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Entomopathogenic nematodes can be mass produced in artificial media for use as biological insecticides. Nematode in vitro media have been primarily developed on the basis of yield without fully considering nematode nutritional requirements. We investigated the quality and quantity of lipids in the entomopathogenic nematode Steinernema glaseri when grown in vivo in Popillia japonica (a natural host), Galleria mellonella (a factitious host), and in solid and liquid media. Nematode yield (infective juveniles per mg dry organic material) was 4 times higher in the in vivo compared with the in vitro cultures. Nematodes produced in vivo using P. japonica accumulated a significantly higher amount of lipids compared with nematodes grown using G. mellonella or in vitro solid and liquid methods, respectively. Fractionation of S. glaseri total lipids revealed that nematodes produced using P. japonica accumulated significantly higher phospholipids and sterols compared with other methods. C:18 fatty acids were the predominant class of lipids in S. glaseri irrespective of production method. In vivo-produced nematodes had oleic 18:1 acid as the major fatty acid, whereas in vitro-produced S. glaseri had a mixture of oleic 18:1 and linoleic 18:2 acids as the predominant fatty acids. We conclude that the lipid composition of entomopathogenic nematode is host or medium dependent. We suggest that adjusting the in vivo medium by addition of components similar to a natural host nutritional composition should improve nematode production.

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Cancer therapy often entails the use of combinations of antineoplastic agents and/or radiotherapy with the aim of reducing tumor cell populations with minimal side effects (1). These treatments render patients deficient in all known parameters of immune defenses and, as such, predispose them to infection (9). Thus, combinations of one or more antimicrobial agents together with one or more antineoplastic drugs are frequently used in treatment. Taking into consideration the high incidence of yeast infections, particularly those due to Candida spp., among cancer patients (8,11,12,16), it is important to investigate the magnitude of interactions among the drugs used in combined antifungal and anticancer treatments.Both antineoplastic and antifungal agents cause undesirable side effects as a result of their high toxicities. Accordingly, a major goal in drug therapy has been to select drug combinations with synergistic action. Although interactions among drugs when used against microorganisms are well documented (2,7,10,14,15,17,19,20,22, 25), studies of interactive effects among antineoplastic and antifungal agents have not yet been reported.Studies investigating the effects of combinations of drugs on microorganisms have generally been limited to tests of only two drugs. Frequently, analyses are made in a onefactor-at-a-time fashion in which the concentration of a single drug is varied in the presence of a constant level(s) of the second. Such experiments have provided valuable information about interactive properties of the drugs, but cannot be used to quantitatively define interactions or to provide information about interactive effects at concentration levels other than those tested. The common approach to solving this dilemma has been to run tests at more concentrations, but the possible number of trials becomes prohibitive (4). A better approach to tests for two-factor interactions has been to use the so-called checkerboard titration, in which concentrations of both drugs are varied simultaneously. Mathematical treatment of this type of data can yield a quantitative * Corresponding author. description of all main and interactive effects of drug action. However, because of the number of tests involved, checkerboard titration becomes impractical for combinations of three or more drugs.There is, however, an important need for testing combinations of more than two drugs. Berenbaum (4) has devised a method for determination of the level of synergy or antagonism for combinations of several drugs with much less effort than would be required in a checkerboard titration. Odds (22) has used the Berenbaum method to study interactions among four antifungal drugs in inhibiting 11 fungal strains. The results clearly show drug interactions and also show the importance of using different assay procedures and conditions which may affect interpretations of the magnitudes of the interactions. Odds (22) draws attention to the power of the Berenbaum method in defining multiple drug responses and, simultaneously, points out some of ...