compounds , 
 a multitarget quantitation can be performed for any mixture containing 
 these components .
hifsa has been shown to be fit for the purpose of 
 obtaining the exact chemical shifts up to ppb level accuracy , as well 
 as coupling constants with 10 mhz precision .
this level of detail is particularly critical in the case of regio-/stereoisomers , 
 higher order spectra , and when determining small coupling constants 
 that can not readily be detected visually .
especially when considered 
 as precise relative values (  and  ) , this helps in structural dereplication , confirmation , 
 and differentiation of closely related analogues .
practical considerations 
 of hifsa processing involved the use of the integral optimization 
 module ( d - mode , coarse adjustment ) of the perch iterator , which helped 
 with the optimization of the chemical shifts , coupling constants , 
 and signal intensities , thereby optimizing the relative ratios of 
 the target components . the total line shape module ( t - mode , fine adjustment ) 
 was used subsequently to refine the simulation of signal overlaps , 
 deconvolute fine line shapes , and achieve the best overall match of 
 the line characteristics of the spectrum . in this study ,
the iterations 
 were performed until the observed and calculated spectrum were visually 
 identical as indicated by a rms value of 0.1 . as the j coupling constants are largely unaffected by extrinsic 
 interactions in the sample , they were kept fixed during the hifsa 
 iterative processes , typically after performing an initial optimization . 

also , a  fit and lock  method was utilized for certain spin parameters of the more problematic 
 regions of the spectrum .
alternatively , in principle it is possible 
 to mask and , thereby , exclude a certain region that still can not be 
 assigned reliably due to excessive overlap or unknown impurities , 
 in order to achieve a converging iteration for the rest of the spectrum . 
 in this scenario ,
hifsa sd retains its qm advantage via conservation 
 of the underlying spin parameters , as long as the spin particles belonging 
 to the molecule present in the overlapped region are also present 
 elsewhere in the spectrum .
additionally , overlap with unknown components 
 can be mimicked by adding simulated ( non - qm ) lines that represent 
 these unknowns , improving the overall fit and giving lower global 
 rms values . a local rms value of 0.030 for the most relevant region 
 of interest ( 7.6 to 9.0 ppm ) indicated an excellent match between 
 the calculated and experimental spectrum ( figure 6 ) .
the percent w / w content of the isoflavones 
 biochanin a ( 1 ) , formononetin ( 2 ) , genistein 
 ( 3 ) , daidzein ( 4 ) , calycosin ( 5 ) , prunetin ( 6 ) , irilone ( 7 ) , and the flavonol 
 quercetin ( 10 ) in the rce was determined as 15.2 , 16.0 , 
 0.64 , 0.40 , 0.53 , 0.71 , 2.21 , and 1.43 , respectively , using the qm - qhnmr 
 method ( table 1 ) . observed 
 ( top / blue ) , residual ( middle / green ) , and calculated ( bottom / red ) qhnmr 
 spectra of rce resulting from the qm - qhnmr analysis .
the residual 
 represents an rms value of 0.031 for the 7.44 to 9.00 ppm region . 
 the more complex part of region 3 ( 7.05 to 6.79 ppm
the final iteration was performed on the 
 marked region , followed by simulation of the entire spectrum .
the alternative quantitative measure 
 for multitarget qhnmr explored in this study involved the non - qm sd 
 of the relevant portions of the spectrum .
the global spectral deconvolution 
 ( gsd ) module of the mestrenova software tool was used for both automated 
 peak picking and sd .
gsd was primarily developed to improve the quality 
 of an nmr spectrum by deconvoluting and performing deliberate subtraction 
 of solvent and/or impurity peaks from the spectrum .
unlike the hifsa - based qm - qhnmr approach , the initial time 
 investment for gsd spectral processing is small , due to automation 
 and the yield of acceptable deconvolution results .
however , it must 
 be kept in mind that gsd does not establish linkages between structural 
 and spectroscopic features , nor can it verify any assignment and/or 
 the recognition of ( hidden ) lines .
this also brings up the need to 
 distinguish qm - based lines ( resonance frequencies ) from experimentally 
 distinguishable peaks ( including peak shoulders ) . in the case of higher 
 ( non - first ) order effects or excessive overlap , and due to its non - qm 
 nature , gsd can not assign peaks and/or achieve resolution of peak 
 overlap , leaving the choice of a simpler , cleaner region of the spectrum 
 as the only option for accurate analysis . based on these considerations , 

a region inclusive of the ic signals and the c - ring h-2 singlets was 
 used for gsd - assisted quantitation .
after deconvolution , the resulting 
 spectrum consisted of the original signal , the deconvoluted lines , 
 the sum / fit peaks , and a residual ( figure 2 ) . the resulting percent
w / w contents of 
 each isoflavone , thus determined , were 14.5 , 15.2 , 0.64 , 0.35 , 0.53 , 
 0.71 , 2.13 , and 1.40 for biochanin a , formononetin , genistein , daidzein , 
 calycosin , prunetin , irilone , and quercetin , respectively ( table 1 ; table s4 ) .
these values are relatively close to those obtained 
 with hifsa - qhnmr , but show more substantial differences when compared 
 to the published hplc quantitation results , despite the similar tifco .
table 1 compares the quantitation results obtained by qm - qhnmr , 
 non - qm qhnmr using gsd , and the newly developed uhplc - uv analysis 
 with the 2009 hplc results .
the goal of 
 achieving a more comprehensive , metabolomic description of the sample 
 calls for the most inclusive quantitative measure , which currently 
 is offered by qm - qhnmr .
although the initial data analysis and preparation 
 of the hifsa profile ( including all the relevant nmr parameters ) can 
 require significant effort for complex samples , the established profile 
 can be readily transferred within and between laboratories .
the generated 
 spin parameter files of the individual compounds can serve as libraries 
 for future analysis of mixtures containing any or all of these compounds . 
 as the qm basis of nmr ensures their validity across the various magnetic 
 field strengths ,
moreover , it can 
 potentially be adopted for industrial quality control applications , 
 e.g. , to monitor batch - to - batch variations of known samples .
more 
 broadly , the present study showed that qm - qhnmr can be a valuable 
 tool for the analyses of complex natural product matrices , including 
 but not limited to botanical extracts .
one of the continuing 
 challenges that are inherent to qnmr and affect qm - qhnmr as well is 
 baseline  imperfections  . while they can represent measurement 
 artifacts
, they can also be real and due to signal overlapping of 
 a myriad of minor constituents that fall well below the limit of detection 
 ( lod ) , particularly in metabolomic samples .
while masking of problematic regions from the iterations can improve 
 the iteration and pf of resonances assigned to components that are 
 identified by other means , these approaches may not be feasible with 
 every sample and/or may require major additional analytical effort , 
 at least for an exemplary sample .
furthermore , as iterators typically 
 give more statistical weight to major signals , optimization of the 
 line characteristics of signals from minor components is often limited 
 when samples exhibit a very broad dynamic range . certain weighting 
 functions such as the  intensity weight parameter  may 
 be used to give higher significance to minor components during iterations . 
 in the experience of the authors , careful selection of processing 
 and quantitation measure in sd - based qnmr
the fundamental qm theory that underlies 
 the observation of nmr infers that qm - based spectral deconvolution 
 and quantitation like qm - qhnmr has a greater intrinsic accuracy compared 
 to non - qm methods such as gsd ( figure 1 ) .
the importance and achievable level of accuracy 
 of a method depends on the intended application and the type of sample , 
 respectively .
for example , in the case of a pharmaceutical formulation 
 that contains a specific active ingredient , inert excipients , and 
 a well - defined pharmacological target , high levels of quantitative 
 accuracy and precision are desired and justified , as both are intertwined 
 with the efficacy and potency of the material .
this situation differs 
 for complex plant extracts : large numbers and dynamic range of the 
 phytochemicals , including multiple unknowns , are natural limits of 
 achievable accuracy . under such circumstances ,
the simultaneous identification 
 and quantitation of as many components as possible , with a reasonable 
 overall accuracy , becomes the primary goal .
accuracy of both 
 the qm - qhnmr and gsd methods was determined by spiking the ic - containing 
 rce sample with a known amount of genistein ( 3 ) .
the 
 spectra thus acquired were subjected to quantitative processing , and 
 the amount of 3 before and after spiking was determined 
 using these methods as described further in the experimental 
 section .
the accuracy of the qm - qhnmr and gsd methods for the 
 multimarker quantitation of rce was determined to be associated with 
 2.3% and 6.5% relative errors , respectively ( s5 and table s7 ) .
this outcome demonstrated that the qm - qhnmr 
 approach holds its theoretical promise of higher accuracy in 1d qhnmr 
 analysis . a 97% recovery associated with the quantitation accuracy 
 for the spiked ge
a comprehensive qhnmr 
 study had reported previously that an s / n ratio of 150 leads 
 to more accurate qhnmr results .
this 
 suggests that all components with abundance levels of > 0.9% w / w 
 ( s / n = 206 ; see also the supporting information ) in the rce were quantified with high accuracy .
a new , 10 min , uhplc method was developed 
 for the quantitation of the four bioactive isoflavones biochanin a 
 ( 1 ) , formononetin ( 2 ) , genistein ( 3 ) , and daidzein ( 4 ) .
their percent w / w content 
 was determined to be 13.0 , 16.0 , 0.43 , and 0.25 , respectively . compared 
 to the qhnmr results
, the differences between the quantities of the 
 major isoflavones 1 and 2 could result from 
 the observed different solubilities of the reference materials that 
 likely affected the standard solutions for lc calibration and led 
 to a slight underestimation of the quantities .
the exploration of 
 polymorphism and other batch - to - batch variations of reference standards 
 was beyond the scope of the present qnmr study .
as 1 exhibited 
 lower solubility in meoh compared to 2 , extended sonication 
 with mild heating was required to solubilize 1 .
however , 
 the uhplc - uv showed a general congruence with the lc - uv / ms methods 
 previously established for this sample and served as an orthogonal approach to the current study . over a period of 10 years
, 
 the clinical rce had been stored in a sealed container at 20 
 c .
the orthogonal analyses used in the present study confirmed 
 its stability over the prolonged storage . a uhplc - uv profile ( figure 7 ) and 

quantitation showed that 1 and 2 were found 
 consistently to be the major constituents , whereas 3 and 4 were present as minor components .
this was confirmed by 
 the two qhnmr methods , and the present outcome was consistent with 
 the original hplc standardization results . despite the 10-year consistency 
 of the findings
, it is important to realize that repetition of any 
 lc - based analysis requires revalidation due to its dependence on numerous 
 instrument - related factors , particularly those related to ( non)linearity 
 of the detectors ( uv , ms ) , the injector system , and the characteristics 
 of the columns .
this does not apply to qhnmr methods : once established , 
 they can be rerun anytime later , provided the nmr instrument is validated 
 per se , and the qhnmr acquisition parameters 
 are identical or demonstrated to be congruent between the different 
 hardware and magnetic fields used .
another unique advantage of qhnmr 
 is that additional analytes can be included even years later when 
 peak assignments have become available , to study the same sample or 
 the original fid of the qhnmr measurement .
the data 
 can be used indefinitely not only for qualitative comparison but also 
 for full - fledged quantitative measurements , provided ic is performed 
 or ec / ecic calibration data are archived concurrently . in the 
 present study , both qhnmr methods enabled the parallel quantitation 
 of eight marker compounds : seven isoflavones , as well as quercetin . 
 from a practical perspective
, qhnmr proved to be the more time- and 
 labor - efficient method in the long term and for large sample sets . 

the observed differences in the percentages of the markers determined 
 using the three different methods are tolerable and can be attributed 
 to the different intrinsic properties of the orthogonal analytical 
 methods . as observed differences were within the combined error parameters 
 of the methods , chemical degradation or interconversion being the 
 cause of these variances seems unlikely .
accordingly , the clinical 
 rce was concluded to be phytochemically stable over the 10-year period 
 and can be used confidently for future biological evaluations .
the study identified quantum - mechanics - driven quantitative h nmr ( qm - qhnmr ) as currently the most capable and flexible 
 method to achieve the targeted multimarker standardization of a complex 
 botanical extract . using a 10-year - old clinical rce as study material , 

qhnmr allowed not only the quantitation of a total of nine biologically 
 relevant and two additional markers but also the determination of 
 the total isoflavone content .
the tifco represents a unique reference 
 point for botanical standardization , as it captures the entire group 
 of bioactive isoflavones and their clinical relevance .
the ability 
 of the hifsa sd process to account for peak overlap and higher order 
 effects of the target markers led to what can be considered the most 
 accurate signal assignment and quantitative measurement currently 
 achievable in qhnmr by available established methods .
the calculated 
 recovery rate following spiking with genistein ( ge ) ( figure s5 and table s6 ) in rce was found to be 97.0% , demonstrating 
 that the developed qm - qhnmr method is reasonably accurate and fit 
 for the intended purpose of multimarker quantitation . additionally , 

considering the complexity of the rce h nmr spectrum , 
 the extensive signal overlap , the large dynamic range of the major / minor 
 components , the unavoidable presence of multiple unknowns , and the 
 general limitations of reasonable experimental effort , the 2.3% relative 
 error in quantitation observed for the qm - qhnmr method can be considered 
 highly acceptable for the intended purpose of botanical standardization . comparing
the two studied sd methods used to derive the quantitation 
 measures , qm - based hifsa vs non - qm - based gsd , the qm - qhnmr method 
 exhibited a significantly lower percent relative quantitation error . 

this is in line with the theoretically predictable higher accuracy 
 of qm - based approaches to h nmr analysis . a particularly 
 notable strength of qm - qhnmr lies in the wealth of qualitative information 
 that can be obtained in conjunction with the quantitative data . due 
 to its qm nature
therefore , qm - qhnmr is a bivalent standardization method , 
 which combines the identification of multiple marker compounds with 
 their simultaneous quantitation ( i.e. , normalization ) , all in a single 
 analysis . on a general note , ( q)nmr analysis enables a highly efficient 
 use of the information produced when made available in the scientific 
 literature in its original form . accordingly , the fids underlying 
 the present work are made available for future use .
finally , the orthogonal 
 uhplc - uv and qhnmr analyses confirmed the stability of rce over a 
 period of 10 years .
good overall consistency with previous standardization 
 data was observed , and the extract was hence deemed fit for further 
 biological studies .
deuterated dimethyl sulfoxide ( dmso - d6 , 99.9% d ) was obtained from cambridge isotope 
 laboratories inc .
biochanin 
 a , daidzein , formononetin , and genistein were purchased from indofine 
 chemical company inc .
the internal calibrant , 
 3,5-dinitrobenzoic acid , was purchased from fluka analytical ( buchs , 
 switzerland ) .
a gastight ( 1 ml ) syringe , purchased from pressure - lok , 
 precision sampling ( baton rouge , la , usa ) , was used for volumetric 
 nmr sample preparation .
the qhnmr experiments were performed on a 
 bruker ( karlsruhe , germany ) avance 600 nmr spectrometer equipped with 
 a 5 mm txi cryoprobe .
nmr data were analyzed and processed with mnova 
 10.0.2 software from mestrelab research s. l. ( santiago de compostela , 
 spain ) .
( kuopio , 
 finland ) was used for all qm - based nmr spectroscopic analysis including 
 iteration , simulation , and hifsa , as described previously .
a shimadzu ( kyoto , japan ) nexera uhplc system equipped with a dad 
 detector was used for the uhplc analysis of the extract .
quantitation 
 was performed on a kinetex 1.7 m xb - c18 100  column ( 50 
 mm  2.1 mm , s / n : 619546 - 18 ) .
the red clover extract prepared previously for clinical trials ( as 
 documented previously ) was used in this study .
the qhnmr spectrum of the rce was acquired 
 using standard qhnmr conditions , which included a relaxation delay ( d1 ) of 60 s , a 
 calibrated 90 pulse ( p1 ) , and tuning and matching of the probe 
 immediately preceding acquisition . for sample preparation , rce and 
 the ic ( 3,5-dnb )
were weighed accurately as 8.05 mg and 1.39 mg , respectively , 
 into one glass vial and dissolved in a total of 200 l of dmso - d6 .
the solution containing the extract and the 
 calibrant was transferred into a 3 mm nmr tube using 200 l 
 drummond calibrated pipets . the qhnmr experiment consisted of 16 scans 
 acquired with an rg ( receiver gain ) value of 64 and an acquisition time of 5.98 s. postacquisition processing included 
 zero - filling of the 256k fid to 512k real data , a mild lorentzian 
gaussian 
 window function ( exponential factor 0.3 , gaussian factor 0.05 
 in gf mode ) , and baseline correction ( fifth - order polynomial ) .
the 
 residual dmso - d5 signal at 2.500 ppm was 
 used for chemical shift referencing .
the nmr spectrum was exported 
 as a jdx ( jcamp ) file for qm - qhnmr processing .
spectra of the pure 
 isoflavones either had been acquired previously or were obtained from 
 the metidb database .
spiking experiments were performed for the minor 
 components , genistein ( 3 ) , daidzein ( 4 ) , 
 calycosin ( 5 ) , and prunetin ( 6 ) , in order 
 to assign their nmr signals unambiguously .
first , h iterative full spin analysis using the perch nmr software tool was performed for all 
 isoflavones ( s1 , supporting information ) identified in the extract , except for the isoflavones 79 .
the analysis involved initial prediction 
 and subsequent iterative refinement of the spin parameters until the 
 simulated spectrum matched the experimental spectrum . as a result , 

all chemical shifts , coupling constants , and individual line widths 
 (  , j , and w1/2 ) were determined for each compound , compiled into a spin parameter 
 set ( pms ) file , one for each individual compound .
once hifsa profiles 
 for all the target components had been generated , the parameter sets 
 for the individual compounds were copied and pasted to produce a combined 
 pms file that will be utilized for the analysis of the rce ( s2 , supporting information ) . in this combined pms 

file the coupling constants previously determined for each individual 
 compound were kept fixed ( unalterable ) before starting the iteration 
 process against the original h nmr spectrum of the rce . 

a simulated spectrum of the combined pms file was then iterated against 
 the experimental rce to produce a fully matched calculated qhnmr spectrum . 

the iterations were performed until a close visual spectral match , 
 also determined by an rms value 0.1 , was observed between 
 the experimental and the calculated spectrum . along with the refined 
 spin parameters for the mixture , the process generated relative populations 
 ( as % mol / mol ) of the individual species in the extract .
considering 
 the exact weights of the extract and the ic , the absolute quantities 
 of each individual component could be calculated using these populations 
 ( scheme 1 ) .
the resulting pms file contains all spin parameters (  , j , and  ) and the individual populations of the target 
 compounds ( highlighted in red ) ; t , target analyte , ic , internal calibrant ; 
 w , weight ; m , molecular weight ; p , purity ; po , population .
after postacquisition processing of the qhnmr spectrum , sd was 
 performed for region 4 ( 7.69.00 ppm ) containing the signals 
 of the ic , h-2 singlets of all isoflavones , and the b - ring h-2 
 doublet of quercetin ( 10 ) ( figure 2 ) .
the sd process was initiated by performing 
 a peak picking of the entire spectrum using the global sd function 
 of the mestrenova software tool with five fitting cycles .
subsequently , the deconvoluted lines and their peak areas were assigned 
 to the h-2 singlet resonances of the individual isoflavones .
similarly , 
 for composite resonances ( doublets , triplets , etc . ) , the total area 
 of their individual deconvoluted peaks additively constituted the 
 area of the resonance , e.g. , by adding the two individual peak areas 
 of a doublet . alternatively , or in addition to the automated gsd - driven 
 method
, peak picking can be performed manually , followed by individual 
 peak fitting and using the  edit fit 
this generates a peak table , which contains the areas of the deconvoluted 
 signals as qhnmr quantitation measures ( s4 , supporting information ) . the absolute weights of the target analytes can 
 then be calculated using the ic method .
accuracy was determined using the spike - recovery method . for the 
 spiking solution , 5.10 mg of genistein ( 3 )
was accurately 
 weighed into a glass vial and dissolved in 100.0 l of dmso - d6 .
three rce samples containing a known amount 
 of 3,5-dnb ( internal calibrant ) were quantified by both the qm - qhnmr 
 and gsd methods as presented above , both before and after spiking 
 the samples with a 1.00 l aliquot of the genistein ( 3 ) standard solution amounting to 0.051 mg of 3 .
a hamilton 
 gastight gc manual syringe ( 1% accuracy ) was used for measuring the 
 spiking solution .
the hifsa profiles of the three samples used for 
 accuracy determination are presented in s5 ( supporting information ) in the perch.pms text file format . from the percent 

w / w ge content of the three spiked samples , the percent relative error 
 was calculated as follows .
first , the amount of ge in each unspiked 
 sample was determined by the qm ( hifsa)-qhnmr method ( table 1 ) . on the basis of the known 
 amount of ge in the spiked sample ,
the true value for each sample 
 was determined as the sum of percent w / w ge in the unspiked sample 
 and the spiked amount , 0.0510 mg ( table s6 , supporting information ) .
the percent recovery was calculated using the 
 following formula : the lod and loq thresholds were determined using the signal - to - noise 
 ratio ( s / n ) method ( table s7 , supporting information ) . in order to keep the matrix effect consistent , another calibrant , 
 caffeine , was added to both the rce and the 3,5-dnb - containing samples 
 at seven concentrations ranging from 0.030% to 1.90% w / w . according 
 to the ich guidelines , the lod at an s / n of 3:1 and loq at the s /
n 
 of 10:1 is commonly used in lc - based applications . a ratio of loq 
 = 3.3  lod was used for the present study according to a previous 
 qhnmr validation report . the s / n ratio 
 calculator function in mestrenova was used to determine the s / n of 
 individual signals .
the methine proton singlet of caffeine at 7.98 
 ppm was used for the s / n determination , as it shares the h relative integral value ( 1.000 ) with those of the target signals 
 and falls into a relatively flat baseline region compared to the range 
 of the upfield methyl singlets .
the 
 mobile phase gradient used was as follows : 2026% b in 0.5 
 min , 2631.3% b at 6.5 min , held isocratic at 31.3% b up to 
 6.7 min ; re - equilibration from 31.320% b at 7 min ; and reconditioning 
 at 20% b up to 10 min .
the flow rate was 0.6 ml / min , and the injection 
 volume was 1.0 l . the column oven , detector cell , and autosampler 
 temperatures were maintained at 40 , 40 , and 4 c , respectively , 
 throughout the analysis .
uhplc - uv quantitation targeted the following 
 four markers : biochanin a ( 1 ) , formononetin ( 2 ) , genistein ( 3 ) , and daidzein ( 4 ) .
calibration 
 curves with nine concentrations ranging from 1.00 to 500 g / ml 
 and 0.25 to 125 g / ml were generated for the major ( 1 and 2 ) and minor ( 3 and 4 ) isoflavones , respectively ( table s8 , supporting information ) .
all samples including 
 the calibrants and the extract were run in triplicate with a blank 
 injection in between each triplicate set .
stock solutions of 2 ( in meoh ) , 1 , 3 , and 4 ( in etoh ) were prepared at 0.50 , 0.50 , 0.125 , and 0.125 mg / ml , respectively . 

uhplc - uv chromatogram ( 254 nm ) of the red clover extract , 
 showing the quantified major bioactive isoflavones 14 .
 chemical standardization , along with 
 morphological and dna analysis ensures the authenticity and advances the 
 integrity evaluation of botanical preparations . 
 achievement of a more 
 comprehensive , metabolomic standardization requires simultaneous quantitation 
 of multiple marker compounds . employing quantitative 1h 
 nmr ( qhnmr ) , this study determined the total isoflavone content ( tifco ; 
 34.536.5% w / w ) via multimarker standardization and assessed 
 the stability of a 10-year - old isoflavone - enriched red clover extract 
 ( rce ) . 
 eleven markers ( nine isoflavones , two flavonols ) were targeted 
 simultaneously , and outcomes were compared with lc - based standardization . 
 two advanced quantitative measures in qhnmr were applied to derive 
 quantities from complex and/or overlapping resonances : a quantum mechanical ( qm ) method ( qm - qhnmr ) that employs 1h iterative full spin analysis , 
 and a non - qm method that uses linear peak fitting 
 algorithms ( pf - qhnmr ) . a 10 min uhplc - uv method provided auxiliary 
 orthogonal quantitation . 
 this is the first systematic evaluation of 
 qm and non - qm deconvolution as qhnmr quantitation measures . 
 it demonstrates 
 that qm - qhnmr can account successfully for the complexity of 1h nmr spectra of individual analytes and how qm - qhnmr can 
 be built for mixtures such as botanical extracts . 
 the contents of 
 the main bioactive markers were in good agreement with earlier hplc - uv 
 results , demonstrating the chemical stability of the rce . 
 qm - qhnmr 
 advances chemical standardization by its inherent qm accuracy and 
 the use of universal calibrants , avoiding the impractical need for 
 identical reference materials . 
Results and Discussion
Conclusions
Experimental Section