SIRT1 regulates endoplasmic reticulum stress-related organ damage.

Endoplasmic reticulum (ER) stress plays a key role in the pathogenesis of several organ damages. Studies show that excessive ER stress (ERS) can destroy cellular homeostasis, causing cell damage and physiological dysfunction in various organs. In recent years, Sirtuin1 (SIRT1) has become a research hotspot on ERS. Increasing evidence suggests that SIRT1 plays a positive role in various ERS-induced organ damage via multiple mechanisms, including inhibiting cellular apoptosis and promoting autophagy. SIRT1 can also alleviate liver, heart, lung, kidney, and intestinal damage by inhibiting ERS. We discuss the possible mechanism of SIRT1, explore potential therapeutic targets of diseases, and provide a theoretical basis for treating ERS-related diseases.

Colon Disease Classification Method Based on Deep Learning.

Objective Colorectal cancer (CRC) is a common malignant tumor of the digestive system with a high incidence rate. It is prone to misdiagnosis or missed diagnosis in clinical practice. Therefore, researching computer-aided diagnostic methods for endoscopic colon disease image classification is of great importance. This study proposes a deep learning-based method for colon disease classification. It utilizes intestinal images or captures from an endoscope camera to achieve intelligent classification of gastrointestinal diseases, providing assistance to doctors in their decision-making process. Methods Firstly, the algorithm is used to preprocess the dataset by removing duplicates and applying enhancement techniques. Two different network architectures, namely A_Vit, MobileNet, are employed. The models are trained using the same parameters and dataset with the Adam optimizer. The training process generates loss curves, accuracy, and recall rates for each of the four network architectures. Results The results indicate that the training with A_Vit has shown better performance, achieving an accuracy rate of 95.76% and an impressive recall rate of 97.21%. Therefore, the model trained using the A_Vit network structure is ultimately selected as the preferred choice. Conclusion This method can improve the efficiency and accuracy of colon disease diagnosis.

Simple synthesis of BiOI/ZnO/rGO for efficient photocatalytic degradation of antibiotic chloramphenicol under visible light.

BiOI/ZnO/rGO (reduced graphene oxide) composite photocatalyst was fabricated using a simple one-step hydrothermal process and applied to the degradation of antibiotic chloramphenicol (CAP). By tuning the Bi/Zn ratios, the structure and photoelectric properties of the catalyst were investigated and characterized in terms of their morphological, structural, optical and photoelectrochemical properties. The as-synthesized composite photocatalysts are well-crystalline, uniform dispersion and exhibit good photocatalytic properties. The photocatalytic degradation rate of CAP by BiOI/ZnO/rGO composite is 8.1 times and 1.8 times that of BiOI and ZnO, respectively. The photocatalytic mechanism studies revealed that the synergistic effect between rGO and BiOI/ZnO can effectively separate photogenerated electron-hole, enhance photocurrents and conductivity, and improve charge carrier densities. Moreover, BiOI/ZnO/rGO possesses good stability and reusability that the degradation efficiency remained above 80% even after 5 recycling. This study reveals that both the introduction of rGO and heterostructure construction between BiOI and ZnO play a crucial role in their photoelectrochemical and photocatalytic properties.

High Hepcidin Levels Promote Abnormal Iron Metabolism and Ferroptosis in Chronic Atrophic Gastritis.

BACKGROUND: Chronic atrophic gastritis (CAG) is a chronic inflammatory disease and premalignant lesion of gastric cancer. As an antimicrobial peptide, hepcidin can maintain iron metabolic balance and is susceptible to inflammation. OBJECTIVES: The objective of this study was to clarify whether hepcidin is involved in abnormal iron metabolism and ferroptosis during CAG pathogenesis. METHODS: Non-atrophic gastritis (NAG) and chronic atrophic gastritis (CAG) patient pathology slides were collected, and related protein expression was detected by immunohistochemical staining. The CAG rat model was established using MNNG combined with an irregular diet. RESULTS: CAG patients and rats exhibited iron deposition in gastric tissue. CAG-induced ferroptosis in the stomach was characterized by decreased GPX4 and FTH levels and increased 4-HNE levels. Hepcidin, which is mainly located in parietal cells, was elevated in CAG gastric tissue. The high gastric level of hepcidin inhibited iron absorption in the duodenum by decreasing the protein expression of DMT1 and FPN1. In addition, the IL-6/STAT3 signaling pathway induced hepcidin production in gastric tissue. CONCLUSION: Our results showed that the high level of gastric hepcidin induced ferroptosis in the stomach but also inhibited iron absorption in the intestines. Inhibiting hepcidin might be a new strategy for the prevention of CAG in the future.

Salt stress altered anaerobic microbial community and carbon metabolism characteristics: The trade-off between methanogenesis and chain elongation.

Discharge of saline organic wastewater is increasing worldwide, yet how salt stress disrupts the microbial community's structure and metabolism in bioreactors has not been systematically investigated. The non-adapted anaerobic granular sludge was inoculated into wastewater with varying salt concentration (ranging from 0% to 5%) to examine the effects of salt stress on the structure and function of the anaerobic microbial community. Result indicated that salt stress had a significant impact on the metabolic function and community structure of the anaerobic granular sludge. Specifically, we observed a notable reduction in methane production in response to all salt stress treatments (r = -0.97, p < 0.01), while an unexpected increase in butyrate production (r = 0.91, p < 0.01) under moderate salt stress (1-3%) with ethanol and acetate as carbon sources. In addition, analysis of microbiome structures and networks demonstrated that as the degree of salt stress increased, the networks exhibited lower connectance and increased compartmentalization. The abundance of interaction partners (methanogenic archaea and syntrophic bacteria) decreased under salt stress. In contrast, the abundance of chain elongation bacteria, specifically Clostridium kluyveri, increased under moderate salt stress (1-3%). As a consequence, the microbial carbon metabolism patterns shifted from cooperative mode (methanogenesis) to independent mode (carbon chain elongation) under moderate salt stress. This study provides evidence that salt stress altered the anaerobic microbial community and carbon metabolism characteristics, and suggests potential guidance for steering the microbiota to promote resource conversion in saline organic wastewater treatment.

Proton transfer triggered in-situ construction of C=N active site to activate PMS for efficient autocatalytic degradation of low-carbon fatty amine.

Removal of low-carbon fatty amines (LCFAs) in wastewater treatment poses a significant technical challenge due to their small molecular size, high polarity, high bond dissociation energy, electron deficiency, and poor biodegradability. Moreover, their low Brønsted acidity deteriorates this issue. To address this problem, we have developed a novel base-induced autocatalytic technique for the highly efficient removal of a model pollutant, dimethylamine (DMA), in a homogeneous peroxymonosulfate (PMS) system. A high reaction rate constant of 0.32 min-1 and almost complete removal of DMA within 12 min are achieved. Multi-scaled characterizations and theoretical calculations reveal that the in situ constructed C=N bond as the crucial active site activates PMS to produce abundant 1O2. Subsequently, 1O2 oxidizes DMA through multiple H-abstractions, accompanied by the generation of another C=N structure, thus achieving the autocatalytic cycle of pollutant. During this process, base-induced proton transfers of pollutant and oxidant are essential prerequisites for C=N fabrication. A relevant mechanism of autocatalytic degradation is unraveled and further supported by DFT calculations at the molecular level. Various assessments indicate that this self-catalytic technique exhibits a reduced toxicity and volatility process, and a low treatment cost (0.47 $/m3). This technology has strong environmental tolerance, especially for the high concentrations of chlorine ion (1775 ppm) and humic acid (50 ppm). Moreover, it not only exhibits excellent degradation performance for different amine organics but also for the coexisting common pollutants including ofloxacin, phenol, and sulforaphane. These results fully demonstrate the superiority of the proposed strategy for practical application in wastewater treatment. Overall, this autocatalysis technology based on the in-situ construction of metal-free active site by regulating proton transfer will provide a brand-new strategy for environmental remediation.

Patient-derived organoid culture of gastric cancer for disease modeling and drug sensitivity testing.

BACKGROUND: Gastric cancer treatment is complicated by the molecular heterogeneity of human tumor cells, which limits the efficacy of standard therapy and necessitates the need for personalized treatment development. Patient-derived organoids (PDOs) are promising preclinical cancer models, exhibiting high clinical efficacy in predicting drug sensitivity, thus providing a new means for personalized precision medicine. METHODS: PDOs were established from surgically resected gastric cancer tumor tissues. Molecular characterization of the tumor tissues and PDOs was performed using whole-exome sequencing analysis. Drug sensitivity tests were performed by treating the PDO cultures with 21 standard-of-care drugs corresponding to patient treatment. We evaluated whether the PDO drug phenotype reflects the corresponding patient's treatment response by comparing the drug sensitivity test results with clinical data. RESULTS: Twelve PDOs that satisfied the drug sensitivity test criteria were successfully constructed. PDOs closely recapitulated the pathophysiology and genetic changes in the corresponding tumors, and exhibited different sensitivities to the tested drugs. In one clinical case study, the PDO accurately predicted the patient's sensitivity to capecitabine and oxaliplatin, and in a second case study the PDO successfully predicted the patient's insensitivity to S-1 chemotherapy. In summary, six of the eight cases exhibited consistency between PDO drug susceptibility test results and the clinical response of the matched patient. CONCLUSIONS: PDO drug sensitivity tests can predict the clinical response of patients with gastric cancer to drugs, and PDOs can therefore be used as a preclinical platform to guide the development of personalized cancer treatment.

Precise Detection on Cell-Cell Fusion by a Facile Molecular Beacon-Based Method.

Cell-cell fusion studies provide an experimental platform for evaluating disease progression and investigating cell infection. However, to realize sensitive and quantitative detection on cell-cell fusion is still a challenge. Herein, we report a facile molecular beacon (MB)-based method for precise detection on cell-cell fusion. By transfection of the spike protein (S protein) and enhanced green fluorescent protein (EGFP) in HEK 293 cells, the virus-mimicking fusogenic effector cells 293-S-EGFP cells were constructed to interact with target cells. Before mixing the effector cells with the target cells, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression in 293-S-EGFP cells was silenced, and the MB for GAPDH mRNA detection was delivered into the GAPDH silenced 293-S-EGFP cells. Once cell-cell fusion occurred, MB migrated from the GAPDH silenced effector cells to the target cells and hybridized with GAPDH mRNA in the target cells to induce fluorescence emission. The cell-cell fusion can be easily visualized and quantitated by fluorescence microscopy and flow cytometry. The fluorescence intensity is strongly dependent on the number of fused target cells. This MB-based method can easily identify the differences in the cell fusions for various target cells with different angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) expression levels, resulting in dramatically different fluorescence intensities in fused target cells. Our study provides a convenient and efficient quantitative detection approach to study cell-cell fusion.

Pharmacological and molecular analysis of the effects of Huangqi Jianzhong decoction on proliferation and apoptosis in GES-1 cells infected with H. pylori.

Background: Infection with Helicobacter pylori (H. pylori) can cause chronic gastritis and other digestive tract diseases, and represents a public health concern. Current anti-H. pylori treatment can result in antibiotic resistance and other adverse reactions. Huangqi Jianzhong decoction (HQJZD) is a prescription form of traditional Chinese medicine for chronic gastritis that increases probiotics and inhibits H. pylori. In this study, its anti-bacterial activity against H. pylori receives a preliminary evaluation, and a pharmacology analysis is performed to predict its underlying mechanisms. Methods: Human GES-1 cells are divided into a blank control group, a model group, a HQJZD low-dose (2.08 mg·mL-1), a high-dose group (4.16 mg·mL-1), and a positive control group (amoxicillin, 5 µg·mL-1). After culture, the CCK-8 method is used to detect cell viability; flow cytometry is used to detect cell apoptosis rate; and RT-qPCR is used to detect the expression of mRNA virulence factors, including HpPrtC, OPiA, IceA1, and BabA2. Network pharmacology analysis and molecular docking were performed to explore the mechanisms of HQJZD in treating H. pylori gastritis, based on its anti-H. pylori infection effect. Results: We noted lower cell survival rates in the model group, but higher apoptosis rates and mRNA expressions of HpPrtC, OPiA, IceA1, and BabA2 than in the control group (p < 0.05). Compared to the model group, the cell survival rate of each dosage group of Huangqi Jianzhong decoction and the positive control group increased significantly, while the apoptosis rate and the mRNA expressions of HpPrtC, OPiA, IceA1, and BabA2 were decreased significantly. The effect in each HQJZD group was dose-dependent (p < 0.05). Network pharmacological analysis involving 159 signaling pathways was used to screen 6 key active components of HQJZD and 102 potential target proteins for the treatment of H. pylori-related gastritis. The molecular docking results revealed that the 6 active compounds had a strong binding ability with the target proteins of ALB, IL-6, AKT1, IL-1B, and JUN. Conclusion: HQJZD effectively increases the proliferation rate of human GES-1 cells after infection, while reducing the level of apoptosis. The mechanism may be related to multiple components, multiple targets and pathways, which provides a scientific basis for further elucidating the mechanism of action, the pharmacodynamic material basis, and the clinical application of HQJZD against H. pylori infection.

Bioaugmentation of quinoline-degrading bacteria for coking wastewater treatment: performance and microbial community analysis.

Ochrobactrum sp. XKL1, previously found to have the ability to efficiently degrade quinoline, was bioaugmented into a lab-scale A/O/O system to treat real coking wastewater. During the bioaugmentation stage, the removal of quinoline and pyridine of the O1 tank could be enhanced by 9.88% and 7.96%, respectively. High-throughput sequencing analysis indicated that the addition of XKL1 could significantly affect the alteration of microbial community structure in the sludge. In addition, the relative abundance of Ochrobactrum has demonstrated a trend of increasing first followed by decreasing with the highest abundance of 7.87% attained on the 94th day. The bioaugmentation effects lasted for about 14 days after the strains was inoculated into the reactor. Although a decrease in the relative abundance of XKL1 was observed for a rather short period of time, the bioaugmented A/O/O system has been proven to be more effective in the removal of organic pollutants than the control. Hence, the results of this study indicated that the bioaugmentation with XKL1 is a feasible operational strategy that would be able to enhance the removal of NHCs in the treatment of coking wastewater with complex composition and high organic concentrations.

Traditional Chinese medicine for precancerous lesions of gastric cancer: A review.

Gastric cancer (GC) is the fifth most common type of cancer and the third leading cause of death due to cancer worldwide. The gastric mucosa often undergoes many years of precancerous lesions of gastric cancer (PLGC) stages before progressing to gastric malignancy. Unfortunately, there are no effective Western drugs for patients with PLGC. In recent years, traditional Chinese medicine (TCM) has been proven effective in treating PLGC. Classical TCM formulas and chemical components isolated from some Chinese herbal medicines have been administered to treat PLGC, and the main advantage is their comprehensive intervention with multiple approaches and multiple targets. In this review, we focus on recent studies using TCM treatment for PLGC, including clinical observations and experimental research, with a focus on targets and mechanisms of drugs. This review provides some ideas and a theoretical basis for applying TCM to treat PLGC and prevent GC.

Performance prediction of ZVI-based anaerobic digestion reactor using machine learning algorithms.

The use of zero-valent iron (ZVI) to enhance anaerobic digestion (AD) systems is widely advocated as it improves methane production and system stability. Accurate modeling of ZVI-based AD reactor is conducive to predicting methane production potential, optimizing operational strategy, and gathering reference information for industrial design in place of time-consuming and laborious tests. In this study, three machine learning (ML) algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and deep learning (DL), were evaluated for their feasibility of predicting the performance of ZVI-based AD reactors based on the operating parameters collected in 9 published articles. XGBoost demonstrated the highest accuracy in predicting total methane production, with a root mean squared error (RMSE) of 21.09, compared to 26.03 and 27.35 of RF and DL, respectively. The accuracy represented by mean absolute percentage error also showed the same trend, with 14.26%, 15.14% and 17.82% for XGBoost, RF and DL, respectively. Through the feature importance generated by XGBoost, the parameters of total solid of feedstock (TSf), sCOD, ZVI dosage and particle size were identified as the dominant parameters that affect the methane production, with feature importance weights of 0.339, 0.238, 0.158, and 0.116, respectively. The digestion time was further introduced into the above-established model to predict the cumulative methane production. With the expansion of training dataset, DL outperformed XGBoost and RF to show the lowest RMSEs of 11.83 and 5.82 in the control and ZVI-added reactors, respectively. This study demonstrates the potential of using ML algorithms to model ZVI-based AD reactors.

[Study on medication regularity of chronic atrophic gastritis in Beijing-Tianjin-Hebei region based on latent structure model].

To explore the etiology, pathogenesis, distribution of syndromes and the rule of medication of chronic atrophic gastritis(CAG) in Beijing-Tianjin-Hebei region based on the latent structure model. Chronic atrophic gastritis of 279 cases in Beijing-Tianjin-Hebei region were extracted from the established database of spleen and stomach diseases of famous veteran Chinese medicine experts. The latent structure models of symptoms and drugs of chronic atrophic gastritis were constructed by using Lantern 3.1.2 software, and the latent structure models were interpreted. SAS 10.0 software was used to mine association rules of drugs and symptoms. The constitutional characteristics of patients with chronic atrophic gastritis in Beijing-Tianjin-Hebei region were "turbid toxin and damaging Yin". The common syndromes were turbid toxin, deficiency of stomach Yin, stagnation of liver and stomach, stagnation of liver and stomach Qi, obstruction of stomach collaterals and blood stasis, and weakness of spleen and stomach. Common medicines are Lobeliae Chinensis Herba, Scutellariae Barbatae Herba, Amomi Fructus Rotundus, Amomi Fructus, Poria, Isatidis Radix, Artemisiae Scopariae Herba, Scorpio, Coptidis Rhizoma, Lilii Bulbus, Linderae Radix, Phragmitis Rhizoma, Ophiopogonis Radix, Pogostemonis Herba, Eupatorii Herba, Magnoliae Officinalis Cortex, Aurantii Fructus Immaturus. Common prescriptions are Baihe Wuyao Powder, Danggui Shaoyao Powder, Xiaoyao Pills, Xiangsu Powder, Dachengqi Decoction, Zuojin Pills, Qingzhong Decoction, Zhishi Daozhi Pills, etc. The application of latent structure model and correlation analysis in the empirical study of famous and veteran Chinese medicine experts is in line with the research direction of modern Chinese medicine "traditional Chinese medicine + X". The conclusions obtained effectively tap the experience of famous and veteran TCM experts, and provide a data and visual clinical reference and prescription compatibility for young TCM physicians in the treatment of chronic atrophic gastritis based on syndrome differentiation.

New insights of enhanced anaerobic degradation of refractory pollutants in coking wastewater: Role of zero-valent iron in metagenomic functions.

Coking wastewater (CWW) has long been a serious challenge for anaerobic treatment due to its high concentrations of phenolics and nitrogen-containing heterocyclic compounds (NHCs). Herein, we proposed and validated a new strategy of using zero-valent iron (ZVI) to strengthen the anaerobic treatment of CWW. Results showed that COD removal efficiencies was increased by 9.5-13.7% with the assistance of ZVI. GC-MS analysis indicated that the removal of phenolics and NHCs was improved, and the intermediate 2(1H)-Quinolinone of quinoline degradation was further removed by ZVI addition. High-throughput sequencing showed that phenolics and NHCs degraders, such as Levilinea and Sedimentibacter were significantly enriched, and the predicted gene abundance of xenobiotic degradation and its downstream metabolic pathways was also increased by ZVI. Network and redundancy analysis indicated that the decreased oxidation-reduction potential (ORP) by ZVI was the main driver for microbial community succession. This study provided an alternative strategy for strengthening CWW anaerobic treatment.

A novel phenol and ammonia recovery process for coal gasification wastewater altering the bacterial community and increasing pollutants removal in anaerobic/anoxic/aerobic system.

Coal gasification wastewater (CGWW) is a typical toxic and refractory industrial wastewater. Here, a novel phenol and ammonia recovery process (IPE) was employed for CGWW pretreatment, and the coupled system assemble by the IPE process with A2/O system (IPE-A2/O) were operated to enhance the treatment performance of CGWW. The results showed that the IPE pre-treated effluent had a higher BOD5/COD ratio and lower refractory compounds compared to a typical process (MIBK). Subsequent A2/O biological treatment indicated that the A2/O-p system (A2/O system followed IPE process) obtained a higher average COD removal of 92% compared to 87.7% of the control (A2/O-m, A2/O system followed MIBK). The GC-MS analysis suggested that the content of alkanes in the IPE-A2/O effluent was lower than that of the MIBK-A2/O. The high-throughput sequencing revealed Levilinea, Alcaligenes, Acinetobacter, Thauera and Thiobacillus were the core genera in A2/O system. The genera Alcaligenes, Acinetobacter, Thauera and Thiobacillus in the degrading consortium were enriched in the A2/O-p system, leading to increased removals of organic pollutants and TN. These results suggested that the IPE process was a feasible pretreatment method, and the coupled IPE-A2/O system was an alternative technique for treating CGWW.

Metagenomic insights into the microbiota profiles and bioaugmentation mechanism of organics removal in coal gasification wastewater in an anaerobic/anoxic/oxic system by methanol.

Coal gasification wastewater is a typical high phenol-containing, toxic and refractory industrial wastewater. Here, lab-scale anaerobic-anoxic-oxic system was employed to treat real coal gasification wastewater, and methanol was added to oxic tank as the co-substrate to enhance the removal of refractory organic pollutants. The results showed that the average COD removal in oxic effluent increased from 24.9% to 36.0% by adding methanol, the total phenols concentration decreased from 54.4 to 44.9 mg/L. GC-MS analysis revealed that contents of phenolic components and polycyclic aromatic hydrocarbons (PAHs) were decreased compared to the control and their degradation intermediates were observed. Microbial community revealed that methanol increased the abundance of phenolics and PAHs degraders such as Comamonas, Burkholderia and Sphingopyxis. Moreover, functional analysis revealed the relative abundance of functional genes associated with toluene, benzoate and PAHs degradation pathways was higher than that of control based on KEGG database.

Tuning Transpiration by Interfacial Solar Absorber-Leaf Engineering.

Plant transpiration, a process of water movement through a plant and its evaporation from aerial parts especially leaves, consumes a large component of the total continental precipitation (≈48%) and significantly influences global water distribution and climate. To date, various chemical and/or biological explorations have been made to tune the transpiration but with uncertain environmental risks. In recent years, interfacial solar steam/vapor generation is attracting a lot of attention for achieving high energy transfer efficiency. Various optical and thermal designs at the solar absorber-water interface for potential applications in water purification, seawater desalination, and power generation appear. In this work, the concept of interfacial solar vapor generation is extended to tunable plant transpiration by showing for the first time that the transpiration efficiency can also be enhanced or suppressed through engineering the solar absorber-leaf interface. By tuning the solar absorption of membrane in direct touch with green leaf, surface temperature of green leaf will change accordingly because of photothermal effect, thus the transpiration efficiency as well as temperature and relative humidity in the surrounding environment will be tuned. This tunable transpiration by interfacial absorber-leaf engineering can open an alternative avenue to regulate local atmospheric temperature, humidity, and eventually hydrologic cycle.

Mushrooms as Efficient Solar Steam-Generation Devices.

Solar steam generation is emerging as a promising technology, for its potential in harvesting solar energy for various applications such as desalination and sterilization. Recent studies have reported a variety of artificial structures that are designed and fabricated to improve energy conversion efficiencies by enhancing solar absorption, heat localization, water supply, and vapor transportation. Mushrooms, as a kind of living organism, are surprisingly found to be efficient solar steam-generation devices for the first time. Natural and carbonized mushrooms can achieve ≈62% and ≈78% conversion efficiencies under 1 sun illumination, respectively. It is found that this capability of high solar steam generation is attributed to the unique natural structure of mushroom, umbrella-shaped black pileus, porous context, and fibrous stipe with a small cross section. These features not only provide efficient light absorption, water supply, and vapor escape, but also suppress three components of heat losses at the same time. These findings not only reveal the hidden talent of mushrooms as low-cost materials for solar steam generation, but also provide inspiration for the future development of high-performance solar thermal conversion devices.

Order Statistics Concordance Coefficient With Applications to Multichannel Biosignal Analysis.

In this paper, we propose a novel concordance coefficient, called order statistics concordance coefficient (OSCOC), to quantify the association among multichannel biosignals. To uncover its properties, we compare OSCOC with three other similar indexes, i.e., average Pearson's product moment correlation coefficient (APPMCC), Kendall's concordance coefficients (KCC), and average Kendall's tau (AKT), under a multivariate normal model (MNM), linear model (LM), and nonlinear model. To further demonstrate its usefulness, we present an example on atrial arrhythmia analysis based on real-world multichannel cardiac signals. Theoretical derivations as well as numerical results suggest that 1) under MNM and LM, OSCOC performs equally well with APPMCC, and outperforms the other two methods, 2) in nonlinear case, OSCOC even has better performance than KCC and AKT, which are well known to be robust under increasing nonlinear transformations, and 3) OSCOC performs the best in the case study of arrhythmia analysis in terms of the volume under the surface.

Tailoring Graphene Oxide-Based Aerogels for Efficient Solar Steam Generation under One Sun.

Graphene oxide-based aerogels with carefully tailored properties are developed to enable efficient solar steam generation. Aerogels, with inherent porous structures, are excellent thermal insulators and provide channels for water supply and vapor escape. With enhanced absorption and hydrophilicity by incorporation of carbon nanotubes and sodium alginate, the resulting aerogels can enable efficient (≈83%) solar steam generation under one-sun illumination.