Cyanide production from glycine by a homogenate from a Pseudomonas species.

A cell-free preparation with cyanide-producing activity was obtained from a bacterium, strain C, of the genus Pseudomonas. To preserve activity, an oxidizing agent, e.g., phenazine methosulphage (PMS), had to be added to the cell suspension before disruption by sonic treatment. By the procedure described, a total homogenate made from a 15% (wet weight) bacterial suspension in tris(hydroxymethyl)aminomethane-hydrochloride buffer (0.05 M, pH 8.2) and with PMS (0.4mM) exhibited about 8% of the activity obtained from a suspension of untreated bacteria. In the presence of flavine-adenine dinucleotide (0.3 mM) and PMS (0.4mM), the activity was augmented to about 16% of that of the intact cells. By gradient centrifugation the homogenate was separated into three fractions. The main enzyme activity was associated with those fractions which by electron microscopy were found to consist of membranous structures.     

Lessons from a kill

During their colonization by Polynesians and later by Europeans, the Hawaiian islands suffered a massive loss of species. All the extinctions are indirectly attributable to human impact. Nonetheless, it has proved extremely difficult to specify which of several possible mechanisms caused each particular extinction. This seems to admit defeat in the battle to understand past extinctions. Such understanding could guide our efforts to protect species that are now threatened with extinction. Will it be easier to understand the causes of future extinctions? Surveys of future extinctions stress habitat destruction as the simple and dominant mechanism. This contrasts to its secondary (and generally confused) role in past extinctions. I argue that this contrast between the complexity of the past and the apparent simplicity of the future arises because extinction mechanisms are inherently synergistic. Once extensive species losses begin, it may be impossible to separate the mechanisms and thus manage an individual species as if its decline had a single cause.     

The estimation of a bivariate fitness function from two samples taken from a population

Summary The fitness of animals subjected to natural selection can be defined as the probability of surviving selection for a given interval of time, or some convenient multiple of this. If the fitness is related to some measurable variablesX, Y, Z,… then the relationship is expressed mathematically in the fitness functionw(x, y, z,…) and this function can be estimated by comparing the joint distribution ofX, Y, Z,… in samples taken before and after selection. In an earlier paper (Manly, 1975) the problems involved in estimating a fitness function of one variable were discussed. In the present paper various methods for estimating a bivariate fitness function are proposed and compared on some semiartificial sample data. It is concluded that either a generalized version ofO’Donald’s (1968) method of moments or a weighted multiple regression method will be most satisfactory. Alternative methods involving assumptions of normality will need to be used with great care.     

The Estimation of a Multivariate Fitness Function from Several Samples Taken from a Population

The situation is considered where the multivariate distribution of certain variables X₁, X₂, …, X_p is changing with time in a population because natural selection related to the X's is taking place. It is assumed that random samples taken from the population at times t₁, t₂, …, t_s are available and it is desirable to estimate the fitness function w_t(x₁, x₂,…,x_p) which shows how the number of individuals with X_i = x_i, i = 1, 2, …, p at time t is related to the number of individuals with the same X values at time zero. Tests for population changes are discussed and indices of the selection on the population dispersion and the population mean are proposed. The situation with a multivariate normal distribution is considered as a special case. A maximum likelihood method that can be applied with any form of population distribution is proposed for estimating w_t. The methods discussed in the paper are illustrated with data on four dimensions of male Egyptian skulls covering a time span from about 4500 B.C. to about 300 A.D. In this case there seems to have been very little selection on the population dispersion but considerable selection on means.     

Characterisation of an amylase from a psychrotrophic Vibrio isolated from a deep-sea mud sample

The gene coding for the class A beta-lactamase of Citrobacter diversus has been cloned and sequenced. It contains the information for a 294-amino-acid precursor protein, including a 27-residue N-terminal signal peptide. The deduced sequence of the N-terminal portion of the mature protein is in excellent agreement with that determined by microsequencing of the protein and readily explains the pI differences observed between the naturally occurring forms I and II of the enzyme. The sequence of the mature protein exhibits a very high degree of similarity with that of the Klebsiella oxytoca class A beta-lactamase.     

Data from a Study of a Neuroallergic Family

Migraine and other types of headaches, serous meningites, encephalomyelites related to the employment of serums and vaccines, including Alazhuanin's hemorrhagic encephalitis, acute hemorrhagic encephalitis, parainfectious encephalites, nervous system damage of arthritic origin (primarily chorea minor), vascular diseases of the nervous system in periarteritis nodosa, cerebral thromboangiitis obliterans in Winiwarter-Buerger's disease, serous and toxic neurites and polyneurites, the Guillain-Barre syndrome, Landry's paralysis, polyneurites resulting from treatment with salvarsan and sulfonamides, certain cases of Meniere's syndrome, demyelinating diseases of the nervous system (multiple sclerosis, related acute and chronic disseminated encephalites, encephalitis periaxialis diffusa, and other forms of sclerous leuco encephalites and, finally, epilepsy (1-24) are diseases of the nervous system associated with immune pathology reactions to various antigens (foods, inhalational, medicamental, viral, bacterial and other foreign agents, and autoantigens).