Specific Distribution Research Articles

Monitoring the Influence of Hand, Foot, and Mouth Disease: New Guidelines on Patient Care during the 2011-2012 Multiwaves and Multivariant Outbreak in Hai Phong City, Vietnam.

From 2011 to 2012, Northern Vietnam suffered its first large-scale hand, foot, and mouth disease (HFMD) epidemic. Two sets of official guidelines were issued during the outbreak to handle the HFMD crisis. The city of Hai Phong was used as a model to analyze the impact of the released guidelines. A total of 9621 HFMD cases were reported in Hai Phong city from April 2011 to December 2012. Three distinct waves of HFMD occurred. Enterovirus A71 and Coxsackievirus A16 were successively associated with the epidemics. Two periods, before and after the guidelines' release, could be distinguished and characterized by different patient patterns. The time to admission and severity changed notably. Guideline publications help the health system refocus on the 0.5-3 years age group with the highest incidence of the disease. The three waves showed different special distribution, but the main routes of infection were rivers and local secondary roads, most likely through local trade and occupational movements of people.

Cu Nanowires Trigger Efficient Cuproptosis via Special Intracellular Distribution and Excessive Cu Ion Release.

Cuproptosis, dependent on Cu overload, presents novel opportunities for cancer therapy. Cu-based nanomaterials have shown excellent advantages for the intracellular delivery of Cu. However, the biological process of Cu nanomaterials transporting Cu ions into cancer cells remains unclear. In this study, we tracked the Cu ion release process of copper nanowires (CuNWs) and copper nanoparticles (CuNPs) at the single-cell level. CuNWs with 5-μm length and CuNPs were found to be completely internalized by cancer cells. Interestingly, CuNWs escaped from the endolysosomal system, whereas CuNPs were mainly trapped in the lysosomes. This specific intracellular distribution of CuNWs led to cytoplasmic Cu ion overload, directly damaging mitochondria and inducing dihydrolipoamide S-acetyltransferase (DLAT) protein aggregation. Through these excessive Cu ions, CuNWs triggered more efficient cuproptosis than CuNPs to further increase cell death. Thus, CuNWs are more effective in delivering Cu ions than CuNPs, providing a novel perspective for designing cuproptosis-based functional nanomaterials for cancer therapy.

QSAR Studies on Thienopyrimidines as Potential Antimicrobial Agents

Background: Recent research has revealed promising antibacterial action for thienopyrimidines. To comprehend the underlying molecular features underlying their antibacterial potency, a thorough quantitative structure-activity relationship (QSAR) investigation is required. Objective: In order to clarify the structural parameters for effective antibacterial activity, we conducted QSAR analyses on a variety of thienopyrimidines in this work. Methods: Through the analysis of physicochemical properties and molecular descriptors, we aimed to develop predictive models that can guide the design of novel thienopyrimidine derivatives with enhanced antimicrobial potential. Results: It was discovered through the descriptor importance analysis that specific physicochemical characteristics, including lipophilicity, electronic distribution, and steric effects, significantly influenced the antibacterial efficacy of these drugs. Conclusion: The identified molecular characteristics and descriptors can be used to guide the development of new thienopyrimidine derivatives with higher antibacterial activity.

Generating broadband cylindrical vector modes based on polarization-dependent acoustically induced fiber gratings using the dispersion turning point

Cylindrical vector beams (CVBs) with special polarization distribution have been extensively investigated due to the unique ways of interacting with matter. Although several configurations have been developed to generate CVBs, such as Q-plates and subwavelength gratings, the bandwidth of a single CVB is inherently narrow due to the phase geometry, which would limit its application for femtosecond lasers. Here, a broadband CVB mode converter based on an acoustically induced fiber grating (AIFG) and a tuning method of dispersion turning point (DTP) is demonstrated both theoretically and experimentally with the 3-dB bandwidth of 125 nm, which is more than 10 times that of conventional AIFGs. Not only can the DTP wavelength be tuned from the original 1500 nm to 1650 nm by thinning the fiber, but also the stable generation of a single broadband HE21odd/even mode can be controllably implemented by adjusting the polarization state of the incident light, owing to the larger beat length difference between HE21 and other CV modes. Additionally, the femtosecond CVBs and orbital angular momentum (OAM) modes are successfully generated and amplified by combining the broadband AIFG with a figure-9 mode-locked fiber laser. Meanwhile, it is verified by simulation that the choice of broadband CV mode and the tunability of DTP wavelength can be realized by designing ring-core fibers with different structures, which can furthermore improve the flexibility of generating high purity CVBs. This study provides a highly controllable technique for the generation of broadband CVBs and OAMs paving the way for high-capacity CVBs communication.

Mechanical stress-induced autophagy is cytoskeleton dependent.

The cytoskeleton is essential for mechanical signal transduction and autophagy. However, few studies have directly demonstrated the contribution of the cytoskeleton to mechanical stress-induced autophagy. We explored the role of the cytoskeleton in response to compressive force-induced autophagy in human cell lines. Inhibition and activation of cytoskeletal polymerization using small chemical molecules revealed that cytoskeletal microfilaments are required for changes in the number of autophagosomes, whereas microtubules play an auxiliary role in mechanical stress-induced autophagy. The intrinsic mechanical properties and special intracellular distribution of microfilaments may account for a large proportion of compression-induced autophagy. Our experimental data support that microfilaments are core components of mechanotransduction signals.

Experimental study and numerical simulation of concrete pavement electrical heating for snow melting

Road snow accumulation can lead to severe traffic delays, and commonly used deicing agents may pose potential environmental risks. Electrically heated concrete pavement systems utilizing heating pipe technology offer a safe and environmentally sustainable alternative. The snow-free ratio was frequently used as an evaluation index to evaluate the snow-melting performance in road infrastructure. However, the unique wavy temperature distribution during the snow-melting process of the heating system results in discontinuous melting, making the existing snow-free ratio inadequate for accurately assessing its performance and effectively guiding the operational strategy of the heating system. Therefore, this study analyzed the special temperature distribution and proposed a new calculation method for snow-free ratio based on the average temperature and the temperature non-uniformity coefficient of the pavement surface. First, the effects of factors such as heating pipe spacing, embedded depth, heating power, and wind velocity on average temperature and the temperature non-uniformity coefficient were analyzed using finite element simulation. Prediction models for average temperature and the temperature non-uniformity coefficient were then established and validated using the response surface method and experiments. Subsequently, using average temperature and the temperature non-uniformity coefficient as intermediate variables, a new functional relationship between the snow-free ratio and the four factors was established, allowing for satisfactory snow-melting performance to be achieved by adjusting the relevant factors of the heating system. The results show that the error rate between the proposed new calculation method and simulation results is only 4.44 %. Moreover, it was concluded that adjusting spacing and heating power is the most effective strategy for heating systems to achieve optimal snow-melting performance.

Special Distribution of Nanoplastics in the Central Nervous System of Zebrafish during Early Development.

There is growing concern about the distribution of nanoplastics (NPs) in the central nervous system (CNS), whereas intrusion is poorly understood. In this study, fluorescent-labeled polystyrene NPs (PS-NPs) were microinjected into different areas of zebrafish embryo to mimic different routes of exposure. PS-NPs were observed in the brain, eyes, and spinal cord through gametal exposure. It indicated that maternally derived PS-NPs were specially distributed in the CNS of zebrafish during early development. Importantly, these NPs were stranded in the CNS but not transferred to other organs during development. Furthermore, using neuron GFP-labeled transgenic zebrafish, colocalization between NPs and the neuron cells revealed that NPs were mostly enriched in the CNS surrounded but not the neurons. Even so, the intrusion of NPs into the CNS induced the significant upregulation of some neurotransmitter receptors, leading to an inhibited effect on the movement of zebrafish larvae. This work provides insights into understanding the intrusion and distribution of NPs in the CNS and the subsequent potential adverse effects.

Weighting ratings: Are people adjusting for bias in extreme reviews?

The increasing importance of consumer ratings raises the question of whether people adjust for potentially fake or biased extreme opinions when judging products. Two studies tested treatments that trimmed the extremes of rating distributions. Neither removing extreme ratings while preserving the mean, nor flagging suspicious extreme ratings, nor priming individuals about review manipulation significantly affect judged product quality on average. However, judgments for specific distributions may be made less extreme by flagging or trimming. On average, it is difficult to override usage of the mean rating as the strongest proxy for product quality. When a weighted-mean model is fitted, the estimated weighting profile is hump-shaped and asymmetric. Consumers appear to discount 5-star ratings but are particularly susceptible to being misled by disingenuous 1-star ratings. The weights suggest that there is a binary bias with an inflection point at 2-stars for product ratings, meaning that any rating above this broadly sends an equally strong positive signal of quality. Further theoretical work is required to understand how people form weights for ratings, and applied work should continue to search for decision aids that could help consumers to better adjust for review bias. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

State measures to ensure the availability of penicillin in the USSR over the second half of the 1940s

Based on the analysis of declassified documents of the State Archive of the Russian Federation and the Russian State Archive of Economics, the article considers the issue of measures taken by the USSR government in the second half of the 1940s to ensure economic and physical accessibility for the population of the country of a new drug — penicillin. The author provides information on the number of enterprises that produced antibiotics in the USSR during this period, the total volume of their production. It is shown that the capacity of domestic enterprises for a long time did not allow covering the calculated healthcare need for the drug, which determined its acute shortage. The article considers the process of pricing and government regulation of the price of a domestic drug. Based on a comparison of the cost of penicillin therapy and the income level of the population, it was concluded that the drug was affordable for the country’s residents by the end of the 1940s — beginning of the 1950s. In the conditions of an acute shortage of penicillin in the USSR in 1947, a system of centralized distribution of an antibiotic, paid for from the state budget, was introduced in medical institutions of the country. The Ministry of Health of the USSR developed a special distribution coefficient that determined the share of a particular republic in the total volume of drug supplies. The same principle was also translated to subsequent levels of distribution: by regions and cities. The article reflects the problems that accompanied the process of managing drug turnover within the country. The author showed that the introduction of penicillin into wide clinical practice, accompanied by state support measures, even despite the continued shortage of the drug, quickly and positively affected the health of the population of the USSR.

Directivity effect of the spatial distribution of co-seismic landslides affected by near-fault ground motions

Numerous co-seismic landslides occur in near-fault areas, and their spatial distribution seems to correlate well with the distribution of the energy and pulse of near-fault ground motions (NFGMs) in all directions. To confirm the relationship between the energy and pulse characteristics of NFGMs and the spatial distribution of co-seismic landslides, three-dimensional discontinuous deformation analysis (3D-DDA) was used to investigate the effect of NFGMs on initiating co-seismic landslides through an octagonal platform model and a generalized landslide. This model was subjected to the influence of two sets of representative three-component NFGMs. The outcomes derived from the block sliding processes revealed pronounced variations in the displacements of blocks in different spatial orientations. The greatest difference was up to 4.2 times, and the sliding blocks were more prone to large displacements in the direction with large energy and pulse. This study confirmed that the distribution characteristics of co-seismic landslides are related to the energy and pulse of NFGMs and provided evidence to illuminate the special distribution characteristics phenomenon of co-seismic landslides and theoretical support for the selection of factors for landslide hazard assessment.

Modulation of Al Distribution in High-Silica ZSM-5 Zeolites for Enhancing Catalytic Performance.

The spatial distribution of framework Al (AlF) has been one of the important factors that affect the catalytic properties of zeolites in diverse chemical reactions; however, the synthesis of high-silica zeolites with special AlF distribution remains a challenge. In this study, we successfully synthesized high-silica ZSM-5 zeolites with a unique AlF distribution by employing pentaerythritol (PET) as an additive in the presence of a few tetrapropylammonium hydroxide (TPAOH). The results demonstrated that the introduction of PET led to a higher proportion of Al atoms located at the sinusoidal and/or straight channels. It was observed that the addition of PET prevented the interaction between TPA+ and tetrahedral [AlO4]- during the crystallization process, resulting in enhanced availability of TPA species in the form of ion-paired TPA+. This effect leads to AlF atoms dominantly distributed away from the intersection and located in narrow channels, where acidic sites more effectively inhibit hydrogen transfer and coke formation. In the reaction of dimethyl ether (DME) to olefins, the catalyst with a unique Al distribution exhibited a significant prolonged catalytic lifetime, surpassing traditional TPA-ZSM-5 by more than 2-fold and maintaining DME conversion above 90% for a maximum of 148 h. The results of multiple pulse experiments also showed that these PET-assisted ZSM-5 zeolites significantly enhanced the selectivity of propene and butene. This approach provides an effective strategy to regulate AlF distribution in high-silica ZSM-5 catalysts with the assistance of neutral alcohol. It holds great potential for application in the synthesis of other high-silica zeolites, thereby enriching the diversity of zeolite catalysis.

A novel interval estimation framework for wind power forecasting using multi-objective gradient descent optimization

Effective wind power forecasting enables reliable integration of renewable energy into the electric grid and enhances wind farm management and power system dispatch. To mitigate uncertainty in wind power forecasting, interval prediction is commonly used to provide information on confidence levels. The lower upper bound estimation (LUBE) method is a quality-driven solution that constructs prediction intervals (PIs) based on an ensemble loss function comprising two PI quality metrics without assuming any specific distribution function. However, the conventional LUBE method suffers from three major drawbacks: 1) it is incompatible with gradient descent (GD) due to its non-differentiable objective function; 2) its objective function is formulated based on qualitative assessment rather than on a statistical basis; and 3) the ensemble loss function cannot fully represent the PI quality information measured by two conflicting metrics, leading to potential performance loss. In this study, we propose a novel multi-objective gradient descent (MOGD)-based LUBE model to address these drawbacks. The loss function is derived based on the maximum likelihood estimation and is approximated by a sigmoid function to ensure its statistical basis and differentiable form. In the training process, MOGD is applied to search for the direction of GD subject to both PI metrics. The proposed model is compared with several benchmarks using four wind power datasets from different spatial locations. The numerical results indicate the superiority of the proposed MOGD-LUBE model over its counterparts in terms of the reliability and sharpness for efficient wind power forecasting.

Abstract 5894: Novel splicing-derived neoantigen in triple negative breast cancer uncovered by SpliceIO™ a robust platform for the discovery and validation of disease-specific immunotherapies

Abstract Splicing dysregulation is a major hallmark of cancer, affecting tumor progression, metastasis, and therapy resistance. Aberrant alternative splicing (AS) plays a critical role in generating tumor-specific neoantigens targetable through an arsenal of immunotherapeutic modalities. Such neoantigens cannot be discovered using conventional DNA-based tools; they require specialized software for AS analysis using RNA-seq data. SpliceIO is Envisagenics’ AI platform for AS-derived neoantigen discovery. SpliceIO uses a “predictive ensemble” approach to uncover neoantigens that are both stably expressed and located on the extracellular membrane of cancer cells. Using SpliceIO, we have analyzed more than 10,000 RNA-seq samples from 5 patient cohorts covering 5 breast cancer subtypes as well as 2,647 normal RNA-seq samples from GTEx. Our analysis has identified tumor-specific neoantigens present in AS transmembrane proteins specific for Triple Negative Breast Cancer. SpliceIO target candidates were validated experimentally using our well-established pipeline in which isoform specific transcripts are tested in cancer cell lines by PCR and primary tumor tissues by qPCR to confirm RNA expression. Tumor heterogeneity and prevalence is confirmed by RNA in-situ hybridization in Tissue Microarrays. Extracellular localization of the novel epitope is confirmed by clone generation with GFP and c-Myc tagging followed by microscopy, Western blotting, and proteomic analysis. Our top validated target presents high TNBC tumor specificity and heterogeneous distribution, and contains a novel extracellular N-terminal domain. These results strongly support the role of aberrant AS as a major source of tumor-specific neoantigens. Our combined computational and experimental approach promotes novel target discovery, enabling the development of novel immunotherapeutic for TNBC patients who are in critical need of better treatment options. Citation Format: Nicole Williams, Miguel A. Manzanares, Kendall Anderson, Hasan Zunrut, Sakshi Gera, Nayab Habib, Shaleigh Stanton, Taylor Floyd, Sanjana Shah, Devon Trahan, Martin Akerman, Gayatri Arun. Novel splicing-derived neoantigen in triple negative breast cancer uncovered by SpliceIO™ a robust platform for the discovery and validation of disease-specific immunotherapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5894.

Validity of Markovian modeling for transient memory-dependent epidemic dynamics

The initial transient phase of an emerging epidemic is of critical importance for data-driven model building, model-based prediction of the epidemic trend, and articulation of control/prevention strategies. Quantitative models for real-world epidemics need to be memory-dependent or non-Markovian, but this presents difficulties for data collection, parameter estimation, computation, and analyses. In contrast, such difficulties do not arise in the traditional Markovian models. To uncover the conditions under which Markovian and non-Markovian models are equivalent, we develop a comprehensive computational and analytic framework. We show that the transient-state equivalence holds when the average generation time matches the average removal time, resulting in minimal Markovian estimation errors in the basic reproduction number, epidemic forecasting, and evaluation of control strategy. The errors depend primarily on the generation-to-removal time ratio, while rarely on the specific values and distributions of these times. Overall, our study provides a general criterion for modeling memory-dependent processes using Markovian frameworks.

Spatial Distribution Pattern of the Mesozooplankton Community in Ross Sea Region Marine Protected Area (RSR MPA) during Summer

The Ross Sea region Marine Protected Area (RSR MPA) is one of the most productive regions in the Southern Ocean. Mesozooplankton intermediates the primary product to the higher predators, such as penguins and seals, in this ecosystem. In this study, the mesozooplankton community structure and spatial pattern in the RSR MPA in January were investigated by using 505 μm-mesh-size bongo net samples. As a result, 37 mesozooplankton taxa with a total mean abundance of 35.26 ind./m3, ranging from 2.94 to 139.17 ind./m3, were confirmed. Of the 37 taxa, 7 occupied almost 84% of the total abundance, with copepods being the main dominant taxa. As shown by our hierarchical analysis, the mesozooplankton community was divided into four groups, each associated with a specific geographical distribution. Group A was composed of stations around Terra Nova Bay and showed relatively low abundance. Group B included stations around the continental slope region. Group D was composed of the Ross Sea continental shelf stations, while group C consisted of stations geographically located between those of groups B and D. These four groups were influenced by various environmental factors, such as water temperature, salinity, and nutrients. In summary, the mesozooplankton community can be separated according to geographical pattern. This pattern is related to several environmental factors.

Research on Collapse Risk Assessment of Karst Tunnels Based on BN Self-Learning

The high risk of collapse is a key issue affecting the construction safety of karst tunnels. A risk assessment method for karst tunnel collapse based on data-driven Bayesian Network (BN) self-learning is proposed in this study. The finite element calculation is used to analyze the distribution law of the plastic zone of the tunnel and the karst cave surrounding rock under different combinations of parameters, and a four-factor three-level data case database is established. Through the self-learning of the BN database, a Bayesian Network model of karst tunnel collapse risk assessment with nodes of four types of karst cave parameters is established. The specific probability distribution state and sensitivity of the parameters of different types of karst caves under the condition of whether the tunnel and the karst cave plastic zone are connected or not are studied. The research results show that the distance and angle of the karst cave are the main influencing parameters of the tunnel collapse probability, and the diameter and number of the karst cave are the secondary influencing parameters. Among them, the distance, diameter, and number of karst caves are proportional to the probability of tunnel collapse, and the most unfavorable orientation of karst caves is 45° above the tunnel. When the tunnel passes through the karst area, it should avoid the radial intersection with the karst cave at the arch waist while staying away from the karst cave. The results of this work can provide a reference for the construction safety of karst tunnels under similar conditions.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Mesoporous molybdate-substituted hydroxyapatite nanopowders obtained via a hydrothermal route

In the last decade, mesoporous hydroxyapatite (HA) materials have received much attention regarding environmental applications (including adsorption of soil and water contaminants, films for lithium batteries, catalysts, and support systems for catalysis) and open up ample opportunities regarding biomedical devices and structures. Molybdenum ions may strongly influence catalytic and sorption properties of materials. The present study shows an influence of hydrothermal-synthesis conditions (including temperature and duration of the treatment) on phase composition, textural properties, and morphology of molybdate-containing HA. Powders with high crystallinity manifested Brunauer–Emmett–Teller specific surface area up to 55 m2/g with a pore volume of 0.33 cm3/g. The molybdate-containing HA powders were investigated by chemical analysis, X-ray diffraction, Fourier-transform IR spectroscopy, and transmission electron microscopy. Their specific surface area, pore volume, and pore size distributions were determined by low-temperature nitrogen adsorption measurements, zeta potential was quantified, and electron paramagnetic resonance spectroscopy was performed. The concentration of MoO42− preserving the one-phase state was found, and the impact of hydrothermal treatment mode was analyzed by machine learning using artificial neural networks.

Representation of the microstructure of pearlitic steels for DEM simulations of fatigue

The fatigue behavior of pearlitic steels in wheel-rails is correlated to the microstructure. However, existing models do barely take this correlation into account. In this work, we propose a hierarchical meshing to describe the microstructure of pearlitic steels. The mesh includes grain and block/colony boundaries, lamellae orientations, and orientation perpendicular to lamellae. We use the Voronoi Tessellation method to generate elements with the specific area fraction distribution for pearlite colony areas. The colony and block information is obtained from SEM and EBSD measurements of R260 steel to construct the mesh that represents the microstructure. Finally, we obtained the deformed microstructure via simple geometrical shearing. This meshing method is the first step for modeling fatigue crack growth anisotropy due to plastic deformation.

Deep‐subwavelength characteristics of focused vector double‐petal linear edge dislocation beams

AbstractRecently, vector beams with special intensity and phase distribution have received much attention due to their unique properties. In this paper, we construct the double‐petal linear edge dislocation (DPLED) beams based on Gaussian vortex beams. The distribution of intensity, polarization, and spin angular momentum (SAM) of the DPLED beams is analyzed in tightly focused based on the Richards‐Wolf vector diffraction theory. The significant difference is occurred in light field, polarization SAM, and polarization distributions before and after focusing of DPLED beams. It's of certain importance for expanding the application of vector beams in optical control, optical imaging, and other fields.