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Targeted protein degradation technology has gained substantial momentum over the past two decades as a revolutionary strategy for eliminating pathogenic proteins that are otherwise refractory to treatment. Among the various approaches developed to harness the body's innate protein homeostasis mechanisms for this purpose, lysosome targeting chimeras (LYTACs) that exploit the lysosomal degradation pathway by coupling the target proteins with lysosome-trafficking receptors represent the latest innovation. These chimeras are uniquely tailored to degrade proteins that are membrane-bound and extracellular, encompassing approximately 40% of all proteome. Several novel LYTAC formulas have been developed recently, providing valuable insights for the design and development of therapeutic degraders. This review delineates the recent progresses of LYTAC technology, its practical applications, and the factors that dictate target degradation efficiency. The potential and emerging trends of this technology are discussed as well. LYTAC technology offers a promising avenue for targeted protein degradation, potentially revolutionizing the therapeutic landscape for numerous diseases.
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In this paper, Bi2S3/AgBiS2 composite nanomaterials and PDA@Ag@N-CQDs were synthesized, and used as substrates and second antibody label respectively to construct a sandwich photoelectrochemical (PEC) sensor. The upconversion luminescence effect of N-CQDs can convert long wavelength light into short wavelength light that can be utilized by the substrate material, which can provide additional excitation light energy for the substrate material and further enhance the photoelectric response. Besides, Ag has SPR effect and can also promote electron transfer. The proposed sandwich immunosensor achieves detection of NSE in the concentration range of 0.001 ng mL-1 to 100 ng mL-1, with a detection limit of 0.28 pg mL-1 (S/N = 3). What's more, the proposed sensor also exhibits good stability, selectivity, as well as reproducibility, indicating its promising application prospects.
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BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images. METHODS: A total of 683 intraoral clinical images acquired from 134 volunteers were used to construct the database and evaluate the models. Four deep ConvNet models were developed using ensemble learning and outperformed a single model. The performances of the different models were evaluated by comparing the accuracy and sensitivity for recognizing the existence of gingivitis from intraoral images. RESULTS: The ResNet model achieved an area under the curve (AUC) value of 97%, while the AUC values for the GoogLeNet, AlexNet, and VGG models were 94%, 92%, and 89%, respectively. Although the ResNet and GoogLeNet models performed best in classifying gingivitis from images, the sensitivity outcomes were not significantly different among the ResNet, GoogLeNet, and Alexnet models (p>0.05). However, the sensitivity of the VGGNet model differed significantly from those of the other models (p < 0.001). CONCLUSION: The ResNet and GoogLeNet models show promise for identifying chronic gingivitis from images. These models can help doctors diagnose periodontal diseases efficiently or based on self-examination of the oral cavity by patients.
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Gingivitis , Redes Neurales de la Computación , Humanos , Gingivitis/diagnóstico , Gingivitis/patología , Enfermedad Crónica , Adulto , Femenino , Fotografía Dental/métodos , Masculino , Aprendizaje Profundo , FotograbarRESUMEN
The redox-diffusion (RD) battery concept introduces an environmentally friendly solution for stretchable batteries in autonomous wearable electronics. By utilising plant-based redox-active biomolecules and cellulose fibers for the electrode scaffold, separator membrane, and current collector, along with a biodegradable elastomer encapsulation, the battery design overcomes the reliance on unsustainable transition metal-based active materials and non-biodegradable elastomers used in existing stretchable batteries. Importantly, it addresses the drawback of limited attainable battery capacity, where increasing the active material loading often leads to thicker and stiffer electrodes with poor mechanical properties. The concept decouples the active material loading from the mechanical structure of the electrode, enabling high mass loadings, while retaining a skin-like young's modulus and stretchability. A stretchable ion-selective membrane facilitates the RD process, allowing two separate redox couples, while preventing crossovers. This results in a high-capacity battery cell that is both electrochemically and mechanically stable, engineered from sustainable plant-based materials. Notably, the battery components are biodegradable at the end of their life, addressing concerns of e-waste and resource depletion.
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The Li-CO2 batteries utilizing greenhouse gas CO2 possess advantages of high energy density and environmental friendliness. However, these batteries following Li2CO3-product route typically exhibit low work voltage (<2.5â V) and energy efficiency. Herein, we have demonstrated for the first time that cobalt phthalocyanine (CoPc) as homogeneous catalyst can elevate the work plateau towards 2.98â V, which is higher than its theoretical discharge voltage without changing the Li2CO3-product route. This unprecedented discharge voltage is illustrated by mass spectrum and electrochemical analyses that CoPc has powerful adsorption capability with CO2 (-7.484â kJ mol-1) and forms discharge intermediate of C33H16CoN8O2. Besides high discharge capacity of 18724â mAh g-1 and robust cyclability over 1600â hours (1000â mAh g-1 cut-off) at a current density of 100â mA g-1, the batteries show high temperature adaptability (-30-80 °C). Our work is paving a promising avenue for the progress of high-efficiency Li-CO2 batteries.
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Soft and stretchable nanocomposites can match the mechanical properties of neural tissue, thereby minimizing foreign body reactions to provide optimal stimulation and recording specificity. Soft materials for neural interfaces should simultaneously fulfill a wide range of requirements, including low Young's modulus (<<1 MPa), stretchability (≥30%), high conductivity (>> 1000 S cm-1), biocompatibility, and chronic stability (>> 1 year). Current nanocomposites do not fulfill the above requirements, in particular not the combination of softness and high conductivity. Here, this challenge is addressed by developing a scalable and robust synthesis route based on polymeric reducing agents for smooth, high-aspect ratio gold nanowires (AuNWs) of controllable dimensions with excellent biocompatibility. AuNW-silicone composites show outstanding performance with nerve-like softness (250 kPa), high conductivity (16 000 S cm-1), and reversible stretchability. Soft multielectrode cuffs based on the composite achieve selective functional stimulation, recordings of sensory stimuli in rat sciatic nerves, and show an accelerated lifetime stability of >3 years. The scalable synthesis method provides a chemically stable alternative to the widely used AgNWs, thereby enabling new applications within electronics, biomedical devices, and electrochemistry.
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Table tennis players have adaptive visual and sensorimotor networks, which are the key brain regions to acquire environmental information and generate motor output. This study examined 20 table tennis players and 21 control subjects through ultrahigh field 7 Tesla magnetic resonance imaging. First, we measured percentage amplitude of fluctuation across five different frequency bands and found that table tennis players had significantly lower percentage amplitude of fluctuation values than control subjects in 18 brain regions, suggesting enhanced stability of spontaneous brain fluctuation amplitudes in visual and sensorimotor networks. Functional connectional analyses revealed increased static functional connectivity between two sensorimotor nodes and other frontal-parietal regions among table tennis players. Additionally, these players displayed enhanced dynamic functional connectivity coupled with reduced static connectivity between five nodes processing visual and sensory information input, and other large-scale cross-regional areas. These findings highlight that table tennis players undergo neural adaptability through a dual mechanism, characterized by global stability in spontaneous brain fluctuation amplitudes and heightened flexibility in visual sensory networks. Our study offers novel insights into the mechanisms of neural adaptability in athletes, providing a foundation for future efforts to enhance cognitive functions in diverse populations, such as athletes, older adults, and individuals with cognitive impairments.
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Encéfalo , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Masculino , Adulto Joven , Encéfalo/fisiología , Encéfalo/diagnóstico por imagen , Femenino , Adulto , Tenis/fisiología , Atletas , Mapeo Encefálico/métodos , Red Nerviosa/fisiología , Red Nerviosa/diagnóstico por imagen , Vías Nerviosas/fisiología , Adaptación Fisiológica/fisiología , AdolescenteRESUMEN
Recent advancements in applications of deep neural network for bearing fault diagnosis under variable operating conditions have shown promising outcomes. However, these approaches are limited in practical applications due to the complexity of neural networks, which require substantial computational resources, thereby hindering the advancement of automated diagnostic tools. To overcome these limitations, this study introduces a new fault diagnosis framework that incorporates a tri-channel preprocessing module for multidimensional feature extraction, coupled with an innovative diagnostic architecture known as the Lightweight Ghost Enhanced Feature Attention Network (GEFA-Net). This system is adept at identifying rolling bearing faults across diverse operational conditions. The FFE module utilizes advanced techniques such as Fast Fourier Transform (FFT), Frequency Weighted Energy Operator (FWEO), and Signal Envelope Analysis to refine signal processing in complex environments. Concurrently, GEFA-Net employs the Ghost Module and the Efficient Pyramid Squared Attention (EPSA) mechanism, which enhances feature representation and generates additional feature maps through linear operations, thereby reducing computational demands. This methodology not only significantly lowers the parameter count of the model, promoting a more streamlined architectural framework, but also improves diagnostic speed. Additionally, the model exhibits enhanced diagnostic accuracy in challenging conditions through the effective synthesis of local and global data contexts. Experimental validation using datasets from the University of Ottawa and our dataset confirms that the framework not only achieves superior diagnostic accuracy but also reduces computational complexity and accelerates detection processes. These findings highlight the robustness of the framework for bearing fault diagnosis under varying operational conditions, showcasing its broad applicational potential in industrial settings. The parameter count was decreased by 63.74% compared to MobileVit, and the recorded diagnostic accuracies were 98.53% and 99.98% for the respective datasets.
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BACKGROUND: To find the factors impacting overall survival (OS) prognosis in patients with endometrioid endometrial carcinoma (EEC) and adenocarcinoma and to establish a nomogram model to validate the 2023 International Federation of Obstetrics and Gynecology (FIGO) staging system for endometrial cancer. METHODS: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) training cohort. An independent validation cohort was obtained from the First Affiliated Hospital of Anhui Medical University between 2008 and 2023. Cox regression analysis identified independent prognostic factors for OS in EEC and adenocarcinoma patients. A nomogram predicting OS was developed and validated utilizing the C-index, calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). The relationship between the tumor grade and prognosis of EEC and adenocarcinoma was quantified using net reclassification improvement (NRI), propensity score matching (PSM), and Kaplan-Meier curves. RESULTS: Cox regression analysis identified age, race, marital status, tumor grade, tumor stage, tumor size, and chemotherapy as independent prognostic factors for OS. A nomogram for predicting OS was developed based on these factors. The C-indexes for the OS nomogram was 0.743 and 0.720 for the SEER training set and external validation set, respectively. The area under the ROC (AUC) for the OS nomogram was 0.755, 0.757, and 0.741 for the SEER data subsets and 0.844, 0.719, and 0.743 for the external validation subsets. Calibration plots showed high concordance between the nomogram-predicted and observed OS. DCA also demonstrated the clinical utility of the OS nomogram. NRI, PSM, and survival analyses revealed that tumor grade was the most important histopathological factor for EEC and adenocarcinoma prognosis. CONCLUSION: Seven independent prognostic variables for the OS of patients with EEC and adenocarcinoma were identified. The established OS nomogram has good predictive ability and clinical utility and validates the 2023 endometrial cancer FIGO staging system.
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Adenocarcinoma , Carcinoma Endometrioide , Neoplasias Endometriales , Estadificación de Neoplasias , Nomogramas , Programa de VERF , Humanos , Femenino , Neoplasias Endometriales/patología , Neoplasias Endometriales/mortalidad , Persona de Mediana Edad , Carcinoma Endometrioide/patología , Carcinoma Endometrioide/mortalidad , Adenocarcinoma/patología , Adenocarcinoma/mortalidad , Anciano , Pronóstico , Curva ROC , Clasificación del Tumor , Adulto , Estimación de Kaplan-MeierRESUMEN
Perovskite nanocrystals (PNCs) offer unique advantages in large-area and thick-film deposition for X-ray detection applications due to the decoupling of the crystallization of perovskite from film formation, as well as their low-temperature and scalable deposition methods. However, the partial detachment of long-chain ligands in PNCs during the purification process would lead to the exposure of surface defects, making it challenging to ensure efficient charge carrier extraction and stable X-ray detection. In this study, we propose a beneficial strategy that involves the in situ reparation of these exposed defects with sodium bromide (NaBr) during the purification process to construct CsPbBr3 PNC-organic bulk heterostructure X-ray detectors. The NaBr-passivated PNCs exhibit stronger photoluminescence intensity and lower trap density in films compared to those of the control samples, confirming the effective passivation of halide vacancy defects. Furthermore, the NiOx hole transport layer with remarkable electron blocking capability is introduced to further suppress the dark current of the devices. Consequently, the optimal devices exhibit a large sensitivity of 4237 µC Gyair-1 cm-2 and a low dark current density of 10 nA cm-2, as well as improved operational stability, which allows for high-contrast and low-dose X-ray imaging applications.
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The establishment of rapid target analysis methods for cytokeratin fragment antigen 21-1 (CYFRA 21-1) is urgently needed. [Ir(pbi)2(acac)] (pbi = 2-(4-bromophenyl)-1-hydrogen -benzimidazole, acac = acetylacetonate) as traditional electrochemiluminescence (ECL) luminophores has been confined due to its non-negligible dark toxicity and poor water solubility leading to poor biocompatibility and electrical conductivity as an organic molecule. Hence, to overcome this limitation, [Ir(pbi)2(acac)] can be effectively loaded on the polyvinyl alcohol hydrogel modified Ti3C2Tx MXene surface (Ir@Ti3C2Tx-PVA) as sensing platform which can emit high ECL signals. Then, a quenching strategy was proposed to fabricate an ECL sandwich immunosensor using H2O2 as quencher molecules which can generated by Pd@Au0.85Pd0.15. Especially, the generation of O2 to H2O2 can be achieved through a two-electron (2e-) reaction pathway by Pd@Au0.85Pd0.15, to overcome the restriction that the H2O2 was virtually impossible to label or immobilize on the non-enzyme nanomaterials. The proposed ECL assay achieves a response to CYFRA 21-1 within the range of 0.1 pg/mL-100 ng/mL, with a detection limit of 8.9 fg/mL (S/N = 3). This work provided a feasible tactic to seek superior-performance ECL luminophore and quencher consequently set up a novel means to makeup ultrasensitive ECL biosensor, which extended the utilization potential of Ir(pbi)2(acac) in ECL assays.
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Técnicas Biosensibles , Técnicas Electroquímicas , Oro , Peróxido de Hidrógeno , Queratina-19 , Mediciones Luminiscentes , Paladio , Alcohol Polivinílico , Peróxido de Hidrógeno/química , Peróxido de Hidrógeno/análisis , Técnicas Electroquímicas/métodos , Paladio/química , Catálisis , Técnicas Biosensibles/métodos , Alcohol Polivinílico/química , Oro/química , Humanos , Mediciones Luminiscentes/métodos , Queratina-19/análisis , Inmunoensayo/métodos , Antígenos de Neoplasias/análisis , Antígenos de Neoplasias/inmunología , Titanio/química , Límite de Detección , Iridio/química , Nanopartículas del Metal/químicaRESUMEN
Metal halide perovskites exhibit substantial potential for advancing next-generation x-ray detection. However, fabricating high-performance pixelated imaging arrays remains challenging due to the substantial dark current density and stability issues associated with common organic-inorganic hybrid perovskites. Here, we develop a vapor deposition method to create the first all-inorganic perovskite heterojunction film. The heterojunction introduction effectively reduces the dark current density of detectors to about 0.8 nA·cm-2, satisfying thin-film transistor (TFT) integration standards, while also increases sensitivity to above 2.6 × 104 µC·Gyair-1·cm-2, thus giving rise to a record low detection limit of <1 nGyair·s-1 among all polycrystalline perovskite-based x-ray detectors. The devices also demonstrate remarkable stability across multifarious demanding working conditions. Last, through monolithic integration of the heterojunction film with a 64 × 64 pixelated TFT array, we have achieved high-resolution real-time x-ray imaging, which paves the way for the application of all-inorganic perovskite in low-dose flat-panel x-ray detection.
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Background: Chloride channel-3 (CLCN3), a crucial component of the voltage-gated chloride channel family, is implicated in numerous physiological and pathophysiological processes. This study aimed to investigate the characteristics of CLCN3 in pancancer and its influence on the immune response through the use of a range of databases. Concurrently, we assessed the impact of CLCN3 on the proliferation of ovarian cancer (OC) cells and explored its potential mechanisms. Methods: We employed the Tumor Immune Estimation Resource (TIMER) 2.0 and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases to examine the messenger RNA (mRNA) and the protein expression of CLCN3 across various cancers. The prognostic significance of CLCN3 was evaluated using the Gene Expression Profiling Interactive Analysis 2.0 (GEPIA 2.0) database. The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) facilitated the analysis of CLCN3 promoter methylation levels. The association between CLCN3 expression and tumor-infiltrating immune cells was investigated using various algorithms. The cBioportal database facilitated the analysis of CLCN3 mutations and mutation sites across various cancers. The Tumor-Immune System Interactions Database (TISIDB) database was employed to explore the correlation between CLCN3 expression and immune or molecular subtypes across a variety of cancer types. We collected ovarian tissue samples, encompassing both normal ovarian and OC tissues. The human OC cell lines, SKOV3 cells and OVCAR433 cells, were cultured. CLCN3 expression was determined via reverse-transcription quantitative polymerase chain reaction (RT-qPCR), while phosphatidylinositol 3-kinase/Akt kinase (PI3K/AKT) expression was detected using Western blot. We utilized small interfering RNA (siRNA) technology to suppress CLCN3 expression. The proliferative capacity of SKOV3 and OVCAR433 cells was assessed using the Cell Counting Kit 8 (CCK-8) assay. Results: CLCN3 demonstrated an aberrant expression in a number of cancer types and was markedly reduced in OC tissues. Poor prognosis in cervical squamous cell cancer and myeloid leukemia was linked to excessive expression of CLCN3. The examination of immune cell infiltration, which included CD8+ T cells, B cells, T regulatory cells, and cancer-associated fibroblast cells, showed a strong association with aberrant CLCN3 expression. Following the use of siRNA technology, the ability of the ovarian carcinoma cell line SKOV3 and OVCAR433 to proliferate as well as the expression of PI3K/AKT both increased. Conclusions: CLCN3 is a possible biomarker for immune-related processes and the prognosis of cancer, and the PI3K/AKT signaling pathway may affect OC cells' ability to proliferate.
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Acoustohydrodynamic micromixers offer excellent mixing efficiency, cost-effectiveness, and flexible controllability compared with conventional micromixers. There are two mechanisms in acoustic micromixers: indirect influence by induced streamlines, exemplified by sharp-edge micromixers, and direct influence by acoustic waves, represented by surface acoustic wave micromixers. The former utilizes sharp-edge structures, while the latter employs acoustic wave action to affect both the fluid and its particles. However, traditional micromixers with acoustic bubbles achieve significant mixing performance and numerous programmable mixing platforms provide excellent solutions with wide applicability. This review offers a comprehensive overview of various micromixers, elucidates their underlying principles, and explores their biomedical applications. In addition, advanced programmable micromixing with impressive versatility, convenience, and ability of cross-scale operations is introduced in detail. We believe this review will benefit the researchers in the biomedical field to know the micromixers and find a suitable micromixing method for their various applications.
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Auxin regulates plant growth and development through downstream signaling pathways, including the best-known SCFTIR1/AFB-Aux/IAA-ARF pathway and several other less characterized "noncanonical" pathways. Recently, one SCFTIR1/AFB-independent noncanonical pathway, mediated by Transmembrane Kinase 1 (TMK1), was discovered through the analyses of its functions in Arabidopsis apical hook development. Asymmetric accumulation of auxin on the concave side of the apical hook triggers DAR1-catalyzed release of the C-terminal of TMK1, which migrates into the nucleus, where it phosphorylates and stabilizes IAA32/34 to inhibit cell elongation, which is essential for full apical hook formation. However, the molecular factors mediating IAA32/34 degradation have not been identified. Here, we show that proteins in the CYTOKININ INDUCED ROOT WAVING 1 (CKRW1)/WAVY GROWTH 3 (WAV3) subfamily act as E3 ubiquitin ligases to target IAA32/34 for ubiquitination and degradation, which is inhibited by TMK1c-mediated phosphorylation. This antagonistic interaction between TMK1c and CKRW1/WAV3 subfamily E3 ubiquitin ligases regulates IAA32/34 levels to control differential cell elongation along opposite sides of the apical hook.
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Proteínas de Arabidopsis , Arabidopsis , Proteínas F-Box , Ubiquitina-Proteína Ligasas/genética , Ubiquitina-Proteína Ligasas/metabolismo , Proteínas de Arabidopsis/genética , Proteínas de Arabidopsis/metabolismo , Arabidopsis/metabolismo , Ácidos Indolacéticos/metabolismo , Transducción de Señal , Ubiquitinas/metabolismo , Regulación de la Expresión Génica de las Plantas , Proteínas F-Box/genética , Proteínas F-Box/metabolismoRESUMEN
The sodium (Na) metal anode encounters issues such as volume expansion and dendrite growth during cycling. Herein, a novel three-dimensional flexible composite Na metal anode was constructed through the conversion-alloying reaction between Na and ultrafine Sb2S3 nanoparticles encapsulated within the electrospun carbon nanofibers (Sb2S3@CNFs). The formed sodiophilic Na3Sb sites and the high Na+-conducting Na2S matrix, coupled with CNFs, establish a spatially confined "sodiophilic-conductive" network, which effectively reduces the Na nucleation barrier, improves the Na+ diffusion kinetics, and suppresses the volume expansion, thereby inhibiting the Na dendrite growth. Consequently, the Na/Sb2S3@CNFs electrode exhibits a high Coulombic efficiency (99.94%), exceptional lifespan (up to 2800 h) at high current densities (up to 5 mA cm-2), and high areal capacities (up to 5 mAh cm-2) in symmetric cells. The coin-type full cells assembled with a Na3V2(PO4)3/C cathode demonstrate significant enhancement in electrochemical performance. The flexible pouch cell achieves an excellent energy density of 301 Wh kg-1.
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Background: The COVID-19 pandemic has presented unique challenges to individuals worldwide, with a significant focus on the impact on sleep. However, the precise mechanisms through which emotional and cognitive variables mediate this relationship remain unclear. To expand our comprehensive understanding of variables, the present study utilizes the Preventive Stress Management theory, to test the relationship between perceived social support and sleep quality, as well as the effect of perceived COVID-19 stress, hope, negative emotions and coping styles. Methods: Data were collected in March 2022 from 1,034 college students in two universities located in Liaoning Province, China, using an online survey platform regarding perceived social support, perceived COVID-19 stress, sleep quality, hope, negative emotions and coping styles. The moderated mediation model were conducted using Process macro program (Model 6) and the syntax in SPSS. Results: The results revealed perceived COVID-19 stress and negative emotions sequentially mediated the negative relationship between perceived social support and sleep quality. Furthermore, hope and coping styles were found to moderate the sequential mediating effect. Conclusion: The present study sheds light on the pathways that affect sleep quality among college students during the COVID-19 pandemic. Findings highlight the protective roles played by positive social and personal resources, such as perceived social support, hope, and effective coping styles, against sleep problems. These insights have important implications for the development of targeted interventions to improve sleep outcomes during this challenging time.
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COVID-19 , Pandemias , Calidad del Sueño , Estrés Psicológico , COVID-19/epidemiología , Estrés Psicológico/prevención & control , Estrés Psicológico/psicología , Humanos , Masculino , Femenino , Adolescente , Adulto Joven , Adulto , Apoyo Social , Habilidades de Afrontamiento , Esperanza , Emociones , China/epidemiología , Universidades , Encuestas y Cuestionarios , Internet , Análisis de Mediación , Estudiantes/psicología , Análisis de Regresión , PercepciónRESUMEN
New particle formation and growth greatly influence air quality and the global climate. Recent CERN Cosmics Leaving OUtdoor Droplets (CLOUD) chamber experiments proposed that in cold urban atmospheres with highly supersaturated HNO3 and NH3, newly formed sub-10 nm nanoparticles can grow rapidly (up to 1000 nm h-1). Here, we present direct observational evidence that in winter Beijing with persistent highly supersaturated HNO3 and NH3, nitrate contributed less than â¼14% of the 8-40 nm nanoparticle composition, and overall growth rates were only â¼0.8-5 nm h-1. To explain the observed growth rates and particulate nitrate fraction, the effective mass accommodation coefficient of HNO3 (αHNO3) on the nanoparticles in urban Beijing needs to be 2-4 orders of magnitude lower than those in the CLOUD chamber. We propose that the inefficient uptake of HNO3 on nanoparticles is mainly due to the much higher particulate organic fraction and lower relative humidity in urban Beijing. To quantitatively reproduce the observed growth, we show that an inhomogeneous "inorganic core-organic shell" nanoparticle morphology might exist for nanoparticles in Beijing. This study emphasized that growth for nanoparticles down to sub-10 nm was largely influenced by their composition, which was previously ignored and should be considered in future studies on nanoparticle growth.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Material Particulado/análisis , Nitratos , Monitoreo del Ambiente , Contaminación del Aire/análisis , Compuestos Orgánicos , Tamaño de la PartículaRESUMEN
Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015-18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming's Greater Sage-Grouse (Centrocercus urophasianus) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ (p <0.05) between the conservation areas compared to only six and seven indicators for the individual surveys. Overall, we found composite estimation to be an efficient and useful option for improving environmental monitoring information where two surveys entirely overlap and suggest how this estimation method could be beneficial where environmental surveys partially overlap and in small area applications.