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Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as empirical studies continue to reflect the (implicit) preferences of scholars. This is challenging for instructors, who may thus ignore critical aspects of a map and/or waste their efforts by examining highly correlated features. To address the research gap of selecting informative graph metrics to assess knowledge maps, this study adopts the machine learning technique of Unsupervised Feature Selection (UFS). Specifically, we extract 12 features used in the prior literature on map assessment (e.g., density, diameter) and use 8 UFS algorithms to rank their importance. By using 202 maps originating from four case studies, we identify features that are generally (un)informative and observe nuances due to context (e.g., learning task, participant profiles). Results suggest that features commonly reported (e.g., number of edges) may not be as informative as less commonly examined aspects (e.g., average degree). Differences exist between maps: the diameter is valuable when learners produce maps from detailed studies, but less informative when maps are directly elicited from the learners' perspectives. The 8 UFS algorithms show five distinct ways to rank features in maps, hence future works may elicit the preferences of instructors for grading and map these preferences to an algorithmic approach (i.e., UFS) that produces a desired ranking.

Abstract Background Few animal populations have been studied under the framework of the OCBIL theory, which addresses the ecology and evolution of biodiversity on old climatically buffered infertile landscapes. Available genetic data challenge the low connectivity and high genetic differentiation predicted for isolated tepui-summit vertebrate communities, suggesting potential dispersal among summits. However, the OCBIL theory posits reduced dispersibility, enhanced resilience to habitat fragmentation and inbreeding due to small populations. We tested these hypotheses by conducting the first analytic evaluation of the spatial ecology and population biology of a tepui-summit vertebrate at multiple spatial scales. Results We used harmonic radar tracking (100 individuals/448 points of contact) and capture-mark-recapture data (596 individuals captured/52 recaptured) to reveal the temporal niche, microhabitat use, population size, and dispersal abilities of the tepui-summit endemic toad Oreophrynella quelchii on Roraima-tepui. Abundance was determined using a closed population model incorporating sources of variation in capture probability. We tested the relative influence of biotic and abiotic variables on distances moved through model selection. Our data indicate that the population size of O. quelchii is remarkably large (ca. 12 million individuals), with strong seasonal demographic fluctuations. Ecology and observed limited spatial movements challenge the likelihood of active dispersal among tepui tops in this species. Our results are counter to those predicted by the available genetic data but support two hypotheses of the OCBIL theory: reduced dispersibility and enhanced resilience. However, they do not support the expectation of a small refugial population size. Conclusion We postulate that the insular, hostile tepui-summit environment tends to produce robust demographic populations, likely to buffer stochastic adverse environmental effects, rather than diversity, as observed in much younger post-Pleistocene Neotropical landscapes. Our results draw attention to the value of faunal studies using an OCBIL framework to better understand the ecology and evolution of this unique biota worldwide.

Abstract Tadpoles serve as crucial evidence for testing systematic and taxonomic hypotheses. Suctorial tadpoles collected in Guyana were initially assigned to Rhaebo nasicus through molecular phylogeny. Subsequent analysis of larval and adult morphological traits revealed synapomorphies within the clade encompassing R. nasicus and R. ceratophrys, prompting the recognition of a new genus described herein as Adhaerobufo. The new genus is distinguished from other bufonids by specific phenotypic traits including an enlarged, suctorial oral disc with distinct papillae arrangements, and the presence of certain muscles and narial vacuities at the larval stage. However, only a few adult external characteristics (e.g., enlarged eyelids, infraocular cream spot), seem to be reliably discriminative from related genera. This study underscores the significance of larval morphology in anuran systematics and offers new insights into the evolution of suctorial and gastromyzophorous larvae within bufonids.

Students employing problem-based learning (PBL) face complex problems admitting multiple solutions. Knowledge maps are an effective tool to support students in PBL to represent, analyze, and guide their knowledge structure. Previous studies have examined the use of knowledge mapping techniques in both individual and collaborative learning process. These studies explored how knowledge mapping influenced students' learning outcomes and their knowledge understanding, but they did not document how the map structure changed when shifting from individual to collaborative mapping process. In this work-in-process study, we collected maps from students first as individuals and then as they collaboratively worked in groups to solve a case. We examined two questions: (Q1) how does the structure of a map change when shifting from individuals to groups, and (Q2) how does the size of a group mediate these changes. We used 12 network science metrics capturing the breadth (e.g., number of edges) and complexity (e.g., number of cycles) of problems and compared these metrics in individuals versus groups (Q1) and across group sizes (Q2). Based on 44 individual maps arranged in 10 groups of four or five students, we found that (1) five metrics significantly differ (p < 0.05 in a one-way ANOVA) between individual and group maps; and (2) only the number of edges and paths are affected by the size of a group (based on Tukey's HSD test). Our first result confirms that learner-learner interactions can enhance performance. The second result shows that group sizes of four or five students have no implications on the results, hence instructors who may currently be hesitating between these two options may choose either size. Future studies may reveal whether differences exist between pairs, medium group sizes, or larger groups.

Abstract Background Rapid point-of-care tests for malaria are now widely used in many countries to guide the initial clinical management of patients presenting with febrile illness. With China having recently achieved malaria elimination, better understanding regarding the identity and distribution of major non-malarial causes of febrile illnesses is of particular importance to inform evidence-based empirical treatment policy. Methods A systematic review of published literature was undertaken to characterise the spectrum of pathogens causing non-malaria febrile illness in China (1980–2015). Literature searches were conducted in English and Chinese languages in six databases: Ovid MEDLINE, Global Health, EMBASE, Web of Science™ – Chinese Science Citation Database SM, The China National Knowledge Infrastructure (CNKI), and WanFang Med Online. Selection criteria included reporting on an infection or infections with a confirmed diagnosis, defined as pathogens detected in or cultured from samples from normally sterile sites, or serological evidence of current or past infection. The number of published articles, reporting a given pathogen were presented, rather than incidence or prevalence of infection. Results A total of 57,181 records from 13 provinces of China where malaria used to be endemic were screened, of which 392 met selection criteria and were included in this review. The review includes 60 (15.3%) records published from 1980 to 2000, 211 (53.8%) from 2001 to 2010 and 121 (30.9%) from 2011 to 2015;. Of the 392 records, 166 (42.3%) were from the eastern region of China, 120 (30.6%) were from the south-west, 102 (26.0%) from south-central, and four (1.0%) were multi-regional studies. Bacterial infections were reported in 154 (39.3%) records, viral infections in 219 (55.9%), parasitic infections in four (1.0%), fungal infections in one (0.3%), and 14 (3.6%) publications reported more than one pathogen group. Participants of all ages were included in 136 (34.7%) studies, only adults in 75 (19.1%), only children in 17 (4.3%), only neonates in two (0.5%) and the age distribution was not specified in 162 (41.3%) records. The most commonly reported bacterial pathogens included Typhoidal Salmonella (n = 30), Orientia/ Rickettsia tsutsugamushi (n = 31), Coxiella burnetii (n = 17), Leptospira spp. (n = 15) and Brucella spp. (n = 15). The most commonly reported viral pathogens included Hantavirus/Hantaan virus (n = 89), dengue virus (DENV) (n = 76 including those with unknown serovars), Japanese encephalitis virus (n = 21), and measles virus (n = 15). The relative lack of data in the western region of the country, as well as in in neonates and children, represented major gaps in the understanding of the aetiology of fever in China. Conclusions This review presents a landscape of non-malaria pathogens causing febrile illness in China over 36 years as the country progressed toward malaria elimination. These findings can inform guidelines for clinical management of fever cases and infection surveillance and prevention, and highlight the need to standardize operational and reporting protocols for better understanding of fever aetiology in the country.

Neuropeptide Y (NPY) and related peptides have been proposed as promising biomarkers for the diagnosis of prostate cancer by previous immunoassays and immunohistochemical studies. In this study, we evaluated the additional value of NPY and related peptides compared with prostate-specific antigen (PSA). We performed a comprehensive analysis of NPY, its precursors, and metabolite concentrations in both plasma and tissue samples from 181 patients using a highly specific liquid chromatography tandem mass spectrometry method. Compared with PSA, NPY and related peptides (NPYs) were less accurate at diagnosing significant prostate cancer. Combinations of NPYs in a stepwise approach did not improve a model that would be beneficial for patients. NPY may be beneficial for patients presenting with a PSA concentration in the gray area between 4 and 9 ng/ml, but the strength of this conclusion is limited. Thus, the use of NPYs as standalone or in combination with other variables, such as PSA, prostate volume, or age, to improve the diagnosis is not supported by our study. Patient summary: This study evaluated neuropeptide Y (NPY) of the family of endogenous peptides as a new biomarker to diagnose prostate cancer. We found that NPY in a patient’s blood was not more helpful at diagnosing prostate cancer than the standard prostate-specific antigen blood test. Further research is needed to explore the potential of NPY and related peptides in specific subgroups of patients.

ABSTRACT Timely and accurate identification of yeasts is essential for adequate treatment, considering the increase in antifungal resistance of some species, particularly for C. auris. Current matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) manufacturer’s protocol for identification of yeasts requires 24- to 72-h cultivation on Sabouraud dextrose media (SAB), but not some of the mainstay primary culture media used in mycology such as inhibitory mold agar (IMA), Mycosel, CHROMagar Candida Plus, and CHROMagar Candida. As culture media can influence MALDI-TOF MS identification results, this study evaluated the accuracy and performance of identification of clinically relevant yeasts on these first-line media using the VITEK-MS MALDI-TOF MS system.IMPORTANCEIn this study, a panel of 140 strains (21 species) was used to assess the performance of the selected media. Although not in the manufacturer’s list of accepted media, IMA and chromogenic media are suitable for the identification of yeasts on the VITEK-MS systems. CHROMagar Candida Plus allowed the identification of 135/140 isolates tested after 24-h incubation similar to SAB reference media (137/140). Yeast isolates that grew on Mycosel selective media were also reliably identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. VITEK-MS system with IVD database V3.2 correctly identified C. auris strains to the species level on CHROMagar Candida Plus alleviating the need for subcultivation and reduced turnaround time (24–72 h) to identification for patient screening.

BACKGROUND: Low mobility of patients during hospitalisation is associated with adverse outcomes. To successfully change behaviours related to mobility of older hospitalised patients, we need to better understand the mechanisms underlying patient and healthcare professional behaviours. In this study, we thus assessed patient- and healthcare professional-reported intentions and behaviours related to mobility of older patients hospitalised on an acute medical ward, based on a theoretical framework – the Health Action Process Approach (HAPA) model – and on additional barriers and facilitators to mobility. METHODS: We conducted a cross-sectional survey in April 2022 among patients aged ≥60 years recently hospitalised on an an acute medical ward of one of three hospitals of different language/cultural regions of Switzerland, and healthcare professionals (physicians, nurses/nursing assistants, physiotherapists) working on those wards. The survey assessed the HAPA model and additional barriers and facilitators to patient mobility at hospital, as previously identified in the literature. The target behaviour studied was “to move as much as possible during hospitalisation” for patients and “to ensure my patients move as much as possible during hospitalisation” for healthcare professionals. We conducted hierarchical linear regressions to determine factors associated with the self-reported intention to perform the behaviour and with the self-reported behaviour itself. RESULTS: A total of 142 healthcare professionals (61 physicians, 59 nurses, 22 physiotherapists) and 200 patients (mean age 74 years) completed the survey. Patients with higher intention to move as much as possible during hospitalisation scored significantly higher on factual knowledge, outcome expectancies and risk perception. Healthcare professionals with higher intention to ensure that their patients move as much as possible during hospitalisation scored higher on action knowledge, outcome expectancies and risk perception. The more the patients reported that they moved as much as possible during hospitalisation, the higher their action knowledge and action control. The more healthcare professionals reported that they ensure that patients move as much as possible during hospitalisation, the higher they scored on factual knowledge, role perception, planning and action control. CONCLUSIONS: factual and action knowledge, self-efficacy, outcome expectancies, risk perception, planning and action control were identified as important drivers of patient- and healthcare professional-reported intentions and behaviours related to inpatient mobility. These parameters can be addressed through behaviour-change interventions and should be considered in future interventions to successfully implement practice changes, with the goal of improving mobility of older patients during hospitalisation, and thus the outcomes of this particularly vulnerable population.

Abstract Background Plasmodium vivax remains a major challenge for malaria control and elimination due to its ability to cause relapsing illness. To prevent relapses the Indian National Center for Vector Borne Diseases Control (NCVBDC) recommends treatment with primaquine at a dose of 0.25 mg/kg/day provided over 14 days. Shorter treatment courses may improve adherence and treatment effectiveness. Methods This is a hospital-based, randomised, controlled, open-label trial in two centres in India. Patients above the age of 16 years, with uncomplicated vivax malaria, G6PD activity of ≥ 30% of the adjusted male median (AMM) and haemoglobin levels ≥ 8 g/dL will be recruited into the study and randomised in a 1:1 ratio to receive standard schizonticidal treatment plus 7-day primaquine at 0.50 mg/kg/day or standard care with schizonticidal treatment plus 14-day primaquine at 0.25 mg/kg/day. Patients will be followed up for 6 months. The primary endpoint is the incidence risk of any P. vivax parasitaemia at 6 months. Safety outcomes include the incidence risk of severe anaemia (haemoglobin < 8 g/dL), the risk of blood transfusion, a > 25% fall in haemoglobin and an acute drop in haemoglobin of > 5 g/dL during primaquine treatment. Discussion This study will evaluate the efficacy and safety of a 7-day primaquine regimen compared to the standard 14-day regimen in India. Results from this trial are likely to directly inform national treatment guidelines. Trial registration Trial is registered on CTRI portal, Registration No: CTRI/2022/12/048283.

Abstract Background Intervention planners use logic models to design evidence-based health behavior interventions. Logic models that capture the complexity of health behavior necessitate additional computational techniques to inform decisions with respect to the design of interventions. Objective Using empirical data from a real intervention, the present paper demonstrates how machine learning can be used together with fuzzy cognitive maps to assist in designing health behavior change interventions. Methods A modified Real Coded Genetic algorithm was applied on longitudinal data from a real intervention study. The dataset contained information about 15 determinants of fruit intake among 257 adults in the Netherlands. Fuzzy cognitive maps were used to analyze the effect of two hypothetical intervention scenarios designed by domain experts. Results Simulations showed that the specified hypothetical interventions would have small impact on fruit intake. The results are consistent with the empirical evidence used in this paper. Conclusions Machine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness.