Using optimal foraging theory to infer how groups make collective decisions

A growing body of evidence emerging from the analysis of advanced animal tracking data shows that moving groups make shared decisions about where to go, with each group member influencing the outcome. How groups coordinate departure decisions (when to go), however, remains poorly understood. Classic models from optimal foraging theory, specifically the marginal value theorem (MVT), are well-established tools that can generate quantitative predictions about when individuals should prefer to leave a food patch, given patch quality and the distribution of patches in the environment. Integrating optimal foraging theory into studies of animal collectives provides rich opportunities for gaining new insights from both empirical and theoretical studies. Specifically, the MVT can be used to make predictions about conflict of interests among group members, how consensus costs vary under different models of collective decision-making, and under what environmental conditions shared decision-making may be favored or disfavored

The medical student

The Medical Student was published from 1888-1921 by the students of Boston University School of Medicine

Estimating encounter location distributions from animal tracking data

1. Ecologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while the relationship between individual movement and the spatial locations of encounter events in the environment has remained conspicuously understudied. 2. Here, we bridge this gap by introducing a method for describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open-source software and demonstrate the broad ecological relevance of this distribution. 3. We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins Cebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizards Tiliqua rugosa, tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location-specific encounter probability. 4. The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via the ctmm R package

Molecular and Phenotypic Characteristics of Healthcare- and Community-Associated Methicillin-Resistant Staphylococcus aureus at a Rural Hospital

BACKGROUND: While methicillin-resistant Staphylococcus aureus (MRSA) originally was associated with healthcare, distinct strains later emerged in patients with no prior hospital contact. The epidemiology of MRSA continues to evolve. METHODS: To characterize the current epidemiology of MRSA-colonized patients entering a hospital serving both rural and urban communities, we interviewed patients with MRSA-positive admission nasal swabs between August 2009 and March 2010. We applied hospitalization risk factor, antimicrobial resistance phenotype, and multi-locus sequence genotype (MLST) classification schemes to 94 case-patients. RESULTS: By MLST analysis, we identified 15 strains with two dominant clonal complexes (CCs)-CC5 (51 isolates), historically associated with hospitals, and CC8 (27 isolates), historically of community origin. Among patients with CC5 isolates, 43% reported no history of hospitalization within the past six months; for CC8, 67% reported the same. Classification by hospitalization risk factor did not correlate strongly with genotypic classification. Sensitivity of isolates to ciprofloxacin, clindamycin, or amikacin was associated with the CC8 genotype; however, among CC8 strains, 59% were resistant to ciprofloxacin, 15% to clindamycin, and 15% to amikacin. CONCLUSIONS: Hospitalization history was not a strong surrogate for the CC5 genotype. Conversely, patients with a history of hospitalization were identified with the CC8 genotype. Although ciprofloxacin, clindamycin, and amikacin susceptibility distinguished CC8 strains, the high prevalence of ciprofloxacin resistance limited its predictive value. As CC8 strains become established in healthcare settings and CC5 strains disseminate into the community, community-associated MRSA definitions based on case-patient hospitalization history may prove less valuable in tracking community MRSA strains

Life in 2.5D: Animal Movement in the Trees

The complex, interconnected, and non-contiguous nature of canopy environments present unique cognitive, locomotor, and sensory challenges to their animal inhabitants. Animal movement through forest canopies is constrained; unlike most aquatic or aerial habitats, the three-dimensional space of a forest canopy is not fully realized or available to the animals within it. Determining how the unique constraints of arboreal habitats shape the ecology and evolution of canopy-dwelling animals is key to fully understanding forest ecosystems. With emerging technologies, there is now the opportunity to quantify and map tree connectivity, and to embed the fine-scale horizontal and vertical position of moving animals into these networks of branching pathways. Integrating detailed multi-dimensional habitat structure and animal movement data will enable us to see the world from the perspective of an arboreal animal. This synthesis will shed light on fundamental aspects of arboreal animals’ cognition and ecology, including how they navigate landscapes of risk and reward and weigh energetic trade-offs, as well as how their environment shapes their spatial cognition and their social dynamics

Early pre-radiographic structural pathology precedes the onset of accelerated knee osteoarthritis.

BACKGROUND: Accelerated knee osteoarthritis (AKOA) is characterized by more pain, impaired physical function, and greater likelihood to receive a joint replacement compared to individuals who develop the typical gradual onset of disease. Prognostic tools are needed to determine which structural pathologies precede the development of AKOA compared to individuals without AKOA. Therefore, the purpose of this manuscript was to determine which pre-radiographic structural features precede the development of AKOA. METHODS: The sample comprised participants in the Osteoarthritis Initiative (OAI) who had at least one radiographically normal knee at baseline (Kellgren-Lawrence [KL] grade  3) and No AKOA. The index visit was the study visit when participants met criteria for AKOA or a matched timepoint for those who did not develop AKOA. Magnetic resonance (MR) images were assessed for 12 structural features at the OAI baseline, and 1 and 2 years prior to the index visit. Separate logistic regression models (i.e. OAI baseline, 1 and 2 years prior) were used to determine which pre-radiographic structural features were more likely to antedate the development of AKOA compared to individuals not developing AKOA. RESULTS: At the OAI baseline visit, degenerative cruciate ligaments (Odds Ratio [OR] = 2.2, 95% Confidence Interval [CI] = 1.3,3.5), infrapatellar fat pad signal intensity alteration (OR = 2.0, 95%CI = 1.2,3.2), medial/lateral meniscal pathology (OR = 2.1/2.4, 95%CI = 1.3,3.4/1.5,3.8), and greater quantitative knee effusion-synovitis (OR = 2.2, 95%CI = 1.4,3.4) were more likely to antedate the development of AKOA when compared to those that did not develop AKOA. These results were similar at one and two years prior to disease onset. Additionally, medial meniscus extrusion at one year prior to disease onset (OR = 3.5, 95%CI = 2.1,6.0) increased the likelihood of developing AKOA. CONCLUSIONS: Early ligamentous degeneration, effusion/synovitis, and meniscal pathology precede the onset of AKOA and may be prognostic biomarkers

Composite quantitative knee structure metrics predict the development of accelerated knee osteoarthritis:data from the osteoarthritis initiative

BACKGROUND: We aimed to determine if composite structural measures of knee osteoarthritis (KOA) progression on magnetic resonance (MR) imaging can predict the radiographic onset of accelerated knee osteoarthritis. METHODS: We used data from a nested case-control study among participants from the Osteoarthritis Initiative without radiographic KOA at baseline. Participants were separated into three groups based on radiographic disease progression over 4 years: 1) accelerated (Kellgren-Lawrence grades [KL] 0/1 to 3/4), 2) typical (increase in KL, excluding accelerated osteoarthritis), or 3) no KOA (no change in KL). We assessed tibiofemoral cartilage damage (four regions: medial/lateral tibia/femur), bone marrow lesion (BML) volume (four regions: medial/lateral tibia/femur), and whole knee effusion-synovitis volume on 3 T MR images with semi-automated programs. We calculated two MR-based composite scores. Cumulative damage was the sum of standardized cartilage damage. Disease activity was the sum of standardized volumes of effusion-synovitis and BMLs. We focused on annual images from 2 years before to 2 years after radiographic onset (or a matched time for those without knee osteoarthritis). To determine between group differences in the composite metrics at all time points, we used generalized linear mixed models with group (3 levels) and time (up to 5 levels). For our prognostic analysis, we used multinomial logistic regression models to determine if one-year worsening in each composite metric change associated with future accelerated knee osteoarthritis (odds ratios [OR] based on units of 1 standard deviation of change). RESULTS: Prior to disease onset, the accelerated KOA group had greater average disease activity compared to the typical and no KOA groups and this persisted up to 2 years after disease onset. During a pre-radiographic disease period, the odds of developing accelerated KOA were greater in people with worsening disease activity [versus typical KOA OR (95% confidence interval [CI]): 1.58 (1.08 to 2.33); versus no KOA: 2.39 (1.55 to 3.71)] or cumulative damage [versus typical KOA: 1.69 (1.14 to 2.51); versus no KOA: 2.11 (1.41 to 3.16)]. CONCLUSIONS: MR-based disease activity and cumulative damage metrics may be prognostic markers to help identify people at risk for accelerated onset and progression of knee osteoarthritis

Strangeness nuclear physics: a critical review on selected topics

Selected topics in strangeness nuclear physics are critically reviewed. This includes production, structure and weak decay of $\Lambda$--Hypernuclei, the $\bar K$ nuclear interaction and the possible existence of $\bar K$ bound states in nuclei. Perspectives for future studies on these issues are also outlined.Comment: 63 pages, 51 figures, accepted for publication on European Physical Journal

Treatment outcomes of new tuberculosis patients hospitalized in Kampala, Uganda: a prospective cohort study.

BACKGROUND: In most resource limited settings, new tuberculosis (TB) patients are usually treated as outpatients. We sought to investigate the reasons for hospitalisation and the predictors of poor treatment outcomes and mortality in a cohort of hospitalized new TB patients in Kampala, Uganda. METHODS AND FINDINGS: Ninety-six new TB patients hospitalised between 2003 and 2006 were enrolled and followed for two years. Thirty two were HIV-uninfected and 64 were HIV-infected. Among the HIV-uninfected, the commonest reasons for hospitalization were low Karnofsky score (47%) and need for diagnostic evaluation (25%). HIV-infected patients were commonly hospitalized due to low Karnofsky score (72%), concurrent illness (16%) and diagnostic evaluation (14%). Eleven HIV uninfected patients died (mortality rate 19.7 per 100 person-years) while 41 deaths occurred among the HIV-infected patients (mortality rate 46.9 per 100 person years). In all patients an unsuccessful treatment outcome (treatment failure, death during the treatment period or an unknown outcome) was associated with duration of TB symptoms, with the odds of an unsuccessful outcome decreasing with increasing duration. Among HIV-infected patients, an unsuccessful treatment outcome was also associated with male sex (P = 0.004) and age (P = 0.034). Low Karnofsky score (aHR = 8.93, 95% CI 1.88 - 42.40, P = 0.001) was the only factor significantly associated with mortality among the HIV-uninfected. Mortality among the HIV-infected was associated with the composite variable of CD4 and ART use, with patients with baseline CD4 below 200 cells/µL who were not on ART at a greater risk of death than those who were on ART, and low Karnofsky score (aHR = 2.02, 95% CI 1.02 - 4.01, P = 0.045). CONCLUSION: Poor health status is a common cause of hospitalisation for new TB patients. Mortality in this study was very high and associated with advanced HIV Disease and no use of ART

TLR 2 and 4 responsiveness from isolated peripheral blood mononuclear cells from rats and humans as potential chronic pain biomarkers

Background: Chronic pain patients have increased peripheral blood mononuclear cell Interkeukin-1β production following TLR2 and TLR4 simulation. Here we have used a human-to-rat and rat-to-human approach to further investigate whether peripheral blood immune responses to TLR agonists might be suitable for development as possible systems biomarkers of chronic pain in humans. Methods and Results: Study 1: using a graded model of chronic constriction injury in rats, behavioral allodynia was assessed followed by in vitro quantification of TLR2 and TLR4 agonist-induced stimulation of IL-1β release by PBMCs and spinal cord tissues (n = 42; 6 rats per group). Statistical models were subsequently developed using the IL-1β responses, which distinguished the pain/no pain states and predicted the degree of allodynia. Study 2: the rat-derived statistical models were tested to assess their predictive utility in determining the pain status of a published human cohort that consists of a heterogeneous clinical pain population (n = 19) and a pain-free population (n = 11). The predictive ability of one of the rat models was able to distinguish pain patients from controls with a ROC AUC of 0.94. The rat model was used to predict the presence of pain in a new chronic pain cohort and was able to accurately predict the presence of pain in 28 out of the 34 chronic pain participants. Conclusions: These clinical findings confirm our previous discoveries of the involvement of the peripheral immune system in chronic pain. Given that these findings are reflected in the prospective graded rat data, it suggests that the TLR response from peripheral blood and spinal cord were related to pain and these clinical findings do indeed act as system biomarkers for the chronic pain state. Hence, they provide additional impetus to the neuroimmune interaction to be a drug target for chronic pain.Yuen H. Kwok, Jonathan Tuke, Lauren L. Nicotra, Peter M. Grace, Paul E. Rolan, Mark R. Hutchinso