23 Bio Signals

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The FASEB Journal Hypothesis

Can specific biological signals be digitized?

Wayne B. Jonas,*,,1,2 John A. Ives,*,,1 Florence Rollwagen,,1 Daniel W. Denman,

Kenneth Hintz, Mitchell Hammer, Cindy Crawford,*,,1 and Kurt Henry**,1

*Samueli Institute for Information Biology, Alexandria, Virginia, 22314, USA

Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA;

Walter Reed ArmyInstitute of Research, Washington, D.C., USA; University of Maryland, College Park, Maryland, USA;George Mason University, Fairfax, Virginia, USA; American University, Washington, D.C., USA; and**Defense Advance Research Projects Agency, Arlington, Virginia, USA

ABSTRACT At the request of the United States De-fense Advanced Research Projects Agency, we at-tempted to replicate the data of Professor JacquesBenveniste that digital signals recorded on a computerdisc produce specific biological effects. The hypothesiswas that a digitized thrombin inhibitor signal wouldinhibit the fibrinogen-thrombin coagulation pathway.

Because of the controversies associated with previousresearch of Prof. Benveniste, we developed a systemfor the management of social controversy in sciencethat incorporated an expert in social communicationand conflict management. The social management ap-proach was an adaptation of interactional communica-tion theory, for management of areas that interferewith the conduct of good science. This process allowedus to successfully complete a coordinated effort by amultidisciplinary team, including Prof. Benveniste, ahematologist, engineer, skeptic, statistician, neurosci-entist and conflict management expert. Our teamfound no replicable effects from digital signals.

Jonas, W. B., Ives, J. A., Rollwagen, F., Denman, D. W.,Hintz K., Hammer, M., Crawford, C., Henry, K. Canspecific biological signals be digitized? FASEB J. 20,2328 (2006)

Key Words: social management of science controversial sci-ence claims electromagnetic signals digital biology throm-bin fibrinogen coagulation

BACKGROUND

In 1988, the journal NATURE published an article on a

controversial claim by Professor Jacques Benveniste ofINSERM in France, and others, reporting that ultra-lowdoses of IgE could induce degranulation of sensitizedbasophils even when the IgE was diluted beyond theprobable presence of the original molecules (1). Thearticle was accompanied by an editorial expressingdisbelief in the phenomenon (2). In an unorthodoxand controversial move, Nature bypassed the normalscientific process of waiting for independent replica-tion and sent a team to investigate the claim in Ben-venistes laboratory. Under emotionally charged condi-tions, they performed and subsequently published their

results (3). Charge and counter-charge ensued (mostlyin the press) (4) while subsequent attempts to scientif-ically investigate the claim produced negative (5),equivocal (6, 7), and positive (8, 9) reports. While thetopic largely disappeared from the scientific literature,it continues to be discussed and evaluated by the publicin prominent media places such as the BBC and ABCs

20/20 (http://www.abcnews.go.com/sections/2020/GiveMeABreak/GMAB_homeopathy_040130-1.html).During the ensuing years Prof. Benveniste has pur-

sued possible mechanisms for the claimed effect. Hereported in The FASEB Journal and in other journalsthat he could mimic the electromagnetic nature ofmolecule-receptor interaction with digital signals towhich biological systems respond in a specific manner(10, 11) (www.digibioSA.com). While it is known thatmolecular interactions in biological systems can beinfluenced by low-level electromagnetic fields (12), theability to specify and deliver signals through electro-magnetic mechanisms has not otherwise been re-

ported. The implications for digitally mimicked biolog-ical signals led the Defense Advance Research ProjectsAgency (DARPA), a branch of the U.S. Department ofDefense, to solicit us for an independent replication ofProf. Benvenistes reports.

MANAGING SOCIAL CONFLICT

The controversial nature of the topic and the handling ofprevious research claims of Prof. Benveniste by the scien-tific community required, in addition to normal scientific

methods of investigation, a social and communicationmanagement process that was capable of dealing withconflicting interpersonal dynamics among vested parties

1The views, opinions, and assertions expressed in thisarticle are those of the authors and do not reflect officialpolicy of the Department of Defense, the Department ofHealth and Human Services, or the U.S. Government. Thisresearch was supported by a grant from the Defense Ad-

vanced Research Projects Agency.2Correspondence: Samueli Institute, 1700 Diagonal Rd., Suite

400, Alexandria, VA 22314, USA. E-mail: [email protected]: 10.1096/fj.05-3815hyp

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in the research effort. The approach we used represents amodification of a communication-based process originallydeveloped within the crisis management arena that fo-cuses on the functional meaning of discourse taking placeunder conditions of disagreement and emotional inten-sity (13, 14). The process is an adaptation from interac-tional communication theory and identifies four conflictdiscourse frames that focus communication among par-ties around interactional triggers of conflict escalationand de-escalation (1517). These four frames and theircorresponding behaviors revolve around 1) substantivedisagreements around the goals and methods of theresearch effort; 2)attunement issues (e.g., degree of trustamong members of the research team, acceptability ofdifferent levels of power and influence, demonstratedconsideration for one another); 3) face concerns (e.g.,degree to which member of the research team perceivetheir reputation or professional identity is being attackedor honored); and 4) emotional discord (e.g., degree towhich negative emotions arise that increase mistrust andinhibit accomplishment of research objectives).

SOCIAL CONFLICT IN MEDICAL RESEARCH

We previously developed a process for the adaptationand application of this social and communication man-agement process to controversial scientific researchtopics. Specifically, under the direction of Dr. WayneJonas, then director of the Office of Alternative Medi-cine (OAM) at the National Institutes of Health (NIH),three major projects were undertaken that providedthe substantive basis for development of a social andcommunication management process for resolving con-flicts that can arise in controversial research topics.

These projects were 1) a comprehensive case studyanalysis of the Burzynski antineoplaston clinical trial onadult brain tumors conducted by the National CancerInstitute (NCI) (18, 19); 2) a one-day meeting thatfocused on the design and implementation of a processfor managing conflict dynamics interpretation andjudgment processes of OAM sponsored research (20);and 3) a 3-day meeting and follow-up activities thatinvolved 80 cancer researchers and practitioners fromthe complementary and alternative cancer therapycommunity and researchers from the NCI. The focus ofthis effort was on the development of conflict manage-ment processes to be integrated into a practice out-

comes monitoring and evaluation system (POMES)designed to address research questions related to con-troversial cancer therapies (21).

These findings indicated that difficulties negativelyaffecting the conduct of research efforts on controversialtopics not only reflect differences of opinion on substan-tive issues (e.g., research protocols, appropriate statisticalanalysis) but, more important, reflect social conflictamong the parties. This leads to interpretive and judg-ment biases that result in selective filtering and recall ofdata, dismissal of nonconforming data, increased mistrustof the motives of the other party, reduced ability to

empathize with the other, simplified thinking, and over-reliance on prior expectations and experiences (18, 19).

INSERTION OF SOCIAL MANAGEMENT INTO ARESEARCH PROJECT

The most visible aspect of the social managementprocess into this study involved the integration of a

communication and conflict resolution professionalinto the research team. His role was to observe, moni-tor, and evaluate the social dynamics during implemen-tation of the research project. This involved severalfunctions, including 1) intervention into group deci-sion-making processes around both substantive issuesand assessment of attunement, face, and emotionaldiscord dimensions; 2) application of conflict commu-nication skills (e.g., active listening) to key prioritiza-tion concerns (e.g., how the research goals are set),development and review of the research approach(e.g., how the research design and protocols are estab-lished), execution of the study (e.g., how are protocols

actually implemented, how are changes/modificationsmade to the previously agreed upon research proto-cols), and interpretation and evaluation of the researchfindings (e.g., what values and criteria are applied tojudge the quality and validity of the research effort); 3)conduct of individual interviews, outside of the normalmeetings, with research team members to assess thequality of the group process; 4), discussion of observa-tions of the ongoing social and management processduring group meetings; and 5)at the conclusion of thestudy, preparation of written analysis along with aformal presentation to the research team of the socialdynamics that characterized the research effort. Thissystem, while it had never been formally tested in alaboratory setting, seemed appropriate to use during anindependent test of Prof. Benventistes claims, re-quested of us by the Department of Defense.

THE DIGITAL BIOLOGY EXPERIMENTS

The attempted replication project was divided into fourphases: protocol development, pre-pilot, pilot, and testphases. In the Protocol Development phase a detailedpreliminary protocol was developed and submitted to

DARPA for review including a description of the com-munication and management process to be used. Theprotocol was reviewed and agreed to by Prof. Ben-veniste and his staff, including the criterion that hewould serve as a consultant and not an author of anyfinal publications that ensued. This was to assure thatthe replication attempt and subsequent paper wereindependent. This protocol was further developed aftera multidisciplinary consultant team consisting of abiologist, hematologist, statistician, electrical engineer,and communication/conflict expert was recruited.Feedback and modifications of the experimental pro-

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cedures were documented via meetings, memoranda,and email throughout the study.

The pre-pilot phase was conducted in our laboratoryJuly 1421, 2001 by Didier Guillonnet and Jamal Aissafrom Benvenistes laboratory. They set up an AutomatedBio-Analyzer (ABA) machine that delivers the digitalsignals and automatically runs the experiments (Fig. 1A).A number of modifications to the ABA program andprotocol were implemented and verified at that time,including blinding and randomization procedures. Thesesame two individuals, along with Prof. Benveniste, re-turned on October 30 through November 3, 2001 to runthe first pilot phase under the modified protocol. The testphase was then conducted by our research team using thesame protocol, but independent of Prof. Benvenistesteam. Between the pre-pilot and pilot experiments, aseries of blank runs were made on the ABA with watersignals to estimate sample sizes required to observe a 20%effect difference between groups with a Pvalue set at 0.05for hypothesis determination.

According to Prof. Benveniste, a biological systemthat can be used to detect digital signals is the inhibi-

tion of fibrinogen-thrombin coagulation by a digitizedthrombin inhibitor (DTI). Our working hypothesis wasthat there would be no difference in coagulation ratesbetween groups exposed to a digitized thrombin inhib-itor (DTI), a digitized water signal (WAT), and nosignal (NS), as measured by optical density (OD) curvesof samples exposed to these signals.

To maximize objectivity and reliability, the DigiBioresearch team set up an ABA robot that performs theentire protocol, including sample pipetting and deliv-ery of the signal, with minimal human intervention(Fig. 1A, B). The protocol can be summarized asfollows. Thrombin dissolved in water (0.3 g/mL) is

exposed to the computer recording of either DTI orcontrol solutions consisting of either no electromag-netic (EM) signal or water signal. After exposure, thesamples are mixed with fibrinogen (24 mg/mL in 0.1%sodium azide, to prevent bacterial growth) and distrib-uted in 96-well plates. Coagulation was assessed byspectrophotometry and expressed as OD. The entireprocedure was automated except for data analysis,stock preparation of fibrinogen and thrombin, andtheir loading into ABA reservoirs.

The basic ABA procedure is as follows. After placementof fibrinogen and thrombin into appropriate reservoirs,the computer program is started. The machine distributes

the thrombin into Eppendorf tubes and then places thetube into an EM coil inside of a grounded copper tubeopen at the top. The computer "informs" the waterthrough the EM coil with the digital signal for 10 min andmoves the tube back to the holding rack. It then proceedsin the same way for the other tubes. The recordings (DTIsignal, WAT signal, NS) are "played" in a random orderdetermined by an Excel program on start-up of thecomputer. The informed thrombin is then mixed withfibrinogen and 2 aliquots of the thrombin/fibrinogenmixture are distributed side-by-side into the wells of a96-well microplate where coagulation starts (Fig. 1A). The

latter is read every 60 s for 1 h using a spectrophotometerand the program saves the data to an Excel spreadsheet.Analysis of this data was done by hand to determinecoagulation kinetics.

It was agreed at the start of the study that only pilotphase and test phase data would be formally analyzed.However, in the pre-pilot phase, DTI, WAT, and NSsamples each produced apparent delayed coagulation(decreased rate of OD increase) 25% of the time,indicating some digital effect might be occurring.

Experiments done between the pre-pilot and pilotphases were designed to determine variance and esti-mate a sample size sufficient to detect a 20% differencebetween groups. These data were obtained with NS andWAT treated samples only. The ABA machine pro-duced a variance of 1% standard error, suggestingthat four experiments would be sufficient to detect a20% difference between samples. No digital effectswere seen in 17 experiments with two investigatorsduring this pre-pilot phase. (Fig. 2A)

During the pilot phase (October 30November 3,2001) Prof. Benveniste and his team conducted 16

experiments using the three-group design. While theseexperiments were randomized it was possible to deter-mine when no signal (NS) was the experimental con-dition by observing a volt/ohm meter placed in parallelwith the signal playing from the computer to coil.However, it was not possible to determine when theDTI or WAT signals were being played. Coagulationdifferences between WAT and NS were 1%. How-ever, in 7 of the experiments a 2128% decrease inmean coagulation rate was observed for DTI (Fig. 2B).

A subgroup analysis of pilot phase data showed thatall DTI effects occurred when experiments were con-ducted by one member of Benvenistes team (Jamal

Aissa) and that this usually occurred when using a splitsample technique in which he interrupted the opera-tion of the ABA machine to do manual plating followedby the automated plating. Two of the 16 experimentsdone only by the ABA machine (no interruption)showed effects when Jamal was present. In three in-stances Jamal set up experiments and then left for theday. None of these showed DTI effects. An examplecurve of a successful experiment is shown in Fig. 2B.

After November 3, 2001, the independent test phasewas conducted. This consisted of 29 formal experi-ments run by six different investigators in two differentlaboratories using the same three group design con-

ducted in the pilot phase. Mean coagulation differ-ences between groups was 12% and nonsignificant(ANOVA F0.04, P0.96; Kruskal-Wallis Chisquare0.06, P0.97). The mean optical densities at40 min were 1.08 0.1 (95% CI: 1.051.12), 1.08 0.09 (95% CI: 1.051.11), and 1.09 0.08 (95% CI:1.061.12) for DTI, water, and blank, respectively. Anexample curve is seen in Fig. 2C.

After the test phase was completed, we conductedseveral experiments using varying concentrations ofthrombin and fibrinogen with and without digital sig-nals in an attempt to reproduce the curves illustrated in

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Fig. 2B with known chemicals. No combination ofsample splitting or concentration change exactly repro-duced the curves of the Benveniste team. However,adding between 100 and 200 L water or between 2and 4 ng/mL of the thrombin inhibitor Lepirudin perwell resulted in a decreased coagulation rate (Fig. 2D).Statistical results similar to the pilot phase experimentscan be produced with these techniques, although thecoagulation curve is flatter and more linear than thoseproduced in the pilot phase experiments. In addition,the volume differences required to produce such ef-fects are easily distinguished by visual inspection. Therewas no evidence of volume or concentration irregular-ities seen during any of the pilot phase experiments.

A detailed analysis of the digital signal conducted byour electrical engineer found no differences between DTIand WAT signals. A simple voltmeter (tester in Fig. 1B)was used to measure the average signal strength beingapplied to the coils. This was used to verify that a signalwas in fact being presented to the samples. The samevoltage, and thus signal intensity, was observed when eachof these signals was presented to the samples.

Verification of procedural protocols was provided byour consultants in statistics and hematology.

APPLICATION OF THE SOCIAL MANAGEMENTPROCESS

Ongoing evaluation by our communication and con-flict management consultant documented the commu-nication and feedback dynamics that operated withinthe research team. Conclusions were drawn from ex-tensive observations of interactions during both theconduct of the experiment and research team meet-

ings, in-depth interviews with Prof. Benventiste and hisassociates along with the members of the researchteam. The following questions were asked and re-sponses were recorded and later reviewed: 1) How doyou feel the study is progressing? 2)Are there particularchallenges you face in the conduct of the study? 3)Howsuccessful/unsuccessful do you feel your (visit, etc.) has

Figure 1. A) Photograph of automated biol-analyzer (ABA).Photograph of ABA work surface. Six Eppendorf tubes areplaced by hand, starting from far left, in each of the twoMetallic (soft iron) Racks. The robot arm (not pictured)

using Disposable tips distributes aliquots of thrombin fromthe Thrombin reservoir into each of the Eppendorf tubes inMetallic Rack 1. After filling each Eppendorf tube with apredetermined volume of thrombin and before filling thenext Eppendorf tube in line, the robot removes the filledEppendorf tube from the Metallic Rack and places it in theSignal Coil. The tube is left there for 10 min during whichtime one of three signals (randomly determined) is played:DTI, WAT, or NS (see text). At the end of 10 min the tube isreturned to the rack, and the disposable tip is ejected into theGarbage Box. A fresh disposable tip is acquired and the nexttube in line is filled and placed in the Signal Coil. After 60min when all tubes have been treated in this way, the robotproceeds to distribute aliquots of fibrinogen from the Fibrin-ogen reservoir into each empty Eppendorf tube in Metallic

Rack 2. After filling each Eppendorf tube with a predeter-mined volume of fibrinogen and before filling the next tubein line, the robot adds, from the parallel tube, a predeter-mined volume of treated thrombin. It then mixes the twocompounds by repeated pipetting and then distributes theresulting mixture into two side-by-side wells of the Microplate.The robot then proceeds to the next tube down the line andrepeats the process until all six of the tubes have beenprocessed and aliquots from each are distributed into theappropriate wells of the Microplate. B)Schematic diagram ofthe apparatus for informing water. The device used forinforming the water consists of a standard computer fitted

with a sound card. The line-out outlet of the sound card islinked to the line-in of a commercially available stereo hi-fi

amplifier by a stereo connection: a male minijack (3.5 mm)plug on the sound card side and two cinch plugs on theamplifier side. The wires from an electromagnetic coil (4ohms) and the probes of an AC voltmeter are plugged into

the speaker outlet at the back of the amplifier. When theprerecorded ".wav" files of either DTI or water (WAT) areplayed by the computer, the signal is delivered to the coil at4V AC for 10 min. The frequency range is that of the soundcard and the amplifier ranging from 20 Hz to 20 kHz. Notshown here is the recording process in which the sample to berecorded is placed between one transmitting and two receiv-ing coils. The transmitting coil produces an electromagneticnoise signal that is passed through the sample and received bythe receiving coils. These two receiving coils drive a differen-tial amplifier whose output is connected to the "mic" input ofthe computer sound card and the recording is achieved as isdone with normal sound through a microphone with settingsat 44.1 kHz, mono, for 3 s.



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been? 4) How confident are you that a rigorous scien-tific study can be completed? 5) Have your own per-sonal views and beliefs been challenged? How? Whathas been your response? and 6) What explanations forthe phenomena under examination do you believe tobe most plausible? Why?

Results from these interviews revealed strong agree-ment among all interviewed that the study was progress-ing well and certain challenges were identified and werethoroughly discussed to everyones satisfaction. Prof. Ben-

venistes group felt their visit and set-up of the experimentwas very successful. To question #4, concerns were ex-pressed by Prof. Benvenistes group concerning the kindsof interpretations one might give to findings of no signif-icance or inconsistent findings. These concerns weredirectly addressed, again to everyones satisfaction, in anexplicit statement by the research team regarding theseissues in a follow-up memo of October 31, 2001 (notshown). Responses to the remaining two questions indi-cated lack of conflict or disagreements in these areas. Theoverall dynamics of the American research teams inter-action with the Digibio members as well as among them-selves was respectful of differences of opinion and collab-

orative in decision-making.A quantitative assessment of the degree of group con-

sensus within the American research team was achieved. A21-item Consensus Scale was administered following theconclusion of the research effort to the five members ofthe American research team. Responses were obtainedfrom three members. This measure, which obtained reli-ability coefficients of 0.89 in previous administrations,assessed the degree of agreement of respondents to fivedimensions of group consensus: effectiveness of decision-making process, individual agreement with the groupdecision, group members' relations, individual effective-

ness and opportunity to participate. Results indicated amean scale score of 4.53/5.00 (4.61, 4.33, and 4.71),suggesting a high degree of overall group consensusamong research team members (22). Overall ratingsamong the three respondents on each of the five sub-scales of the social consensus measure were similarly high.Overall, all three respondents were in high agreementwith one another concerning the strong level of socialconsensus obtained among the members. The social andcommunication process was characterized as open in

providing opportunities for improvement in communica-tion, establishing fair and consistent protocols for thestudy, and respectful and direct resolution of differencesof opinion during the experiment. Thus, there was anavoidance of the perils of groupthink phenomena (23,24).

In addition, a set of guiding principles was estab-lished that aided the research team in addressing someimportant changes/concerns expressed by Prof. Ben-veniste and his associates at different times during thestudy as well as facilitating agreement on the interpre-tation and judgment of the obtained findings by theresearch team. Prof. Benveniste provided comments on

these test results and suggestions but no editing orauthorship on the final report for DARPA. For exam-ple, one guideline stated, "differing interpretations ofthe meaning and implications of the data are possibleand can be reflected in individual research team mem-ber reports." This guideline permitted alternativevoices to be heard if full agreement on specific issues orfindings was not obtained.

Overall, a fair and effective communicative processwas established and maintained around research con-ducted on a highly controversial topic. Thus, the socialmanagement process allowed for the project to be

Figure 2. Thrombin-fibrinogen coagulationrates optical density curves representing co-agulation rates of the thrombin-fibrinogenmixture exposed to various digital signals,thrombin inhibitors and controls. E,

water (sample not exposed to any digitalsignal); , water signal (sample ex-posed to signal produced from plain water);F, samples exposed to digitized signalproduced from thrombin inhibitor (DTI).A) Example run produced by automated

biological analyzer (ABA) with no signalsrunning. Variation between samples was 1% over 10 runs completed on 5 differentdays. B) Example run from successful ex-periment conducted by Jamal Aissa. Delayedcoagulation was observed in samples ex-posed to DTI in 11 of 23 samples analyzed,average inhibition 24% (P0.0001). C) Ex-ample curve selected from over 40 runsconducted by seven independent investiga-tors on the digital effect. Variation betweensamples 2% throughout replication at-tempts (P0.96). D) Example coagulationinhibition differences produced by adding 5

concentrations of the thrombin inhibitor Lepirudin (a hirudin derivative) to test samples compared with digitized water and

plain water demonstrating ability of ABA to produce a coagulation inhibition effect with a standard chemical thrombininhibitor. F 4 ng/mL; E 2 ng/mL; 1 ng/mL; 400 pg/mL; 200 pg/mL; zero Lepirudin present.

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completed in a fair and collegial manner in a highlycontroversial area of science.

SUMMARY AND CONCLUSIONS

We found no effects from digital signals on the inhibi-tion of thrombin/fibrinogen coagulation. We observedapparent inhibition of thrombin/fibrinogen coagula-tion by a digital signal when one member of theBenveniste team conducted experiments in our labora-tory. We did not observe systematic influences such aspipetting differences, contamination, or violations inblinding or randomization that would explain theseeffects from the Benveniste investigator. However, ourobservations do not exclude these possibilities. Thedigital effects found during ABA runs were seen aftermanual pipetting by the experimenter in 14 of the 16runs. While concentration changes in fibrinogen pro-duce statistically similar reduced coagulation rates, thecurves from such concentration changes do not mimicthose seen in the pilot experiments. In addition, vol-ume changes were not found between samples and allprotocol data were run blind, thereby decreasing theprobability that pipetting differences occurred system-atically between groups. Improvements in blinding (byeliminating the NS control group) and prerandomiza-tion control (by delivering randomization codes beforeeach run separate from those generated by Excel)would not alter the basic findings that digital effectswere not reproduced by our investigators.

Prof. Benveniste died on October 3, 2004. Before hepassed away, however, he posited unknown interactionswith digital signals that produce these effects and statesthat he observed similar experimenter variability in his

laboratory (personal communication). He stated thatcertain individuals consistently get digital effects andother individuals get no effects or block those effects.While it is possible that other, unknown experimenterfactors, such as the influence of chemical residues, ener-getic emanations or intentionality from individual exper-imenters could be an explanation for these findings, wedid not test these hypotheses nor developed a frameworkthat would control for such factors. Without such aframework, continued research on this approach to digi-tal biology would be at worst an endless pursuit withoutlikely conclusion, or at best premature (25).

In addition, we feel that this first incorporation of a

systematic social management process into research on acontroversial issue has proven useful and is a betterskeptical approach to such claims than armchair criti-cism. Future research teams exploring claims that lieoutside the normal paradigms of science should considerincorporating such procedures into their investigations.

We are pleased to acknowledge with appreciation the lateJacques Benveniste, and his colleagues Didier Guillonnet, andJamal Aissa for their time, open cooperation, patience, flexi-bility and assistance in setting up, adjusting and conductingthe experiments. Thanks to Ronald A. Chez for his review andediting of the paper.

1. Davenas, E., Beauvais, J., Oberbaum, M., Robinzon, B., Mia-donna, A., Tedeschi, A., Pomeranz, B., Fortner, P., Belon, P.,Sainte-Laudy, J., et al. (1988) Human basophil degranulationtriggered by very dilute antiserum against IgE. Nature (London)333, 816818

2. (1988) When to believe the unbelievable. Nature (London) 333,787

3. Maddox, J. (1988) High-dilution" experiments a delusion. Na-ture (London) 334, 287289

4. Coles, P. (1988) Benveniste controversy rages on in the Frenchpress. Nature (London) 334, 372

5. Ovelgonne, J. H., Bol, A. W., Hop, W. C., and van Wijk, R. (1992)

Mechanical agitation of very dilute antiserum against IgE has noeffect on basophil staining properties. Experientia48, 5045086. Hirst, S. J., Hayes, N. A., Burridge, J., Pearce, F. L., and

Foreman, J. C. (1993) Human basophil degranulation is nottriggered by very dilute antiserum against human IgE. Nature(London) 366, 525527 (see comments)

7. Schiff, M. (1994) The Memory of Water, Thorsons (division ofHarper Collins Publishers), London

8. Belon, P., Cumps, J., Ennis, M., Mannaioni, P., Sainte-Laudy, J.,Roberfroid, M., and Wiegant, F. (1999) Inhibition of humanbasophil degranulation by successive histamine dilutions: Re-sults of a European multi-centre trial. Inflamm. Res. 48, S17S18

9. Brown, V., and Ennis, M. (2001) Flow-cytometric analysis ofbasophil activation: inhibition by histamine at conventional andhomeopathic concentrations. Inflamm. Res. 50, S47S48

10. Benveniste, J., Aissa, J., and Guillonnet, D. (1999) The molecu-lar signal is not functional in the absence of "informed water."

FASEB J. 13, A163 (abstr.)11. Thomas, Y., Schiff, M., Belkadi, L., Jurgens, P., Kahhak, L., and

Benveniste, J. (2000) Activation of human eurtrophils by elec-tronically transmitted phorbol-myristate acetate. Med. Hypotheses54, 3339

12. Walleczek, J. (2000) Self-organized Biological Dynamics & NonlinearControl, Cambridge University, Cambridge

13. Hammer, M., and Rogan, R. (1997) Negotiation models in crisissituations: The value of a communication based approach. In

Dynamic Processes of Crisis Negotiation: Theory, Research and Practice(Rogan, R., Hammer, M., and Van Zandt, C., eds) pp. 923,Praeger, Westport, CT

14. Rogan, R., and Hammer, M. (2002) Crisis/hostage negotiations:a communication-based approach. In Law Enforcement, Commu-nication, and Community (Giles, H., ed) pp. 229254, JohnBenjamins, Amsherdam

15. Cissna, K., and Sieburg, E. (1981) Patterns of interactionconfirmation and disconfirmation. In Rigor and Imagination:Essays from the Legacy of Gregory Bateson (Wilder, C., and Weak-land, J., eds) pp. 253282, Praeger, New York

16. Ruesch, J., and Bateson, G. (1951) Communication: The SocialMatrix of Psychiatry, WW Norton, New York

17. Watzlawick, P., Beavin, J., and Jackson, D. (1967) Pragmatics of Human Communication, WW Norton, New York

18. Hammer, M. (1996) Burzynski antineoplaston case study: con-flict issues and recommendations. In Office of AlternativeMedicine, NIH, Bethesda, MD

19. Hammer, M., and Jonas, W. (2004) Managing social conflict inCAM research: the case of antineoplastons. Integr. Cancer Ther. 3,5965

20. Hammer, M. (1996) The management of dispute and judgmentprocess in controversial complementary and alternative medicineresearch. In Office of Alternative Medicine, NIH, Bethesda, MD

21. Hammer, M. (1997) Practice outcomes monitoring and evalua-tion system (POMES): Report of recommendations concerningthe POMES system. In Office of Alternative Medicine, NIH,Bethesda, MD

22. DeStephens, R., and Hirokawa, R. (1988) Small group consen-sus: stability of group support of the decision task process, andgroup relationships. Small Group Behavior 19, 227239

23. Janis, I. (1982) Groupthink, Houghton Mifflin, Boston24. Janis, I. (1989) Crucial Decisions: Leadership in Policymaking and

Crisis Management, The Free Press, New York25. Stent, G. S. (1972) Prematurity and uniqueness in scientific

discovery. Sci. Am. 227, 8493

Received for publication March 1, 2005.Accepted for publication September 23, 2005.


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