Aggregation Number Research Articles

Particle counting immunoassay system using a low-aspect-ratio pore

We have developed a new particle counting immunoassay system integrated with a resistive-pulse sensor with a low-aspect-ratio pore. The particle counting immunoassay is based on the principle of latex aggregation. The target single-molecule concentration is measured by counting aggregated latex particles that form multimers over the reaction time. To enable highly accurate identification of the number of aggregated particles, we designed and fabricated a low-aspect-ratio pore device to perform quantitative structural analysis of particles. The aggregation numbers of the conjugated particles were classified based on blockade current profiles when the particles translocated through the pore. Time-dependent agglutination reaction monitoring demonstrated that the reaction speed increased for a solution containing a higher concentration of antigens. The results prove the feasibility of using the proposed immunoassay system to count particles while determining the aggregation number based on their current profiles.

A multihead LSTM technique for prognostic prediction of soil moisture

Prognostic prediction of soil moisture is a critical step in various fields such as geotechnical engineering, agriculture, geology, hydrology, and climatology. For example, in agricultural applications, soil moisture prediction is needed one-day and one-week ahead of time to optimize crop planting quality and set irrigation schedule, respectively. In soil and environmental management applications, soil moisture prediction is usually needed one-month ahead of time. Therefore, a capability to accurately forecast soil moisture is of paramount importance. For this purpose, deep learning methods, especially the long short-term memory network (LSTM) method, have been used extensively. It is shown that such models can successfully forecast the soil moisture for a short time frame in future, but their accuracy sharply decreases for long time frames. To resolve this issue, in this study, we present a multihead LSTM model that learns a number of hypotheses and aggregates them for prognostic prediction tasks. The multihead LSTM model is comprised of four LSTM models that digest time series data of soil moisture aggregated at different scales as inputs. The outputs of these models, i.e., predicted soil moisture at a certain time in future, are then combined using a weighted averaging method to obtain the final prediction values. Different statistical measures, such as the root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared are employed to assess the performance of the multihead LSTM model predictions against the ground truth. The results show that the proposed multihead LSTM method is effective to forecast the soil moisture up to one-month in future with a R-squared value of 95.04%.

Post-COVID ethics of work as a perspective for the development of self-employment in Russia

The article discusses the process of transferring the financial and economic activities of most self-employed entrepreneurs to the digital space, which was forced by the conditions of the remote work format during the COVID-19 pandemic, as well as the established legislative framework during the period of self-isolation. The analysis of the current legislative framework, which is included in the article, makes it possible to identify general trends in removing barriers to engage a larger group of entrepreneurs in a new format of working, as well as immersing the main financial instruments in the Internet. On the basis of empirical data obtained in the course of quantitative (data analytics of queries in Yandex.Direct) and qualitative sociological research (content analysis of financial applications) the features of registration and registration procedures in the digital space were formed, the online platforms of the Federal Tax Service and the largest banking organizations for servicing financial and economic activities for the self-employed were analyzed, including financial instruments. A number of main aggregators and marketplaces are distinguished by industries of the activity sphere of the self-employed according to the criterion of popularity in Internet search engines. The specificity of web analytics of the dynamics and content of search queries allows us to draw conclusions about the most pressing topics, both for the self-employed and for those interested in this topic for the purpose of subsequent registration and use of financial instruments on the Internet. Based on these requests, there is a surge of interest in self-employed entrepreneurship, the criteria for registering self-employment during the pandemic and post-pandemic, an active study of the specifics of tax liabilities and financial and economic activities, typical characteristics of search behavior and priority online platforms in the Yandex.Direct system have been formed.

Data-driven approach for investigating and predicting rutting depth of asphalt concrete containing reclaimed asphalt pavement

The aim of this paper is to investigate and predict the rutting depth of asphalt concrete containing Reclaimed Asphalt Pavement (RAP) content by the data-driven approach with aid of 6 six tree algorithm including Random Forest (RF), Gradient Boosting (GB), Adaptive Boosting (AdaB), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LightGB) and Categorial Gradient Boosting (CatB) using default hyperparameters. A database containing 396 data samples derived from Hamburg Wheel Tracking Test (HWTT) and consisting of 11 input variables such as Corrected Optimum Asphalt Content (COAC), Reclaimed Asphalt Pavement, Nominal Maximum Aggregate Size (NMAS), Flashpoint, m-Value, Mass loss, Specific gravity, Viscosity, Creep stiffness, Temperature, and Number of wheels and 1 output Rutting depth are created. 10 times of 10-Fold CV and four metrics such as R2, RMSE, MAE and MAPE are used to verify the robustness of ML models. XGB model has highest performance with the mean value of R2, RMSE, MAE and MAPE to be equal to 0.9792, 1.0767 mm, 0.7085 mm, 0.1034% respectively. Comparing with other factors like the number of load cycles (number of wheels) and mix design considerations, temperature has a dominant impact on the rutting depth of asphalt pavement (type of binder, NMAS, RAP content). The rutting depth value rises with increasing temperature and COAC. NMAS has a negligible impact on asphalt pavement's resistance to rutting. To increase the rutting resistance when building the asphalt pavement, the chosen asphalt binder has high Viscosity and Flashpoint values. The local interpretation clearly demonstrates each factor's contribution to the rutting depth value in each unique scenario. Engineers can design the rutting resistance of asphalt pavement in advance thanks to the mapping produced by the Partial Dependence Plot 2D under grid contour.

Properties of Pluronic F68 and F127 micelles interacting furosemide from coarse-grained molecular simulations as validated by experiments

Understanding properties of the drug delivery nanoparticles is of utmost importance to investigate the properties of the currently used systems and/or to design new drug delivery materials. Therefore, in this work we strive to study particular FDA approved drug delivery materials, namely Pluronics, to understand micellization properties and drug encapsulation behaviour at the molecular-level. Our main approach is to employ molecular simulations, which are confirmed by experiments performed within the scope of this work. To that aim, dissipative particle dynamics (DPD) simulations are employed. We quantify the encapsulation efficiency properties of Pluronics, namely F68 and F127, where furosemide as the drug. The DPD simulations predict the encapsulation efficiency of the F68 system higher than F127 system due to a shorter hydrophobic section. Moreover, the micelle properties of Pluronics are quantified by means of the number of micelles, aggregation number, surface area to volume ratio, micelle sizes; and polymer chain properties such as, chain end-to-end distance, radius of gyration properties. We observe similar number of micelles for both systems and the aggregation numbers are rather higher for the F127 system. Moreover, both systems adopt alike end-to-end distance and radius-of-gyration values, and the micelle sizes agree with the experimental data in literature. Furthermore, the interactions of hydrophilic and hydrophobic groups with furosemide and water are analysed by computing the radial distribution functions. Long-range hydrophobic-furosemide interactions indicate that furosemide beads are mainly located near core/corona interface. In all, our manuscript can be viewed as an attempt to provide insights on the structural and micellization properties of Pluronics by molecular simulations, where the findings can be utilized to guide attempts in designing prospective drug carrier nanoparticles.

Tracking COVID-19 in the United States With Surveillance of Aggregate Cases and Deaths.

Early during the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) leveraged an existing surveillance system infrastructure to monitor COVID-19 cases and deaths in the United States. Given the time needed to report individual-level (also called line-level) COVID-19 case and death data containing detailed information from individual case reports, CDC designed and implemented a new aggregate case surveillance system to inform emergency response decisions more efficiently, with timelier indicators of emerging areas of concern. We describe the processes implemented by CDC to operationalize this novel, multifaceted aggregate surveillance system for collecting COVID-19 case and death data to track the spread and impact of the SARS-CoV-2 virus at national, state, and county levels. We also review the processes established to acquire, process, and validate the aggregate number of cases and deaths due to COVID-19 in the United States at the county and jurisdiction levels during the pandemic. These processes include time-saving tools and strategies implemented to collect and validate authoritative COVID-19 case and death data from jurisdictions, such as web scraping to automate data collection and algorithms to identify and correct data anomalies. This topical review highlights the need to prepare for future emergencies, such as novel disease outbreaks, by having an event-agnostic aggregate surveillance system infrastructure in place to supplement line-level case reporting for near-real-time situational awareness and timely data.

Understanding the role of the hematopoietic niche in Huntington's disease's phenotypic expression: in vivo evidence using a parabiosis model

In a previous study, we have shown that parabiotic coupling of a knock-in mouse model (zQ175) of Huntington's disease (HD) to wild-type (WT) littermates resulted in a worsening of the normal phenotype as seen by detection of mutant huntingtin protein (mHTT) aggregates within peripheral organs and the cerebral cortex as well as vascular abnormalities in WT mice. In contrast, parabiosis improved disease features in the zQ175 mice such as reduction of mHTT aggregate number in the liver and cortex, decrease in blood-brain barrier (BBB) permeability and attenuation of mitochondrial impairments. While the shared circulation mediated these effects, no specific factor was identified. To better understand which blood elements were involved in the aforementioned changes, WT and zQ175 mice underwent parabiotic surgery prior to exposing one of the paired animals to irradiation. The irradiation procedure successfully eliminated the hematopoietic niche followed by repopulation with cells originating from the non-irradiated parabiont, as measured by the quantification of mHTT levels in peripheral blood mononuclear cells. Although irradiation of the WT parabiont, causing the loss of healthy hematopoietic cells, did lead to a few alterations in mitochondrial function in the muscle (TOM40 levels), and increased neuroinflammation in the striatum (GFAP levels), most of the changes observed were likely attributable to the irradiation procedure itself (e.g. mHTT aggregates in cortex and liver; cellular stress in peripheral organs). However, factors such as mHTT aggregation in the brain and periphery, and BBB leakage, which were improved in zQ175 mice when paired to WT littermates in the previous parabiosis experiment, were unaffected by perturbation of the hematopoietic niche. It would therefore appear that cells of the hematopoietic stem cell niche are largely uninvolved in the beneficial effects of parabiosis.

Studying pulmonary fibrosis due to microbial infection via automated microscopic image analysis.

Pulmonary fibrosis is a consequential complication of microbial infections, which has notably been observed in SARS-CoV-2 infections in recent times. Macrophage polarization, specifically the M2-type, is a significant mechanism that induces pulmonary fibrosis, and its role in the development of Post- COVID-19 Pulmonary Fibrosis is worth investigating. While pathological examination is the gold standard for studying pulmonary fibrosis, manual review is subject to limitations. In light of this, we have constructed a novel method that utilizes artificial intelligence techniques to analyze fibro-pathological images. This method involves image registration, cropping, fibrosis degree classification, cell counting and calibration, and it has been utilized to analyze microscopic images of COVID-19 lung tissue. Our approach combines the Transformer network with ResNet for fibrosis degree classification, leading to a significant improvement over the use of ResNet or Transformer individually. Furthermore, we employ semi-supervised learning which utilize both labeled and unlabeled data to enhance the ability of the classification network in analyzing complex samples. To facilitate cell counting, we applied the Trimap method to localize target cells. To further improve the accuracy of the counting results, we utilized an effective area calibration method that better reflects the positive density of target cells. The image analysis method developed in this paper allows for standardization, precision, and staging of pulmonary fibrosis. Analysis of microscopic images of COVID-19 lung tissue revealed a significant number of macrophage aggregates, among which the number of M2-type macrophages was proportional to the degree of fibrosis. The image analysis method provids a more standardized approach and more accurate data for correlation studies on the degree of pulmonary fibrosis. This advancement can assist in the treatment and prevention of pulmonary fibrosis. And M2-type macrophage polarization is a critical mechanism that affects pulmonary fibrosis, and its specific molecular mechanism warrants further exploration.

Fabrication and Tailoring the Structural and Dielectric Characteristics of GO/Sb2O3/PMMA/PC Quaternary Nanostructures For Solid State Electronics Nanodevices

In this paper, films of (PMMA-PC/Sb2O3-GO) quaternary nanostructures were prepared by casting method with different concentrations of Sb2O3/GO NPs are (0, 1.4 %, 2.8 %, 4.2 %,and 5.6 %). The structural and dielectric characteristics of nanostructures system (PMMA-PC/Sb2O3-GO) have been explored to use in different solid state electronics nanodevices applications. The morphology of (PMMA-PC/Sb2O3-GO) nanostructures films was studied using a scanning electron microscope (SEM). SEM images indicate a large number of uniform and coherent aggregates or chunks. The Fourier transform infrared spectroscopy(FTIR) analysis were studied to show the interactions between the Sb2O3/GO NPs and PMMA/PC blend. The dielectric properties of nanostructures films were investigated in the frequency range (100HZ-5MHZ). The dielectric constant, dielectric loss, and A.C electrical conductivity increase with the concentration of (Sb2O3-GO) NPs. The dielectric constant and dielectric loss were reduced, whereas electrical conductivity increased with frequency. Finally, results showed the PMMA-PC/Sb2O3-GO nanostructures may be considered as promising materials for solid state electronics nanodevices.

New charged aggregate mathematical models to predict the behavior, structural parameters, and geometrical features of microemulsions

Experimental characterization techniques can provide qualitative and quantitative information on the behavior and properties of microemulsion systems. However, they suffer from several inherent drawbacks that often restrict their application to research settings rather than routine practice in various industries. Also, the majority of theoretical studies on microemulsion systems have focused on nonionic surfactants and suffer from restrictive assumptions and limitations that can be violated under realistic conditions. Therefore, their practical applications to real-world problems such as surfactant-based enhanced oil recovery (EOR) processes require the exercise of extreme caution. This work is intended to fill existing research gaps and solve industrial challenges by developing new mathematical models for predicting micelle size besides other structural and geometrical parameters in ionic surfactant-induced oil-in-water (O/W) and water-in-oil (W/O) microemulsions. The main purpose of the present study is to derive novel models that are not only fitting-free, objective, independent of iterative algorithms and experimental data, and inclusive of intermicellar interactions, but also applicable to complex systems containing real crude oil, experiencing compositional changes, and under any thermodynamic conditions. First, a recently proposed surface charging model for dispersions of charged particles in electrolyte solutions is combined with the DLVO theory of colloidal interactions to develop a thermodynamic model for the structural description of O/W microemulsions. Then, upon coupling a surface charging model for non-electrolyte dispersions of charged aqueous cavities with the DLVO theory, another thermodynamic model is developed for W/O microemulsions. Next, the developed mathematical models are supplemented with an auxiliary material balance equation and an equilibrium condition to calculate the radius of micelles in each type of systems. After determining the radii of oil- and water-swollen micelles using the new models, other geometrical and structural parameters such as solubilized phase-to-surfactant molar ratio, aggregation number, the volumes of microemulsion and excess phases, intermicellar distance, and periodicity are readily calculated in an explicit manner using the derived relationships. Afterwards, some reliable complementary tools are discussed for calculations of the associated physical parameters to avoid the need for experimental measurements, thereby making the models more practical and operational. Finally, the validity of the developed models is verified using literature experimental data.

Immunohistochemical profiling of the tumour microenvironment in borderline and malignant ovarian tumours in young women.

Ovarian cancer is a major cause of cancer-related deaths in women. Our previous study highlighted the interaction between cancer cells and the host immune response in solid cancers. The present study aimed to analyse the proportion, density and distribution of T and B lymphocytes within the tumour and surrounding stroma, and their prognostic significance in young women with borderline and malignant ovarian surface epithelial tumours. Full clinicopathological and outcome data were collected for 57 women aged <50 years diagnosed between January 2010 and December 2015. Representative tumour sections were stained for CD3 (T cells) and CD20 (B cells) and tumour-infiltrating lymphocytes (TILs) were scored following the TILs Working Group Recommendations and described as stromal, intra-tumoural, lymphoid aggregates and touching lymphocytes. Data were statistically analysed and the association with clinicopathological variables was assessed. The median age was 41 years and the most common histological type was serous carcinoma (n=21). The risk of malignancy index was a significant predictor of ovarian cancer diagnosis (P<0.05). A total of 15 out of 34 patients with cancer died. There was significantly greater stromal infiltration of CD3 and CD20 TILs (P=0.01 and P=0.03, respectively) and higher intratumoral CD20 expression in ovarian epithelial cancers compared with borderline tumours. The highest CD3 stroma count and density were observed in serous carcinoma, which also exhibited the highest numbers of CD3 and CD20 aggregates. There was no statistically significant difference between touching lymphocytes and tumour histological subtype. There was no significant association between TIL expression and patient survival. The count, distribution and density of T and B lymphocytes in ovarian tumours varied depending on tumour type and invasiveness. Their topographic distribution within the tumour and surrounding stroma did not impact prognosis in young women with ovarian cancer. TIL analysis in an older age group of women with ovarian tumours is ongoing to determine its potential prognostic significance.

Carotenoids: Role in Neurodegenerative Diseases Remediation.

Numerous factors can contribute to the development of neurodegenerative disorders (NDs), such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, and multiple sclerosis. Oxidative stress (OS), a fairly common ND symptom, can be caused by more reactive oxygen species being made. In addition, the pathological state of NDs, which includes a high number of protein aggregates, could make chronic inflammation worse by activating microglia. Carotenoids, often known as "CTs", are pigments that exist naturally and play a vital role in the prevention of several brain illnesses. CTs are organic pigments with major significance in ND prevention. More than 600 CTs have been discovered in nature, and they may be found in a wide variety of creatures. Different forms of CTs are responsible for the red, yellow, and orange pigments seen in many animals and plants. Because of their unique structure, CTs exhibit a wide range of bioactive effects, such as anti-inflammatory and antioxidant effects. The preventive effects of CTs have led researchers to find a strong correlation between CT levels in the body and the avoidance and treatment of several ailments, including NDs. To further understand the connection between OS, neuroinflammation, and NDs, a literature review has been compiled. In addition, we have focused on the anti-inflammatory and antioxidant properties of CTs for the treatment and management of NDs.

Can sodium 1-alkylsulfonates participate in the sodium dodecyl sulfate micelle formation?

The aggregation behavior of sodium dodecyl sulfate (SDS) was studied in an aqueous solution in the presence of increasing concentrations of selected sodium 1-alkylsulfonates, namely sodium 1-octanesulfonate, sodium 1-decanesulfonate, and sodium 1-dodecanesufonate. The critical micelle concentration (CMC) of SDS was determined by conductivity and fluorescence intensity measurements. The steady-state fluorescence quenching experiments with pyrene as a fluorescent probe were performed to obtain micellar aggregation numbers (Nagg) of the surfactant. The thermodynamic parameters of micellization (ΔGmic0 for all studied systems; ΔHmic0 and ΔSmic0 for sodium 1-dodecanesufonate) have been determined and compared. The influence of alkyl chain length and concentration of the selected sodium 1-alkylsulfonates on the values of CMC, Nagg, ΔGmic0, ΔHmic0, and ΔSmic0 of SDS has been discussed. As it was found, all selected for the experiments electrolytes decrease significantly the CMC of the surfactant, while an opposite effect is observed for Nagg values. The obtained experimental results have been supported by theoretical calculations. Interestingly, it has been proven that solely the molecules of sodium 1-dodecanesufonate (of the same carbon chain length) may act as the SDS mimetics – they are not recognized by SDS as the ones with a different structure and consequently are allowed to participate in the formation of the surfactant’s micelles.

Agrophysical indicators of ordinary chernozem depending on the methods of its tillage in the Northern Steppe of Ukraine

Topicality. The spread of negative processes in the soil associated with the aggravation of the economic situation in modern Ukraine, the rapid rise in prices for equipment, fuels and lubricants, the replacement of energy-intensive traditional tillage systems with non-moldboard and other resource-saving ones, requires further and deeper research on their impact on her agrophysical indicators. Purpose. To study the influence of the primary tillage on the agrophysical indicators of ordinary chernozem in the link of the field grain-fallow-row crop rotation (winter wheat after maize of milk-wax ripeness - peas for grain - winter wheat) in the conditions of the Northern Steppe of Ukraine. Materials and Methods. Methods of primary tillage based on moldboard plowing and non-moldboard loosening against the background of moldboard plowing for corn were studied. In experimental studies, we used field, laboratory and statistical-mathematical methods. The agrophysical parameters of the soil were determined according to generally accepted methods. Results. No significant difference has been found in the influence of the primary tillage methods on the soil density in the 0–30 cm layer under the crops of the crop rotation link in spring and at their harvesting. In 2011 and 2012, there was a significant increase in the number of water-stable aggregates (over 0.25 mm) in the soil under non-moldboard tillage, compared with plowing, under all crops of the crop rotation link in the spring and during harvesting, mainly in the 0–10 and 10–20 cm layers. This was more often observed in the spring – on average for 2010–2012, the difference in this indicator in the soil layer of 0–30 cm for the crops of the crop rotation link was: winter wheat after maize of milk-wax ripeness – 1.9, peas – 4.4 and winter wheat after peas – 3.0 %, and on average for the crop rotation link – 3.1 It is established that moldboardless tillage contributes to a significant reduction in moisture consumption for unproductive evaporation in conditions of frequently repeated drought events. Conclusions. The studied methods of primary tillage of ordinary heavy loam chernozem equally affect the bulk density and do not cause deterioration of this indicator. The non-moldboard tillage improves the water resistance of the arable soil layer under crops in the crop rotation link and reduces moisture consumption for evaporation, compared to plowing. Key words: tillage, density, water resistance, productive moisture, winter wheat, peas

Percolation critical exponents in cluster kinetics of pulse-coupled oscillators.

Transient dynamics leading to the synchrony of a type of pulse-coupled oscillators, so-called scrambler oscillators, has previously been studied as an aggregation process of synchronous clusters, and a rate equation for the cluster size distribution has been proposed. However, the evolution of the cluster size distribution for general cluster sizes has not been fully understood yet. In this paper, we study the evolution of the cluster size distribution from the perspective of a percolation model by regarding the number of aggregations as the number of attached bonds. Specifically, we derive the scaling form of the cluster size distribution with specific values of the critical exponents using the property that the characteristic cluster size diverges as the percolation threshold is approached from below. Through simulation, it is confirmed that the scaling form well explains the evolution of the cluster size distribution. Based on the distribution behavior, we find that a giant cluster of all oscillators is formed discontinuously at the threshold and also that further aggregation does not occur like in a one-dimensional bond percolation model. Finally, we discuss the origin of the discontinuous formation of the giant cluster from the perspective of global suppression in explosive percolation models. For this, we approximate the aggregation process as a cluster-cluster aggregation with a given collision kernel. We believe that the theoretical approach presented in this paper can be used to understand the transient dynamics of a broad range of synchronizations.

IRRIGATION AND MINERAL FERTILIZER EFFECTS ON PHYSICAL PROPERTIES OF LIGHT CHESTNUT SOIL USED IN THE CULTIVATION OF SUGAR BEET (BETA VULGARIS L.)

This work studied the effect of irrigation and mineral fertilizers on the physical properties of light chestnut soil used in cultivating sugar beet (Beta vulgaris L.). The experiment happened in 2021 on an irrigated field with an area of 2 ha in the territory of the Kazakh Research Institute of Agriculture and Plant Growing, District Karasai, Almaty region, Kazakhstan. A sugar beet hybrid (obtained from domestic selection ‘Aksu’ and foreign selection ‘Yampol’) cultivation used four levels of mineral fertilizers, i.e., 0:0:0 (control), 90:90:60, 120:120:90, and 150:150:120 NPK kg ha-1. During the sugar beet growing season, all periods of observations recorded an increase in the bulk density in the upper, middle, and lower soil layers, from 1.14–1.27 g/cm3 to 1.31–1.48 g/cm3. The content of agronomically valuable aggregates in 0–10 cm, 10–20 cm, and 20–30 cm soil layers decreased from the germination phase to harvesting of sugar beet in extensive technology (10.0%–15.7%) and intensive technologies (2.3%–13.1%). In these soil layers, the number of water-stable aggregates decreased from the beginning of renewal to the end of the growing season of sugar beet in technology without the use of fertilizers (2.9%–6.4%) and in technologies with the application of mineral fertilizers (1.6%–7.6%). In the soil layers, the noted highest content of productive moisture occurred in the phase of closing the leaves in the rows with the extensive technology of sugar beet cultivation (51.5–213.2 mm). Irrigation during the sugar beet growing season reduces the content of agronomically-valuable and water-stable aggregates in soil layers to the minimum values for harvesting in technology without the use of fertilizers (50.5%–54.4% and 12.9%–14.2%) and technology with the use of mineral fertilizers (52.3%–54.4% and 10.9%–13.5%), respectively.

Single-Molecule Two-Color Coincidence Detection of Unlabeled alpha-Synuclein Aggregates.

Protein misfolding and aggregation into oligomeric and fibrillar structures is a common feature of many neurogenerative disorders. Single-molecule techniques have enabled characterization of these lowly abundant, highly heterogeneous protein aggregates, previously inaccessible using ensemble averaging techniques. However, they usually rely on the use of recombinantly-expressed labeled protein, or on the addition of amyloid stains that are not protein-specific. To circumvent these challenges, we have made use of a high affinity antibody labeled with orthogonal fluorophores combined with fast-flow microfluidics and single-molecule confocal microscopy to specifically detect α-synuclein, the protein associated with Parkinson's disease. We used this approach to determine the number and size of α-synuclein aggregates down to picomolar concentrations in biologically relevant samples.

Single-Molecule Two-Color Coincidence Detection of Unlabeled alpha-Synuclein Aggregates.

Protein misfolding and aggregation into oligomeric and fibrillar structures is a common feature of many neurogenerative disorders. Single-molecule techniques have enabled characterization of these lowly abundant, highly heterogeneous protein aggregates, previously inaccessible using ensemble averaging techniques. However, they usually rely on the use of recombinantly-expressed labeled protein, or on the addition of amyloid stains that are not protein-specific. To circumvent these challenges, we have made use of a high affinity antibody labeled with orthogonal fluorophores combined with fast-flow microfluidics and single-molecule confocal microscopy to specifically detect α-synuclein, the protein associated with Parkinson's disease. We used this approach to determine the number and size of α-synuclein aggregates down to picomolar concentrations in biologically relevant samples.

Influence of Mechanical Properties on the Piezoelectric Response of UV-Cured Composite Films Containing Different ZnO Morphologies

ZnO flower-like (ZFL) and needle (ZLN) structures were synthesized and embedded into UV-curable acrylic resin (EB), with the aim to study the effect of filler loading on the piezoelectric properties of the resulting composite films. The composites showed uniform dispersion of fillers within the polymer matrix. However, by increasing the filler amount, the number of aggregates increased, and ZnO fillers appeared not to be perfectly embedded in polymer film, indicating poor interaction with acrylic resin. The filler content increase caused an increase in glass transition temperature (Tg) and a decrease in storage modulus in the glassy state. In particular, compared with pure UV-cured EB (Tg = 50 °C), 10 wt.% ZFL and ZLN presented Tg values of 68 and 77 °C, respectively. The piezoelectric response generated by the polymer composites was good when measured at 19 Hz as a function of the acceleration; the RMS output voltages achieved at 5 g were 4.94 and 1.85 mV for the composite films containing ZFL and ZLN, respectively, at their maximum loading levels (i.e., 20 wt.%). Further, the RMS output voltage increase was not proportional to the filler loading; this finding was attributable to the decrease in the storage modulus of the composites at high ZnO loading rather than the dispersion of filler or the number of particles on the surface.

Model of inverse “dry” micelles with coexisting spherical, globular and cylindrical aggregates

A new statistical thermodynamic model of inverse nonionic aggregates of surfactant molecules in nonpolar solvents is considered. This model admits the fluctuation coexistence of inverse spherical, globular, and spherocylindrical aggregates without activation barriers between them. The model is based on the assumption of a uniform bulk density of the number of molecular groups inside the core of an aggregate that can continuously transform into a sphere, a globule, and a spherocylinder. In this model, for any aggregation numbers, the work of aggregation depends not only on the aggregation numbers and the concentration of surfactant monomers, but also on two independent geometric parameters characterizing, at the same aggregation numbers, the deviation from the spherical form of the aggregate towards globular and spherocylindrical forms. Even in the range of small aggregation numbers, this fact leads to a significant difference between the equilibrium distribution function of aggregates, which depends on the aggregation number and two form parameters, and the one-dimensional distribution function in terms of aggregation numbers. It is shown that the optimal values of the form parameters, which minimize the work of aggregation, are in good agreement for spherocylindrical aggregates with the predictions of a purely geometric model of such aggregates under the additional assumption of a uniform surface density of molecular groups at the micelle core. The predictions of a new molecular thermodynamic model for the degrees of surfactant micellization in inverse aggregates of various forms at different surfactant concentrations are considered.