Physiological Interference Research Articles

LBODP101 Misleading FT4 Result In A Patient With Hashimoto's Thyroiditis

Abstract Thyroid hormones and thyroid-stimulating hormone (TSH) laboratory tests are widely utilized worldwide, and their results have a significant impact on treatment decisions and subsequent diagnostic processes. In order to avoid misdiagnosis and inappropriate therapy, any differences between symptoms and laboratory findings should be thoroughly investigated. Many factors can cause discrepancies between thyroid function test and the patients’ clinical picture such as physiological changes, severe illness, drugs, or laboratory interference. Thyroid hormone autoantibodies, anti-streptavidin, and anti-ruthenium antibodies are the major thyroid function test interferers. Here, we present a case of a 70-year-old woman who is known to have hashimoto's thyroiditis maintained on Levothyroxine (LT4) for more than 10 years, but was stopped by her primary care physician due to abnormal thyroid panel results (high TSH and high fT4). She was referred to the endocrinology clinic for further evaluation. The patient complained of generalized fatigue and weakness. She had no hyperthyroid symptoms. She was not on any supplements. Testing thyroid hormones with the 2-step assay revealed severe hypothyroidism, so LT4 was resumed, and patient symptoms improved. This case aims to direct clinicians’ attention to the importance of considering the patient's clinical status in the diagnostic process and not replacing it with the laboratory diagnosis, given the possibility of many laboratories’ interference. Also, to underline the available methods to minimize false results and misleading diagnoses to avoid unnecessary investigations and interventions. Presentation: No date and time listed

Deep-learning informed Kalman filtering for priori-free and real-time hemodynamics extraction in functional near-infrared spectroscopy.

Separation of the physiological interferences and the neural hemodynamics has been a vitally important task in the realistic implementation of functional near-infrared spectroscopy (fNIRS). Although many efforts have been devoted, the established solutions to this issue additionally rely on priori information on the interferences and activation responses, such as time-frequency characteristics and spatial patterns, etc., also hindering the realization of real-time. To tackle the adversity, we herein propose a novel priori-free scheme for real-time physiological interference suppression. This method combines the robustness of deep-leaning-based interference characterization and adaptivity of Kalman filtering: a long short-term memory (LSTM) network is trained with the time-courses of the absorption perturbation baseline for interferences profiling, and successively, a Kalman filtering process is applied with reference to the noise prediction for real-time activation extraction. The proposed method is validated using both simulated dynamic data and in-vivo experiments, showing the comprehensively improved performance and promisingly appended superiority achieved in the purely data-driven way.

Highly Stable and Selective Sensing of Hydrogen Sulfide in Living Mouse Brain with NiN4 Single-Atom Catalyst-Based Galvanic Redox Potentiometry

Hydrogen sulfide (H2S) is recognized as a gasotransmitter and multifunctional signaling molecule in the central nervous system. Despite its essential neurofunctions, the chemical dynamics of H2S during physiological and pathological processes remains poorly understood, emphasizing the significance of H2S sensor development. However, the broadly utilized electrochemical H2S sensors suffer from low stability and sensitivity loss in vivo due to sulfur poisoning-caused electrode passivation. Herein, we report a high-performance H2S sensor that combines single-atom catalyst strategy and galvanic redox potentiometry to overcome the issue. Atomically dispersed NiN4 active sites on the sensing interface promote electrochemical H2S oxidation at an extremely low potential to drive spontaneous bipolarization of a single carbon fiber. Bias-free potentiometric sensing at open-circuit condition minimizes sulfur accumulation on the electrode surface, thus significantly enhancing the stability and sensitivity. The resulting sensor displays high selectivity to H2S against physiological interferents and enables real-time accurate quantification of H2S-releasing behavior in the living mouse brain.

Intelligent Extraction of Salient Feature From Electroencephalogram Using Redundant Discrete Wavelet Transform.

At present, electroencephalogram (EEG) signals play an irreplaceable role in the diagnosis and treatment of human diseases and medical research. EEG signals need to be processed in order to reduce the adverse effects of irrelevant physiological process interference and measurement noise. Wavelet transform (WT) can provide a time-frequency representation of a dynamic process, and it has been widely utilized in salient feature analysis of EEG. In this paper, we investigate the problem of translation variability (TV) in discrete wavelet transform (DWT), which causes degradation of time-frequency localization. It will be verified through numerical simulations that TV is caused by downsampling operations in decomposition process of DWT. The presence of TV may cause severe distortions of features in wavelet subspaces. However, this phenomenon has not attracted much attention in the scientific community. Redundant discrete wavelet transform (RDWT) is derived by eliminating the downsampling operation. RDWT enjoys the attractive merit of translation invariance. RDWT shares the same time-frequency pattern with that of DWT. The discrete delta impulse function is used to test the time-frequency response of DWT and RDWT in wavelet subspaces. The results show that DWT is very sensitive to the translation of delta impulse function, while RDWT keeps the decomposition results unchanged. This conclusion has also been verified again in decomposition of actual EEG signals. In conclusion, to avoid possible distortions of features caused by translation sensitivity in DWT, we recommend the use of RDWT with more stable performance in BCI research and clinical applications.

Characteristics of the Dynamic Electrocardiogram in the Elderly with Nonvalvular Atrial Fibrillation Combined with Long R-R Intervals.

Objective To investigate the characteristics of dynamic electrocardiogram and their clinical implications in elderly patients with nonvalvular atrial fibrillation combined with long R-R intervals. Methods Elderly patients diagnosed with nonvalvular atrial fibrillation who were admitted as an inpatient or attended the outpatient department from January 2015 to January 2020 were selected. Patients were divided into two groups based on the presence of a long R-R interval. The characteristics and therapeutic significance of dynamic electrocardiogram between the two groups were compared. Results A total of 532 patients were included in our analyses. Of these, 399 patients were in the long R-R interval group and 133 in the nonlong R-R interval group. In 399 patients, there were 48,840 long R-R intervals manifested within 24 hours. The average, slowest, and fastest ventricular rates during sleep time were higher than those in nonsleep time, while the number of long R-R intervals in sleep time was significantly smaller than that in nonsleep time (P < 0.05). Clinical parameters including dizziness/syncope, cerebral infarction, ST-segment changes, platelet count, average hematocrit, prothrombin time (PT), left ventricular systolic function, end-diastolic diameter, pulmonary artery pressure, and left ventricular ejection fraction were comparable between the groups (P > 0.05). When compared with the nonlong R-R interval group, the level of C-reactive protein was slightly lower in the long R-R interval group (P < 0.05). In addition, the long R-R interval group had a higher incidence of atrial premature beats but a lower incidence of ventricular premature beats. Furthermore, the probability of long R-R interval combined with paroxysmal atrial tachycardia, transient ventricular arrest, second-degree atrioventricular block, and complete or incomplete right bundle branch block was higher than that of nonlong R-R interval (P < 0.05). In patients with long R-R interval >3 s, the risk of having second-degree atrioventricular block and complete or incomplete right bundle branch block was significantly lower, while the risk of having transient ventricular arrest was higher when compared to patients with long R-R intervals of 2-3 s (P < 0.05P). Conclusions Long R-R interval is a common electrocardiographic phenomenon among the elderly with nonvalvular atrial fibrillation. The long R-R interval mostly occurs in nonsleeping time. The average ventricular rate, slowest ventricular rate, and fastest ventricular rate of sleep time are higher than nonsleeping time. Analysis of the characteristics of the dynamic electrocardiogram of these patients may shed light on the mechanisms for long R-R intervals, including the likelihood of concealed conduction and physiological interference in the atrioventricular node, overspeed inhibition, increased vagus nerve tension, or pathological atrioventricular block.

Assessment of Human Exposure (Including Interference to Implantable Devices) to Low-Frequency Electromagnetic Field in Modern Microgrids, Power Systems and Electric Transports

Electromagnetic field emissions of modern power systems have increased in complexity if the many power conversion forms by means of power electronics and static converters are considered. In addition, the installed electric power has grown in many everyday applications such as wireless charging of vehicles, home integrated photovoltaic systems, high-performance electrified transportation systems, and so on. Attention must then be shifted to include harmonics and commutation components on one side, as well as closer interaction with humans, that concretizes in impact on physiological functions and interference to implantable medical devices and hearing aids. The panorama is complex in that standards and regulations have also increased significantly or underwent extensive revisions in the last 10 years or so. For assessment, the straightforward application of the limits of exposure is hindered by measurement problems (time or frequency domain methods, positioning errors, impact of uncertainty) and complex scenarios of exposure (multiple sources, large field gradient, time-varying emissions). This work considers thus both the clarification of the principles of interaction for each affected system (including humans) and the discussion of the large set of related normative and technical documents, deriving a picture of requirements and constraints. The methods of assessment are discussed in a metrological perspective using a range of examples.

Repeated exposure to simulated marine heatwaves enhances the thermal tolerance in pearl oysters.

In an era of unprecedented climate change, marine heatwaves (MHWs) are projected to increase in frequency, intensity, and duration, severely affecting marine organisms and fisheries and causing profound ecological and socioeconomic impacts. However, very little is known about effects of MHWs on ecologically and economically important bivalve species. Here, we investigate how pearl oysters, Pinctada maxima (Jameson), respond to MHWs under various simulated scenarios. Acute 3-day exposure to MHWs, mimicked by increasing the ambient seawater temperature from 24°C to 28°C, 32°C, and 36°C, respectively, induced significant changes (initially sustained increase and late decrease) in activities of antioxidant enzymes (GSH-Px, SOD, CAT, MDA, and T-AOC) and biomineralizaiton-related enzymes (AKP and ACP). Likewise, energy-metabolizing enzymes (NKA, CMA, and T-ATP) showed remarkable acute responses, with significant increases occurring at the beginning and end of thermal exposure. Following repeated exposure to MHWs, without exception, acute responses of assayed enzymes to MHWs were significantly alleviated, implying that pearl oysters have the ability to implement more efficient and less costly energy-utilizing strategies to compensate for thermal stress induced physiological interferences. These findings indicate that marine bivalves can respond plastically and acclimate rapidly to MHWs and pave the way for predicting the fate of this important taxonomic groups in rapidly changing oceans.

The Role of Temperature in Moral Decision-Making: Limited Reproducibility.

Temperature is one of the major environmental factors that people are exposed to on a daily basis, often in conditions that do not afford control. It is known that heat and cold can influence a person’s productivity and performance in simple tasks. With respect to social cognition, it has also been suggested that temperature impacts on relatively high-level forms of decision-making. For instance, previous research demonstrated that cold temperature promotes utilitarian judgment in a moral dilemma task. This effect could be due to psychological processing, when a cool temperature primes a set of internal representations (associated with “coldness”). Alternatively, the promotion of utilitarian judgment in cold conditions could be due to physiological interference from temperature, impeding on social cognition. Refuting both explanations of psychological or physiological processing, however, it has been suggested that there may be problems of reproducibility in the literature on temperature modulating complex or abstract information processing. To examine the role of temperature in moral decision-making, we conducted a series of experiments using ambient and haptic temperature with careful manipulation checks and modified task methodology. Experiment 1 manipulated room temperature with cool (21°C), control (24°C) and hot (27°C) conditions and found only a cool temperature effect, promoting utilitarian judgment as in the previous study. Experiment 2 manipulated the intensity of haptic temperature but failed to obtain the cool temperature effect. Experiments 3 and 4 examined the generalizability of the cool ambient temperature effect with another moral judgment task and with manipulation of exposure duration. However, again there were no cool temperature effects, suggesting a lack of reproducibility. Despite successful manipulations of temperature in all four experiments, as measured in body temperature and the participants’ self-reported perception, we found no systematic influence of temperature on moral decision-making. A Bayesian meta-analysis of the four experiments showed that the overall data tended to provide strong support in favor of the null hypothesis. We propose that, at least in the range of temperatures from 21 to 27°C, the cool temperature effect in moral decision-making is not a robust phenomenon.

Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification.

For performance enhancement of functional diffuse optical tomography (fDOT), we propose a tandem method that takes advantage of the inversion filtering and the long short term memory (LSTM) classification to simultaneously suppress the physiological interferences and physical noises in fDOT. In the former phase, the absorption perturbation maps over the scalp-skull (SS) and cerebral-cortex (CC) layers are firstly pre-reconstructed using a two-layer topography scheme. Then, the recovered SS-map is inversed into measurement space by the forward calculation to estimate the intensity changes associated with the physiological interferences. Finally, the raw measurements are adaptively filtered with reference to the estimated intensity changes for accomplishing the model-based full three-dimension (3D) reconstruction. In the later phase, for further removing the randomly distributed physical noises, mainly instrumental noise, a LSTM network based fusion strategy is applied, where a pixel-wise binary mask of "activated" or "inactive" state is generated by performing LSTM classification and then fused with the 3D reconstruction. The results of the simulative investigation and in-vivo experiment show the proposed tandem scheme achieves improved performance in fDOT using a cost-effective and physically explicable way. Thus, the proposed method can be promisingly applied in real-time neuroimaging to acquire cortical neural activation information with improved reliability, quantification and resolution.

Development of an electrochemical sensor for nitric oxide based on carbon paste electrode modified with Nafion, gold nanoparticles and graphene nanoribbons

Various physiological as well as pathophysiological processes in the cardiovascular system, in the immune response or in neurotransmission depend on changes of the concentration of nitric oxide (NO). Due to the instability of this ubiquitous signal molecule in vivo and in vitro, its rapid and direct detection is necessary to obtain meaningful results. Therefore, the development of a method for the rapid electrochemical detection of nitric oxide at 0.72 V (vs. Ag/AgCl) using a carbon paste electrode, modified by drop casting, is presented. As modifying solution, a nanocomposite consisting of Nafion, graphene nanoribbons, and gold nanoparticles was prepared. The voltammetric investigations with the optimized sensor were performed at room temperature in phosphate buffer solution (0.1 M, pH 7.4) as supporting electrolyte. Based on differential pulse voltammetry measurements, the obtained results for the analytical signal showed good linear response in the range of 0.39–2.34 μM and 2.34–104.7 μM with a correlation coefficient of 0.9941 and 0.9984, respectively. For both linear ranges, the repeatability as well as the reproducibility was <5% and <10%, respectively. A concentration of 40 nM was determined for the detection limit, whereas the limit of quantification was 130 nM. In addition, the influence of physiological interferences was also investigated and resulted in negligible effects. Finally, the sensor was successfully used to measure the NO release of NO donors. Based on the results obtained, the new sensor provides a simple and fast method for a direct voltammetric determination of low nitric oxide concentrations in solutions.

The effect of pyriproxyfen on the concentration of circulating metabolic fuel molecules and chemical elements in the hemolymph of Acraea horta L. (Lepidoptera: Nymphalidae): A quantitative analysis

Many pollinating insects expand their niche to adjacent agricultural areas and are, therefore, exposed to chemical insecticides. Acraea horta L. (Lepidoptera: Nymphalidae) is a pollinator butterfly widely distributed in the Southern African region. The objectives of this work were to evaluate carbohydrate, lipid and chemical elements in the hemolymph of A. horta exposed to pyriproxyfen, a juvenile hormone analog (JHA). Last instar larvae (L6: day 1 or day 2) were topically exposed to an aqueous solution of pyriproxyfen (100 μg of the active ingredient per insect) or to diluent (control group). Hemolymph was collected after adult eclosion to determine total carbohydrate and lipid concentrations: in the control group lipids were present in lower concentrations than carbohydrates and there was no significant difference in metabolite levels between sexes; a similar pattern with similar levels were measured in the treated group, except that lipid concentrations in treated males were lower, and carbohydrate concentrations in treated females were lower than the control values. Morphologically intact adult males from treated larvae were subjected to free flight; their hemolymph carbohydrate levels were significantly reduced and did not recover to starting levels in a 30 min rest period following the exhaustive flight episode. To assess the effect of pyriproxyfen on a different stage of development, 48 h old butterflies were treated in the same way as described for the L6 larvae above; hemolymph samples were taken 48 h later for metabolite measurements and for quantification of chemical elements: carbohydrate levels decreased significantly after pyriproxyfen exposure, while lipid levels increased; inorganic elements measured in untreated adults were more abundant in females, with a general decrease in concentration following pyriproxyfen exposure, except for an increase in Fe levels in males and Cl levels in females. The quantitative changes measured in A. horta hemolymph via biochemical and chemical element analyses may indicate distinct physiological interferences beyond the main mode of action of pyriproxyfen on JH activity. In conclusion, the use and quantification of pyriproxyfen should be carefully evaluated prior to application in areas where A. horta and other pollinator species occur.

Perylene diimide/MXene-modified graphitic pencil electrode-based electrochemical sensor for dopamine detection.

The synthesis of novel architecture comprising perylene diimide (PDI)-MXene (Ti3C2TX)-integrated graphitic pencil electrode for electrochemical detection of dopamine (DA)is reported. The good electron passage between PDI-MXene resulted in an unprecedented nano-adduct bearing enhanced electrocatalytic activity with low-energy electronic transitions. The anionic groups of PDI corroborated enhanced active surface area for selective binding and robust oxidation of DA, thereby decreasing the applied potential. Meanwhile, the MXene layers acted as functional conducive support for PDI absorption via strong H-bonding. The considerable conductivity of MXene enhanced electron transportation thus increasing the sensitivity of sensing interface. Theinclusively engineered nano-adduct resulted in robust DA oxidation with ultra-sensitivity (38.1 μAμM-1cm-2), andlow detection limit (240 nM) at very low oxidation potential (-0.135 V). Moreover, it selectively signaled DA in the presence of physiological interferents with wide linearity (100-1000 μM). The developed transducing interface performed well in human serum samples with RSD (0.1 to 0.4%) and recovery (98.6 to 100.2%) corroborating the viability of the practical implementation of this integrated system. Graphical abstract Schematic illustration of the oxidative process involved on constructed sensing interface for the development of a non-enzymatic dopamine sensor.

Chitotriosidase Activity Is Counterproductive in a Mouse Model of Systemic Candidiasis.

Mammalian cells do not produce chitin, an insoluble polymer of N-acetyl-D-glucosamine (GlcNAc), although chitin is a structural component of the cell wall of pathogenic microorganisms such as Candida albicans. Mammalian cells, including cells of the innate immune system elaborate chitinases, including chitotriosidase (Chit1), which may play a role in the anti-fungal immune response. In the current study, using knockout mice, we determined the role of Chit1 against systemic candidiasis. Chit1-deficient mice showed significant decrease in kidney fungal burden compared to mice expressing the functional enzyme. Using in vitro anti-candidal neutrophil functional assays, the introduction of the Chit1:chitin digestion end-product, chitobiose (N-acetyl-D-glucosamine dimer, GlcNAc2), decreased fungal-induced neutrophil swarming and Candida killing in vitro. Also, a role for the lectin-like binding site on the neutrophil integrin CR3 (Mac-1, CD11b/CD18) was found through physiological competitive interference by chitobiose. Furthermore, chitobiose treatment of wild type mice during systemic candidiasis resulted in the significant increase in fungal burden in the kidney. These data suggest a counterproductive role of Chit1 in mounting an efficient anti-fungal defense against systemic candidiasis.

Nanostructured zinc oxide film amalgamated with functionalized carbon nanotubes for facile electrochemical determination of nifedipine

An innovative approach has been employed for the detection of nifedipine at glassy carbon electrode fabricated with zinc oxide nanoparticles embedded on functionalized multi walled carbon nanotubes. Herein, square wave voltammetry being an expeditious electrochemical technique has been utilized for the first time for the determination of nifedipine. Instrumental variables were altered to acquire optimized operational parameters. The electrochemical oxidation peak of nifedipine was procured at ∼ 807 mV which was recorded versus Ag/AgCl reference electrode. The oxidation peak was used to quantify the analyte in the dynamic linear range of 1 nM to 40 μM with highest sensitivity and lowest detection limit of 21.8 μA μM−1 and 0.49 nM respectively. The influence of common physiological interferents on the current signal of the analyte was examined. Pronounced stability and reproducibility of fabricated sensor was attained by the neoteric electrochemical approach. The developed protocol was efficaciously applied to quantify nifedipine in pharmaceutical formulations. The urine and blood serum sample of patients being treated for hypertension was effectively detected with nifedipine for the first time. The biological sample assay without the interference of the metabolites coexisting in the samples outlined the insight of selectivity of the developed sensor.

Optimal Hemodynamic Parameters for Brain-injured Patients in the Clinical Setting: A Narrative Review of the Evidence

Defining optimal hemodynamic targets for brain-injured patients is a challenging undertaking. The physiological interference observed in various intracranial pathologies can have varying effects on cerebral physiology at different time points. This narrative review provides an overview of cerebral autoregulatory physiology and common misconceptions, and examines the physiological considerations and clinical evidence for determining optimal hemodynamic parameters in acutely brain-injured patients with relevance to modern neuroanesthesia and neurocritical care practice.

Combining Two-Layer Semi-Three-Dimensional Reconstruction and Multi-Wavelength Image Fusion for Functional Diffuse Optical Tomography

High-density (HD) diffuse optical tomography (DOT), as an advanced modality of functional near-infrared spectroscopy, is finding increasing applications in neuroimaging regime. However, it is a primary challenge that the superficial physiological interferences usually significantly contaminate the functional activation reconstruction. In addition, the random noises, majorly the photon-shot and instrumental ones, also cast negative influences on the measurements, and further distort the reconstructed image. To mitigate the adversities, we herein propose a combined scheme of two-layer semi-three-dimensional (S3D) reconstruction and multi-wavelength image fusion, which leverages a mathematical model with explicit physical significance, to suppress the physiological interferences and random noises in HD-DOT reconstruction, respectively. The approach is purely data-driven without additional auxiliary measurement, and comprised of two steps: First, the absorption perturbations are topographically reconstructed over both the scalp (SC) and cerebral-cortex (CC) layers using the two-layer S3D scheme, of which the superficial interferences are estimated from the SC reconstruction and adaptively filtered out from the CC one; Second, the interference-suppressed multi-wavelength CC-images are decomposed using the discrete wavelet transform, and fused at multi-resolutions into a mask for further removal of the random noises. We comprehensively validate the proposed scheme using simulations and phantom experiments, and demonstrate its sound effectiveness in suppressing the physiological interferences and random noises. The performance improvement rather than by more cycles or longer sampling time offers additional payoff: shorter measurement time or higher temporal resolution.

Hybrid Method of Automated EEG Signals' Selection Using Reversed Correlation Algorithm for Improved Classification of Emotions.

Based on the growing interest in encephalography to enhance human–computer interaction (HCI) and develop brain–computer interfaces (BCIs) for control and monitoring applications, efficient information retrieval from EEG sensors is of great importance. It is difficult due to noise from the internal and external artifacts and physiological interferences. The enhancement of the EEG-based emotion recognition processes can be achieved by selecting features that should be taken into account in further analysis. Therefore, the automatic feature selection of EEG signals is an important research area. We propose a multistep hybrid approach incorporating the Reversed Correlation Algorithm for automated frequency band—electrode combinations selection. Our method is simple to use and significantly reduces the number of sensors to only three channels. The proposed method has been verified by experiments performed on the DEAP dataset. The obtained effects have been evaluated regarding the accuracy of two emotions—valence and arousal. In comparison to other research studies, our method achieved classification results that were 4.20–8.44% greater. Moreover, it can be perceived as a universal EEG signal classification technique, as it belongs to unsupervised methods.

S(O)MWCNT/modified Carbon Paste – A Non‐enzymatic Amperometric Sensor for Direct Determination of 6‐Mercaptopurine in Biological Fluids

AbstractIn this study, carbon paste electrode (CPE) modified with strongly oxidized MWCNT (S(O)MWCNT) was developed as an efficient, economical, electrochemical sensor for the detection of 6‐mercaptopurine (6MP) with antineoplastic and immunosuppressive activities. However, this cytotoxic anticancer drug is associated with adverse side‐effects; hence 6MP determination becomes crucial. Drop‐cast‐coating was an effective strategy in the fabrication of S(O)MWCNT/MCPE to increase surface area. Electrochemical measurements were performed using cyclic voltammetry (CV) and amperometry. Electrochemical Impedance Spectroscopy (EIS), Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive X‐ray (EDX) elucidated surface characteristics. With S(O)MWCNT's good conductive ability, we achieved rapid electron transfer that amplified 6MP anodic signal by 3.8 folds higher compared to bare CPE. Additionally, great consonance between CPE loaded with S(O)MWCNT yielded superior current response with decreased activation energy compared to S(O)MWCNT/modified glassy carbon electrode (S(O)MWCNT/MGCE). Under optimal conditions S(O)MWCNT/MCPE displayed a wide‐single‐linearity range from 1.0 to 100.0 μM with an excellent detection limit of 0.24 μM during amperometric quantification for the first time. It also exhibited good selectivity, after a series of common physiological interferents’ assessment. As a part of proof‐of‐concept, the proposed sensor was investigated in 6MP fortified human fluids, and the satisfactory recoveries obtained authenticated S(O)MWCNT/MCPE's accuracy and reliability for practical applicability.

Enhancing the atrazine tolerance of Pennisetum americanum (L.) K. Schum by inoculating with indole-3-acetic acid producing strain Pseudomonas chlororaphis PAS18

Atrazine as a kind of herbicide could cause damage to the sensitive plants. Though plant growth promoting rhizobacteria (PGPR) have been proven with the potential to enhance the resistance of plants against various abiotic stresses, whether it could alleviate phytotoxicity caused by atrazine is sill unclear. In present study, the effects of strain Pseudomonas chlororaphis PAS18, a kind of PGPR enable to produce indole-3-acetic acid (IAA), on the growth and physiological responses of Pennisetum americanum (L.) K.Schum seedlings were investigated under three different levels (0, 20 and 100 mg kg−1) of atrazine in pot experiment. The results suggest that strain PAS18 could alleviate the growth and physiological interference caused by 20 mg kg−1 of atrazine. Physiological analysis showed strain PAS18 could further decrease the damaged extent of photosystem II, superoxide radical level and malondialdehyde content of test plant via up-regulating psbA expression, enhancing superoxide dismutase activity and reducing atrazine accumulation in the test plant. Moreover, ion flux measurements suggest that IAA could alleviate the Ca2+ exflux state of the test plant which caused by atrazine stress. Hence, it is plausible that strain PAS18 could alleviate atrazine-induced stress to P. americanum by enhancing the photosystem II repair and antioxidant defense ability as well as balancing the Ca2+ flux.

Ca2+ influx and clearance at hyperpolarized membrane potentials modulate spontaneous and stimulated exocytosis in neuroendocrine cells

Neuroendocrine adrenal chromaffin cells release neurohormones catecholamines in response to Ca2+ entry via voltage-gated Ca2+ channels (VGCCs). Adrenal chromaffin cells also express non-voltage-gated channels, which may conduct Ca2+ at negative membrane potentials, whose role in regulation of exocytosis is poorly understood. We explored how modulation of Ca2+ influx at negative membrane potentials affects basal cytosolic Ca2+ concentration ([Ca2+]i) and exocytosis in metabolically intact voltage-clamped bovine adrenal chromaffin cells. We found that in these cells, Ca2+ entry at negative membrane potentials is balanced by Ca2+ extrusion by the Na+/Ca2+ exchanger and that this balance can be altered by membrane hyperpolarization or stimulation with an inflammatory hormone bradykinin. Membrane hyperpolarization or application of bradykinin augmented Ca2+-carrying current at negative membrane potentials, elevated basal [Ca2+]i, and facilitated synchronous exocytosis evoked by the small amounts of Ca2+ injected into the cell via VGCCs (up to 20 pC). Exocytotic responses evoked by the injections of the larger amounts of Ca2+ via VGCCs (> 20 pC) were suppressed by preceding hyperpolarization. In the absence of Ca2+ entry via VGCCs and Ca2+ extrusion via the Na+/Ca2+ exchanger, membrane hyperpolarization induced a significant elevation in [Ca2+]i and asynchronous exocytosis. Our results indicate that physiological interferences, such as membrane hyperpolarization and/or activation of non-voltage-gated Ca2+ channels, modulate basal [Ca2+]i and, consequently, segregation of exocytotic vesicles and their readiness to be released spontaneously and in response to Ca2+ entry via VGCCs. These mechanisms may play role in homeostatic plasticity of neuronal and endocrine cells.