Principles and research progress of physical prevention and control technologies for algae in eutrophic water.

The abnormal reproduction of algae in water worldwide is prominent in the context of human interference and global climate change. This study first thoroughly analyzed the effects of physical factors, such as light, temperature, hydrodynamics, and operational strategies, on algal growth and their mechanisms. Physical control techniques are safe and have great potential for preventing abnormal algal blooms in the absence of chemical reagents. The focus was on the principles and possible engineering applications of physical shading, ultrasound, micro-current, and ultraviolet (UV) technologies, in controlling abnormal algal reproduction. Physical shading can inhibit or weaken photosynthesis in algae, thereby inhibiting their growth. Ultrasound mainly affects the physiological and biochemical activities of cells by destroying the cell walls, air cells, and active enzymes. Micro-currents destroy the algal cell structure through direct and indirect oxidation, leading to algal cell death. UV irradiation can damage DNA, causing organisms to be unable to reproduce or algal cells to die directly. This article comprehensively summarizes and analyzes the advantages of physical prevention and control technologies for the abnormal reproduction of algae, providing a scientific basis for future research. In the future, attempts will be made toward appropriately and comprehensively utilizing various physical technologies to control algal blooms. The establishment of an intelligent, comprehensive physical prevention and control system to achieve environmentally friendly, economical, and effective physical prevention and control of algae, such as the South-to-North Water Diversion Project in China, is of great importance for specific waters.

High sensitivity distributed dynamic pressure sensor based on dual-linear frequency modulated optical frequency domain reflectometry.

In this Letter, we propose and experimentally demonstrate a highly sensitive distributed dynamic pressure sensor based on a dual-linear frequency modulated optical frequency domain reflectometry (OFDR) and a coating thickness-enhanced single-mode fiber (SMF). A dual-sideband linear frequency modulation (LFM) signal is used to interrogate the sensing fiber, which allows us to obtain a dual-sideband Rayleigh backscattering signal. Due to the opposite slopes of the two LFM sidebands, the Rayleigh backscattering spectra of the two sidebands drift in opposite directions when the fiber is disturbed. By subtracting the frequency shifts of the two spectra, we can double the system's sensitivity. We further enhance the sensitivity by using an SMF with a coating thickness of 200 µm. This results in a pressure sensitivity of 3979 MHz/MPa, a measurement accuracy of 0.76 kPa, and a spatial resolution of 35 cm over a 500 m optical fiber. Our system successfully detected a dynamic pressure change at a sampling rate of 1.25 kHz, demonstrating the sensor's excellent dynamic measuring capabilities.

Optimized strategies of cloud droplet distribution retrieval using satellite multi-directional polarimetric optical measurements: information content approach.

Multi-directional polarized optical sensors are increasingly vital in passive remote sensing, deepening our understanding of global cloud properties. Nevertheless, uncertainty lingers on how these observations can contribute to our knowledge of cloud diversity. The variability in cloud PSD (Particle Size Distribution) significantly influences a wide array of cloud characteristics, while unidentified factors in RT (Radiative Transfer) may introduce errors into the cloud PSD retrieval algorithm. Therefore, establishing unified evaluation criteria for both optical device configuration and inversion methods is crucial. Our study, based on Bayesian theory and RT, assesses the information content of both cloud effective radius and effective variance retrieval, along with the key factors affecting their retrieval in multi-directional polarized observations, using the calculation of DFS (Degree of Freedom for Signals).We consider the process of solar incidence, cloud scattering, and sensor reception, and discuss the impact of various sensor configurations, cloud characteristics, and other components on the retrieval of cloud PSD. Correspondingly, we observed a 48% improvement in the information content of cloud PSD with the incorporation of multi-directional polarized measurements in the rainbow region. Cloud droplet concentration significantly influences inversion, but its PSD does not cause monotonic linear interference on information content. The blending of particle mixtures with different PSD has a significant negative impact on DFS. In cases where the AOD (Aerosol Optical Depth) is less than 0.5 and the COT (Cloud Optical Thickness) exceeds 5, the influence of aerosol and surface contributions on inversion can be neglected. Our findings would serve as a foundation for future instrument design improvements and enhancements to retrieval algorithms.

Adaptive temporal compression for reduction of computational complexity in human behavior recognition.

The research on video analytics especially in the area of human behavior recognition has become increasingly popular recently. It is widely applied in virtual reality, video surveillance, and video retrieval. With the advancement of deep learning algorithms and computer hardware, the conventional two-dimensional convolution technique for training video models has been replaced by three-dimensional convolution, which enables the extraction of spatio-temporal features. Specifically, the use of 3D convolution in human behavior recognition has been the subject of growing interest. However, the increased dimensionality has led to challenges such as the dramatic increase in the number of parameters, increased time complexity, and a strong dependence on GPUs for effective spatio-temporal feature extraction. The training speed can be considerably slow without the support of powerful GPU hardware. To address these issues, this study proposes an Adaptive Time Compression (ATC) module. Functioning as an independent component, ATC can be seamlessly integrated into existing architectures and achieves data compression by eliminating redundant frames within video data. The ATC module effectively reduces GPU computing load and time complexity with negligible loss of accuracy, thereby facilitating real-time human behavior recognition.

Comprehensive analysis of disulfidptosis-related lncRNAs for predicting prognosis and response of immunotherapy in pancreatic adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is a common and deadly tumor. Currently, there is a severe lack of therapeutic options. As a novel mode of cell death, increasing evidence reveals the important role of the disulfidptosis in cancer. However, few studies have utilized disulfidptosis-related long-stranded non-coding RNAs (DRlncRNAs) to investigate the prognosis of PAAD. Methods: We comprehensively analyzed the expression and prognostic value of 958 DRlncRNAs in PAAD using data from The Cancer Genome Atlas (TCGA). We established and validated a new DRlncRNAs-related prognostic index by least absolute shrinkage and selection operator (LASSO) and COX regression analysis. In addition, we built a nomogram consisting of risk score, age, gender, tumor grade and stage to validate the clinical feasibility of the index. We further evaluated the value of the index in terms of PAAD functional pathways, tumor microenvironment (TME) and tumor mutations. Results: We designed a risk model for five DRlncRNAs and demonstrated its accuracy using receiver operating characteristic (ROC) curves. COX regression suggested that the model may be an independent predictor of cancer prognosis. Tumor immune infiltration analysis revealed that low-risk subgroups had higher extent of immune infiltration, higher sensitivity to immunotherapy and a higher TME score. This is helpful for us to discover more precise immunotherapy for PAAD patients. Conclusions: In conclusion, we established a DRlncRNA index comprising of five DRlncRNAs, which may provide new insights for clinical diagnosis and precision therapy.

Characteristics of DOM and Their Relationships with Potentially Toxic Elements in the Inner Mongolia Section of the Yellow River, China.

The characterization of dissolved organic matter (DOM) is important for better understanding of the migration and transformation mechanisms of DOM in water bodies and its interaction with other contaminants. In this work, fluorescence characteristics and molecular compositions of the DOM samples collected from the mainstream, tributary, and sewage outfall of the Inner Mongolia section of the Yellow River (IMYR) were determined by using fluorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). In addition, concentrations of potentially toxic elements (PTEs) in the relevant surface water and their potential relationships with DOM were investigated. The results showed that the abundance of tyrosine-like components increased significantly in downstream waters impacted by outfall effluents and was negatively correlated with the humification index (HIX). Compared to the mainstream, outfall and tributaries have a high number of molecular formulas and a higher proportion of CHOS molecular formulas. In particular, the O5S class has a relative intensity of 41.6% and the O5-7S class has more than 70%. Thirty-eight PTEs were measured in the surface water samples, and 12 found above their detective levels at all sampling sites. Protein-like components are positively correlated with Cu, which is likely indicating the source of Cu in the aquatic environment of the IMYR. Our results demonstrated that urban wastewater discharges significantly alter characteristics and compositions of DOM in the mainstream of IMYR with strongly anthropogenic features. These results and conclusions are important for understanding the role and sources of DOM in the Yellow River aquatic environment.

Biosynthesis of mannose from glucose via constructing phosphorylation-dephosphorylation reactions in Escherichia coli.

d-mannose has been widely used in food, medicine, cosmetic, and food-additive industries. To date, chemical synthesis or enzymatic conversion approaches based on iso/epimerization reactions for d-mannose production suffered from low conversion rate due to the reaction equilibrium, necessitating intricate separation processes for obtaining pure products on an industrial scale. To circumvent this challenge, this study showcased a new approach for d-mannose synthesis from glucose through constructing a phosphorylation-dephosphorylation pathway in an engineered strain. Specifically, the gene encoding phosphofructokinase (PfkA) in glycolytic pathway was deleted in Escherichia coli to accumulate fructose-6-phosphate (F6P). Additionally, one endogenous phosphatase, YniC, with high specificity to mannose-6-phosphate, was identified. In ΔpfkA strain, a recombinant synthetic pathway based on mannose-6-phosphate isomerase and YniC was developed to direct F6P to mannose. The resulting strain successfully produced 25.2 g/L mannose from glucose with a high conversion rate of 63% after transformation for 48 h. This performance surpassed the 15% conversion rate observed with 2-epimerases. In conclusion, this study presents an efficient method for achieving high-yield mannose synthesis from cost-effective glucose.

The causal relationship between autoimmune thyroid disorders and telomere length: A Mendelian randomization and colocalization study.

This study aimed to evaluate whether there is a causal relationship between autoimmune thyroid disorders (AITDs) and telomere length (TL) in the European population and whether there is reverse causality. In this study, Mendelian randomization (MR) and colocalization analysis were conducted to assess the potential causal relationship between AITDs and TL using summary statistics from large-scale genome-wide association studies, followed by analysis of the relationship between TL and thyroid stimulating hormone and free thyroxine (FT4) to help interpret the findings. The inverse variance weighted (IVW) method was used to estimate the causal estimates. The weighted median, MR-Egger and leave-one-out methods were used as sensitivity analyses. The IVW method results showed a significant causal relationship between autoimmune hyperthyroidism and TL (ß = -1.93 × 10-2 ; p = 4.54 × 10-5 ). There was no causal relationship between autoimmune hypothyroidism and TL (ß = -3.99 × 10-3 ; p = 0.324). The results of the reverse MR analysis showed that genetically TL had a significant causal relationship on autoimmune hyperthyroidism (IVW: odds ratio (OR) = 0.49; p = 2.83 × 10-4 ) and autoimmune hypothyroidism (IVW: OR = 0.86; p = 7.46 × 10-3 ). Both horizontal pleiotropy and heterogeneity tests indicated the validity of our bidirectional MR study. Finally, colocalization analysis suggested that there were shared causal variants between autoimmune hyperthyroidism and TL, further highlighting the robustness of the results. In conclusion, autoimmune hyperthyroidism may accelerate telomere attrition, and telomere attrition is a causal factor for AITDs.

Research progress of the inferior colliculus: from Neuron, neural circuit to auditory disease.

The auditory midbrain, also known as the inferior colliculus (IC), serves as a crucial hub in the auditory pathway. Comprising diverse cell types, the IC plays a pivotal role in various auditory functions, including sound localization, auditory plasticity, sound detection, and sound-induced behaviors. Notably, the IC is implicated in several auditory central disorders, such as tinnitus, age-related hearing loss, autism and Fragile X syndrome. Accurate classification of IC neurons is vital for comprehending both normal and dysfunctional aspects of IC function. Various parameters, including dendritic morphology, neurotransmitter synthesis, potassium currents, biomarkers, and axonal targets, have been employed to identify distinct neuron types within the IC. However, the challenge persists in effectively classifying IC neurons into functional categories due to the limited clustering capabilities of most parameters. Recent studies utilizing advanced neuroscience technologies have begun to shed light on biomarker-based approaches in the IC, providing insights into specific cellular properties and offering a potential avenue for understanding IC functions. This review focuses on recent advancements in IC research, spanning from neurons and neural circuits to aspects related to auditory diseases.

Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.

OBJECTIVE: The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas. METHODS: Grade II/III glioma patients diagnosed at the Tangdu Hospital (August 2009 to May 2017) were retrospectively enrolled, including 54 patients with IDH1 mutant and 56 patients with wild-type IDH1 . Convolutional neural networks, AlexNet, GoogLeNet, ResNet, and VGGNet were fine-tuned with T2-weighted imaging (T2WI), fluid attenuation inversion recovery (FLAIR), and contrast-enhanced T1-weighted imaging (T1CE) images. The single-modal networks were integrated with averaged sigmoid probabilities, logistic regression, and support vector machine. FLAIR-T1CE-fusion (FC-fusion), T2WI-T1CE-fusion (TC-fusion), and FLAIR-T2WI-T1CE-fusion (FTC-fusion) were used for fine-tuning TL-CNNs. RESULTS: IDH1 -mutant prediction accuracies using AlexNet, GoogLeNet, ResNet, and VGGNet achieved 70.0% (AUC = 0.660), 65.0% (AUC = 0.600), 70.0% (AUC = 0.700), and 80.0% (AUC = 0.730) for T2WI images, 70.0% (AUC = 0.660), 70.0% (AUC = 0.620), 70.0% (AUC = 0.710), and 80.0% (AUC = 0.720) for FLAIR images, and 73.7% (AUC = 0.744), 73.7% (AUC = 0.656), 73.7% (AUC = 0.633), and 73.7% (AUC = 0.700) for T1CE images, respectively. The highest AUC (0.800) was achieved using VGGNet and FC-fusion images. CONCLUSIONS: TL-CNNs (especially VGGNet) had a potential predictive value for IDH1 -mutant status of grade II/III gliomas.

Intraocular Lens Power Calculation in Eyes After Myopic Laser Refractive Surgery and Radial Keratotomy: Bayesian Network Meta-analysis.

PURPOSE: To compare the accuracy of formulas for calculating intraocular lens power in eyes after myopic laser refractive surgery or radial keratotomy. DESIGN: Bayesian network meta-analysis. METHODS: PubMed, Embase, the Cochrane Data Base of Systematic Reviews, and the Cochrane Central Register of Controlled Trials databases were searched for retrospective and prospective clinical studies published from January 1, 2012, to August 24, 2022. The outcome measurement was the percentage of eyes with a predicted error within the target refractive range (±0.50 diopter [D] or ±1.00 D). RESULTS: Our meta-analysis includes 24 studies of 1172 eyes after myopic refractive surgery that use 12 formulas for intraocular lens power calculation. (1) A network meta-analysis showed that Barrett true-K no history, the optical coherence tomography (OCT) formula, and the Masket formula had a significantly higher percent of eyes within ±0.50 D of the goal than the Haigis-L formula, whereas the Wang-Koch-Maloney formula showed the poor predictability. Using an error criterion of within ±1.00 D, the same 3 formulas performed slightly better than the Haigis-L formula. Based on performance using both prediction error criteria, the Barrett true-K no history formula, OCT formula, and Masket formula showed the highest probability of ranking as the top 3 among the 12 methods. (2) A direct meta-analysis with a subset of 4 studies and 5 formulas indicated that formulas did not differ in percent success for either the ±0.5 D or ±1.0 D error range in eyes that had undergone radial keratotomy. CONCLUSIONS: The OCT, Masket, and Barrett true-K no history formulas are more accurate for eyes with previous myopic laser refractive surgery, whereas no significant difference was found among the formulas for eyes that had undergone radial keratotomy.

Experimental Investigation of Electrochemical Capacitive Responses versus Pore Geometries through Artificial Nanotubes.

Electrochemical supercapacitors have attracted significant attention due to their large capacity, high-power output, and long cycle life. However, despite extensive studies and advancements in developing highly porous electrode materials, little quantitative research on the impact of pore geometry on electrochemical responses has been conducted. This paper presents the first quantitative investigation of the relationship between electrochemical capacitive responses and pore geometries at the nanoscale. To achieve this, we constructed a uniform cylindrical pore array with controllable pore diameter and depth by using anodized aluminum oxide (AAO) to serve as a template and atomic layer deposition (ALD) technology for TiN conductive layer decoration. Our findings reveal that, at the nanoscale, increasing the specific surface area through pore diameter and depth does not proportionally increase the capacitive response, even at low scan rates. Meanwhile, we observe a critical pore parameter (170/5000 nm, diameter/depth), where the specific capacitance density and characteristic frequency dramatically decrease with a further increase in the pore aspect ratio. These results indicate that blindly pursuing the absolute specific surface area of the electrode material is not advisable. Instead, optimal pore geometry should be designed based on the desired operational conditions, and this work may serve as valuable guidance.

Utilization of broken rock in shallow gobs for mitigating mining-induced water inrush disaster risks and environmental damage: Experimental study and permeability model.

Coal mining-induced groundwater losses may trigger water inrush disasters and surface ecological degradation. The compaction and seepage characteristics of broken rock in gobs can be used to find the balance point of water inrush prevention and water resource protection in shallow coal seam groups. These characteristics, as well as geological and engineering parameters of shallow coal seam mining, are experimentally determined in this study. The performed permeability tests revealed that the percentage of voids in broken rock exponentially decreased with the axial stress. The water seepage of broken rock in the compaction process conformed to the Forchheimer theory, with the permeability ranging from 10-1 to 10 D. The initial value and reduction range of mudstone permeability in the three lithologic samples were the smallest. The uniaxial compression strength reduction caused by the increase in unit mass water due to water saturation of natural rock samples were 5.8 and 3.2 % for coal and sandstone, respectively. Based on the experimental results on compaction and seepage of broken rock, the axial stress-percentage of voids-permeability model considering compaction and re-crushing was established. The mudstone roof was found to be the key rock stratum during re-mining for ecological protection and hydraulic connection evaluation of the overburden.

De novo artificial synthesis of hexoses from carbon dioxide.

Developing artificial "CO2-sugar" platforms is meaningful for addressing challenges posed by land scarcity and climate change to the supply of dietary sugar. However, upcycling CO2 into complex polyoxygenated carbohydrates involves several major challenges, including achieving enantioselective and thermodynamically driven transformation and expanding product repertoires while reducing energy consumption. We present a versatile chemoenzymatic roadmap based on aldol condensation, iso/epimerization, and dephosphorylation reactions for asymmetric CO2 and H2 assembly into sugars with perfect stereocontrol. In particular, we developed a minimum ATP consumption and the shortest pathway for bottom-up biosynthesis of the fundamental precursor, fructose-6-phosphate, which is valuable for synthesizing structure-diverse sugars and derivatives. Engineering bottleneck-associated enzyme catalysts aided in the thermodynamically driven synthesis of several energy-dense and functional hexoses, such as glucose and D-allulose, featuring higher titer (63 mmol L-1) and CO2-product conversion rates (25 mmol C L-1 h-1) compared to established in vitro CO2-fixing pathways. This chemical-biological platform demonstrated greater carbon conversion yield than the conventional "CO2-bioresource-sugar" process and could be easily extended to precisely synthesize other high-order sugars from CO2.

Artificial Intelligence and Machine (Deep) Learning in Otorhinolaryngology: A Bibliometric Analysis Based on VOSviewer and CiteSpace.

BACKGROUND: Otorhinolaryngology diseases are well suited for artificial intelligence (AI)-based interpretation. The use of AI, particularly AI based on deep learning (DL), in the treatment of human diseases is becoming more and more popular. However, there are few bibliometric analyses that have systematically studied this field. OBJECTIVE: The objective of this study was to visualize the research hot spots and trends of AI and DL in ENT diseases through bibliometric analysis to help researchers understand the future development of basic and clinical research. METHODS: In all, 232 articles and reviews were retrieved from The Web of Science Core Collection. Using CiteSpace and VOSviewer software, countries, institutions, authors, references, and keywords in the field were visualized and examined. RESULTS: The majority of these papers came from 44 nations and 498 institutions, with China and the United States leading the way. Common diseases used by AI in ENT include otosclerosis, otitis media, nasal polyps, sinusitis, and so on. In the early years, research focused on the analysis of hearing and articulation disorders, and in recent years mainly on the diagnosis, localization, and grading of diseases. CONCLUSIONS: The analysis shows the periodical hot spots and development direction of AI and DL application in ENT diseases from the time dimension. The diagnosis and prognosis of otolaryngology diseases and the analysis of otolaryngology endoscopic images have been the focus of current research and the development trend of future.

Coherent OTDR with large dynamic range based on double-sideband linear frequency modulation pulse.

Rayleigh scattering-based distributed optical fiber sensors with long sensing distance and large dynamic range are highly desired for application scenarios such as vehicle tracking, structure health monitoring, and geological survey. To enlarge the dynamic range, we propose a coherent optical time domain reflectometry (COTDR) based on double-sideband linear frequency modulation (LFM) pulse. By utilizing I/Q demodulation, both the positive and negative frequency band of the Rayleigh backscattering (RBS) signal can be properly demodulated. Consequently, the dynamic range is doubled without increasing the bandwidth of signal generator, photodetector (PD), and oscilloscope. In the experiment, the chirped pulse with 10 µs pulse width and 498 MHz frequency sweeping range is launched into the sensing fiber. Single-shot strain measurement is achieved over 5 km single-mode fiber with a spatial resolution of 2.5 m and a strain sensitivity of 7.5 pε/H z. A vibration signal with 3.09 µÎµ peak-to-peak amplitude (corresponding to 461 MHz frequency shift) is successfully measured with the double-sideband spectrum, which cannot be properly recovered with the single-sideband spectrum.

Serine-arginine splicing factor 2 promotes oesophageal cancer progression by regulating alternative splicing of interferon regulatory factor 3.

OBJECTIVE: Often, alternative splicing is used by cancer cells to produce or increase proteins that promote growth and survival through alternative splicing. Although RNA-binding proteins are known to regulate alternative splicing events associated with tumorigenesis, their role in oesophageal cancer (EC) has rarely been explored. METHODS: We analysed the expression pattern of several relatively well characterized splicing regulators on 183 samples from TCGA cohort of oesophageal cancer; the effectiveness of the knockdown of SRSF2 was subsequently verified by immunoblotting; we measured the ability of cells treated with lenti-sh-SRSF2/lenti-sh2-SRSF2 to invade through an extracellular matrix coating by transwell invasion assay; using RNA-seq data to identify its potential target genes; we performed qRT-PCR to detect the changes of exon 2 usage in lenti-sh-SRSF2 transduced KYSE30 cells to determine the possible effect of SRSF2 on splicing regulation of IRF3; RNA Electrophoretic mobility shift assay (RNA-EMSA) was performed by the incubation of purified SRSF2 protein and biotinylated RNA probes; we performed luciferase assay to confirm the effect of SRSF2 on IFN1 promoter activity. RESULTS: We found upregulation of SRSF2 is correlated with the development of EC; Knock-down of SRSF2 inhibits EC cell proliferation, migration, and invasion; SRSF2 regulates the splicing pattern of IRF3 in EC cells; SRSF2 interacts with exon 2 of IRF3 to regulate its exclusion; SRSF2 inhibits the transcription of IFN1 in EC cells. CONCLUSION: This study identified a novel regulatory axis involved in EC from the various aspects of splicing regulation.

Association Between Educational Attainment and Thyroid Function: Results From Mendelian Randomization and the NHANES Study.

CONTEXT: Many observational studies have reported on the association between educational attainment (EA) and thyroid function, but the causal relationship remains unclear. OBJECTIVE: We aimed to obtain causal effects of EA on thyroid function and to quantify the mediating effects of modifiable risk factors. METHODS: Two-sample mendelian randomization (MR) was performed by using summary statistics from large genome-wide association studies (GWAS) to assess the effect of EA on thyroid function, including hypothyroidism, hyperthyroidism, thyrotropin (TSH), and free thyroxine (FT4). A multivariable analysis was conducted to assess the mediating role of smoking and help to explain the association between EA and thyroid function. Similar analysis was further performed using data from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2002. RESULTS: In MR analysis, EA was causally associated with TSH (ß = .046; 95% CI, 0.015-0.077; P = 4.00 × 10-3), rather than hypothyroidism, hyperthyroidism, and FT4. Importantly, smoking could serve as a mediator in the association between EA and TSH, in which the mediating proportion was estimated to be 10.38%. After adjusting for smoking in the multivariable MR analysis, the ß value of EA on TSH was attenuated to 0.030 (95% CI, 0.016-0.045; P = 9.32 × 10-3). Multivariable logistic regression model in NHANES suggested a dose-response relationship between TSH (quartile [Q]4 vs Q1: odds ratio = 1.33; 95% CI, 1.05-1.68; P for trend = .023) and EA. Smoking, systolic blood pressure, and body mass index partially mediated the association between EA and TSH, with the proportion of the mediation effects being 43.82%, 12.28%, and 6.81%, respectively. CONCLUSION: There is a potentially causal association between EA and TSH, which could be mediated by several risk factors, such as smoking.

Nodular Fasciitis of the Nose and External Auditory Canal: Two Rare Case Reports.

Nodular fasciitis(NF) is a proliferative disease of fibroblasts and myofibroblasts that generally affects subcutaneous tissue, muscle tissue, and fascia. NF usually occurs in young adults aged 20-40 and is more common in the upper extremities and relatively rare in the region of the head and neck. Here, we report on two patients with NF in the ear and nose. Under general anesthesia, the masses of NF were completely resected along the safety margin. The patients recovered well after surgery and there was no recurrence after more than half a year of follow-up.