Lipid Nanoparticles Elicit Reactogenicity and Sickness Behavior in Mice Via Toll-Like Receptor 4 and Myeloid Differentiation Protein 88 Axis.

mRNA therapeutics encapsulated in lipid nanoparticles (LNPs) offer promising avenues for treating various diseases. While mRNA vaccines anticipate immunogenicity, the associated reactogenicity of mRNA-loaded LNPs poses significant challenges, especially in protein replacement therapies requiring multiple administrations, leading to adverse effects and suboptimal therapeutic outcomes. Historically, research has primarily focused on the reactogenicity of mRNA cargo, leaving the role of LNPs understudied in this context. Adjuvanticity and pro-inflammatory characteristics of LNPs, originating at least in part from ionizable lipids, may induce inflammation, activate toll-like receptors (TLRs), and impact mRNA translation. Knowledge gaps remain in understanding LNP-induced TLR activation and its impact on induction of animal sickness behavior. We hypothesized that ionizable lipids in LNPs, structurally resembling lipid A from lipopolysaccharide, could activate TLR4 signaling via MyD88 and TRIF adaptors, thereby propagating LNP-associated reactogenicity. Our comprehensive investigation utilizing gene ablation studies and pharmacological receptor manipulation proves that TLR4 activation by LNPs triggers distinct physiologically meaningful responses in mice. We show that TLR4 and MyD88 are essential for reactogenic signal initiation, pro-inflammatory gene expression, and physiological outcomes like food intake and body weight─robust metrics of sickness behavior in mice. The application of the TLR4 inhibitor TAK-242 effectively reduces the reactogenicity associated with LNPs by mitigating TLR4-driven inflammatory responses. Our findings elucidate the critical role of the TLR4-MyD88 axis in LNP-induced reactogenicity, providing a mechanistic framework for developing safer mRNA therapeutics and offering a strategy to mitigate adverse effects through targeted inhibition of this pathway.

Simulation and Controller Design for a Fish Robot with Control Fins.

In this paper, a nonlinear simulation block for a fish robot was designed using MATLAB Simulink. The simulation block incorporated added masses, hydrodynamic damping forces, restoring forces, and forces and moments due to dorsal fins, pectoral fins, and caudal fins into six-degree-of-freedom equations of motion. To obtain a linearized model, we used three different nominal surge velocities (i.e., 0.2 m/s, 0.4 m/s, and 0.6 m/s). After obtaining output responses by applying pseudo-random binary signal inputs to a nonlinear model, an identification tool was used to obtain approximated linear models between inputs and outputs. Utilizing the obtained linearized models, two-degree-of-freedom proportional, integral, and derivative controllers were designed, and their characteristics were analyzed. For the 0.4 m/s nominal surge velocity models, the gain margins and phase margins of the surge, pitch, and yaw controllers were infinity and 69 degrees, 26.3 dB and 85 degrees, and infinity and 69 degrees, respectively. The bandwidths of surge, pitch, and yaw control loops were determined to be 2.3 rad/s, 0.17 rad/s, and 2.0 rad/s, respectively. Similar characteristics were observed when controllers designed for linear models were applied to the nonlinear model. When step inputs were applied to the nonlinear model, the maximum overshoot and steady-state errors were very small. It was also found that the nonlinear plant with three different nominal surge velocities could be controlled by a single controller designed for a linear model with a nominal surge velocity of 0.4 m/s. Therefore, controllers designed using linear approximation models are expected to work well with an actual nonlinear model.

DRG2 is required for surface localization of PD-L1 and the efficacy of anti-PD-1 therapy.

More than half of tumor patients with high PD-L1 expression do not respond to anti-PD-1/PD-L1 therapy, and the underlying mechanisms are yet to be clarified. Here we show that developmentally regulated GTP-binding protein 2 (DRG2) is required for response of PD-L1-expressing tumors to anti-PD-1 therapy. DRG2 depletion enhanced IFN-γ signaling and increased the PD-L1 level in melanoma cells. However, it inhibited recycling of endosomal PD-L1 and reduced surface PD-L1 levels, which led to defects in interaction with PD-1. Anti-PD-1 did not expand effector-like T cells within DRG2-depleted tumors and failed to improve the survival of DRG2-depleted tumor-bearing mice. Cohort analysis revealed that patients bearing melanoma with low DRG2 protein levels were resistant to anti-PD-1 therapy. These findings identify DRG2 as a key regulator of recycling of endosomal PD-L1 and response to anti-PD-1 therapy and provide insights into how to increase the correlation between PD-L1 expression and response to anti-PD-1 therapy.

CILP2 is a potential biomarker for the prediction and therapeutic target of peritoneal metastases in colorectal cancer.

Peritoneal metastases (PM) in colorectal cancer (CRC) is associated with a dismal prognosis. Identifying and exploiting new biomarkers, signatures, and molecular targets for personalised interventions in the treatment of PM in CRC is imperative. We conducted transcriptomic profiling using RNA-seq data generated from the primary tissues of 19 CRC patients with PM. Using our dataset established in a previous study, we identified 1422 differentially expressed genes compared to non-metastatic CRC. The profiling demonstrated no differential expression in liver and lung metastatic CRC. We selected 12 genes based on stringent criteria and evaluated their expression patterns in a validation cohort of 32 PM patients and 84 without PM using real-time reverse transcription-polymerase chain reaction. We selected cartilage intermediate layer protein 2 (CILP2) because of high mRNA expression in PM patients in our validation cohort and its association with a poor prognosis in The Cancer Genome Atlas. Kaplan-Meier survival analysis in our validation cohort demonstrated that CRC patients with high CILP2 expression had significantly poor survival outcomes. Knockdown of CILP2 significantly reduced the proliferation, colony-forming ability, invasiveness, and migratory capacity and downregulated the expression of molecules related to epithelial-mesenchymal transition in HCT116 cells. In an in vivo peritoneal dissemination mouse knockdown of CILP2 also inhibited CRC growth. Therefore, CILP2 is a promising biomarker for the prediction and treatment of PM in CRC.

Microfluidic Platform Enables Shearless Aerosolization of Lipid Nanoparticles for mRNA Inhalation.

Leveraging the extensive surface area of the lungs for gene therapy, the inhalation route offers distinct advantages for delivery. Clinical nebulizers that employ vibrating mesh technology are the standard choice for converting liquid medicines into aerosols. However, they have limitations when it comes to delivering mRNA through inhalation, including severe damage to nanoparticles due to shearing forces. Here, we introduce a microfluidic aerosolization platform (MAP) that preserves the structural and physicochemical integrity of lipid nanoparticles, enabling safe and efficient delivery of mRNA to the respiratory system. Our results demonstrated the superiority of the MAP over the conventional vibrating mesh nebulizer, as it avoided problems such as particle aggregation, loss of mRNA encapsulation, and deformation of the nanoparticle morphology. Notably, aerosolized nanoparticles generated by the microfluidic device led to enhanced transfection efficiency across various cell lines. In vivo experiments with mice that inhaled these aerosolized nanoparticles revealed successful lung-specific mRNA transfection without observable signs of toxicity. This MAP may represent an advancement for the pulmonary gene therapy, enabling precise and effective delivery of aerosolized nanoparticles.

Proteogenomic Characterization Reveals Estrogen Signaling as a Target for Never-Smoker Lung Adenocarcinoma Patients without EGFR or ALK Alterations.

Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies. SIGNIFICANCE: The proteogenomic landscape in never-smoker lung cancer without known driver mutations reveals prognostic proteins and enhanced estrogen signaling that can be targeted as a potential therapeutic strategy to improve patient outcomes.

Optimization of photocatalytic ceramic membrane filtration by response surface methodology: Effects of hydrodynamic conditions on organic fouling and removal efficiency.

The effects of the operating conditions, including the applied pressure, feed organic concentration, and recirculation flowrate along the TiO2-coated ceramic membrane, on the normalized membrane permeability and organic removal efficiency were systematically investigated by operating a photocatalytic membrane reactor (PMR). Response surface methodology (RSM) was conducted to better understand the interactive effect of operational conditions as well as their individual and combined effects to control membrane performance. Our results showed that the applied pressure and feed organic concentration, as single parameter, affected the normalized membrane permeability and organic removal efficiency more dominantly than the recirculation flowrate. The polynomial performance equations generated by RSM successfully predicted the membrane performance of the PMR. The responses to the normalized membrane permeability and organic removal efficiency with respect to the operational conditions were less sensitive to any combination of operational conditions than to their individual impacts. The combined effects of the operating conditions were less pronounced in promoting the catalytic performance of organic contaminants on the TiO2 surface. Our RSM analysis based on experimental observations designed by Box-Behnken Design (BBD) suggested that 1.3 bar of applied pressure, 44 mg/L of feed organic dye concentration and 0.8 L/min as recirculation flowrate as optimum conditions achieved more than 98% of organic removal efficiency and less than 5% of decline in normalized membrane permeability. This research shows that the RSM provides effective tool to optimize operational conditions to determine fouling rate and organic removal in PMR.

The impact of bioaerosol trajectories on microbial community assembly and physicochemical dynamics in the atmosphere.

This study explored the assembly mechanisms and physicochemical dynamics of microbial communities within atmospheric bioaerosols, focusing on the influence of different aerial trajectories. Over two years, samples near Seoul were classified into 'North', 'Southwest', and 'Others' categories based on their aerial trajectories. Physicochemical analysis of the PM2.5 particles revealed distinct ion compositions for each cluster, reflecting diverse environmental influences. Microbial community analysis revealed that shared dominant bacterial phyla were present in all clusters. However, distinct taxonomic profiles and biomarkers were also evident, such as coastal bacteria in the 'Southwest' cluster correlating with wind speed, and arid soil-originated bacteria in the 'North' cluster correlating with cations. These findings demonstrate that biomarkers in each cluster are representative of the distinct environments associated with their aerial trajectories. Notably, cluster 'Southwest' the highest microbial diversity and a strong alignment with the neutral community model, suggesting a large influence of passive dispersal from marine environments. Contrarily, 'North' and 'Others' were more influenced by niche-dependent factors. This study highlights the complex interplay between environmental factors and microbial dynamics in bioaerosols and provides important insights for environmental monitoring and public health risk assessment.

Thiophene-based lipids for mRNA delivery to pulmonary and retinal tissues.

Lipid nanoparticles (LNPs) largely rely on ionizable lipids to yield successful nucleic acid delivery via electrostatic disruption of the endosomal membrane. Here, we report the identification and evaluation of ionizable lipids containing a thiophene moiety (Thio-lipids). The Thio-lipids can be readily synthesized via the Gewald reaction, allowing for modular lipid design with functional constituents at various positions of the thiophene ring. Through the rational design of ionizable lipid structure, we prepared 47 Thio-lipids and identified some structural criteria required in Thio-lipids for efficient mRNA (messenger RNA) encapsulation and delivery in vitro and in vivo. Notably, none of the tested lipids have a pH-response profile like traditional ionizable lipids, potentially due to the electron delocalization in the thiophene core. Placement of the tails and localization of the ionizable headgroup in the thiophene core can endow the nanoparticles with the capability to reach various tissues. Using high-throughput formulation and barcoding techniques, we optimized the formulations to select two top lipids-20b and 29d-and investigated their biodistribution in mice. Lipid 20b enabled LNPs to transfect the liver and spleen, and 29d LNP transfected the lung and spleen. Unexpectedly, LNP with lipid 20b was especially potent in mRNA delivery to the retina with no acute toxicity, leading to the successful delivery to the photoreceptors and retinal pigment epithelium in non-human primates.

Antiangiogenic Therapeutic mRNA Delivery Using Lung-Selective Polymeric Nanomedicine for Lung Cancer Treatment.

Therapeutic antibodies that block vascular endothelial growth factor (VEGF) show clinical benefits in treating nonsmall cell lung cancers (NSCLCs) by inhibiting tumor angiogenesis. Nonetheless, the therapeutic effects of systemically administered anti-VEGF antibodies are often hindered in NSCLCs because of their limited distribution in the lungs and their adverse effects on normal tissues. These challenges can be overcome by delivering therapeutic antibodies in their mRNA form to lung endothelial cells, a primary target of VEGF-mediated pulmonary angiogenesis, to suppress the NSCLCs. In this study, we synthesized derivatives of poly(ß-amino esters) (PBAEs) and prepared nanoparticles to encapsulate the synthetic mRNA encoding bevacizumab, an anti-VEGF antibody used in the clinic. Optimization of nanoparticle formulations resulted in a selective lung transfection after intravenous administration. Notably, the optimized PBAE nanoparticles were distributed in lung endothelial cells, resulting in the secretion of bevacizumab. We analyzed the protein corona on the lung- and spleen-targeting nanoparticles using proteomics and found distinctive features potentially contributing to their organ-selectivity. Lastly, bevacizumab mRNA delivered by the lung-targeting PBAE nanoparticles more significantly inhibited tumor proliferation and angiogenesis than recombinant bevacizumab protein in orthotopic NSCLC mouse models, supporting the therapeutic potential of bevacizumab mRNA therapy and its selective delivery through lung-targeting nanoparticles. Our proof-of-principle results highlight the clinical benefits of nanoparticle-mediated mRNA therapy in anticancer antibody treatment in preclinical models.

Identification of Membrane Fouling with Greywater Filtration by Porous Membranes: Combined Effect of Membrane Pore Size and Applied Pressure.

Membrane fouling caused by complex greywater synthesized by personal care products and detergents commercially available for household applications was investigated using dead-end microfiltration (MF) and analyzed systematically by a multistage Hermia blocking model as a first attempt. The highest flux decline was associated with the smallest pore size of the membrane (0.03 µm). This effectiveness was more pronounced at higher applied pressures to the membrane. A cake layer was formed on the membrane consisting mainly of silica particles present as ingredients in greywater. Although organic rejection was low by the porous MF membrane, the organic compound contributed to membrane fouling in the filtration stage. With a 0.03 µm pore size of the membrane, dominant fouling mechanisms were classified into three stages as applied pressure increased, such as complete pore blocking, intermediate pore blocking, and cake layer formation. Specifically, during the early stage of membrane filtration at 1.5 bar, membrane fouling was determined by complete pore blocking in the 0.10 µm pore size of the membrane. However, the later stage of membrane fouling was controlled mainly by intermediate pore blocking. Regardless of the applied pressure, pore constriction or standard blocking played an important role in the fouling rate with a 0.45 µm pore size of the membrane. Our results also support that complex formation can occur due to the concentration of organic and inorganic species present in simulated greywater. Thus, strategic approaches such as periodic, chemically enhanced backwashing need to be developed and tailored to remove both organic and inorganic fouling from MF membranes treating greywater.

Microfluidic platform enables shear-less aerosolization of lipid nanoparticles for messenger RNA inhalation.

Leveraging the extensive surface area of the lungs for gene therapy, inhalation route offers distinct advantages for delivery. Clinical nebulizers that employ vibrating mesh technology are the standard choice for converting liquid medicines into aerosols. However, they have limitations when it comes to delivering mRNA through inhalation, including severe damage to nanoparticles due to shearing forces. Here, we introduce a novel microfluidic aerosolization platform (MAP) that preserves the structural and physicochemical integrity of lipid nanoparticles, enabling safe and efficient mRNA delivery to the respiratory system. Our results demonstrated the superiority of the novel MAP over the conventional vibrating mesh nebulizer, as it avoided problems such as particle aggregation, loss of mRNA encapsulation, and deformation of nanoparticle morphology. Notably, aerosolized nanoparticles generated by the microfluidic device led to enhanced transfection efficiency across various cell lines. In vivo experiments with mice that inhaled these aerosolized nanoparticles revealed successful, lung-specific mRNA transfection without observable signs of toxicity. This pioneering MAP represents a significant advancement for the pulmonary gene therapy, enabling precise and effective delivery of aerosolized nanoparticles.

Strategies for non-viral vectors targeting organs beyond the liver.

In recent years, nanoparticles have evolved to a clinical modality to deliver diverse nucleic acids. Rising interest in nanomedicines comes from proven safety and efficacy profiles established by continuous efforts to optimize physicochemical properties and endosomal escape. However, despite their transformative impact on the pharmaceutical industry, the clinical use of non-viral nucleic acid delivery is limited to hepatic diseases and vaccines due to liver accumulation. Overcoming liver tropism of nanoparticles is vital to meet clinical needs in other organs. Understanding the anatomical structure and physiological features of various organs would help to identify potential strategies for fine-tuning nanoparticle characteristics. In this Review, we discuss the source of liver tropism of non-viral vectors, present a brief overview of biological structure, processes and barriers in select organs, highlight approaches available to reach non-liver targets, and discuss techniques to accelerate the discovery of non-hepatic therapies.

Plasmonic metasurfaces of cellulose nanocrystal matrices with quadrants of aligned gold nanorods for photothermal anti-icing.

Cellulose nanocrystals (CNCs) are intriguing as a matrix for plasmonic metasurfaces made of gold nanorods (GNRs) because of their distinctive properties, including renewability, biodegradability, non-toxicity, and low cost. Nevertheless, it is very difficult to precisely regulate the positioning and orientation of CNCs on the substrate in a consistent pattern. In this study, CNCs and GNRs, which exhibit tunable optical and anti-icing capabilities, are employed to manufacture a uniform plasmonic metasurface using a drop-casting technique. Two physical phenomena-(i) spontaneous and rapid self-dewetting and (ii) evaporation-induced self-assembly-are used to accomplish this. Additionally, we improve the CNC-GNR ink composition and determine the crucial coating parameters necessary to balance the two physical mechanisms in order to produce thin films without coffee rings. The final homogeneous CNC-GNR film has consistent annular ring patterns with plasmonic quadrant hues that are properly aligned, which enhances plasmonic photothermal effects. The CNC-GNR multi-array platform offers above-zero temperatures on a substrate that is subcooled below the freezing point. The current study presents a physicochemical approach for functional nanomaterial-based CNC control.

Electroconvective viscous fingering in a single polyelectrolyte fluid on a charge selective surface.

When a low-viscosity fluid displaces into a higher-viscosity fluid, the liquid-liquid interface becomes unstable causing finger-like patterns. This viscous fingering instability has been widely observed in nature and engineering systems with two adjoined fluids. Here, we demonstrate a hitherto-unrealizable viscous fingering in a single fluid-solid interface. In a single polyelectrolyte fluid on a charge selective surface, selective ion rejection through the surface initiates i) stepwise ion concentration and viscosity gradient boundaries in the fluid and ii) electroconvective vortices on the surface. As the vortices grow, the viscosity gradient boundary pushes away from the surface, resulting viscous fingering. Comparable to conventional one with two fluids, i) a viscosity ratio ([Formula: see text]) governs the onset of this electroconvective viscous fingering, and ii) the boundary properties (finger velocity and rheological effects) - represented by [Formula: see text], electric Rayleigh ([Formula: see text]), Schmidt ([Formula: see text]), and Deborah ([Formula: see text]) numbers - determine finger shapes (straight v.s. ramified, the onset length of fingering, and relative finger width). With controllable onset and shape, the mechanism of electroconvective viscous fingering offers new possibilities for manipulating ion transport and dendritic instability in electrochemical systems.

Integrative analysis of single-cell RNA-seq and ATAC-seq reveals heterogeneity of induced pluripotent stem cell-derived hepatic organoids.

To gain deeper insights into transcriptomes and epigenomes of organoids, liver organoids from two states (expandable and more differentiated) were subjected to single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) analyses. Mitochondrial gene expression was higher in differentiated than in non-differentiated hepatocytes, with ATAC-seq peaks increasing near the mitochondrial control region. Differentiation of liver organoids resulted in the expression of transcription factors that act as enhancers and repressors. In addition, epigenetic mechanisms regulating the expression of alpha-fetoprotein (AFP) and albumin (ALB) differed in liver organoids and adult liver. Knockdown of PDX1, an essential transcription factor for pancreas development, led to the hepatic maturation of liver organoids through regulation of AFP and ALB expression. This integrative analysis of the transcriptomes and epigenomes of liver organoids at the single-cell level may contribute to a better understanding of the regulatory networks during liver development and the further development of mature in vitro human liver models.

Anthropogenic fingerprints in daily precipitation revealed by deep learning.

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1-4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Liposomal co-delivery of toll-like receptors 3 and 7 agonists induce a hot triple-negative breast cancer immune environment.

Triple-negative breast cancer (TNBC) is highly aggressive and has no standard treatment. Although being considered as an alternative to conventional treatments for TNBC, immunotherapy has to deal with many challenges that hinder its efficacy, particularly the poor immunogenic condition of the tumor microenvironment (TME). Herein, we designed a liposomal nanoparticle (LN) platform that delivers simultaneously toll-like receptor 7 (imiquimod, IQ) and toll-like receptor 3 (poly(I:C), IC) agonists to take advantage of the different toll-like receptor (TLR) signaling pathways, which enhances the condition of TME from a "cold" to a "hot" immunogenic state. The optimized IQ/IC-loaded LN (IQ/IC-LN) was effectively internalized by cancer cells, macrophages, and dendritic cells, followed by the release of the delivered drugs and subsequent stimulation of the TLR3 and TLR7 signaling pathways. This stimulation encouraged the secretion of type I interferon (IFN-α, IFN-ß) and CXCLl0, a T-cell and antigen-presenting cells (APCs) recruitment chemokine, from both cancer cells and macrophages and polarized macrophages to the M1 subtype in in vitro studies. Notably, systemic administration of IQ/IC-LN allowed for the high accumulation of drug content in the tumor, followed by the effective uptake by immune cells in the TME. IQ/IC-LN treatment comprehensively enhanced the immunogenic condition in the TME, which robustly inhibited tumor growth in tumor-bearing mice. Furthermore, synergistic antitumor efficacy was obtained when the IQ/IC-LN-induced immunogenic state in TME was combined with anti-PD1 antibody therapy. Thus, our results suggest the potential of combining 2 TLR agonists to reform the TME from a "cold" to a "hot" state, supporting the therapeutic efficacy of immune checkpoint inhibitors.

Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering Sensors.

With the increasing need for particulate matter (PM) monitoring, the demand for light-scattering sensors that allow for real-time measurements of PM is increasing. This light-scattering method involves irradiating light to the aerosols in the atmosphere to analyze the scattered light and measure mass concentrations. Humidity affects the measurement results. The humidity in an outdoor environment may exist as gas or steam, such as fog. While the impact of humidity on the light-scattering measurement remains unclear, an accurate estimation of ambient PM concentration is a practical challenge. Therefore, this study investigated the effects of humidity on light-scattering measurements by analyzing the variation in the PM concentration measured by the sensor when relative humidity was due to gaseous and steam vapor. The gaseous humidity did not cause errors in the PM measurements via the light-scattering method. In contrast, steam humidity, such as that caused by fog, resulted in errors in the PM measurement. The results help determine the factors to be considered before applying a light-scattering sensor in an outdoor environment. Based on these factors, directions for technological development can be presented regarding the correction of measurement errors induced by vapor in outdoor environments.

Revisiting the analysis pipeline for overdispersed Poisson and binomial data.

Overdispersion is a common feature in categorical data analysis and several methods have been developed for detecting and handling it in generalized linear models. The first aim of this study is to clarify the relationships among various score statistics for testing overdispersion and to compare their performances. In addition, we investigate a principled way to correct finite sample bias in the score statistic caused by estimating regression parameters with restricted likelihood. The second aim is to reconsider the current practice for handling overdispersed categorical data. Although the conventional models are based on substantially different mechanisms for generating overdispersion, model selection in practice has not been well studied. We perform an intensive numerical study for determining which method is more robust to various overdispersion mechanisms. In addition, we provide some graphical tools for identifying the better model. The last aim is to reconsider the key assumption for deriving the score statistics. We study the meaning of testing overdispersion when this assumption is violated, and we analytically show the conditions for which it is not appropriate to employ the current statistical practices for analyzing overdispersed data.