Polylactic acid nanoparticles for co-delivery of dinotefuran and avermectin against pear tree pests with improved effective period and enhanced bioactivity.

Pesticide compounding technology for disease and pest control emerges as an effective way to increase the effectiveness of pesticides while reducing pesticides resistance. Nanomaterials and encapsulation technology have offered a new insight into preparing efficient pesticide formulations, especially constructing a co-delivery nanoparticle for synergistic pesticides. In this study, a dinotefuran/avermectin co-delivery nanoparticles (DACNPs) against pear tree pests with polylactic acid (PLA) as the wall material were constructed by double-emulsion method combined with high-pressure homogenization technique. The drug content of the DACNPs was 39.1% with an average size of 245.7 ± 4.2 nm and the mean polymer dispersity index (PDI) value was 0.123. The DACNPs showed high foliar retention and good spread performance on target leaves due to the nanoscale effect. The obtained DACNPs showed a better control effect on Grapholitha molesta Busck and Psylla chinensis Yang et Li compared with the commercial formulations, which could significantly prolong the effective duration and enhance the bioactivity with lower amounts and application frequency of pesticides. This study may provide new insights into developing novel pesticide formulations to improve the utilization rate of pesticides, reduce environmental pollution and minimize the cost of farming.

Biomechanically Based Correlate for Localized Lung Contusion From Nonlethal Blunt Impact Projectiles.

INTRODUCTION: Injury mechanics of blunt impact projectiles differ from those experienced in whole body motor vehicle collisions because the effects are localized around the point of impact, and thus, injury thresholds based upon gross chest kinematics (e.g., force, velocity) may not be applicable across impact types. Therefore, knowledge of biomechanically based tissue injury correlates for blunt impact projectiles are needed to better guide design and development of protective systems as well as assess injury risks from blunt impact projectile weapons. MATERIALS AND METHODS: In this study, subject-specific swine finite element models were used to quantify the tissue-level stresses and strains resulting from high speed projectile impact. These tissue-level injury doses were correlated to pathology injury outcomes to produce injury risk curves for lung contusion. Details of the pathology data and finite element results are provided in Appendix 1. Survival analysis regression methods were applied to develop lung injury regression curves and a number of statistical methods were used to evaluate several biomechanical metrics as correlates to lung contusion. Uncertainty and sensitivity analyses were used to further confirm the selection of the correlate. RESULTS: Statistical analysis revealed that normalized strain-energy density was the best correlate for prediction of lung tissue damage. Going further, normalized strain-energy density also proved to be suitable for prediction of the percentage of contused lung volume, a more meaningful medical diagnosis. As expected, peak strain-energy density is most sensitive to muscle-skin properties, as quantified through a comprehensive uncertainty and sensitivity analysis over three sets of projectile weights and speeds. CONCLUSIONS: Normalized strain-energy density was found to be the best correlate for prediction of lung tissue damage and correlate well to extent of contused lung volume.

Preparation and characterization of a novel controlled-release nano-delivery system loaded with pyraclostrobin via high-pressure homogenization.

BACKGROUND: The development of efficient and safe green pesticides is a scientific strategy to alleviate current pesticide residues, environmental pollution, and threats to non-target organisms. Pesticide controlled-release formulations (CRFs) have attracted wide attention because they can control the rate of release of active ingredients and prolong the effective duration. In particular, nanoscale pesticide sustained-release systems have excellent biological activity and distribution performance because of their small particle size. Some technical difficulties remain in obtaining nanoscale CRFs. RESULTS: We successfully fabricated pyraclostrobin nanosphere CRF by combining high-pressure homogenization technology and emulsion-solvent evaporation methods. The pyraclostrobin nanospheres had a uniform spherical shape with a mean particle size of 450 nm and polydispersity index of less than 0.3. The pyraclostrobin loading capacity reached 53.6%, with excellent storage stability. The contact angle of nanospheres on cucumber leaf surfaces demonstrated that it had good wettability. Compared with pyraclostrobin technical and commercial formulations, the nanosphere systems showed a significantly sustained release of pyraclostrobin for longer (up to 250 h). A preliminary bioassay against Penicillium ochrochloron showed that the bioactivity and long-term efficiency of pyraclostrobin nanospheres were superior to those of the commercial formulation. CONCLUSION: This research introduced a simple, fast, expandable method for preparing pyraclostrobin nanospheres. The results showed that pyraclostrobin nanospheres could prolong the duration of pesticide efficacy and enhance bioactivity. Furthermore, this technology provides a platform for scale-up production of nano-scale pesticide CRFs. © 2020 Society of Chemical Industry.

Dual-Functionalized Pesticide Nanocapsule Delivery System with Improved Spreading Behavior and Enhanced Bioactivity.

The prevention and control of pests and diseases are becoming increasingly difficult owing to extensive pesticide resistance. The synergistic use of pesticides for disease control is an effective way of slowing pesticide resistance, reducing the number of pesticide applications, and protecting the environment. In this study, a dual-functionalized pesticide nanocapsule delivery system loaded with two active ingredients (AIs)-validamycin and thifluzamide-was developed to prevent and control rice sheath blight; the nanocapsule system was based on a water-oil-water double emulsion method combined with high-pressure homogenization technology. Our results showed that the dual-functionalized pesticide nanocapsules were monodisperse spheres with a mean particle size of ~260 nm and had good storage stability. Compared with commercial formulations, the dual-functionalized pesticide nanocapsules exhibited good foliar spread owing to their small size, which is beneficial for reducing the loss of pesticides on the leaves. The 50% median effect concentration and synergistic ratio against Rhizoctonia solani of the dual-functionalized pesticide nanocapsules and commercial formulation were 0.0082 and 0.0350 µg/mL, and 2.088 and 0.917, respectively. These findings indicate that the bioactivity of the dual-functionalized system was significantly better than that of the commercial formulations and that the dual-functionalized system demonstrated a clear synergistic effect between the two AIs. The system presented here is simple, fast, and capable of dual-pesticide loading with significant synergistic effects. Our findings could help to facilitate the improvement of pesticides efficiency and the slowing of pesticide resistance.

Construction of Lambda-Cyhalothrin Nano-Delivery System with a High Loading Content and Controlled-Release Property.

Traditional pesticide formulations are limited by large organic solvent consumption, poor dispersibility, and poor foliar adhesion, resulting in low effective pesticides utilization and environmental pollution. To prolong the foliar pesticide retention and release time, a high lambda-cyhalothrin (LC)-loaded nano-delivery system was constructed, using polylactic acid (PLA) as a carrier through a solvent evaporation method. The obtained results showed that the stabilizer concentration, water⁻oil ratio, and carrier content exert a major influence on the LC loading, particle size, and size distribution. The prepared LC/PLA nanoparticles have a uniform spherical shape with a smooth surface. The size of the nanoparticles was less than 200 nm, and the LC loading capacity reached up to 46.6 wt.%, with a high encapsulation efficiency (exceeding 90%). Adjustment of the shear and ultrasonic time changed the size of the nanoparticles. Significant differences were found in the sustained release properties of LC/PLA nanoparticles with different LC loadings. The foliage adhesion of the LC nano-delivery system far exceeded that of the commercial LC formulation due to a low surface tension and a low contact angle, this foliage adhesion would greatly help to improve pesticide utilization.

A Fast-Running, End-to-End Concussion Risk Model for Assessment of Complex Human Head Kinematics.

An end-to-end, mechanism-based concussion risk model, linking head motion to axonal injury, has been demonstrated to predict concussion outcomes with greater sensitivity and specificity than external correlates such as peak head acceleration. The development of this model was driven by the need to more accurately translate head-worn sensor measurements into injury assessment in near-real time. The full end-to-end model is a detailed multi-scale model, composed of complex components (e.g., a human head finite element model), is computationally expensive, and requires specialized software. For practicality, this research-level model must be simplified into a standalone, fast-running algorithm that can be embedded on the microprocessor of a head-worn sensor. This article describes the development of a simplified, fast-running algorithm that delivers comparable results to those of the full end-to-end model. The dynamic axonal response of the human head finite element model to head motion is mathematically modeled using a lumped parameter system fitted to the finite element model response for a range of head motions. The other component models of the full end-to-end model were similarly reduced. For the same head kinematic scenarios, the probabilities of concussion obtained from the end-to-end model and from the simplified algorithm are compared well.

Callosal injury-induced working memory impairment: a computational network modeling study.

Mild traumatic brain injury (mTBI) often results in working memory (WM) impairment, but the mechanistic relationship between the two remains elusive. We used a computational model of two cortical neuronal networks linked by myelinated callosal axons with distance-dependent conduction delays to simulate callosal dysfunction in mTBI and quantify its impact on WM. WM maintenance and termination in the model network depended on short-term synaptic plasticity. In injured networks, WM duration depended on the extent of callosal injury, consistent with clinical data. The model provides a framework for studying callosal injury-induced neurobehavioral alterations following mTBI, and, to the best of our knowledge, is the first computational model to address mTBI-induced WM impairment.

A Mechanistic End-to-End Concussion Model That Translates Head Kinematics to Neurologic Injury.

Past concussion studies have focused on understanding the injury processes occurring on discrete length scales (e.g., tissue-level stresses and strains, cell-level stresses and strains, or injury-induced cellular pathology). A comprehensive approach that connects all length scales and relates measurable macroscopic parameters to neurological outcomes is the first step toward rationally unraveling the complexity of this multi-scale system, for better guidance of future research. This paper describes the development of the first quantitative end-to-end (E2E) multi-scale model that links gross head motion to neurological injury by integrating fundamental elements of tissue and cellular mechanical response with axonal dysfunction. The model quantifies axonal stretch (i.e., tension) injury in the corpus callosum, with axonal functionality parameterized in terms of axonal signaling. An internal injury correlate is obtained by calculating a neurological injury measure (the average reduction in the axonal signal amplitude) over the corpus callosum. By using a neurologically based quantity rather than externally measured head kinematics, the E2E model is able to unify concussion data across a range of exposure conditions and species with greater sensitivity and specificity than correlates based on external measures. In addition, this model quantitatively links injury of the corpus callosum to observed specific neurobehavioral outcomes that reflect clinical measures of mild traumatic brain injury. This comprehensive modeling framework provides a basis for the systematic improvement and expansion of this mechanistic-based understanding, including widening the range of neurological injury estimation, improving concussion risk correlates, guiding the design of protective equipment, and setting safety standards.

Callosal dysfunction explains injury sequelae in a computational network model of axonal injury.

Mild traumatic brain injury (mTBI) often results in neurobehavioral aberrations such as impaired attention and increased reaction time. Diffusion imaging and postmortem analysis studies suggest that mTBI primarily affects myelinated axons in white matter tracts. In particular, corpus callosum, mediating interhemispheric information exchange, has been shown to be affected in mTBI. Yet little is known about the mechanisms linking the injury of myelinated callosal axons to the neurobehavioral sequelae of mTBI. To address this issue, we devised and studied a large, biologically plausible neuronal network model of cortical tissue. Importantly, the model architecture incorporated intra- and interhemispheric organization, including myelinated callosal axons and distance-dependent axonal conduction delays. In the resting state, the intact model network exhibited several salient features, including alpha-band (8-12 Hz) collective activity with low-frequency irregular spiking of individual neurons. The network model of callosal injury captured several clinical observations, including 1) "slowing down" of the network rhythms, manifested as an increased resting-state theta-to-alpha power ratio, 2) reduced response to attention-like network stimulation, manifested as a reduced spectral power of collective activity, and 3) increased population response time in response to stimulation. Importantly, these changes were positively correlated with injury severity, supporting proposals to use neurobehavioral indices as biomarkers for determining the severity of injury. Our modeling effort helps to understand the role played by the injury of callosal myelinated axons in defining the neurobehavioral sequelae of mTBI.

Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.

In vivo stimulus-induced vasodilation occurs without IP3 receptor activation and may precede astrocytic calcium increase.

Calcium-dependent release of vasoactive gliotransmitters is widely assumed to trigger vasodilation associated with rapid increases in neuronal activity. Inconsistent with this hypothesis, intact stimulus-induced vasodilation was observed in inositol 1,4,5-triphosphate (IP3) type-2 receptor (R2) knock-out (KO) mice, in which the primary mechanism of astrocytic calcium increase-the release of calcium from intracellular stores following activation of an IP3-dependent pathway-is lacking. Further, our results in wild-type (WT) mice indicate that in vivo onset of astrocytic calcium increase in response to sensory stimulus could be considerably delayed relative to the simultaneously measured onset of arteriolar dilation. Delayed calcium increases in WT mice were observed in both astrocytic cell bodies and perivascular endfeet. Thus, astrocytes may not play a role in the initiation of blood flow response, at least not via calcium-dependent mechanisms. Moreover, an increase in astrocytic intracellular calcium was not required for normal vasodilation in the IP3R2-KO animals.

Functional phase response curves: a method for understanding synchronization of adapting neurons.

Phase response curves (PRCs) for a single neuron are often used to predict the synchrony of mutually coupled neurons. Previous theoretical work on pulse-coupled oscillators used single-pulse perturbations. We propose an alternate method in which functional PRCs (fPRCs) are generated using a train of pulses applied at a fixed delay after each spike, with the PRC measured when the phasic relationship between the stimulus and the subsequent spike in the neuron has converged. The essential information is the dependence of the recovery time from pulse onset until the next spike as a function of the delay between the previous spike and the onset of the applied pulse. Experimental fPRCs in Aplysia pacemaker neurons were different from single-pulse PRCs, principally due to adaptation. In the biological neuron, convergence to the fully adapted recovery interval was slower at some phases than that at others because the change in the effective intrinsic period due to adaptation changes the effective phase resetting in a way that opposes and slows the effects of adaptation. The fPRCs for two isolated adapting model neurons were used to predict the existence and stability of 1:1 phase-locked network activity when the two neurons were coupled. A stability criterion was derived by linearizing a coupled map based on the fPRC and the existence and stability criteria were successfully tested in two-simulated-neuron networks with reciprocal inhibition or excitation. The fPRC is the first PRC-based tool that can account for adaptation in analyzing networks of neural oscillators.

[Development of a presenteeism questionnaire for skilled workers at high-technology enterprises].

OBJECTIVE: To develop a presenteeism questionnaire for Chinese high-technology skilled workers. METHODS: Methods being used would include literature review, face-to-face in depth interview, experts' consultation in developing the questionnaire. RESULTS: The presenteeism questionnaire includes two sections;one on employee's general health condition and the second one is a survey on the influences of employees'health conditions on their productivity. The first section includes 55 terms and 8 dimensionalities as below: Ache, Symptoms, Sleeping problem, Attention, Bad emotion, Pressure, Fatigue, Social adapting. These dimensionalities Cronbach's alpha are 0.79, 0.83, 0.75, 0.69, 0.83, 0.86, 0.80, 0.88 respectively and their half Spearman-Browns are 0.78, 0.75, 0.61, 0.62, 0.82, 0.81, 0.77, 0.88, respectively. Goodness of fit test model indices are as below: chi(2)/df -3.68, normed fit index 0.95, non-normed fit index 0.96, compatative fit index 0.96, standardized root mean residual 0.05, root mean square error of approximation 0.05. The relate-coefficient with SF-36 is 0.55. 42.77% of employees having received the survey, claim that their health problem do not influence their productivity, and 55.72% of them claiming that their productivity are reduced to 50%-90% because of their health problems while another 1.51% of them claim that their productivity reduced more than 50%. 84.5% of the interviewees claim that they have never been absent at work because of health problems, and 15.3% of them claim that their total hours of absence are between 0 and 100. Only 0.2% of the workers claim that the total hours of absence are more than 100. CONCLUSION: The developed presenteeism shows good reliability and higher validity, so can be used to measure the presenteeism of skilled workers working at high-technology enterprises.

Spatiotemporal networks in addressable excitable media.

Spatiotemporal networks are studied in a photosensitive Belousov-Zhabotinsky medium that allows both local and nonlocal transmission of excitation. Local transmission occurs via propagating excitation waves, while nonlocal transmission takes place by nondiffusive jumps to destination sites linked to excited sites in the medium. Static, dynamic, and domain link networks are experimentally and computationally characterized. Transitions to synchronized behavior are exhibited with increasing link density, and power-law relations are observed for first-coverage time as a function of link probability.

Synchronization of spatiotemporal patterns in locally coupled excitable media.

The synchronization of two distributed Belousov-Zhabotinsky systems is experimentally and theoretically investigated. Symmetric local coupling of the systems is made possible with the use of a video camera-projector scheme. The spatial disorder of the coupled systems, with random initial configurations of spirals, gradually decreases until a final state is attained, which corresponds to a synchronized state with a single spiral in each system. The experimental observations are confirmed with numerical simulations of two identical Oregonator models with symmetric local coupling, and a systematic study reveals generalized synchronization of spiral waves. Several different types of synchronization attractors are distinguished.