Do focused interests support word learning? A study with autistic and nonautistic children

Although focused interests are often associated with a diagnosis of autism, they are common in nonautistic individuals as well. Previous studies have explored how these interests impact cognitive, social, and language development. While some research has suggested that strong interests can detract from learning (particularly for autistic children), newer research has indicated that they can be advantageous. In this pre-registered study, we asked whether focused interests support word learning in 44 autistic children and a vocabulary-matched sample of 44 nonautistic children (mean ages 58 and 34 months respectively). In a word-learning task administered over Zoom, children were exposed to an action labeled by a novel word. The action was either depicted by their focused interest or by a neutral image; stimuli were personalized for each child. At test, they were asked to identify the referent of the novel word, and their eye gaze was evaluated as a measure of learning. The preregistered analyses revealed an effect of focused interests, and post-hoc analyses clarified that autistic children learned the novel word in both the focused interest and neutral conditions, while nonautistic children only showed evidence of learning in the neutral condition. These results suggest that focused interests are not disruptive for vocabulary learning in autism, and thus they could be utilized in programming that supports early language learning in this population.

Endophytic fungi of Tradescantia pallida mediated targeting of Multi-Drug resistant human pathogens

Antimicrobial resistance (AMR) has emerged as one of the most serious worldwide public health issues of the twenty-first century. The expeditious rise of AMR has urged the development of new, natural effective therapeutic strategies against drug-resistant pathogens. Endophytic fungi, which inhabit distinctive environments like endosymbiotic relationships with plants, are gaining interest as alternative reservoirs for novel compounds that exhibit a broad range of chemical diversity and unique modes of action by releasing a variety of secondary metabolites with antimicrobial properties. The objective of the current research was to isolate and identify endophytic fungal species from leaves of Tradescantia pallida and to investigate their antagonistic effects on Multi-Drug-Resistant human pathogens. Endophytic fungus TPL11 and TPL14 showed maximum inhibition in agar plug and agar well diffusion assay. The ethyl acetate crude extract effectively suppressed growth of MRSA (Methicillin-resistant Staphylococcus aureus) ATCC 43300,700699 strains and VRE (Vancomycin-resistant Enterococcus) with the Inhibition zone of 22 ± 0.05, 23 ± 0.11 and 24 ± 0.11 mm respectively with minimum inhibitory concentration (MIC) of 3.125 µg/mL. Whereas TPL11 fungus revealed antibiosis of 22 ± 0.05 and 21 ± 0.15 mm against MRSA(ATCC 43300,700699) and 24 ± 0.05 mm for VRE with MIC of 6.25,3.125 and 1.56 μg/mL respectively. The MIC (Minimum inhibitory concentration) index further confirmed that both the extracts were bacteriostatic against MRSA and bactericidal against VRE. The isolates TPL11 and TPL14 were identified as Fusarium oxysporum and Nigrospora sphaerica by 18S rRNA internal transcribed spacer (ITS) sequencing. To our insight, it is the first report to reveal the presence of F.oxysporum and N.sphaerica in T.pallida and their antibacterial activity.

Xenomyrothecium tongaense PTS8: a rare endophyte of Polianthes tuberosa with salient antagonism against multidrug-resistant pathogens

Introduction

Endophytes refer to microorganisms residing within the endosphere of plants, particularly perennials, without inflicting noticeable injury or inducing obvious morphological variations to their host plant or host organism. Endophytic fungi, although often overlooked microorganisms, have garnered interest due to their significant biological diversity and ability to produce novel pharmacological substances.

Methods

In this study, fourteen endophytic fungi retrieved were from the stem of the perennial plant Polianthes tuberosa of the Asparagaceae family. These fungal crude metabolites were tested for antagonistic susceptibility to Multi-Drug Resistant (MDR) pathogens using agar well diffusion, Minimum Inhibitory Concentration (MIC), and Minimum Bactericidal Concentration (MBC) assays. The chequerboard test was used to assess the synergistic impact of active extract.

Results and discussion

In early antibacterial screening using the Agar plug diffusion test, three of fourteen endophytes demonstrated antagonism against Methicillin-resistant Staphylococcus aureus (MRSA) and Vancomycin-resistant Enterococcus (VRE). Three isolates were grown in liquid medium and their secondary metabolites were recovered using various organic solvents. Eight extracts from three endophytic fungi displayed antagonism against one or more human pathogens with diameters ranging from 11 to 24 mm. The highest antagonistic effect was obtained in ethyl acetate extract for PTS8 isolate against two MRSA (ATCC 43300, 700699) with 20 ± 0.27 and 22 ± 0.47 mm zones of inhibition, respectively, among different solvent extracts. The extract had MICs of 3.12 ± 0.05 and 1.56 ± 0.05 μg/mL, and MBCs of 50 ± 0.01 and 12.5 ± 0.04 μg/mL, respectively. Antagonism against VRE was 18 ± 0.23 mm Zone of Inhibition (ZOI) with MIC and MBC of 6.25 ± 0.25 and 25 ± 0.01 μg/mL. When ethyl acetate extract was coupled with antibiotics, the chequerboard assay demonstrated a synergistic impact against MDR bacteria. In an antioxidant test, it had an inhibitory impact of 87 ± 0.5% and 88.5 ± 0.5% in 2,2-Diphenyl-1-Picrylhydrazyl and reducing power assay, respectively, at 150 μg/mL concentration. PTS8 was identified as a Xenomyrothecium tongaense strain by 18S rRNA internal transcribed spacer (ITS) sequencing. To our insight, it is the foremost study to demonstrate the presence of an X. tongaense endophyte in the stem of P. tuberosa and the first report to study the antibacterial efficacy of X. tongaense which might serve as a powerful antibacterial source against antibiotic-resistant human infections.

Anti-MRSA activity of Pollianthes tuberosa leaf extracts

NA

Superhydrophobicity and size reduction enabled Halobates (Insecta: Heteroptera, Gerridae) to colonize the open ocean

Despite the remarkable evolutionary success of insects at colonizing every conceivable terrestrial and aquatic habitat, only five Halobates (Heteroptera: Gerridae) species (~0.0001% of all known insect species) have succeeded at colonizing the open ocean - the largest biome on Earth. This remarkable evolutionary achievement likely required unique adaptations for them to survive and thrive in the challenging oceanic environment. For the first time, we explore the morphology and behavior of an open-ocean Halobates germanus and a related coastal species H. hayanus to understand mechanisms of these adaptations. We provide direct experimental evidence based on high-speed videos which reveal that Halobates exploit their specialized and self-groomed body hair to achieve extreme water repellence, which facilitates rapid skating and plastron respiration under water. Moreover, the grooming behavior and presence of cuticular wax aids in the maintenance of superhydrophobicity. Further, reductions of their body mass and size enable them to achieve impressive accelerations (~400 ms-2) and reaction times (~12 ms) to escape approaching predators or environmental threats and are crucial to their survival under harsh marine conditions. These findings might also inspire rational strategies for developing liquid-repellent surfaces for drag reduction, water desalination, and preventing bio-fouling.

Enhancing Models and Measurements of Traffic-Related Air Pollutants for Health Studies Using Dispersion Modeling and Bayesian Data Fusion

INTRODUCTION

The adverse health effects associated with exposure to traffic-related air pollutants (TRAPs) remain a key public health issue. Often, exposure assessments have not represented the small-scale variation and elevated concentrations found near major roads and in urban settings. This research explores approaches aimed at improving exposure estimates of TRAPs that can reduce exposure measurement error when used in health studies. We consider dispersion models designed specifically for the near-road environment, as well as spatiotemporal and data fusion models. These approaches are implemented and evaluated utilizing data collected in recent modeling, monitoring, and epidemiological studies conducted in Detroit, Michigan.

APPROACH

Dispersion models, which estimate near-road pollutant concentrations and individual exposures based on first principles - and in particular, high fidelity models - can provide great flexibility and theoretical strength. They can represent the spatial variability of TRAP concentrations at locations not measured by conventional and spatially sparse air quality monitoring networks. A number of enhancements to dispersion modeling and mobile on-road emissions inventories were considered, including the representation of link-based road networks and updated estimates of temporal allocation of traffic activity, emission factors, and meteorological inputs. The recently developed Research LINE-source model (RLINE), a Gaussian line-source dispersion model specifically designed for the near-road environment, was used in an operational evaluation that compared predicted concentrations of nitrogen oxides (NOx), carbon monoxide (CO), and PM2.5 (particulate matter ≤ 2.5 µm in aerodynamic diameter) with observed concentrations at air quality monitoring stations located near high-traffic roads. Spatiotemporal and data fusion models provided additional and complementary approaches for estimating TRAP exposures. We formulated both nonstationary universal kriging models that exploit the spatial correlation in the monitoring data, and data fusion models that leverage the information contained in both the monitoring data and the output of numerical models, specifically RLINE. These models were evaluated using observations of nitric oxide (NO), NOx, black carbon (BC), and PM2.5 monitored along transects crossing major roads in Detroit. We also examined model assumptions, including the appropriateness of the covariance functions, errors in RLINE outputs, and the effects of jointly modeling two pollutants and using an updated emission inventory.

RESULTS

For CO and NOx, dispersion model performance was best when monitoring sites were close to major roads, during downwind conditions, during weekdays, and during certain seasons. The ability to discern local and particularly the traffic-related portion of PM2.5 was limited, a result of high background levels, the sparseness of the monitoring network, and large uncertainties for certain sources (e.g., area, fugitive) and some processes (e.g., formation of secondary aerosols). Sensitivity analyses of alternative meteorological inputs and updated emission factors showed some performance gain when using local (on-site) meteorological data and updated inventories. Overall, the operational evaluation suggested RLINE's usefulness for estimating spatially and temporally resolved exposure estimates. The application of the universal kriging models confirmed that wind speed and direction are important drivers of nonstationarity in pollutant concentrations, and that these models can predict exposure estimates that have lower prediction errors than do stationary model counterparts. The application of the Bayesian data fusion models suggested that the RLINE output had a spatially varying additive bias for NOx and PM2.5 and provided little additional information for NOx, besides what is already contained in traffic and geographical information system (GIS) covariates, but had improved estimates of PM2.5 concentrations. Results of the nonstationary Bayesian data fusion model that used RLINE output across a field spanning the measurement sites were similar to a regression-based Bayesian data fusion approach that used only RLINE output at the monitoring locations, with the latter being computationally less burdensome. Using the regression-based Bayesian data fusion model, we found that RLINE with the updated emission inventory provided results that were more useful for estimating NOx concentration at unmonitored sites, but the updated emission inventory did not improve predictions of PM2.5 concentrations. Joint modeling of NOx and PM2.5 was not useful, a result of differences in RLINE's utility in predicting PM2.5 and NOx - useful for the former, but not for the latter - and differences in the spatial dependence structures of the two pollutants. Overall, information provided by RLINE was shown to have the potential to improve spatiotemporal estimates of TRAP concentrations.

CONCLUSIONS

The study results should be interpreted and generalized cautiously given the limitations of the data used. Similar analyses in other settings are recommended for confirming and extending our findings. Still, the study highlights considerations that are relevant for exposure estimates used in health studies. The ability of a dispersion model to accurately reproduce and predict a pollutant depends on the pollutant as well as on spatial and temporal factors, such as the distance and direction from the road, time-of-day, and day-of-week. The nature and source of exposure measurement errors should be taken into consideration, particularly in health studies that take advantage of time- activity information that describes where and when individuals are exposed to pollution. Efforts to refine model inputs and improve model performance can be helpful; meteorological inputs may be the most critical. For both dispersion and spatiotemporal statistical models, sufficient and high-quality monitoring data are essential for developing and evaluating these models. Our analyses using Bayesian data fusion models confirm the presence of spatially varying errors in dispersion model outputs and allow quantification of both the magnitude and the spatial nature of these errors. This valuable information can be leveraged in health studies examining air pollution exposure as well as in studies informing regulatory responses.

Protein binding and antioxidant studies of diimine based emissive surfactant-ruthenium(II) complexes

Biophysical interaction of amphiphilic fluorescent surfactant-ruthenium(II) complexes and its precursor ruthenium(II) complexes with drug carrying proteins such as bovine and human serum albumins (BSA and HSA) have been studied through the UV-visible absorption, fluorescence and circular dichroism spectroscopic techniques to correlate the impact of head and tail groups of the metallosurfactants towards the designing of metallodrugs for the biomedical applications. The obtained results showed that both precursor- and surfactant-ruthenium(II) complexes interact with BSA/HSA via ground state protein-complex formation and their quenching follows the static mechanism. The extent of protein quenching and binding parameters resulted that the surfactant-ruthenium(II) complexes effectively interact with protein compared to their precursor-ruthenium(II) complexes, and also those interaction have greatly influenced by the change in the head group size compared to change in the tail group length. Interestingly on increasing the temperature, the protein-complex binding strength was decreased for the precursor-ruthenium(II) complexes, those increased for the surfactant-ruthenium(II) complexes, probably due to the respective involvement of electrostatic and hydrophobic interactions as supported by the thermodynamics of protein-complex interaction. Moreover, the results from UV-visible, synchronous and circular dichroism studies confirmed the occurrence of conformational and micro environmental changes in BSA/HSA upon binding with these complexes. It is also noted that HSA has more binding affinity with surfactant-ruthenium(II) complexes compared to BSA. The free radical scavenging ability against DPPH, ABTS, NO and superoxide free radical assays suggested that surfactant-ruthenium(II) complexes have better free radical scavenging ability compared to precursor-ruthenium(II) complexes.Communicated by Ramaswamy H. Sarma.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m³) of total O₃ and PM_2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O₃ 0.69, 0.5-0.85 ppbv) and 0.5% (PM_2.5 0.03, 0.01-0.05 μg/m³)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km²) and fine (36 × 36 km²) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O₃ and PM_2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Studies on the synthesis, characterization, human serum albumin binding and biological activity of single chain surfactant-cobalt(III) complexes

The interaction of surfactant-cobalt(III) complexes [Co(bpy)(dien)TA](ClO4)3 · 3H2O (1) and [Co(dien)(phen)TA](ClO4)3 · 4H2O (2), where bpy = 2,2'-bipyridine, dien = diethylenetriamine, phen = 1,10-phenanthroline and TA = tetradecylamine with human serum albumin (HSA) under physiological conditions was analyzed using steady state, synchronous, 3D fluorescence, UV/visabsorption and circular dichroism spectroscopic techniques. The results show that these complexes cause the fluorescence quenching of HSA through a static mechanism. The binding constant (Kb ) and number of binding-sites (n) were obtained at different temperatures. The corresponding thermodynamic parameters (∆G°, ∆H° and ∆S°) and Ea were also obtained. According to Förster's non-radiation energy transfer theory, the binding distance (r) between the complexes and HSA were calculated. The results of synchronous and 3D fluorescence spectroscopy indicate that the binding process has changed considerably the polarity around the fluorophores, along with changes in the conformation of the protein. The antimicrobial and anticancer activities of the complexes were tested and the results show that the complexes have good activities against pathogenic microorganisms and cancer cells.

A comparative study on the binding of single and double chain surfactant-cobalt(III) complexes with bovine serum albumin

The comparative binding effect of single and double aliphatic chain containing surfactant-cobalt(III) complexes cis-[Co(bpy)2(DA)2](ClO4)3·2H2O (1), cis-[Co(bpy)2(DA)Cl](ClO4)2·2H2O (2), cis-[Co(phen)2(CA)2](ClO4)3·2H2O (3), and cis-[Co(phen)2(CA)Cl](ClO4)2·2H2O (4) with bovine serum albumin (BSA) under physiological condition was analyzed by steady state, time resolved fluorescence, synchronous, three-dimensional fluorescence, UV-Visible absorption and circular dichroism spectroscopic techniques. The results show that these complexes cause the fluorescence quenching of BSA through a static mechanism. The binding constants (Kb) and the number of binding sites were calculated and binding constant values are found in the range of 10(4)-10(5) M(-1). The results indicate that compared to single chain complex, double chain surfactant-cobalt(III) complex interacts strongly with BSA. Also the sign of thermodynamic parameters (ΔG°, ΔH°, and ΔS°) indicate that all the complexes interact with BSA through hydrophobic force. The binding distance (r) between complexes and BSA was calculated using Förster non-radiation energy transfer theory and found to be less than 7 nm. The results of synchronous, three dimensional fluorescence and circular dichroism spectroscopic methods indicate that the double chain surfactant-cobalt(III) complexes changed the conformation of the protein considerably than the respective single chain surfactant-cobalt(III) complexes. Antimicrobial studies of the complexes showed good activities against pathogenic microorganisms.

Synthesis, Characterization and CMC Determination of some Double-Chain Surfactant-Cobalt(III) Complexes

Some new surfactant-cobalt(III) complex ions of the type, cis-[Co(X)2(C14H29NH2)2]3+ (where X = ethylenediamine or 2,2’ bipyridyl or 1,10-phenanthroline) and cis-α-[Co(trien)(C14H29NH2)2]3+ were synthesized and characterized by IR, NMR, UV-Visible electronic absorption spectra, elemental analysis and metal analysis. The critical micelle concentration (CMC) values of these surfactant-cobalt(III) complexes in aqueous solution were obtained from conductance measurements. Specific conductivity data (at 298, 308 and 318 K) served for the evaluation of temperature-dependent CMC and the thermodynamics of micellization (ΔG0 m, ΔH0 m, ΔS0 m).

Synthesis, spectral characterization, catalytic and antibacterial studies of new Ru(III) Schiff base complexes containing chloride/bromide and triphenylphosphine/arsine as co-ligands

A new Ru(III) Schiff base complexes of the type [RuX(EPh(3))L] (X = Cl/Br; E = P/As; L = dianion of the Schiff bases were derived by the condensation of 1,4-diformylbenzene with o-aminobenzoic acid/o-aminophenol/o-aminothiophenol in the 1:2 stoichiometric ratio) have been synthesized from the reactions of [RuX(3)(EPh(3))(3)] with appropriate Schiff base ligands in benzene in the 2:1 stoichiometric ratio. The new complexes have been characterized by analytical, spectral (IR, electronic, (1)H, (13)C NMR and ESR), magnetic moment and electrochemical studies. An octahedral structure has been tentatively proposed for all these new complexes. All the new complexes have been found to be better catalyst for the oxidation of alcohols using molecular oxygen as co-oxidant at ambient temperature and aryl-aryl coupling reactions. These complexes were also subjected to antibacterial activity studies against Escherichia coli, Aeromonas hydrophilla and Salmonella typhi.

Mononuclear Ru(III) Schiff base complexes: synthesis, spectral, redox, catalytic and biological activity studies

An octahedral ruthenium(III) Schiff base complexes of the type [RuX(EPh(3))(L)] (where, X=Cl/Br; E=As/P; L=dianion of the Schiff bases derived from acetoacetanilide with o-phenylenediamine and salicylaldehyde/o-hydroxyacetophenone/o-vanillin/2-hydroxy-1-naphthaldehyde) have been synthesized from the reactions of equimolar reactions of [RuX(3)(EPh(3))(3)] and Schiff bases in benzene. The new Ru(III) Schiff base complexes have been characterized by elemental analyses, FT-IR, electronic, (1)H NMR and (13)C NMR spectra, EPR spectral studies, powder X-ray diffraction (XRD) and electrochemical studies. The new complexes were found to be effective catalysts for aryl-aryl coupling and the oxidation of alcohols into their corresponding carbonyl compounds, respectively, using molecular oxygen atmosphere at ambient temperature. Further, the new Ru(III) Schiff base complexes were screened for their antibacterial activity against Pseudomonas aeruginosa, Vibrio cholera, Salomonella typhi and Staphylococcus aureaus.

Control of neurohypophysial hormone secretion, blood osmolality and volume in pregnancy

In pregnancy, blood volume increases greatly and plasma osmolality is reduced, due to mild hyponatraemia despite sodium retention. In rats, both vasopressin and oxytocin neurones in the supraoptic nucleus are osmosensitive and have contrasting roles in these adaptations. Increased vasopressin secretion stimulates water retention by renal actions, while oxytocin is natriuretic, partly by stimulating cardiac atrial natriuretic peptide (ANP) secretion. In pregnancy, relaxin from the corpora lutea, acting via the lamina terminalis in the presence of pregnancy levels of oestrogen and progesterone, stimulates vasopressin secretion and drinking, resulting in hypervolaemia and hyponatraemia. Initial stimulation of oxytocin secretion by relaxin is lost in late pregnancy, and oxytocin neurone responses to modest osmotic stimulation are reduced. Consequently, with reduced ANP secretion and action, sodium is retained and hypervolaemia maintained. Oxytocin neurone responses to other inputs, from hypervolaemia, immune or satiety signals, are reduced in late pregnancy by up-regulated central endogenous opioid mechanisms. Neither inhibition by opioid nor nitric oxide explains reduced responses to osmotic stimulation. Increased activity of GABA input, by allopregnanolone action, might be involved. However, the lack of a shift in threshold for hyperosmotic stimulation of oxytocin secretion in pregnancy, despite the hyponatraemia caused by relaxin, seems a sufficient explanation.

Uncertainty in ERP-Controlled Manufacturing Systems

The use of Enterprise Resource Planning (ERP) is becoming increasingly prevalent in many modern manufacturing enterprises. However, knowledge of their performance when perturbed simultaneously by several significant uncertainties is not as widespread as it should have been. This paper presents the developmental and experimental work on modeling uncertainty within an ERP multi-product, multi-level dependent demand manufacturing planning, and scheduling system in a simulation model developed using ARENA/SIMAN. To enumerate how uncertainty affects the performance of an ERP-controlled manufacturing system, the percentages of Finished Products Delivered Late (FPDL) and Parts Delivered Late (PDL) are measured. Sensitivity analysis shows that PDL gives a more accurate effect. Simulation results are analyzed using Analysis of Variance (ANOVA), which identifies four uncertainties; namely, late delivery from suppliers, machine breakdowns, unexpected/urgent changes to machine assignments, and customer design changes, which significantly affect PDL. Some uncertainties are found significantly interactive in two and three ways. They produce either knock-on and/or compound effects, a factor not generally recognized as a criterion for decision-making.