Result of a Pilot External Quality Assessment Scheme for Clinical Diagnosis of Inherited Metabolic Disorders in China.

BACKGROUND: We aimed to evaluate the diagnostic capabilities of Chinese laboratories for inherited metabolic disorders (IMDs) using gas chromatography-mass spectrometry (GC-MS) on urine samples. Meanwhile, based on the result of the pilot external quality assessment (EQA) scheme, we hope to establish a standardized and reliable procedure for future EQA practice. METHODS: We recruited laboratories that participated in the EQA of quantitative analysis of urinary organic acids with GC-MS before joining the surveys. In each survey, a set of five real urine samples was distributed to each participant. The participants should analyze the sample by GC-MS and report the "analytical result", "the most likely diagnosis", and "recommendation for further tests" to the NCCL before the deadline. RESULTS: A total of 21 laboratories participated in the scheme. The pass rates were 94.4% in 2020 and 89.5% in 2021. For all eight IMDs tested, the analytical proficiency rates ranged from 84.7% - 100%, and the interpretational performance rate ranged from 88.2% - 97.0%. The performance on hyperphenylalaninemia (HPA), 3-methylcrotonyl-CoA carboxylase deficiency (MCCD), and ethylmalonic encephalopathy (EE) samples were not satisfactory. CONCLUSIONS: In general, the participants of this pilot EQA scheme are equipped with the basic capability for qualitative organic acid analysis and interpretation of the results. Limited by the small size of laboratories and samples involved, this activity could not fully reflect the state of clinical practice of Chinese laboratories. NCCL will improve the EQA scheme and implement more EQA activities in the future.

Latent Prototype-Based Clustering: A Novel Exploratory Electroencephalography Analysis Approach.

Electroencephalography (EEG)-based applications in brain-computer interfaces (BCIs), neurological disease diagnosis, rehabilitation, etc., rely on supervised approaches such as classification that requires given labels. However, with the ever-increasing amount of EEG data, incomplete or incorrectly labeled or unlabeled EEG data are increasing. It likely degrades the performance of supervised approaches. In this work, we put forward a novel unsupervised exploratory EEG analysis solution by clustering based on low-dimensional prototypes in latent space that are associated with the respective clusters. Having the prototype as a baseline of each cluster, a compositive similarity is defined to act as the critic function in clustering, which incorporates similarities on three levels. The approach is implemented with a Generative Adversarial Network (GAN), termed W-SLOGAN, by extending the Stein Latent Optimization for GANs (SLOGAN). The Gaussian Mixture Model (GMM) is utilized as the latent distribution to adapt to the diversity of EEG signal patterns. The W-SLOGAN ensures that images generated from each Gaussian component belong to the associated cluster. The adaptively learned Gaussian mixing coefficients make the model remain effective in dealing with an imbalanced dataset. By applying the proposed approach to two public EEG or intracranial EEG (iEEG) epilepsy datasets, our experiments demonstrate that the clustering results are close to the classification of the data. Moreover, we present several findings that were discovered by intra-class clustering and cross-analysis of clustering and classification. They show that the approach is attractive in practice in the diagnosis of the epileptic subtype, multiple labelling of EEG data, etc.

ABCModeller: an automatic data mining tool based on a consistent voting method with a user-friendly graphical interface.

In order to extract useful information from a huge amount of biological data nowadays, simple and convenient tools are urgently needed for data analysis and modeling. In this paper, an automatic data mining tool, termed as ABCModeller (Automatic Binary Classification Modeller), with a user-friendly graphical interface was developed here, which includes automated functions as data preprocessing, significant feature extraction, classification modeling, model evaluation and prediction. In order to enhance the generalization ability of the final model, a consistent voting method was built here in this tool with the utilization of three popular machine-learning algorithms, as artificial neural network, support vector machine and random forest. Besides, Fibonacci search and orthogonal experimental design methods were also employed here to automatically select significant features in the data space and optimal hyperparameters of the three algorithms to achieve the best model. The reliability of this tool has been verified through multiple benchmark data sets. In addition, with the advantage of a user-friendly graphical interface of this tool, users without any programming skills can easily obtain reliable models directly from original data, which can reduce the complexity of modeling and data mining, and contribute to the development of related research including but not limited to biology. The excitable file of this tool can be downloaded from http://lishuyan.lzu.edu.cn/ABCModeller.rar.

GCdiscrimination: identification of gastric cancer based on a milliliter of blood.

Gastric cancer (GC) continues to be one of the major causes of cancer deaths worldwide. Meanwhile, liquid biopsies have received extensive attention in the screening and detection of cancer along with better understanding and clinical practice of biomarkers. In this work, 58 routine blood biochemical indices were tentatively used as integrated markers, which further expanded the scope of liquid biopsies and a discrimination system for GC consisting of 17 top-ranked indices, elaborated by random forest method was constructed to assist in preliminary assessment prior to histological and gastroscopic diagnosis based on the test data of a total of 2951 samples. The selected indices are composed of eight routine blood indices (MO%, IG#, IG%, EO%, P-LCR, RDW-SD, HCT and RDW-CV) and nine blood biochemical indices (TP, AMY, GLO, CK, CHO, CK-MB, TG, ALB and γ-GGT). The system presented a robust classification performance, which can quickly distinguish GC from other stomach diseases, different cancers and healthy people with sensitivity, specificity, total accuracy and area under the curve of 0.9067, 0.9216, 0.9138 and 0.9720 for the cross-validation set, respectively. Besides, this system can not only provide an innovative strategy to facilitate rapid and real-time GC identification, but also reveal the remote correlation between GC and these routine blood biochemical parameters, which helped to unravel the hidden association of these parameters with GC and serve as the basis for subsequent studies of the clinical value in prevention program and surveillance management for GC. The identification system, called GC discrimination, is now available online at http://lishuyan.lzu.edu.cn/GC/.

The mitochondrial complex I proteins of Candida albicans moderate phagocytosis and the production of pro-inflammatory cytokines in murine macrophages and dendritic cells.

Loss of respiratory functions impairs Candida albicans colonization of host tissues and virulence in a murine model of candidiasis. Furthermore, it is known that respiratory inhibitors decrease mannan synthesis and glucan exposure and thereby promotes phagocytosis. To understand the impact of respiratory proteins of C. albicans on host innate immunity, we characterized cell wall defects in three mitochondrial complex I (CI) null mutants (nuo1Δ, nuo2Δ and ndh51Δ) and in one CI regulator mutant (goa1Δ), and we studied the corresponding effects of these mutants on phagocytosis, neutrophil killing and cytokine production by dendritic cells (DCs). We find that reductions of phosphopeptidomannan (PPM) in goa1Δ, nuo1Δ and phospholipomannan (PLM) in nuo2Δ lead to reductions of IL-2, IL-4, and IL-10 but increase of TNF-α in infected DCs. While PPM loss is a consequence of a reduced phospho-Cek1/2 MAPK that failed to promote phagocytosis and IL-22 production in goa1Δ and nuo1Δ, a 30% glucan reduction and a defective Mek1 MAPK response in ndh51Δ lead to only minor changes in phagocytosis and cytokine production. Glucan exposure and PLM abundance seem to remain sufficient to opsonize neutrophil killing perhaps via humoral immunity. The diversity of immune phenotypes in these mutants possessing divergent cell wall defects is further supported by their transcriptional profiles in each infected murine macrophage scenario. Since metabolic processes, oxidative stress-induced senescence, and apoptosis are differently affected in these scenarios, we speculate that during the early stages of infection, host immune cells coordinate their bioactivities based upon a mixture of signals generated during host-fungi interactions.

Fabrication of MnO2 coating on aluminum honeycomb for fast catalytic decomposition of ozone at room temperature.

Herein, the coating of MnO2 nanomaterials on the surface of aluminum honeycomb was carried out to meet the requirements of high air velocity, low pressure drop and high activity in ozone removal scenarios. A commercially readily available waterborne silica sol mixed with waterborne acrylate latex was creatively utilized as the binder. A series of coating samples were prepared by spray coating method and evaluated focusing on their adhesion strength and catalytic activity towards ozone decomposition in an air duct at room temperature, by varying MnO2/binder mass ratio and number of sprayings. It was found that the adhesion strength of the catalytic coatings on the aluminum honeycomb increased with the increase of binder mass ratio, but the increased binder made the catalyst particles closely packed, resulting in reduced exposure of active sites and decrease of ozone conversion. Accordingly, catalyst slurry with 81.8 wt.% MnO2 in dry coating and spraying times of two were determined as the optimal process parameters. As-prepared aluminum honeycomb filter with MnO2 layer of 50 µm thickness achieved ozone conversion of 29.3%±1.7% under conditions of air velocity 3.0 m/sec, relative humidity ∼50%, room temperature (26°C) and initial ozone concentration of 200 ppbV. This filter can be well adaptable to indoor air purification equipment operating at high air velocity with low wind resistance.

Functionalized Activated Carbon Fibers by Hydrogen Peroxide and Polydopamine for Efficient Trace Lead Removal from Drinking Water.

To achieve efficient and selective trace heavy metals removal from drinking water, a low-cost purification material polydopamine/activated carbon fibers (PDA/H-ACF) was successfully prepared by polymerizing dopamine on the surface of activated carbon fibers pretreated with hydrogen peroxide. The morphology, phase, surface functional groups, specific surface, and pore size distribution of the as-prepared sample were analyzed using FESEM, XPS, BET and pore size distribution test (PST), and FTIR, and orthogonal experiments were used to investigate the influences of concentration of H2O2, pretreatment time, and reflux temperature on trace lead removal. The results showed that the sample pretreated under optimized conditions could produce different pore structures, and the content of functional group -COOH obviously increased. After further modification by polydopamine, the contents of -NH-, -NH2, and -OH functional groups on the surface obviously enhanced, which were beneficial to increase adsorption site and promote trace lead removal. The effluent lead concentration decreased from initial 150 to 3.18 ppb within 5 min, meeting the requirement of NSF International Standard/American National Standard for Drinking Water Treatment Units (NSF/ANSI 53-2020) (5 ppb). The isothermal adsorption process and adsorption kinetics could be well-fitted by the Langmuir isotherm and pseudo-second-order kinetics model, indicating that the adsorption process of trace lead by PDA/H-ACF belonged to monolayer and chemical adsorption. Moreover, the as-prepared PDA/H-ACF also showed superior trace lead adsorption performance in the presence of high concentration competitive metal ions, in a wide pH range and in tap water, and therefore had good application prospect in the field of drinking water purification.

ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results.

Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with Mycobacterium tuberculosis develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinical treatment schedule. However, most current clinical diagnostic methods are based on the immune response of M. tuberculosis infections and cannot distinguish ATB from LTBIs. Thus, the rapid diagnosis of active or latent tuberculosis infections remains a serious challenge for clinicians. In this work, based on the test data of a total of 478 patients, 36 blood biochemical data were specially included with T-SPOT.TB detection results which are all from routine clinical practice as commercially available. Then a discrimination method to detect ATB infections was successfully developed based on these data by the random forest algorithm. This method presents a robust classification performance with AUC as 0.9256 and 0.8731 for the cross-validation set and the external validation set, respectively. This work suggests an innovative strategy for identification of ATB disease from a single drop of blood with advantages of being timely, efficient, and economical. It also provides valuable information for the comprehensive understanding of TB with deep associations between TB infection and routine blood test data. The web server of this identification method, called ATBdiscrimination, is now available online at http://lishuyan.lzu.edu.cn/ATB/ATBdiscrimination.html .

Respiratory stress in mitochondrial electron transport chain complex mutants of Candida albicans activates Snf1 kinase response.

We have previously established that mitochondrial Complex I (CI) mutants of Candida albicans display reduced oxygen consumption, decreased ATP production, and increased reactive oxidant species (ROS) during cell growth. Using the Seahorse XF96 analyzer, the energetic phenotypes of Electron Transport Chain (ETC) complex mutants are further characterized in the current study. The underlying regulation of energetic changes in these mutants is determined in glucose and non-glucose conditions when compared to wild type (WT) cells. In parental cells, the rate of oxygen consumption remains constant for 2.5 h following the addition of glucose, oligomycin, and 2-DG, but glycolysis is highly active upon the addition of glucose. In comparison, over the same time period, electron transport complex mutants (CI, CIII and CIV) have heightened activities in both oxygen consumption and glycolysis upon glucose uptake. We refer to the response in these mutants as an "explosive respiration," which we believe is caused by low energy levels and increased production of reactive oxygen species (ROS). Accompanying this phenotype in mutants is a hyperphosphorylation of Snf1p which in Saccharomyces cerevisiae serves as an energetic stress response protein kinase for maintaining energy homeostasis. Compared to wild type cells, a 2.9- to 4.4-fold hyperphosphorylation of Snf1p is observed in all ETC mutants in the presence of glucose. However, the explosive respiration and hyperphosphorylation of Snf1 can be partially reduced by the replacement of glucose with either glycerol or oleic acid in a mutant-specific manner. Furthermore, Inhibitors of glutathione synthesis (BSO) or anti-oxidants (mito-TEMPO) likewise confirmed an increase of Sfn1 phosphorylation in WT or mutant due to increased levels of ROS. Our data establish the role of the C. albicans Snf1 as a surveyor of cell energy and ROS levels. We interpret the "explosive respiration" as a failed attempt by ETC mutants to restore energy and ROS homeostasis via Snf1 activation. An inherently high OCR baseline in WT C. albicans with a background level of Snf1 activation is a prerequisite for success in quickly fermenting glucose.

Photochemical decomposition of 1H,1H,2H,2H-perfluorooctane sulfonate (6:2FTS) induced by ferric ions.

Perfluorooctane sulfonate (PFOS) had wide applications, such as in the electroplating industry, but its use was restricted in 2009 by the Stockholm Convention, due to its environmental persistence and potential hazards. As the most common PFOS alternative, 1H,1H,2H,2H-perfluorooctane sulfonic acid (6:2FTS) and its salts have been increasingly used. However, little is known about its photochemical decomposition. This paper reports the ferric ion-induced efficient decomposition and defluorination of 6:2FTS under 254nm ultraviolet (UV) irradiation; the underlying mechanisms were also investigated. In the presence of 100µmol/L ferric ion and at pH3.0, the first-order decomposition rate constant of 6:2FTS (10mg/L) was 1.59/hr, which was 6 times higher than for direct UV photolysis. The effects of the ferric ion concentration and the solution pH on the 6:2FTS photodecomposition were investigated and the optimal reaction conditions were determined. In addition to fluoride and sulfate ions, shorter-chain PFCAs (C2-C7) were detected as major intermediates. The addition of hydrogen peroxide or oxalic acid accelerated the decomposition of 6:2FTS under UV irradiation, but not its defluorination, indicating that hydroxyl radicals can directly react with 6:2FTS but not with the shorter-chain PFCAs. Accordingly, a mechanism for 6:2FTS photochemical decomposition in the presence of ferric ion was proposed, which comprises two reaction pathways. First, hydroxyl radicals can directly attack 6:2FTS, leading to CC bond cleavage. Alternatively, 6:2FTS coordinates with ferric ion to form Fe(III)-6:2FTS complexes, which can undergo ligand-to-metal charge transfer under UV irradiation, causing CS bond cleavage.

VUV-Photocatalytic Degradation of Bezafibrate by Hydrothermally Synthesized Enhanced {001} Facets TiO2/Ti Film.

In the present study, a novel TiO2/Ti film with enhanced {001} facets was synthesized by the hydrothermal technique followed by calcination for studying the removal of bezafibrate (BZF), from an aqueous environment. The synthesized photocatalyst was characterized by FE-SEM, XRD, HR-TEM, and PL-technique. The second-order rate constant of (•)OH with BZF was found to be 5.66 × 10(9) M(-1) s(-1). The steady state [(•)OH] was measured as 1.16 × 10(-11) M, on the basis of oxidation of terephthalic acid. The photocatalytic degradation of BZF followed pseudo-first-order kinetics according to the Langmuir-Hinshelwood model (k1 = 2.617 mg L(-1) min(-1) and k2 = 0.0796 (mg L(-1))(-1)). The effects of concentration and the nature of various additives including inorganic anions (NO3(-), NO2(-), HCO3(-), CO3(2-), Cl(-)) and organic species (fulvic acid) and initial solution pHs (2, 4, 6, 9) on photocatalytic degradation of BZF were investigated. It was found that the nature and concentration of studied additives significantly affected the photocatalytic degradation of BZF. The efficiency of the photocatalytic degradation process in terms of electrical energy per order was estimated. Degradation schemes were proposed on the basis of the identified degradation byproducts by ultraperformance liquid chromatography.

Efficient Photocatalytic Degradation of Norfloxacin in Aqueous Media by Hydrothermally Synthesized Immobilized TiO2/Ti Films with Exposed {001} Facets.

In this study, a novel immobilized TiO2/Ti film with exposed {001} facets was prepared via a facile one-pot hydrothermal route for the degradation of norfloxacin from aqueous media. The effects of various hydrothermal conditions (i.e., solution pH, hydrothermal time (HT) and HF concentration) on the growth of {001} faceted TiO2/Ti film were investigated. The maximum photocatalytic performance of {001} faceted TiO2/Ti film was observed when prepared at pH 2.62, HT of 3 h and at HF concentration of 0.02 M. The as-prepared {001} faceted TiO2/Ti films were fully characterized by field-emission scanning electron microscope (FE-SEM), X-ray diffraction (XRD), high resolution transmission electron microscope (HR-TEM), and X-ray photoelectron spectroscopy (XPS). More importantly, the as-prepared {001} faceted TiO2/Ti film exhibited excellent photocatalytic performance toward degradation of norfloxacin in various water matrices (Milli-Q water, tap water, river water and synthetic wastewater). The individual influence of various anions (SO42-, HCO3-, NO3-, Cl-) and cations (K+, Ca2+, Mg2+, Cu2+, Na+, Fe3+) usually present in the real water samples on the photocatalytic performance of as-prepared TiO2/Ti film with exposed {001} facet was investigated. The mechanistic studies revealed that •OH is mainly involved in the photocatalytic degradation of norfloxacin by {001} faceted TiO2/Ti film. In addition, norfloxacin degradation byproducts were investigated, on the basis of which degradation schemes were proposed.

Room-Temperature Oxidation of Formaldehyde by Layered Manganese Oxide: Effect of Water.

Layered manganese oxide, i.e., birnessite was prepared via the reaction of potassium permanganate with ammonium oxalate. The water content in the birnessite was adjusted by drying/calcining the samples at various temperatures (30 °C, 100 °C, 200 °C, 300 °C, and 500 °C). Thermogravimetry-mass spectroscopy showed three types of water released from birnessite, which can be ascribed to physically adsorbed H2O, interlayer H2O and hydroxyl, respectively. The activity of birnessite for formaldehyde oxidation was positively associated with its water content, i.e., the higher the water content, the better activity it has. In-situ DRIFTS and step scanning XRD analysis indicate that adsorbed formaldehyde, which is promoted by bonded water via hydrogen bonding, is transformed into formate and carbonate with the consumption of hydroxyl and bonded water. Both bonded water and water in air can compensate the consumed hydroxyl groups to sustain the mineralization of formaldehyde at room temperature. In addition, water in air stimulates the desorption of carbonate via water competitive adsorption, and accordingly the birnessite recovers its activity. This investigation elucidated the role of water in oxidizing formaldehyde by layered manganese oxides at room temperature, which may be helpful for the development of more efficient materials.

Efficient removal of formaldehyde by nanosized gold on well-defined CeO2 nanorods at room temperature.

Gold (Au) nanoparticles (NPs) supported on well-defined ceria (CeO2) nanorods with exposed {110} and {100} facets were prepared by a deposition-precipitation method and characterized by powder X-ray diffraction, micro-Raman spectroscopy, X-ray photoelectron spectroscopy, nitrogen adsorption-desorption, transmission electron microscopy, high-resolution transmission electron microscopy, and high-angle annular dark-field scanning transmission electron microscopy. Both nanometer and subnanometer gold particles were found to coexist on ceria supports with various Au contents (0.01-5.4 wt %). The catalytic performance of Au/CeO2 catalysts was examined for formaldehyde (HCHO) oxidation into CO2 and H2O at room temperature and shown to be Au content dependent, with 1.8 wt % Au/CeO2 displaying the best performance. On the basis of the results from hydrogen temperature-programmed reduction and in situ Fourier transform infrared spectroscopy observations, the high reactivity and stability of Au/CeO2 catalysts is mainly attributed to the well-defined ceria nanorods with {110} and {100} facets which present a relatively low energy for oxygen vacancy formation. Furthermore, gold NPs could induce the weakened Ce-O bond which in turn promotes HCHO oxidation.

Effects of pH on photochemical decomposition of perfluorooctanoic acid in different atmospheres by 185nm vacuum ultraviolet.

Perfluorooctanoic acid (PFOA), a persistent organic pollutant, receives increasing concerns due to its worldwide occurrence and resistance to most conventional treatment processes. The photochemical decomposition by 185nm vacuum ultraviolet (VUV) is one of the efficient methods for PFOA decomposition. The effects of pH on PFOA decomposition in nitrogen atmosphere or oxygen atmosphere were investigated. At its original pH (4.5) of PFOA aqueous solution, PFOA decomposed efficiently both in nitrogen and in oxygen atmosphere. However, when the pH increased to 12.0, PFOA decomposition was greatly inhibited in oxygen atmosphere, while it was greatly accelerated in nitrogen atmosphere with a very short half-life time (9min). Furthermore, fluorine atoms originally contained in PFOA molecules were almost completely transformed into fluoride ions. Two decomposition pathways have been proposed to explain the PFOA decomposition under different conditions. In acidic and neutral solutions, PFOA predominantly decomposes via the direct photolysis in both atmospheres; while in the alkaline solution and in the absence of oxygen, the decomposition of PFOA is mainly induced by hydrated electrons.

CLASH: Complementary Learning with Neural Architecture Search for Gait Recognition.

Gait recognition, which aims at identifying individuals by their walking patterns, has achieved great success based on silhouette. The binary silhouette sequence encodes the walking pattern within the sparse boundary representation. Therefore, most pixels in the silhouette are under-sensitive to the walking pattern since the sparse boundary lacks dense spatial-temporal information, which is suitable to be represented with dense texture. To enhance the sensitivity to the walking pattern while maintaining the robustness of recognition, we present a Complementary Learning with neural Architecture SearcH (CLASH) framework, consisting of walking pattern sensitive gait descriptor named dense spatial-temporal field (DSTF) and neural architecture search based complementary learning (NCL). Specifically, DSTF transforms the representation from the sparse binary boundary into the dense distance-based texture, which is sensitive to the walking pattern at the pixel level. Further, NCL presents a task-specific search space for complementary learning, which mutually complements the sensitivity of DSTF and the robustness of the silhouette to represent the walking pattern effectively. Extensive experiments demonstrate the effectiveness of the proposed methods under both in-the-lab and in-the-wild scenarios. On CASIA-B, we achieve rank-1 accuracy of 98.8%, 96.5%, and 89.3% under three conditions. On OU-MVLP, we achieve rank-1 accuracy of 91.9%. Under the latest in-the-wild datasets, we outperform the latest silhouette-based methods by 16.3% and 19.7% on Gait3D and GREW, respectively.

Room temperature synthesis of monolithic MIL-100(Fe) in aqueous solution for energy-efficient removal and recovery of aromatic volatile organic compounds.

The removal and recovery of volatile organic compounds (VOCs) are widely used in many industrials. Unfortunately, most conventional porous materials not only have low VOCs uptake, but also need to be regenerated at relatively high temperature. Metal-organic frameworks (MOFs) have great potential for the removal and recovery of VOCs as their record-breaking gas adsorption capacity, easy regeneration, tunable pore structure and functional groups. Whereas, powdered MOFs are hardly implemented in industrial fields owing to their low bulk density and high pressure drop. Exploring a green method to prepare granular MOFs for the removal and recovery of VOCs is still a challenge. Herein, we report the room temperature green synthesis of a stable Fe-based MOF monolith by using water as the solvent without applying high pressure and chemical binders. The static and dynamic experiments show that the optimized centimeter-scale monolith has high porosity and mechanical strength, and exhibits much better adsorption performance for representative aromatic VOCs (benzene, toluene and p-xylene), than commercial activated carbon and activated carbon fiber under the same conditions. Remarkably, as-synthesized monolith can be rapidly regenerated at lower temperature. These results clearly demonstrate the advantages of MOF monoliths in removing and recovering VOCs, and also provide new insight into the effects of drying temperature, washing and centrifugation procedures on MOF shaping.

Green synthesis of a hydrophobic metal-organic gel for the capture of trace odorous hexanal from humid air.

The development of superhydrophobic adsorbents for the capture of trace volatile organic compounds (VOCs) from humid indoor air is still a challenge. Herein, we reported the formation of a granular zinc-based metal-organic gel, i.e., ZIF-412(gel) by optimizing the synthesis conditions. The thermally stable xerogel exhibited high surface area (1008 m2/g), hydrophobicity, and viscosity for self-depositing on the substrate such as non-woven fibers. Dynamic adsorption experiments under various humidity conditions demonstrated as-synthesized ZIF-412(gel) owned excellent VOC (hexanal) adsorption performance with adsorption capacity higher than commercial activated carbon and some water-stable MOFs including ZIF-8, ZIF-67, MIL-101(Cr) and ZIF-414. ZIF-412(gel) could be regenerated at temperature as low as 358 K without obvious loss in adsorption capacity. The adsorption mechanism of hexanal over ZIF-412(gel) is also simulated by Grand canonical Monte Carlo (GCMC).

Repair of Rabbit Knee Cartilage by Bipolar Radiofrequency with Different Energy Settings and Recovery Periods.

BACKGROUND: Arthroscopic bipolar radiofrequency energy (bRFE) is a common method for minimally invasive treatment of cartilage injuries. The benefits of bRFE are still controversial, and its safety has become the focus of attention. OBJECTIVE: This study aimed to reveal the effects of energy setting and recovery period on the efficacy and safety of bRFE. METHODS: The New Zealand white rabbit knee cartilage injury model was established, and bRFE was used to treat the cartilage with different energy settings, including 20 W and 40 W, and recovery periods of 0 and 1 month. By observing the immediate and late results on damaged cartilage, along with chondrocyte apoptosis, the effects of energy setting and recovery period on the efficacy and safety of bRFE were accessed. RESULTS: The pathological conditions, surface profile and chondrocyte viability in the bRFE treatment group produced greater late effects and were significantly better than those in the model group. Nevertheless, bRFE produced a timely injury that resulted in an increased rate of apoptosis (p < 0.05), which was alleviated in subsequent recovery (p < 0.05). CONCLUSIONS: bRFE can effectively trim and improve the cartilage lesion area, and reduce cracks. Although bRFE produced timely chondrocyte damage, this was alleviated on subsequent recovery. Therefore, bRFE with appropriate energy is beneficial to the recovery of cartilage damage, proper attention should be paid to the recovery period.

Facile green preparation of single- and two-component modified activated carbon fibers for efficient trace heavy metals removal from drinking water.

Trace heavy metals exist in drinking water, having great adverse effects on human health and making it a huge challenge to remove. Herein, novel materials have been prepared by a simple and green method using single- (polydopamine (PDA) or 2,3-dimercaptopropanesulfonic sodium (DMPS)) (PDA-OACF or DMPS-OACF) and two-component (PDA and DMPS) (DMPS-PDA-OACF) functionalized activated carbon fibers pretreated by hydrogen peroxide for the removal of trace heavy metals. The as-prepared DMPS-OACF (7.5,20) under DMPS addition of 7.5 mg and sonication time of 20 min retained large specific surface area, micro-mesoporous structure and rich functional groups and showed better adsorption performance for trace lead and mercury. It also exhibited wide applicable ranges of pH (3.50-10.50) and concentration (50-1136 µg L-1), rapid adsorption kinetics, and excellently selective removal performance for trace lead. The maximum lead adsorption capacity reached 16.03 mg g-1 when the effluent lead concentration met World Health Organization (WHO) standard and the adsorbent can be regenerated by EDTA solution. The fitting results of adsorption kinetics and isotherm models revealed that the lead adsorption process was multi-site adsorption on heterogeneous surfaces and chemical adsorption. The excellent adsorption properties for trace heavy metals were attributed that the sulfur/oxygen/nitrogen-containing functional groups boosted diffusion and adsorption by electrostatic attraction and coordination, suggesting that DMPS-OACF (7.5,20) has great application potential in the removal of trace heavy metals.