Almira L. Hoogesteijn

Conflicts between cattle ranching and large predators in Venezuela: could use of water buffalo facilitate felid conservation?

The mortality of water buffalo Bubalus bubalis and cattle Bos indicus and B. taurus associated with predation by jaguar Panthera onca and puma Puma concolor, both of which are categorized as Near Threat- ened on the IUCN Red List, was examined in six Venezuelan ranches. There was significantly higher cattle than buffalo mortality due to predators in all ranches. Compared to buffaloes, cattle had a greater risk of being predated. Variations in monthly predation were observed, with greater cattle mortality during the peak of the rainy season (June-July). Buffalo, but not cattle, displayed defensive behaviour against predators. We suggest that livestock mortality associated with jaguar and puma may be reduced by keeping buffaloes and cattle in the same paddock, or by keeping only buffalo. Reduction of cattle losses is needed to increase tolerance towards jaguar and puma and thus facilitate their conservation. B. bubalis has higher production than cattle in South American flooded tropical grasslands. How- ever, buffalo kept as livestock have two limitations: (1) they may revert to their feral condition if not managed according to the requirements of the species, and (2) some markets pay low prices for buffalo meat or may be reluctant to consume buffalo products.

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

Background Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. Methods To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. Results In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. Conclusions More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

Lessons from Nigeria : the role of roads in the geo-temporal progression of avian influenza (H5N1) virus

The daily progression of the 2006 (January-June) Nigerian avian influenza (AI H5N1) epidemic was assessed in relation to both spatial variables and the generation interval of the invading virus. Proximity to the highway network appeared to promote epidemic dispersal: from the first AI generation interval onwards > 20% of all cases were located at < 5 km from the nearest major road. Fifty-seven per cent of all cases were located 31 km from three highway intersections. Findings suggest that the spatial features of emerging infections could be key in their control. When the spatial location of a transmission factor is well known, such as that of the highway network, and a substantial percentage of cases (e.g. > 20%) are near that factor, early interventions focusing on transmission factors, such as road blocks that prevent poultry trade, may be more efficacious than interventions applied only to the susceptible population.

Reproductive impairment in zebra finches (Taeniopygia guttata)

The effects of polychlorinated biphenyls (PCBs) as compounds that may disrupt endocrine activity and, consequently, alter reproductive performance were investigated in altricial zebra finches (Taeniopygia guttata). The breeding performance and breeding cycle of zebra finches differed significantly between nonexposed birds and those experimentally pulse-exposed to Aroclor 1248, a PCB compound (40 microg/bird). Aroclor-exposed birds showed significantly increased numbers of clutches laid, nests constructed per pair, incubation time per pair, and percentage of hatchling mortality compared to controls. Not all reproductive parameters were affected. Those traditionally regarded as indicators of reproductive capacity (number of eggs laid per clutch, number of eggs laid per pair, hatchlings per clutch, and fledglings per clutch) did not differ statistically between exposed and control birds. Findings support the hypothesis that very low PCB doses may be associated with endocrine disruption. It is suggested that evaluation of reproductive parameters related to parental care is more adequate to assess endocrine disruption than is evaluation of reproductive success parameters. Given its short breeding cycle, altricial breeding behavior, and other advantages not possessed by precocial birds, we propose using the zebra finch for evaluations of chemicals with endocrine-disruptive activity.

ORAL TREATMENT OF AVIAN LEAD INTOXICATION WITH MESO-2,3-DIMERCAPTOSUCCINIC ACID

Abstract The efficacy of meso-dimercaptosuccinic acid (DMSA) (succimer) in treating avian lead intoxication was studied in a retrospective, nonrandomized, longitudinal study. Nineteen birds with moderate to high blood lead concentration and neurologic signs compatible with lead toxicity were treated with DMSA (30 mg/kg p.o., b.i.d.; n = 15) for a minimum of 7 days. In cases with severe neurologic signs, DMSA was supplemented with a single dose of edetate calcium disodium (<50.0 mg/kg of body weight i.m.; n = 4). Blood lead concentrations were measured two or more times (before and after treatment). Median blood lead concentration decreased (87%), neurologic signs were resolved, and there were no apparent adverse secondary effects.

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Evolution has conserved “economic” systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions—including the use of arrows that connect pairs of consecutive observations—non-reductionist (spatial–temporal) constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist) methods can (i) distinguish data subsets that differ immunologically and statistically; (ii) differentiate false-negative from -positive errors; (iii) discriminate disease stages; (iv) capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v) assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

Livestock predation by jaguars Panthera onca in south-eastern Mexico: the role of local peoples’ practices

Inadequate livestock husbandry practices threaten the maintenance of global biodiversity and provoke conflicts between people and wildlife, and large carnivorous mammals are among the most affected. The jaguar Panthera onca is one of the most threatened species in the Americas, being targeted by livestock producers who suffer economic losses as a result of predation. The way in which rural producers in countries such as Mexico conduct husbandry practices may influence levels of predation by jaguars. Our objective was to understand how such practices are conducted in the Selva Lacandona in south-eastern Mexico, to identify their influence on the vulnerability of livestock to predation by jaguars. We characterized local husbandry practices through participant observation, interviews and surveys. Our results show that the most important practices that make livestock vulnerable to predation include the location of grazing lands close to forested areas and water sources, the absence of practices for the proper disposal of carcasses, and poor control of calving and care of calves. Our recommendations include monitoring of livestock movements and synchronization of calving. Economic investment and behavioural change can be accomplished through capacity building and providing people with the means to monitor and manage their livestock. Small actions can reduce livestock losses and improve the economic circumstances of rural people, and thus increase their tolerance and respect towards jaguars.

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Background Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise-reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality-based) version. Results In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

Detecting the Hidden Properties of Immunological Data and Predicting the Mortality Risks of Infectious Syndromes

Background To extract more information, the properties of infectious disease data, including hidden relationships, could be considered. Here, blood leukocyte data were explored to elucidate whether hidden information, if uncovered, could forecast mortality. Methods Three sets of individuals (n = 132) were investigated, from whom blood leukocyte profiles and microbial tests were conducted (i) cross-sectional analyses performed at admission (before bacteriological tests were completed) from two groups of hospital patients, randomly selected at different time periods, who met septic criteria [confirmed infection and at least three systemic inflammatory response syndrome (SIRS) criteria] but lacked chronic conditions (study I, n = 36; and study II, n = 69); (ii) a similar group, tested over 3 days (n = 7); and (iii) non-infected, SIRS-negative individuals, tested once (n = 20). The data were analyzed by (i) a method that creates complex data combinations, which, based on graphic patterns, partitions the data into subsets and (ii) an approach that does not partition the data. Admission data from SIRS+/infection+ patients were related to 30-day, in-hospital mortality. Results The non-partitioning approach was not informative: in both study I and study II, the leukocyte data intervals of non-survivors and survivors overlapped. In contrast, the combinatorial method distinguished two subsets that, later, showed twofold (or larger) differences in mortality. While the two subsets did not differ in gender, age, microbial species, or antimicrobial resistance, they revealed different immune profiles. Non-infected, SIRS-negative individuals did not express the high-mortality profile. Longitudinal data from septic patients displayed the pattern associated with the highest mortality within the first 24 h post-admission. Suggesting inflammation coexisted with immunosuppression, one high-mortality sub-subset displayed high neutrophil/lymphocyte ratio values and low lymphocyte percents. A second high-mortality subset showed monocyte-mediated deficiencies. Numerous within- and between-subset comparisons revealed statistically significantly different immune profiles. Conclusion While the analysis of non-partitioned data can result in information loss, complex (combinatorial) data structures can uncover hidden patterns, which guide data partitioning into subsets that differ in mortality rates and immune profiles. Such information can facilitate diagnostics, monitoring of disease dynamics, and evaluation of subset-specific, patient-specific therapies.

Epidemic Protection Zones: Centred on Cases or Based on Connectivity?

When an exotic infectious disease invades a susceptible environment, protection zones are enforced. Historically, such zones have been shaped as circles of equal radius (ER), centred on the location of infected premises. Because the ER policy seems to assume that epidemic dissemination is driven by a similar number of secondary cases generated per primary case, it does not consider whether local features, such as connectivity, influence epidemic dispersal. Here we explored the efficacy of ER protection zones. By generating a geographically explicit scenario that mimicked an actual epidemic, we created protection zones of different geometry, comparing the cost-benefit estimates of ER protection zones to a set of alternatives, which considered a pre-existing connecting network (CN) - the road network. The hypothesis of similar number of cases per ER circle was not substantiated: the number of units at risk per circle differed up to four times among ER circles. Findings also showed that even a small area (of <115 km(2) ) revealed network properties. Because the CN policy required 20% less area to be protected than the ER policy, and the CN-based protection zone included a 23.8% greater density of units at risk/km(2) than the ER-based alternative, findings supported the view that protection zones are likely to be less costly and more effective if they consider connecting structures, such as road, railroad and/or river networks. The analysis of local geographical factors (contacts, vectors and connectivity) may optimize the efficacy of control measures against epidemics.