Dynamic temperature control in microfluidics for in vivo imaging of cold-sensing in C. elegans.

The ability to perceive temperature is crucial for most animals. It enables them to maintain their body temperature and swiftly react to noxiously cold or hot objects. Caenorhabditis elegans is a powerful genetic model for the study of thermosensation as its simple nervous system is well characterized and its transparent body is suited for in vivo functional imaging of neurons. The behavior triggered by experience-dependent thermosensation has been well studied in C. elegans under temperature-gradient environments. However, how C. elegans senses temperature via its nervous system is not well understood due to the limitations of currently available technologies. One major bottleneck is the difficulty in creating fast temperature changes, especially cold stimuli. Here, we developed a microfluidic-based platform that allowed the in vivo functional imaging of C. elegans responding to well-controlled temporally varying temperature stimulation by rapidly switching fluid streams at different temperatures. We used computational models to enable rational design and optimization of experimental conditions. We validated the design and utility of our system with studies of the functional role of thermosensory neurons. We showed that the responses of PVD polymodal nociceptor neurons observed in previous studies can be recapitulated. Further, we highlighted how this platform may be used to dissect neuronal circuits with an example of activity recording in PVC interneurons. Both of these neuron types show sensitization phenotypes. We envision that both the engineered system and the findings in this work will spur further studies of molecular and cellular mechanisms underlying cold-sensing through the nervous system.

High-throughput screening of small-molecules libraries identified antibacterials against clinically relevant multidrug-resistant A. baumannii and K. pneumoniae.

BACKGROUND: The current pipeline for new antibiotics fails to fully address the significant threat posed by drug-resistant Gram-negative bacteria that have been identified by the World Health Organization (WHO) as a global health priority. New antibacterials acting through novel mechanisms of action are urgently needed. We aimed to identify new chemical entities (NCEs) with activity against Klebsiella pneumoniae and Acinetobacter baumannii that could be developed into a new treatment for drug-resistant infections. METHODS: We developed a high-throughput phenotypic screen and selection cascade for generation of hit compounds active against multidrug-resistant (MDR) strains of K. pneumoniae and A. baumannii. We screened compound libraries selected from the proprietary collections of three pharmaceutical companies that had exited antibacterial drug discovery but continued to accumulate new compounds to their collection. Compounds from two out of three libraries were selected using "eNTRy rules" criteria associated with increased likelihood of intracellular accumulation in Escherichia coli. FINDINGS: We identified 72 compounds with confirmed activity against K. pneumoniae and/or drug-resistant A. baumannii. Two new chemical series with activity against XDR A. baumannii were identified meeting our criteria of potency (EC50 ≤50 µM) and absence of cytotoxicity (HepG2 CC50 ≥100 µM and red blood cell lysis HC50 ≥100 µM). The activity of close analogues of the two chemical series was also determined against A. baumannii clinical isolates. INTERPRETATION: This work provides proof of principle for the screening strategy developed to identify NCEs with antibacterial activity against multidrug-resistant critical priority pathogens such as K. pneumoniae and A. baumannii. The screening and hit selection cascade established here provide an excellent foundation for further screening of new compound libraries to identify high quality starting points for new antibacterial lead generation projects. FUNDING: BMBF and GARDP.

Electron beam-induced demetallation of Fe, Co, Ni, Cu, Zn, Pd, and Pt metalloporphyrins: insights in e-beam chemistry and metal cluster formations.

Electron beams are versatile tools for nanoscale fabrication processes, however, the underlying e-beam chemistry remains in its infancy. Through operando transmission electron microscopy investigations, we elucidate a redox-driven cargo release of individual metal atoms triggered by electron beams. The chosen organic delivery molecule, tetraphenylporphyrin (TPP), proves highly versatile, forming complexes with nearly all metals from the periodic table and being easily processed in solution. A comprehensive cinematographic analysis of the dynamics of single metal atoms confirms the nearly instantaneous ejection of complexed metal atoms under an 80 kV electron beam, underscoring the system's broad versatility. Providing mechanistic insights, we employ density functional theory to support the proposed reductive demetallation pathway facilitated by secondary electrons, contributing novel perspectives to electron beam-mediated chemical reaction mechanisms. Lastly, our findings demonstrate that all seven metals investigated form nanoclusters once ejected from TPP, highlighting the method's potential for studying and developing sustainable single-atom and nanocluster catalysts.

Low-input and single-cell methods for Infinium DNA methylation BeadChips.

The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection P-value calculation achieved higher sensitivities for low-input datasets and was validated in over 100 000 public diverse methylome profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.

A magnetically powered nanomachine with a DNA clutch.

Machines found in nature and human-made machines share common components, such as an engine, and an output element, such as a rotor, linked by a clutch. This clutch, as seen in biological structures such as dynein, myosin or bacterial flagellar motors, allows for temporary disengagement of the moving parts from the running engine. However, such sophistication is still challenging to achieve in artificial nanomachines. Here we present a spherical rotary nanomotor with a reversible clutch system based on precise molecular recognition of built-in DNA strands. The clutch couples and decouples the engine from the machine's rotor in response to encoded inputs such as DNA or RNA. The nanomotor comprises a porous nanocage as a spherical rotor to confine the magnetic engine particle within the nanospace (∼0.004 µm3) of the cage. Thus, the entropically driven irreversible disintegration of the magnetic engine and the spherical rotor during the disengagement process is eliminated, and an exchange of microenvironmental inputs is possible through the nanopores. Our motor is only 200 nm in size and the clutch-mediated force transmission powered by an embedded ferromagnetic nanocrystal is high enough (∼15.5 pN at 50 mT) for the in vitro mechanical activation of Notch and integrin receptors, demonstrating its potential as nano-bio machinery.

Effects of uric acid on ischemic diseases, stratified by lipid levels: a drug-target, nonlinear Mendelian randomization study.

Although uric acid-lowering agents such as xanthine oxidase inhibitors have potential cardioprotective effects, studies on their use in preventing cardiovascular diseases are lacking. We investigated the genetically proxied effects of reducing uric acid on ischemic cardiovascular diseases in a lipid-level-stratified population. We performed drug-target Mendelian randomization (MR) analyses using UK Biobank data to select genetic instruments within a uric acid-lowering gene, xanthine dehydrogenase (XDH), and construct genetic scores. For nonlinear MR analyses, individuals were stratified by lipid level. Outcomes included acute myocardial infarction (AMI), ischemic heart disease, cerebral infarction, transient cerebral ischemic attack, overall ischemic disease, and gout. We included 474,983 non-gout individuals with XDH-associated single-nucleotide polymorphisms. The XDH-variant-induced uric acid reduction was associated with reduced risk of gout (odds ratio [OR], 0.85; 95% confidence interval [CI], 0.78-0.93; P < 0.001), cerebral infarction (OR, 0.86; 95% CI, 0.75-0.98; P = 0.023), AMI (OR, 0.79; 95% CI, 0.66-0.94; P = 0.010) in individuals with triglycerides ≥ 188.00 mg/dL, and cerebral infarction in individuals with low-density lipoprotein cholesterol (LDL-C) ≤ 112.30 mg/dL (OR, 0.76; 95% CI, 0.61-0.96; P = 0.020) or LDL-C of 136.90-157.40 mg/dL (OR, 0.67; 95% CI, 0.49-0.92; P = 0.012). XDH-variant-induced uric acid reduction lowers the risk of gout, AMI for individuals with high triglycerides, and cerebral infarction except for individuals with high LDL-C, highlighting the potential heterogeneity in the protective effects of xanthine oxidase inhibitors for treating AMI and cerebral infarction depending on the lipid profiles.

A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace.

BACKGROUND: Convolutional neural network-based image processing research is actively being conducted for pathology image analysis. As a convolutional neural network model requires a large amount of image data for training, active learning (AL) has been developed to produce efficient learning with a small amount of training data. However, existing studies have not specifically considered the characteristics of pathological data collected from the workplace. For various reasons, noisy patches can be selected instead of clean patches during AL, thereby reducing its efficiency. This study proposes an effective AL method for cancer pathology that works robustly on noisy datasets. METHODS: Our proposed method to develop a robust AL approach for noisy histopathology datasets consists of the following three steps: 1) training a loss prediction module, 2) collecting predicted loss values, and 3) sampling data for labeling. This proposed method calculates the amount of information in unlabeled data as predicted loss values and removes noisy data based on predicted loss values to reduce the rate at which noisy data are selected from the unlabeled dataset. We identified a suitable threshold for optimizing the efficiency of AL through sensitivity analysis. RESULTS: We compared the results obtained with the identified threshold with those of existing representative AL methods. In the final iteration, the proposed method achieved a performance of 91.7% on the noisy dataset and 92.4% on the clean dataset, resulting in a performance reduction of less than 1%. Concomitantly, the noise selection ratio averaged only 2.93% on each iteration. CONCLUSIONS: The proposed AL method showed robust performance on datasets containing noisy data by avoiding data selection in predictive loss intervals where noisy data are likely to be distributed. The proposed method contributes to medical image analysis by screening data and producing a robust and effective classification model tailored for cancer pathology image processing in the workplace.

Learning Curve for Endoscopic Transsphenoidal Surgery: A Systematic Review and Meta-Analysis.

BACKGROUND: Endoscopic transsphenoidal surgery (ETSS) is emerging as an effective, minimally invasive surgery technique for brain tumors of the pituitary fossa. Using a surgical endoscope, surgeons can obtain a broader, nearer, and more apparent visual field with minimal keyhole entrance. However, ETSS may require a steep learning curve to achieve technical competence and relevant outcomes. Moreover, there is no consensus on the learning process of ETSS. We aimed to review and determine the technical proficiency points of ETSS and discuss how to accelerate the learning curve. METHODS: Core databases, including PubMed, Embase, and the Cochrane Library, were systematically searched for learning curve studies that demonstrated the clinical outcomes and learning status of ETSS for pituitary adenomas using numerical data. Quality assessments of the included articles were performed using the Newcastle-Ottawa scale. The cutoff points were evaluated based on various outcome measures. RESULTS: Eleven full-text articles, representing 2780 cases, were selected from 317 screened studies. The outcome measures were operative time, tumor removal, endocrinological results, visual field, and surgical complications. The plateaus or cutoff points in the learning curve varied with a mean of 103 ± 139.43 (range, 9-500) cases. CONCLUSIONS: ETSS is an efficient and minimally invasive alternative surgical option for pituitary tumors. Plateau points may differ according to outcome measures, patient selection, training status, and surgical conditions. Therefore, great care should be taken when interpreting the learning curve. A systematic training program is essential to improve the learning process of endoscopic neurosurgical procedures.

Digital Health Interventions to Enhance Tuberculosis Treatment Adherence: Scoping Review.

Background: Digital health technologies are widely used for disease management, with their computing platforms, software, and sensors being used for health care. These technologies are developed to manage chronic diseases and infectious bacterial diseases, including tuberculosis (TB). Objective: This study aims to comprehensively review the literature on the use of digital health interventions (DHIs) for enhancing TB treatment adherence and identify major strategies for their adoption. Methods: We conducted a literature search in the PubMed, Cochrane Library, Ovid Embase, and Scopus databases for relevant studies published between January 2012 and March 2022. Studies that focused on web-based or mobile phone-based interventions, medication adherence, digital health, randomized controlled trials, digital interventions, or mobile health and ubiquitous health technology for TB treatment and related health outcomes were included. Results: We identified 27 relevant studies and classified them according to the intervention method, a significant difference in treatment success, and health outcomes. The following interventions were emphasized: SMS text messaging interventions (8/27, 30%), medicine reminders (6/27, 22%), and web-based direct observation therapy (9/27, 33%). Digital health technology significantly promoted disease management among individuals and health care professionals. However, only a few studies addressed 2-way communication therapies, such as interactive SMS text messaging and feedback systems. Conclusions: This scoping review classified studies on DHIs for patients with TB and demonstrated their potential for the self-management of TB. DHIs are still being developed, and evidence on the impact of digital technologies on enhancing TB treatment adherence remains limited. However, it is necessary to encourage patients' participation in TB treatment and self-management through bidirectional communication. We emphasize the importance of developing a communication system.

Low-input and single-cell methods for Infinium DNA methylation BeadChips.

The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection p -values calculation achieved higher sensitivities for low-input datasets and was validated in over 100,000 public datasets with diverse methylation profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.

Proteolysis Analysis and Sensory Evaluation of Fermented Sausages using Strains Isolated from Korean Fermented Foods.

We studied the proteolysis and conducted a sensory evaluation of fermented sausages using strains derived from Kimchi [Pediococcus pentosaceus-SMFM2021-GK1 (GK1); P. pentosaceus-SMFM2021-NK3 (NK3)], Doenjang [Debaryomyces hansenii-SMFM2021-D1 (D1)], and spontaneous fermented sausage [Penicillium nalgiovense-SMFM2021-S6 (S6)]. Fermented sausages were classified as commercial starter culture (CST), mixed with GK1, D1, and S6 (GKDS), and mixed with NK3, D1, and S6 (NKDS). The protein content and pH of GKDS and NKDS were significantly higher than those of CST on days 3 and 31, respectively (p<0.05). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed that the NKDS had higher molecular weight proteins than the GKDS and CST. The myofibrillar protein solubility of the GKDS and NKDS was significantly higher than that of the CST on day 31 (p<0.05). The GKDS displayed significantly higher pepsin and trypsin digestion than the NKDS on day 31 (p<0.05). The hardness, chewiness, gumminess, and cohesiveness of the GKDS were not significantly different from those of the CST. The GKDS exhibited the highest values for flavor, tenderness, texture, and overall acceptability. According to this study, sausages fermented using lactic acid bacteria (GK1), yeast (D1), and mold (S6) derived from Korean fermented foods displayed high proteolysis and excellent sensory evaluation results.

Temporal Estimation of Non-Rigid Dynamic Human Point Cloud Sequence Using 3D Skeleton-Based Deformation for Compression.

This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud by temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCFs), and a key PCF is selected. The 3D skeleton is predicted through 3D pose estimation, and the motion of the skeleton is estimated by analyzing the joints and bones of the 3D skeleton. For the deformation of the non-rigid human PC, the 3D PC model is transformed into a mesh model, and the key PCF is rigged using the 3D skeleton. After deforming the key PCF into the target PCF utilizing the motion vector of the estimated skeleton, the residual PC between the motion compensation PCF and the target PCF is generated. If there is a key PCF, the motion vector of the target PCF, and a residual PC, the target PCF can be reconstructed. Just as compression is performed using pixel correlation between frames in a 2D video, this paper compresses 3D PCFs by estimating the non-rigid 3D motion of a 3D object in a 3D PC. The proposed algorithm can be regarded as an extension of the 2D motion estimation of a rigid local region in a 2D plane to the 3D motion estimation of a non-rigid object (human) in 3D space. Experimental results show that the proposed method can successfully compress 3D PC sequences. If it is used together with a PC compression technique such as MPEG PCC (point cloud compression) in the future, a system with high compression efficiency may be configured.

Fast and Durable Nanofiber Mat Channel Organic Electrochemical Transistors.

Bioelectronic devices that offer real-time measurements, biological signal processing, and continuous monitoring while maintaining stable performance are in high demand. The materials used in organic electrochemical transistors (OECTs) demonstrate high transconductance (GM) and excellent biocompatibility, making them suitable for bioelectronics in a biological environment. However, ion migration in OECTs induces a delayed response time and low cut-off frequency, and the adverse biological environment causes OECT durability problems. Herein, we present OECTs with a faster response time and improved durability, made possible by using a nanofiber mat channel of a conventional OECT structure. Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)/polyacrylamide (PAAm) nanofiber mat channel OECTs are fabricated and subjected to various durability tests for the first time based on continuous measurements and mechanical stability assessments. The results indicate that the nanofiber mat channel OECTs have a faster response time and longer life spans compared to those of film channel OECTs. The improvements can be attributed to the increased surface area and fibrous structure of the nanofiber mat channel. Furthermore, the hydrogel helps to maintain the structure of the nanofiber, facilitates material exchange, and eliminates the need for a crosslinker.

Analysis of Quality and Color Properties according to the Gas Composition (Modified Atmosphere Packaging) of Pork Sous-Vide Ham Preserved in Natural Brine.

The purpose of this study was to analyze whether seawater has positive effects on appearance characteristics, such as CIE a*, and to determine the gas composition concentration that is suitable for maintaining it. Pork hind meat was cured with four types of curing agent for 5 d at 4°C. The different curing agents comprised the control salt, control nitrite pickling salt (CN), treatment brine, and treatment bittern (BT). The cured hams were cooked at 65°C for 4 h and packaged at O2:N2 gas ratios of 7:3, 8:2, and 9:1 for 3 wk. The physicochemical properties were assessed immediately after heating the sample, and the color properties were measured after a 3 wk storage period. Based on the correlation results of the physicochemical properties, BT had a higher curing and cooking yield than the other treatments, owing to its high salinity. Results of color properties for BT (7:3) and CN (8:2) showed similar color CIE L*, CIE a* chroma, and hue angle values. Therefore, BT can be said to be a sous-vide curing agent suitable for preserving the color of ham, and a high nitrogen concentration of 30% helps to maintain the appearance of seawater sous-vide ham.

Ultrafast van der Waals diode using graphene quantum capacitance and Fermi-level depinning.

Graphene, with superior electrical tunabilities, has arisen as a multifunctional insertion layer in vertically stacked devices. Although the role of graphene inserted in metal-semiconductor junctions has been well investigated in quasi-static charge transport regime, the implication of graphene insertion at ultrahigh frequencies has rarely been considered. Here, we demonstrate the diode operation of vertical Pt/n-MoSe2/graphene/Au assemblies at ~200-GHz cutoff frequency (fC). The electric charge modulation by the inserted graphene becomes essentially frozen above a few GHz frequencies due to graphene quantum capacitance-induced delay, so that the Ohmic graphene/MoSe2 junction may be transformed to a pinning-free Schottky junction. Our diodes exhibit much lower total capacitance than devices without graphene insertion, deriving an order of magnitude higher fC, which clearly demonstrates the merit of graphene at high frequencies.

Time-resolved imaging and analysis of the electron beam-induced formation of an open-cage metallo-azafullerene.

The visualization of single-molecule reactions provides crucial insights into chemical processes, and the ability to do so has grown with the advances in high-resolution transmission electron microscopy. There is currently a limited mechanistic understanding of chemical reactions under the electron beam. However, such reactions may enable synthetic methodologies that cannot be accessed by traditional organic chemistry methods. Here we demonstrate the synthetic use of the electron beam, by in-depth single-molecule, atomic-resolution, time-resolved transmission electron microscopy studies, in inducing the formation of a doubly holed fullerene-porphyrin cage structure from a well-defined benzoporphyrin precursor deposited on graphene. Through real-time imaging, we analyse the hybrid's ability to host up to two Pb atoms, and subsequently probe the dynamics of the Pb-Pb binding motif in this exotic metallo-organic cage structure. Through simulation, we conclude that the secondary electrons, which accumulate in the periphery of the irradiated area, can also initiate chemical reactions. Consequently, designing advanced carbon nanostructures by electron-beam lithography will depend on the understanding and limitations of molecular radiation chemistry.

Conductivity-Controlled Polyvinylidene Fluoride Nanofiber Stack for Absorption-Dominant Electromagnetic Interference Shielding Materials.

This work presents a novel method for achieving lightweight electromagnetic interference (EMI) shielding materials with high EMI shielding effectiveness (SE) through absorption-dominant mechanisms, utilizing only organic polymer nanofibers (NFs). Instead of incorporating high-density fillers, the approach involves adjusting the concentrations of iron chloride in the NFs and subsequent vapor phase polymerization (VPP) to control the polymerization density of poly(3,4-ethylenedioxythiophene) (PEDOT) on the surface of polyvinylidene fluoride (PVDF) NFs. This process results in NF layers with varying conductivity, creating a conductivity gradient structure. The conductivity gradient structure of the NF layers significantly enhances absorptivity by reducing impedance mismatches between the shielding material and the surrounding air, as well as between different interlayers. This reduction in impedance mismatches allows for efficient dissipation of absorbed electromagnetic (EM) waves within the highly conductive NF layer. This improved absorptivity is also attributed to the attenuation of EM wave energy through multiple reflections and scattering within the NF pores. Moreover, the gradient structure of the NF layers promotes interfacial polarization, further contributing to the effective absorption of electromagnetic waves. As a result, a high absolute EMI SE (SSEt) of 12,390 dB·cm2 g-1 with low reflectivity (0.32) was achieved without compromising the lightweight and flexible properties.

Analysis of physicochemical properties of dry-cured beef made from Hanwoo and Holstein meat distributed in South Korea.

The purpose of the study is to check the possibility of developing dry-cured meat from Hanwoo (South Korean native cattle) and Holstein cattle considering the differences between breeds and use this data for the preparation and development of dry cured ham unique to South Korea. Same-grade Semitendinosus muscle from Hanwoo and Holstein was cured using a curing agent with 4.6% salt content at 4 °C for 7 days, and then aged for 70 days. Data was analyzed through physicochemical characterization, and the manufacturing period was established through weight loss, volatile basic nitrogen (VBN), thiobarbituric acid reactive substances (TBARS). Moisture content and weight loss of both samples significantly decreased during the manufacturing process (P < 0.05). TBARS was significantly higher in Hanwoo and VBN in Holstein (P < 0.05). According to the values of VBN (less than 20 mg/100 g) and TBARS (less than 2 mg MDA/kg), dry aging for 5 weeks is appropriate for both samples. The principal component analysis of 5 weeks-aged Holstein showed a dramatically changing trend due to myofibril fragmentation as indicated by Sodium dodecyl sulfate-polyacrylamide-gel electrophoresis. In addition, 5 weeks-aged Holstein contains methanethiol (cheese), butan-2-one (butter), and 3-3-ethyl-2-methyl-1,3-hexadiene (fatty acid-derive) compounds that represent fermentation and aging flavors. Therefore, the possibility of product development was confirmed by the 5-week aging of Holstein dry-cured ham.

Inhibitory effect of fucoidan on TNF-α-induced inflammation in human retinal pigment epithelium cells.

Sargassum horneri (S. horneri) is a brown seaweed that contains a fucose-rich sulfated polysaccharide called fucoidan and is known to possess beneficial bioactivities, such as anti-inflammatory, antiviral, antioxidative, and antitumoral effects. This study aimed to determine the anti-inflammatory effects of AB_SH (hydrothermal extracts from S. horneri) and its bioactive compound (fucoidan) against tumor necrosis factor alpha (TNF-α)-induced inflammation in human retinal pigment epithelial (RPE) cells. AB_SH did not exhibit any cytotoxicity, and it decreased the mRNA expression of interleukin (IL)-6 and IL-8 and the production of the cytokines IL-6 and TNF-α. It also suppressed the expression levels of phosphorylated nuclear factor kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs), including c-Jun amino-terminal kinases (JNK), p38 protein kinases (p38), and extracellular signal-regulated kinase (ERK) proteins, suggesting that AB_SH inhibits activation of the NF-kB/MAPK signaling pathway. Since fucoidan was identified in the composition analysis of AB_SH, it was additionally shown to be required for its anti-inflammatory effects in TNF-α-stimulated human RPE cells. In line with the AB_SH results, fucoidan reduced the mRNA levels of IL-6, IL-1ß, and IL-8 and production of the cytokines IL-6, TNF-α, and IL-8 through the downregulation of the NF-kB/MAPK signaling pathway in a dose-dependent manner. Collectively, the ability of AB_SH from S. horneri hydrothermal extracts to reduce inflammation indicates that it may be a good functional ingredient for managing ocular disorders.