Analysis Of Distribution Research Articles

Unveiling dissociation mechanisms and binding patterns in the UHRF1-DPPA3 complex via multi-replica molecular dynamics simulations.

Ubiquitin-like with PHD and RING finger domain containing protein 1 (UHRF1) is responsible for preserving the stability of genomic methylation through the recruitment of DNA methyltransferase 1 (DNMT1). However, the interaction between Developmental pluripotency associated 3 (DPPA3) and the pre-PHD-PHD (PPHD) domain of UHRF1 hinders the nuclear localization of UHRF1. This disruption has implications for potential cancer treatment strategies. Drugs that mimic the binding pattern between DPPA3 and PPHD could offer a promising approach to cancer treatment. Our study reveals that DPPA3 undergoes dissociation from the C-terminal through three different modes of helix unfolding. Furthermore, we have identified key residue pairs involved in this dissociation process and potential drug-targeting residues. These findings offer valuable insights into the dissociation mechanism of DPPA3 from PPHD and have the potential to inform the design of novel drugs targeting UHRF1 for cancer therapy. To comprehend the dissociation process and binding patterns of PPHD-DPPA3, we employed enhanced sampling techniques, including steered molecular dynamics (SMD) and conventional molecular dynamics (cMD). Additionally, we utilized self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. The Gromacs software was used for performing molecular dynamics simulations, and the AMBER FF14SB force field was applied to the protein.

Analysis of Distribution and Marketing Efficiency of Pineapples from a Sharia Economic Perspective

Analysis of Distribution and Marketing Efficiency of Pineapples from a Sharia Economic Perspective

Estimating and Rewarding the Value of Healthcare Interventions Beyond the Healthcare Sector: A Conceptual Framework.

Evaluating healthcare interventions for their impacts beyond health outcomes may result in recognition of changes in human capital, income level, tax revenue, and government spending, which could affect economic growth and population health. In this paper, we document instances where current health technology assessment (HTA) practices fail to account for the impacts of healthcare interventions on broader society beyond the healthcare sector. We propose a novel conceptual framework, highlighting its three components (distributional cost-effectiveness analysis [DCEA], input-output model, and voting scheme) and their contributions to capturing the economic and societal ripple effects of healthcare interventions. This manuscript also outlines a case study in which the framework is applied to the reassessment of a previously evaluated digital health therapeutic for the treatment of opioid use disorder (OUD) compared with standard of care, demonstrating its practical application. The DCEA health value metric indicates that digital therapeutic is more equitable, favoring socioeconomically disadvantaged groups, while standard of care exacerbates health inequality by benefiting the already advantaged. Additionally, digital therapeutic shows potential for boosting productivity, raising income, and creating jobs, supporting its consideration by employer-sponsored health plans to optimize resource allocation for treating OUD. The conceptual framework provides insights for enhancing HTAs to incorporate the broader economic and societal impacts of healthcare interventions. By integrating DCEA, extended HTA analysis with input-output modeling, and a voting scheme, decision makers can make informed choices aligned with societal priorities, although further research and validation are necessary for practical implementation across diverse healthcare contexts.

Establishment of artificial intelligence model for precise histological subtyping of lung adenocarcinoma and its application to quantitative and spatial analysis.

The histological subtype of lung adenocarcinoma is a major prognostic factor. We developed a new artificial intelligence model to classify lung adenocarcinoma images into seven histological subtypes and adopted the model for whole-slide images to investigate the relationship between the distribution of histological subtypes and clinicopathological factors. Using histological subtype images, which are typical for pathologists, we trained and validated an artificial intelligence model. Then, the model was applied to whole-slide images of resected lung adenocarcinoma specimens from 147 cases. The model achieved an accuracy of 99.7% in training sets and 90.4% in validation sets consisting of typical tiles of histological subtyping for pathologists. When the model was applied to whole-slide images, the predominant subtype according to the artificial intelligence model classification matched that determined by pathologists in 75.5% of cases. The predominant subtype and tumor grade (using the WHO fourth and fifth classifications) determined by the artificial intelligence model resulted in similar recurrence-free survival curves to those determined by pathologists. Furthermore, we stratified the recurrence-free survival curves for patients with different proportions of high-grade components (solid, micropapillary and cribriform) according to the physical distribution of the high-grade component. The results suggested that tumors with centrally located high-grade components had a higher malignant potential (P<0.001 for 5-20% high-grade component). The new artificial intelligence model for histological subtyping of lung adenocarcinoma achieved high accuracy, and subtype quantification and subtype distribution analyses could be achieved. Artificial intelligence model therefore has potential for clinical application for both quantification and spatial analysis.

Giant goos–hanchen shift with heigh reflection base on guided mode resonance in trapezoidal hBN/dielectric metasurface

hBN is a natural hyperbolic van der Waals material that can enhance light–matter interactions. In this work, the maximum Goos-Hanchen(GH) shift has a magnitude of −4680 μm with high reflection using the central beam method in the trapezoidal dielectric/hBN grating (TDG) metasurface (MS) where the beam waist w0≥4λ. Analysis of the electromagnetic field distribution indicated that the amplified GH shift was a result of guided mode resonances excited in the waveguide dielectric layer. The frequency and magnitude of GH shifts can be effectively controlled by adjusting the height of the trapezoidal hBN, as well as by manipulating the widths of the top and bottom dielectric layers, the period of the TDG structure, and the height of the multi-layered structure. Moreover, an evaluation of the structure-sensing properties based on the GH shift was conducted. The enhanced and controllable GH shift exhibited by the TDG MS presents promising prospects for applications in optical sensors, optical switches, and optoelectronic detectors.

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

Unveiling non-communicable disease trends among Indian states: predicting health outcomes with socioeconomic and demographic factors

PurposeThe present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.Design/methodology/approachThe study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.FindingsOverall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.Originality/valueThe study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.

Hydraulic property variations with depth in a loess mudstone landslide

In areas where loess is distributed, landslides represent a significant geohazard with severe implications. Among these events, loess-mudstone landslides are particularly prevalent, posing substantial risks to the safety and property of local residents, and moisture plays a pivotal role as a key factor in causing these disasters. In this study, the hydraulic properties of the soils along the longitudinal section of an ongoing loess-mudstone landslide are investigated through the variation of soil water characteristic curves, which are subsequently fitted by utilizing van Genuchten model. Moreover, a comprehensive experimental investigation was conducted on the loess, mudstone, and loess-mudstone mixtures to facilitate analysis, including X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM) observation, particle size distribution (PSD) analysis, along with fundamental geotechnical tests for parameter determination. It is found that mudstone and loess have distinct SWCC distribution. The SWCC of loess at various depths exhibits a similar distribution pattern due to the occurrence of landslide. The SWCC distribution of loess-mudstone mixture displays a transitional trend between the SWCC of mudstone and that of loess, and the water retention capacity increases as the mudstone content increases. The experimental findings have demonstrated notable agreement between each other and exhibited a satisfactory level of concurrence with the observed phenomena in geological surveys.

Intra- and interspecies variation and population dynamics of Fasciola gigantica among ruminants in Sudan.

Fasciola gigantica is a widespread parasite that causes neglected disease in livestock worldwide. Its high transmissibility and dispersion are attributed to its ability to infect intermediate snail hosts and adapt to various mammalian definitive hosts. This study investigated the variation and population dynamics of F. gigantica in cattle, sheep, and goats from three states in Sudan. Mitochondrial cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit 1 (ND1) genes were sequenced successfully to examine intra and interspecific differences. ND1 exhibited higher diversity than COI, with 15 haplotypes and 10 haplotypes, respectively. Both genes had high haplotype diversity but low nucleotide diversity, with 21 and 11 polymorphic sites for ND1 and COI, respectively. Mismatch distribution analysis and neutrality tests revealed that F. gigantica from different host species was in a state of population expansion. Maximum likelihood phylogenetic trees and median networks revealed that F. gigantica in Sudan and other African countries had host-specific and country-specific lineages for both genes. The study also indicated that F. gigantica-infected small ruminants were evolutionarily distant, suggesting deep and historical interspecies adaptation.

Expanding the wrench feasible workspace of quadrotor-based mobile cable-driven parallel manipulators using multi-objective optimization and machine learning

Quadrotor-based Reconfigurable Cable-Driven Parallel Manipulators (QRCDPMs) have previously been introduced as having significant potential in extending the feasible workspace of Cable-Driven Parallel Manipulators (CDPMs). However, such configurations have limitations in executing positive Z-direction trajectories resulting in non-optimal workspace and performance. This study proposes a novel Quadrotor-based Enhanced Reconfiguration Cable-Driven Parallel Manipulator (QERCDPM) that significantly enhances the Wrench Feasible Workspace (WFW). This allows for extended safe platform operation along all XYZ directions by adjusting the bottom cable exit point. Simulation results indicate that the proposed setup achieves a 96.39 % ratio of safe workspace to available workspace in various cable exit points configurations. Tension Distribution analysis for different trajectories demonstrates the proposed setup's superior cable tension management, increased flexibility and reachability. A Random Forest based Particle Swarm Optimization - Modified Frequency Bat Algorithm (RFPSOMFB) optimization algorithm is proposed, which outperforms existing methods in terms of run time and solution quality. The findings hold significance for applications requiring safe and efficient trajectory execution in dynamic and constrained environments, contributing to the evolution of multi-robot based intelligent and distributed systems.

Mechanical recycling process: An alternative for a viable disposal of carbon fiber‐reinforced thermoplastic waste

AbstractConcern for the environment has increased the interest of the automotive and aerospace industries in evaluating the feasibility of mechanical recycling of waste carbon‐fiber‐reinforced polymer composites (CFRP) and waste from protective films used during the transport and storage of thermosetting composites, which are removed and discarded during manufacturing. Therefore, this work aimed to develop a recyclable composite from protective film waste by incorporating carbon fiber/poly(aryl ether ketone) (CF/PAEK) composite particles obtained through grinding in knife mills, followed by an analysis of the particle size distribution. Protective film residues (PEres) were cut to facilitate processing. A mixture of low‐density polyethylene and PEres (50/50) was used as the composite matrix, and 5, 10, 15, and 20 wt% CF/PAEK composite particles were added as the reinforcing agents. Then, these recycled composites were prepared by melt mixing using a twin‐screw extruder and injection molding to obtain standardized samples. Mechanical, thermal, electrical, and electromagnetic properties were evaluated. It was possible to observe that the increase in the addition of CF/PAEK composite particles contributed to a 290% increase in elastic modulus values and a 9.1% increase in Shore D hardness, electrical conductivity, and attenuation of the electromagnetic wave. Furthermore, satisfactory adhesion between filler and matrix contributed to a good interface and reinforcement of the final material.Highlights Mechanical recycling by extrusion of waste from the automotive and aerospace sectors Grinding of carbon fiber/poly(aryl ether ketone) composite waste to be used as filler Protective film waste used as matrix Composites developed with waste with good electrical and electromagnetic properties The addition of thermoplastic composite residues does not affect thermal and mechanical properties

Cost Budget Analysis for Equal Distribution of Labour for Multi-Storey Buildings Construction

Although all resources on a construction project have their respective roles, the availability of labour significantly impacts how far the project moves forward and is completed. According to Kastor and Sirakoulis (2009), calculating the number of workers according to the construction schedule is crucial because, without this consideration, the resulting schedule may not be effective and efficient. process used for construction project resources to reduce fluctuations (Waluyo &amp; Aditama, 2017). This research compares labour allocation, duration, and labour wage cost budgets under several conditions. These conditions include actual project conditions, planning, and results after levelling using an auto schedule. In project planning, the fluctuations obtained are pretty sharp. After the auto schedule levelling, the manpower no longer experienced overallocation, but fluctuations between weeks were still relatively high. This can happen because the quantity of work and labour in the construction projects under review is not comparable to the effects of project delays. The results obtained from the comparisons analyzed on the X-storey building construction project are that the auto schedule does not change the initial planning duration, which remains at 133 days. There was a disparity of 0.02% in auto schedule planning costs from 1,098,345,000.00. Meanwhile, in actual conditions, the labour cost budget increased by 0.12% from IDR 967,880,000.00 after the auto-schedule levelling process. It can be concluded that before resource levelling is carried out, it is necessary to review project scheduling and accelerate the duration of implementation, specifically if construction projects experience delays and other factors, so as not to cause fluctuations caused by the uneven quantity of work over some time.

Nuclear patterns of phosphatidylinositol 4,5- and 3,4-bisphosphate revealed by super-resolution microscopy differ between the consecutive stages of RNA polymerase II transcription.

Phosphatidylinositol phosphates are powerful signaling molecules that orchestrate signaling and direct membrane trafficking in the cytosol. Interestingly, phosphatidylinositol phosphates also localize within the membrane-less compartments of the cell nucleus, where they participate in the regulation of gene expression. Nevertheless, current models of gene expression, which include condensates of proteins and nucleic acids, do not include nuclear phosphatidylinositol phosphates. This gap is partly a result of the missing detailed analysis of the subnuclear distribution of phosphatidylinositol phosphates and their relationships with gene expression. Here, we used quantitative dual-color direct stochastic optical reconstruction microscopy to analyze the nanoscale co-patterning between RNA polymerase II transcription initiation and elongation markers with respect to phosphatidylinositol 4,5- or 3,4-bisphosphate in the nucleoplasm and nuclear speckles and compared it with randomized data and cells with inhibited transcription. We found specific co-patterning of the transcription initiation marker P-S5 with phosphatidylinositol 4,5-bisphosphate in the nucleoplasm and with phosphatidylinositol 3,4-bisphosphate at the periphery of nuclear speckles. We showed the specific accumulation of the transcription elongation marker PS-2 and of nascent RNA in the proximity of phosphatidylinositol 3,4-bisphosphate associated with nuclear speckles. Taken together, this shows that the distinct spatial associations between the consecutive stages of RNA polymerase II transcription and nuclear phosphatidylinositol phosphates exhibit specificity within the gene expression compartments. Thus, in analogy to the cellular membranes, where phospholipid composition orchestrates signaling pathways and directs membrane trafficking, we propose a model in which the phospholipid identity of gene expression compartments orchestrates RNA polymerase II transcription.

Temperature distribution analysis and mechanical property prediction of wire loops in the Stelmor air-cooling system

During the Stelmor air-cooling process, the temperature distribution has a significant impact on the wire loops' final mechanical properties. The temperature distribution during air-cooling process is accurately solved by establishing three-dimensional model and Computational Fluid Dynamics (CFD) simulation. It is also found that the heat transfer coefficient on the cross section of the wire loop is very different, with a difference of 70–100 Wm−2K−1. The average value of the surface heat transfer coefficient of the wire loops section is used to replace the surface heat transfer coefficient of the wire loops, which improves the temperature distribution calculation accuracy, which is not considered by previous scholars. The finite difference method is used to calculate the mathematical model of the temperature distribution during the Stelmor air-cooling process. It is found that the maximum temperature difference of the wire during the cooling process is 90–110 K. The prediction model of mechanical property of wire after air-cooling was established, and distribution of mechanical property of the wire loops was obtained, and the reason for the uneven distribution of mechanical property of the wire loops was found.

Assessment and measurement of ground motion risk levels for structures isolated by double concave friction pendulum system

Determining the risk level of ground motions (GM) for structures is crucial for their damage control and resilience enhancement, while the assessment and measurement criteria of GM risk levels for structures isolated by double concave friction pendulum system (DCFPS) remain unclear. Through statistical analysis of the response distribution of DCFPS with various design parameters under 1013 GM records, this study determines an energy dissipation efficacy of 99 %, a floor velocity of 0.35 m/s, a floor velocity of 0.60 m/s, and the displacement capacity of DCFPS as the response criteria for assessing four performance states of efficacy, habitability, functionality, and safety, respectively. In addition, the value of GM intensity in PGA, PGV, PGD, and the equivalent velocity of seismic input energy (VE) for measuring the four GM risk levels corresponding to the four performance states are obtained. Furthermore, a classification of GMs based on earthquake magnitude and fault distance is proposed according to their risk to DCFPS. It is found that the intensity value of each GM risk level varies for different design parameters of DCFPS but fluctuate within a small range, however, great differences exist when using different intensity measures (IM) in classifying GM risk levels. Therefore, based on the correlation between IMs and DCFPS responses, the conservatism of PGA, PGV, PGD and VE in assessing the risk of GMs for DCFPS are evaluated.

Program VUE: analysing distributions of cryo-EM projections using uniform spherical grids

Three-dimensional cryo electron microscopy reconstructions are obtained by extracting information from a large number of projections of the object. These projections correspond to different `views' or `orientations', i.e. directions in which these projections show the reconstructed object. Uneven distribution of these views and the presence of dominating preferred orientations may distort the reconstructed spatial images. This work describes the program VUE (views on uniform grids for cryo electron microscopy), designed to study such distributions. Its algorithms, based on uniform virtual grids on a sphere, allow an easy calculation and accurate quantitative analysis of the frequency distribution of the views. The key computational element is the Lambert azimuthal equal-area projection of a spherical uniform grid onto a disc. This projection keeps the surface area constant and represents the frequency distribution with no visual bias. Since it has multiple tunable parameters, the program is easily adaptable to individual needs, and to the features of a particular project or of the figure to be produced. It can help identify problems related to an uneven distribution of views. Optionally, it can modify the list of projections, distributing the views more uniformly. The program can also be used as a teaching tool.

Inhibitory subpopulations in preBötzinger Complex play distinct roles in modulating inspiratory rhythm and pattern.

Inhibitory neurons embedded within mammalian neural circuits shape breathing, walking, and other rhythmic motor behaviors. At the core of the neural circuit controlling breathing is the preBötzinger Complex (preBötC), where GABAergic (GAD1/2+) and glycinergic (GlyT2+) neurons are functionally and anatomically intercalated among glutamatergic Dbx1-derived (Dbx1+) neurons that generate rhythmic inspiratory drive. The roles of these preBötC inhibitory neurons in breathing remain unclear. We first characterized the spatial distribution of molecularly-defined preBötC inhibitory subpopulations in male and female neonatal double reporter mice expressing either tdTomato or EGFP in GlyT2+, GAD1+, or GAD2+ neurons. We found that the majority of preBötC inhibitory neurons expressed both GlyT2 and GAD2 while a much smaller subpopulation also expressed GAD1. To determine the functional role of these subpopulations, we used holographic photostimulation, a patterned illumination technique, in rhythmically active medullary slices from neonatal Dbx1tdTomato;GlyT2EGFP and Dbx1tdTomato;GAD1EGFP double reporter mice of either sex. Stimulation of 4 or 8 preBötC GlyT2+ neurons during endogenous rhythm prolonged the interburst interval in a phase-dependent manner and increased the latency to burst initiation when bursts were evoked by stimulation of Dbx1+ neurons. In contrast, stimulation of 4 or 8 preBötC GAD1+ neurons did not affect interburst interval or latency to burst initiation. Instead, photoactivation of GAD1+ neurons during the inspiratory burst prolonged endogenous and evoked burst duration and decreased evoked burst amplitude. We conclude that GlyT2+/GAD2+ neurons modulate breathing rhythm by delaying burst initiation while a smaller GAD1+ subpopulation shapes inspiratory patterning by altering burst duration and amplitude.Significance Statement Inhibition is critical for control of rhythmic motor behaviors, such as breathing, walking, and chewing. We reveal functional differences among embedded preBötC inhibitory micro-cir-cuits that contribute to excitation-inhibition balance governing distinct processes in the breathing motor program. We develop approaches for high throughput analysis of spatial distributions of neurons in tissue and for dynamic functional manipulations via an important extension of holographic photostimulation to sequences of patterns that more closely mimics physiological neural activity. Our study challenges the current understanding of the role of inhibition in breathing and provides novel insights into specific roles of inhibitory neurons in neural circuits controlling breathing that are applicable to other rhythmic motor behaviors in health and disease.

Managing the E-commerce Data Deluge through Text Analytics and Web Management (Overview of Amazon.com)

Today, more than 80% of the big data handled in the e-commerce industry is text and unstructured data. Text analytics is an automated process for analyzing text and extracting useful information from it. It can discover trends and relationships in data. Web analytics is the collection, processing, and analysis of data in order to draw conclusions to optimize usability on a website. Web analytics can be used to improve the usability of a site by analyzing user behavior patterns such as time spent on the site, abandonment rates, most frequently accessed products, click-through rates, etc. It can also help analyze the interests of different user demographics, as it tracks granular details such as user demographics, age and gender, geography, and devices used as data. In order to obtain UpToDate information, the business can utilize business intelligence for real-time data processing, then they can practice stream analysis to analyse continuous flow of data. For instance, the business can collect instant information in Twitter or other social media and analyse it by using social media analysis. For website management, business can practice web analysis to analyse the customer’s behaviours. Tracking the customer’s activity, page view and conversion rate is important for business to analyse how to improve the website performance. Text analytics of comments received on Amazon can be used to group text data and produce results in terms of word frequency distribution and sentiment analysis. Text analytics could be used for decision making, improving service quality, and developing new business models.

Spatial and Temporal Characteristic Analysis and Risk Assessment of Global Highly Pathogenic Avian Influenza H5N8 Subtype

H5N8 HPAI is a highly infectious avian disease that now poses a serious threat and potential risk to poultry farming, wild birds, and public health. In this study, to investigate the seasonality and transmission directionality of global H5N8 HPAI, the spatial and temporal analysis of H5N8 HPAI was conducted using time series decomposition and directional distribution analysis. An ecological niche model was developed for H5N8 HPAI in poultry to identify areas at high risk of H5N8 HPAI in poultry and associated risk factors. The results indicated that three global pandemics of H5N8 HPAI emerged from 2014 to 2022, all showing a southeast–northwest distribution direction. H5N8 HPAI occurred more frequently in winter and less frequently in summer. The southwestern border region and the southeastern region of North America, the southern region of South America, most of Europe, the southern border region and the northern border region of Africa, and the southwestern region and the southeastern region of Asia provide the suitable environment for the occurrence of H5N8 HPAI in poultry. Chicken density, duck density, population density, bio1 (annual mean temperature), and land cover were considered important variables for the occurrence of H5N8 HPAI in poultry. This study can help optimize the use of resources and provide new information for policymakers to carry out prevention and control efforts.

Correlation of TRPA1 RNAscope and Agonist Responses.

The TRPA1 ion channel is a sensitive detector of reactive chemicals, found primarily on sensory neurons. The phenotype exhibited by mice lacking TRPA1 suggests its potential as a target for pharmacological intervention. Antibody-based detection for distribution analysis is a standard technique. In the case of TRPA1, however, there is no antibody with a plausible validation in knockout animals or functional studies, but many that have failed in this regard. To this end we employed the single molecule in situ hybridization technique RNAscope on sensory neurons immediately after detection of calcium responses to the TRPA1 agonist allyl isothiocyanate. There is a clearly positive correlation between TRPA1 calcium imaging and RNAscope detection (R = 0.43), although less than what might have been expected. Thus, the technique of choice should be carefully considered to suit the research question. The marginal correlation between TRPV1 RNAscope and the specific agonist capsaicin indicates that such validation is advisable for every RNAscope target. Given the recent description of a long-awaited TRPA1 reporter mouse, TRPA1 RNAscope detection might still have its use cases, for detection of RNA at particular sites, for example, defined structurally or by other molecular markers.