Miracle-dz/UniFAR-FTUs huggingface dataset:
Early renal injury indicators can help evaluate renal injury in patients with chronic hepatitis B with long-term nucleos(t)ide therapy

BACKGROUND Patients with chronic hepatitis B (CHB) with long-term nucleos(t)ide therapy may experience renal insufficiency. Traditional renal function indicators, such as urine protein, serum urea nitrogen (BUN), and serum creatinine, are normal when early mild lesions occur. Therefore, more sensitive renal function indicators are needed. AIM To investigate the significance of early renal injury indicators in evaluating renal injury in patients with CHB with long-term nucleos(t)ide therapy. METHODS We collected the clinical data of 69 outpatients with CHB at Peking University First Hospital from March 2018 to January 2020 who had been treated with long-term nucleos(t)ide therapy and analyzed the results of early renal injury indicators. Continuous normal distribution data were analyzed by the t-test to determine the difference between two groups. Continuous non-normally distributed data were analyzed by the Mann-Whitney U-test between two groups. The Kruskal-Wallis H test was used to determine the differences among multiple groups. Enumeration data were analyzed by the chi-square test. The related factors of early renal injury indicators were analyzed by logistic regression analysis. RESULTS The average treatment duration with nucleos(t)ide analogs of the 69 patients with CHB was 99.7 ± 28.7 mo. The cases of patients with elevated BUN and hypophosphatemia were 6 (8.7%) and 13 (18.8%), respectively; 31 (44.9%) patients had abnormal early renal injury indicators, including 9 patients with abnormal urine microalbumin, 7 patients with abnormal urine immunoglobulin, 6 patients with abnormal urine transferrin, and 19 patients with abnormal α1 microglobulin. There were no significant differences in the mean values of age, sex, BUN, estimated glomerular filtration rate (eGFR), serum uric acid, serum calcium, or serum phosphorus between the two groups of patients with and without early renal injury indicators. However, the mean levels of serum creatinine and urine creatinine, N-acetyl-β-D-glucosidase enzyme, α1 microglobulin, and urine immunoglobulin in the former group of patients were significantly higher than those in the latter group of patients (P < 0.05). The incidence of early renal injury in patients with eGFR ≥ 90, 60-89, and 30-59 mL/(min·1.73 m2) was 36.4% (8/22), 47.6% (20/42), and 60% (3/5), respectively. Logistic regression analysis results showed that gamma-glutamyl transpeptidase [odds ratio (OR) = 1.05 (1.008-1.093), P = 0.020], direct bilirubin [OR = 1.548 (1.111-2.159), P = 0.010], serum creatinine [OR = 1.079 (1.022-1.139), P = 0.006], and age [OR = 0.981 (0.942-1.022), P = 0.357] were independent predictors of early renal injury. CONCLUSION Patients with CHB treated with long-term nucleos(t)ide analog therapy had a high probability of early renal injury, and early renal injury indicators were highly sensitive and could be used to monitor early renal impairment.
Review of Kelvin's Equation and Its Modification in Characterization of Mesoporous Materials

Physical and mathematical models as well as calculation methods of nitrogen bed on porous media have been introduced to evaluate the structural parameters of mesoporous materials. Kelvin's equation is a link between the relative adsorbate pressure, the mean pore radius, and pore capillarity on the basis of macroscopic capillary condensation. However, Kelvin's equation has been identified that it underestimates the calculated pore size of a material especially in the boundary of pore size which is between 2 and 4 nm. Various modifications on Kelvin's equation were mentioned in order to develop a new model to improve the accuracy of pore size calculation. The problems on conventional mathematical models were analyzed and discussed. A number of calculation methods on physisorption and pore size, especially fundamental theories of physisorption, basis of models and their deficiencies are reviewed. It can provide guidance on developing a modified Kelvin's equation for pore size calculation.
LncRNA XIST acts as a MicroRNA-520 sponge to regulate the Cisplatin resistance in NSCLC cells by mediating BAX through CeRNA network

Background: In recent years, LncRNA acts as a member of competing endogenous RNA (ceRNA), playing an important role in drug resistance of lung cancer. The aim of this study was to identify potential biomarkers about cisplatin resistant lung cancer cells using a comprehensive ceRNA network. Methods: GSE6410 (GPL-201) analyzed gene expression changes about cisplatin resistance in A549 NSCLC cells. GSE43249 (GPL-14613) included noncoding RNA expression profiling derived from the cisplatin resistant A549 lung cells. GEO2R, an online analysis tool, analyzed the differentially expressed mRNAs and miRNAs (DEmRNAs and DEmiRNAs). To explore the functional enrichment implication of differentially expressed mRNAs, we used the GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Through miRDB, Targetscan, Starbase and miRWalk, we found targeted miRNAs. The Kaplan-Meier curve method was used to show clinical survival analysis of targeted RNAs (P<0.05). The Starbase database predicted potential lncRNAs mediated targeted miRNAs. Eventually, the novel ceRNA network of lncRNAs, miRNAs, mRNA was constructed by cytoscape3.7. 2. Results: 118 differentially expressed mRNAs were the basis of the mediated ceRNA network. DAVID and Kaplan-Meier picked out BAX, an apoptosis regulator. Venn diagram demonstrated 8 miRNAs commonly regulating BAX. Starbase predicted lncRNA XIST mediated miRNAs. Finally, lncRNA XIST may be a useful biomarker regulating cisplatin resistance in lung cancer cells and further, we explored the BAX may effect tumor-infiltrating immune cells. Conclusions: LncRNA XIST competitively bound to miRNA 520 in the regulation of cisplatin resistance by BAX, participating apoptosis in the p53 signaling pathway.
Separation of methanol from methanol/water mixtures with pervaporation hybrid membranes

A series of pervaporation (PV) hybrid membranes were prepared via the crosslinking of poly(vinyl alcohol) with formaldehyde solution with N-3-(trimethoxysilyl) propyl ethylenediamine (TMSPEDA) as a hybrid precursor of the sol–gel process. Both the thermal stability and separation performances of the prepared hybrid membranes were investigated. Thermogravimetric analysis showed that the thermal degradation temperature of the hybrid membranes was beyond 250°C. Differential scanning calorimetry indicated that both the glass-transition temperature and the crystallization temperature increased with elevated TMSPEDA contents in the hybrid membranes. PV experiments demonstrated that for membranes A–D, both the permeation flux and separation factor indicated the same trade-off effect. Moreover, it was found that for individual membranes, the permeation flux increased as the feed temperature was increased. Meanwhile, the separation factor revealed an change trend opposite to that of the permeation flux. Furthermore, proper addition of TMSPEDA in the hybrid membrane was found to reduce the permeation activation energy. On the basis of these findings, we deduced that these hybrid membranes have potential applications in the separation of methanol/water mixtures. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
Protein binding to soft polymeric layers: a quantitative study by fluorescence spectroscopy

We present a comprehensive investigation of the adsorption of several proteins, i.e., lysozyme, β-D-glucosidase, and cytochrome c, onto microgels in aqueous solution. The microgels consist of a solid core from polystyrene (PS) onto which a shell of poly(N-isopropylacrylamide) (pNiPAm) together with 10 mol% acrylic acid is grafted. The pronounced fluorescence response observed upon transfer of fluorescent marked lysozyme from the bulk solution to the gel allows us to monitor its uptake by the shell in situ. All data demonstrate directly that full equilibrium is reached rendering the binding of proteins to the particles as a reversible process. We also study the competitive adsorption of lysozyme with cytochrome c or β-D-glucosidase. Here we show that the data obtained for a mixture of lysozyme and cytochrome c can be modeled quantitatively by a competitive Langmuir isotherm. Using time-resolved fluorescence spectroscopy we elucidate the kinetics of protein adsorption. We find that the uptake of proteins by these particles is described by a fast, diffusion-limited binding regime which is followed by a slow binding regime, most probably caused by a slow rearrangement of the proteins within the network. All data demonstrate that charged pNiPAm-microgels present a model system for which the thermodynamics and kinetics of protein adsorption including competitive adsorption can be analyzed in a quantitative manner.
Angucycline-like Aromatic Polyketide from a Novel Streptomyces Species Reveals Freshwater Snail Physa acuta as Underexplored Reservoir for Antibiotic-Producing Actinomycetes

Simple Summary The current study shows that freshwater snails can be considered as new sources for bioactive metabolites, since a novel Streptomyces species 7NS3 produced four active compounds against Gram-positive bacteria. One of the compounds was an angucycline-like aromatic polyketide matched with a known compound, emycin A. Genome mining studies based on the whole-genome sequence of 7NS3 resulted in the identification of a gene cluster potentially coding for emycin A biosynthesis. Abstract Antibiotic producers have mainly been isolated from soil, which often has led to the rediscovery of known compounds. In this study, we identified the freshwater snail Physa acuta as an unexplored source for new antibiotic producers. The bacterial diversity associated with the snail was characterized by a metagenomic approach using cultivation-independent high-throughput sequencing. Although Actinobacteria represented only 2% of the bacterial community, the focus was laid on the isolation of the genus Streptomyces due to its potential to produce antibiotics. Three Streptomyces strains (7NS1, 7NS2 and 7NS3) were isolated from P. acuta, and the antimicrobial activity of the crude extracts were tested against a selection of Gram-positive and Gram-negative bacteria and fungi. 7NS3 showed the strongest activity against Gram-positive bacteria and, thus, was selected for genome sequencing and a phylogenomic analysis. 7NS3 represents a novel Streptomyces species, which was deposited as Streptomyces sp. DSM 110735 at the Leibniz Institute-German Collection of Microorganisms and Cell Cultures (DSMZ). Bioassay-guided high-performance liquid chromatography (HPLC) and high-resolution electrospray ionization-mass spectrometry (HR-ESI-MS) analyses of crude extract fractions resulted in the detection of four compounds, one of which matched the compound characteristics of emycin A, an angucycline-like aromatic polyketide. Genome mining studies based on the whole-genome sequence of 7NS3 resulted in the identification of a gene cluster potentially coding for emycin A biosynthesis. Our study demonstrates that freshwater snails like P. acuta can represent promising reservoirs for the isolation of new antibiotic-producing actinobacterial species.
Microwave absorption properties of MWCNT-SiC composites synthesized via a low temperature induced reaction

The composites containing SiC and multiwalled carbon nanotubes (MWCNTs) were synthesized via the reaction of Si powders and MWCNTs induced by that of Na and sulfur. The MWCNT-SiC composites prepared at 600 °C exhibit excellent microwave absorbing properties, which reach a minimum reflection loss of -38.7 dB at a frequency around 12.9 GHz. The absorbing properties are bound up with the high yield of porous SiC spheres comprised of nanocrystals. The porous structure, high density of stacking faults in SiC crystallites, interfaces between MWCNTs and SiC spheres, grain boundaries between SiC nanocrystals, as well as the interfacial polarizations aroused therefrom, are responsible for the excellent microwave absorbing properties.
Enzyme Reactions in Microstructured Media. Subtilisin Catalysis in Alkyl Glucopyranosides Aggregates

In order to understand the effect of the structures of the surrounding medium on biocatalytic reactions, hydrolytic catalysis by subtilisin Carlsberg in a ternary system containing octyl β-D-glucopyranoside (β-OG), water, and octanol (OcOH) was studied, with special reference to the enzyme reactivity and the morphology of the surfactant aggregates. First, the effect of β-OG and other alkyl D-glucopyranosides (AG) on the subtilisin reaction was studied in the surfactant/water binary system; all four surfactants tested were found to inhibit the subtilisin catalysis. Then, a detailed phase diagram of β-OG/water/octanol was determined and several liquid crystalline phases were found. When the subtilisin reactions were measured in several compositions in the phase diagram, the maximum of the apparent rate was observed in reversed micells as well as in the reversed hexagonal phase at a certain [water]/[surfactant] ratio (wo). The apparent optimal wo was calculated to be around 5—6. These results were compared w.
The Chemistry of Hydrocarbon Ions in the Jovian Ionosphere

Abstract We have modeled the chemistry of hydrocarbon ions in the jovian ionosphere. We find that a layer of hydrocarbon ions is formed in the altitude range 300-400 km above the ammonia cloud tops, due largely to direct ionization of hydrocarbons by photons in the wings of the H2 absorption lines in the 912- to 1100-A region that penetrate to below the methane homopause. We have explicitly included in the model 156 ion-neutral reactions involving hydrocarbon ions with up to two carbon atoms. Larger hydrocarbon ions are included as two pseudoions, C3H+n and C4H+n. The model shows that 15 reactions of H+, CH+3, CH+5, C2H+3, C2H+4, C2H+5, AND C2H+6 with hydrocarbon neutrals are the major processes that are responsible for the production and growth of C1-, C2- and C3- or C-4ions in the hydrocarbon ion layer. The model also shows that ions initially produced in the hydrocarbon ion layer are converted into hydrocarbon ions with more than two carbon atoms with very little loss by recombination. It is likely that successive hydrocarbon ion-neutral reactions continue to produce even larger hydrocarbon ions, so the terminal ions probably have more than three or four carbon atoms. In the auroral regions, the chemistry of hydrocarbon ions may modify the densities of neutral hydrocarbons, especially C2H2 in the upper mesosphere, and may play a major role in the production of polar haze particles.
Innovative Bioactive Ag-SiO2/TiO2 Coating on a NiTi Shape Memory Alloy: Structure and Mechanism of Its Formation

In recent years, more and more emphasis has been placed on the development and functionalization of metallic substrates for medical applications to improve their properties and increase their applicability. Today, there are many different types of approaches and materials that are used for this purpose. Our idea was based on a combination of a chemically synthesized Ag-SiO2 nanocomposite and the electrophoretic deposition approach on a NiTi shape memory substrate. As a result, silver-silica coating was developed on a previously passivated alloy, which was then subjected to sintering at 700 °C for 2 h. The micrometer-sized coat-forming material was composed of large agglomerates consisting of silica and a thin film of submicron- and nano- spherical-shaped particles built of silver, carbon, and oxygen. Structurally, the coatings consisted of a combination of nanometer-sized silver-carbonate that was embedded in thin amorphous silica and siloxy network. The temperature impact had forced morphological and structural changes such as the consolidation of the coat-forming material, and the partial coalescence of the silver and silica particles. As a result, a new continuous complex ceramic coating was formed and was analyzed in more detail using the XPS, XRD, and Raman methods. According to the structural and chemical analyses, the deposited Ag-SiO2 nanocomposite material’s reorganization was due to its reaction with a passivated TiO2 layer, which formed an atypical glass-like composite that consisted of SiO2-TiO2 with silver particles that stabilized the network. Finally, the functionalization of the NiTi surface did not block the shape memory effect.
Femur Auxetic Meta-Implants with Tuned Micromotion Distribution

Stress shielding and micromotions are the most significant problems occurring at the bone-implants interface due to a mismatch of their mechanical properties. Mechanical 3D metamaterials, with their exceptional behaviour and characteristics, can provide an opportunity to solve the mismatch of mechanical properties between the bone and implant. In this study, a new porous femoral hip meta-implant with graded Poisson’s ratio distribution was introduced and its results were compared to three other femoral hip implants (one solid implant, and two porous meta-implants, one with positive and the other with a negative distribution of Poisson’s ratio) in terms of stress and micromotion distributions. For this aim, first, a well-known auxetic 3D re-entrant structure was studied analytically, and precise closed-form analytical relationships for its elastic modulus and Poisson’s ratio were derived. The results of the analytical solution for mechanical properties of the 3D re-entrant structure presented great improvements in comparison to previous analytical studies on the structure. Moreover, the implementation of the re-entrant structure in the hip implant provided very smooth results for stress and strain distributions in the lattice meta-implants and could solve the stress shielding problem which occurred in the solid implant. The lattice meta-implant based on the graded unit cell distribution presented smoother stress-strain distribution in comparison with the other lattice meta-implants. Moreover, the graded lattice meta-implant gave minimum areas of local stress and local strain concentration at the contact region of the implants with the internal bone surfaces. Among all the cases, the graded meta-implant also gave micromotion levels which are the closest to values reported to be desirable for bone growth (40 µm).
Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study

Background A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making regarding a service response in terms of more detailed assessments and/or intervention. The aim of this study was to predict self-harm within six-months after initial presentation. Method The study included 1962 young people (12–30 years) presenting to youth mental health services in Australia. Six machine learning algorithms were trained and tested with ten repeats of ten-fold cross-validation. The net benefit of these models were evaluated using decision curve analysis. Results Out of 1962 young people, 320 (16%) engaged in self-harm in the six months after first assessment and 1642 (84%) did not. The top 25% of young people as ranked by mean predicted probability accounted for 51.6% - 56.2% of all who engaged in self-harm. By the top 50%, this increased to 82.1%-84.4%. Models demonstrated fair overall prediction (AUROCs; 0.744–0.755) and calibration which indicates that predicted probabilities were close to the true probabilities (brier scores; 0.185–0.196). The net benefit of these models were positive and superior to the ‘treat everyone’ strategy. The strongest predictors were (in ranked order); a history of self-harm, age, social and occupational functioning, sex, bipolar disorder, psychosis-like experiences, treatment with antipsychotics, and a history of suicide ideation. Conclusion Prediction models for self-harm may have utility to identify a large sub population who would benefit from further assessment and targeted (low intensity) interventions. Such models could enhance health service approaches to identify and reduce self-harm, a considerable source of distress, morbidity, ongoing health care utilisation and mortality.
Hypoxia-inducible factor 1 alpha limits dendritic cell stimulation of CD8 T cell immunity

Dendritic cells are sentinels of the immune system and represent a key cell in the activation of the adaptive immune response. Hypoxia-inducible factor 1 alpha (HIF-1α)–a crucial oxygen sensor stabilized during hypoxic conditions–has been shown to have both activating and inhibitory effects in immune cells in a context- and cell-dependent manner. Previous studies have demonstrated that in some immune cell types, HIF-1α serves a pro-inflammatory role. Genetic deletion of HIF-1α in macrophages has been reported to reduce their pro-inflammatory function. In contrast, loss of HIF-1α enhanced the pro-inflammatory activity of dendritic cells in a bacterial infection model. In this study, we aimed to further clarify the effects of HIF-1α in dendritic cells. Constitutive expression of HIF-1α resulted in diminished immunostimulatory capacity of dendritic cells in vivo, while conditional deletion of HIF-1α in dendritic cells enhanced their ability to induce a cytotoxic T cell response. HIF-1α-expressing dendritic cells demonstrated increased production of inhibitory mediators including IL-10, iNOS and VEGF, which correlated with their reduced capacity to drive effector CD8+ T cell function. Altogether, these data reveal that HIF-1α can promote the anti-inflammatory functions of dendritic cells and provides insight into dysfunctional immune responses in the context of HIF-1α activation.
Boundary-Aware Supervoxel-Level Iteratively Refined Interactive 3D Image Segmentation With Multi-Agent Reinforcement Learning

Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative in nature, most existing interactive segmentation methods tend to ignore the dynamics of successive interactions and take each interaction independently. We here propose to model iterative interactive image segmentation with a Markov decision process (MDP) and solve it with reinforcement learning (RL) where each voxel is treated as an agent. Considering the large exploration space for voxel-wise prediction and the dependence among neighboring voxels for the segmentation tasks, multi-agent reinforcement learning is adopted, where the voxel-level policy is shared among agents. Considering that boundary voxels are more important for segmentation, we further introduce a boundary-aware reward, which consists of a global reward in the form of relative cross-entropy gain, to update the policy in a constrained direction, and a boundary reward in the form of relative weight, to emphasize the correctness of boundary predictions. To combine the advantages of different types of interactions, i. e. , simple and efficient for point-clicking, and stable and robust for scribbles, we propose a supervoxel-clicking based interaction design. Experimental results on four benchmark datasets have shown that the proposed method significantly outperforms the state-of-the-arts, with the advantage of fewer interactions, higher accuracy, and enhanced robustness.