Synergistic Conductivity and Electromagnetic Interference Shielding Effectiveness of Epoxy/Carbon Fiber and Epoxy/Carbon Black Composites via Mixing with Bamboo Charcoal

This study was aimed at preparing electromagnetic interference (EMI) shielding materials based on carbon black (CB), carbon fiber (CF), bamboo charcoal (BC), and epoxy resin. The effects of adding bamboo charcoal on the mechanical properties and electrical resistivity of epoxy composites were studied. Scanning electron microscopic (SEM) analysis, electrical resistivity, and electromagnetic interference (EMI) shielding effectiveness were also investigated. The composites were prepared at 120 °C by the curing-molding method through blending the fillers in epoxy resin. The results revealed that the BC/CB and BC/CF composites had perfect conductive network structure and resulted in better dynamic thermal mechanical properties. The electrical resistivity declined with the increase of bamboo charcoal contents; consequently, the EMI shielding effectiveness improved gradually. The lowest electrical resistivity, down to 0.071 Ω·m, corresponded to the best EMI shielding effectiveness of BC/CF composites, which could be above 60 dB over a frequency range of 30 MHz to 1500 MHz while the carbon fiber content was at 40 wt.%

A causal relationship between panic disorder and risk of alzheimer disease: a two-sample mendelian randomization analysis

Abstract Background Observational studies have suggested a link between panic disorder (PD) and Alzheimer disease (AD). This study aimed to identify the underlying association of PD with the risk of AD using Mendelian randomization. Methods Genetic instrumental variables (IVs) were retrieved in the genome-wide association study between PD and AD. Then, five different models, namely inverse variance weighting (IVW), weighted median, weighted mode, MR-Egger and MR-robust adjusted profile scores (MR-RAPS), were used for MR Analysis. Finally, the heterogeneity and pleiotropy of identified IVs were verified by multiple sensitivity tests. Results The Cochran’s Q test based on MR Egger and IVW showed that no evidence of heterogeneity was found in the effects of instrumental variables, so a fixed-effect model was used. IVW analysis (OR 1.000479, 95% CI [1.000147056, 1.000811539], p = 0.005) indicated that PD was associated with an increased risk of AD, and a causal association existed between them. Meanwhile, weighted median (OR 1.000513373, 95% CI [1.000052145, 1.000974814], p = 0.029) and MR-RAPS (OR 1.000510118, 95% CI [1.000148046, 1.00087232], p = 0.006) also showed the similar findings. In addition, extensive sensitivity analyses confirmed the robustness and accuracy of these results. Conclusion This investigation provides evidence of a potential causal relationship between PD and the increased risk of AD. Based on our MR results, when diagnosing and treating patients with PD, clinicians should pay more attention to their AD-related symptoms to choose therapeutic measures or minimize comorbidities. Furthermore, the development of drugs that improve both PD and AD may better treat patients with these comorbidities

Lightweight Cellulose/Carbon Fiber Composite Foam for Electromagnetic Interference (EMI) Shielding

Lightweight electromagnetic interference shielding cellulose foam/carbon fiber composites were prepared by blending cellulose foam solution with carbon fibers and then freeze drying. Two kinds of carbon fiber (diameter of 7 μm) with different lengths were used, short carbon fibers (SCF, L/D = 100) and long carbon fibers (LCF, L/D = 300). It was observed that SCFs and LCFs built efficient network structures during the foaming process. Furthermore, the foaming process significantly increased the specific electromagnetic interference shielding effectiveness from 10 to 60 dB. In addition, cellulose/carbon fiber composite foams possessed good mechanical properties and low thermal conductivity of 0.021⁻0.046 W/(m·K)

A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications

The development of analytical and computational techniques and growing scientific funds collectively contribute to the rapid accumulation of geoscience data. The massive amount of existing data, the increasing complexity, and the rapid acquisition rates require novel approaches to efficiently discover scientific stories embedded in the data related to geochemistry and cosmochemistry. Machine learning methods can discover and describe the hidden patterns in intricate geochemical and cosmochemical big data. In recent years, considerable efforts have been devoted to the applications of machine learning methods in geochemistry and cosmochemistry. Here, we review the main applications including rock and sediment identification, digital mapping, water and soil quality prediction, and deep space exploration. Research method improvements, such as spectroscopy interpretation, numerical modeling, and molecular machine learning, are also discussed. Based on the up-to-date machine learning/deep learning techniques, we foresee the vast opportunities of implementing artificial intelligence and developing databases in geochemistry and cosmochemistry studies, as well as communicating geochemists/ cosmochemists and data scientists

Hydrophobic Modification of Nanocellulose via a Two-Step Silanation Method

Dodecyltrimethoxysilane (DTMOS), which is a silanation modifier, was grafted onto nanocellulose crystals (NCC) through a two-step method using KH560 (ɤ-(2,3-epoxyproxy)propytrimethoxysilane) as a linker to improve the hydrophobicity of NCC. The reaction mechanism of NCC with KH560 and DTMOS and its surface chemical characteristics were investigated using Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and HCl–acetone titration. These analyses confirmed that KH560 was grafted onto the surface of NCC through the ring-opening reaction, before DTMOS was covalently grafted onto the surface of NCC using KH560 as a linker. The grafting of NCC with DTMOS resulted in an improvement in its hydrophobicity due to an increase in its water contact angle from 0° to about 140°. In addition, the modified NCC also possessed enhanced thermal stability

Effects of Protein Restriction and Subsequent Realimentation on Body Composition, Gut Microbiota and Metabolite Profiles in Weaned Piglets

The objective of this study was to evaluate the effects of protein restriction and subsequent protein realimentation on the body composition, gut microbiota and metabolite profiles of piglets. Fifty weaned piglets were randomly assigned to two treatments: a normal protein (NP) group (20% crude protein (CP)) or a low protein (LP) group (16% CP) with five animals per pen and five pens per group. Treatment diets were fed for 14 d during the protein restriction phase, and then all pigs were fed the same nursery diets with a normal CP level (19% CP) during the protein realimentation phase until they reached an average target body weight (BW) of 25 ± 0.15 kg. At day 14 and the end of the experiment, one piglet close to the average BW of each pen was slaughtered to determine body composition, microbial composition and microbial metabolites. Results showed that there was no difference (p > 0.05) in the experimental days to reach target BW between the LP and NP groups. The average daily gain (ADG) and gain:feed ratio (G:F) during the protein restriction phase as well as BW at day 14, were significantly decreased (p p > 0.05) during the protein realimentation phase and the overall experiment. Similarly, piglets in the LP group showed a significantly decreased body protein content (p p > 0.05) at the end of the experiment. The relative abundance of Parabacteroides, Butyricicoccus, Olsenella, Succinivibrio and Pseudoramibacter were significantly increased (p Alloprevotella and Faecalicoccus were significantly decreased (p p Parabacteroides, unidentified Christensenellaceae and Caproiciproducens, and a lower (p Prevotellaceae, Haemophilus, Marvinbryantia, Faecalibaculum, Neisseria and Dubosiella than those in the NP group. Metabolomics analyses indicated that tryptophan metabolism and vitamin metabolism were enriched in the LP group at day 14, and glycerophospholipid metabolism and fatty acid esters of hydroxy fatty acid metabolism were enriched at the end of the experiment. Moreover, Spearman’s correlation analysis demonstrated that the microbial composition was highly correlated with changes in colonic metabolites. Collectively, these results indicated that protein restriction and subsequent realimentation lead to compensatory growth and compensatory protein deposition in piglets and contribute to animal intestinal health by altering the gut microbiota and its metabolites

Additional file 1 of A causal relationship between panic disorder and risk of alzheimer disease: a two-sample mendelian randomization analysis

Supplementary Material

From agaric hydrogel to nitrogen-doped 3D porous carbon for high-performance Li–S batteries

Reproducible massive biochar with low cost has attracted great attentions due to their potential applications in the future environment and energy. In this work, a nitrogen-doped 3D porous agaric carbon (N-AC) with high specific surface area (1568.2 m2 g−1) was fabricated without adding any activator by using the agaric hydrogel as a precursor. And when employed as a sulfur host, the resulted N-AC–sulfur composite electrode with 60 wt% sulfur content illustrates a high reversible capacity of 875 mAh g−1 at 0.2 C (1 C = 1675 mA g−1) over 100 cycles as well as an excellent rate capability of 620 mAh g−1 at 2 C. Such excellent electrochemical performances could attribute to (1) the conductive carbon skeleton of N-AC that provides rapid electron/ion transfer; (2) abundant pores range from micropores to macropores in N-AC that are beneficial to accommodating the active sulfur and polysulfides and (3) the nitrogen dopants that provide polarized sites in chemical binding of polysulfides. In a word, this work provides a compelling avenue to the design of multifunctional sulfur host for advanced Li–S batteries

Enhanced In Vivo Antitumor Efficacy of Doxorubicin Encapsulated within Laponite Nanodisks

Development of various nanoscale drug carriers for enhanced antitumor therapy still remains a great challenge. In this study, laponite (LAP) nanodisks encapsulated with anticancer drug doxorubicin (DOX) at an exceptionally high loading efficiency (98.3 ± 0.77%) were used for tumor therapy applications. The long-term in vivo antitumor efficacy and toxicology of the prepared LAP/DOX complexes were analyzed using a tumor-bearing mouse model. Long-term tumor appearance, normalized tumor volume, CD31 staining, and hematoxylin and eosin (H&E)-stained tumor sections were used to evaluate the tumor therapy efficacy, while long-term animal body weight changes and H&E-stained tissue sections of different major organs were used to evaluate the toxicology of LAP/DOX complexes. Finally, the in vivo biodistribution of magnesium ions and DOX in different organs was analyzed. We showed that under the same DOX concentration, LAP/DOX complexes displayed enhanced tumor inhibition efficacy and afforded the treated mice with dramatically prolonged survival time. In vivo biodistribution data revealed that the reticuloendothelial systems (especially liver) had significantly higher magnesium uptake than other major organs, and the LAP carrier was able to be cleared out of the body at 45 days post treatment. Furthermore, LAP/DOX afforded a higher DOX uptake in the tumor region than free DOX, presumably due to the known enhanced permeability and retention effect. The developed LAP-based drug delivery system with an exceptionally high DOX payload, enhanced in vivo antitumor efficacy, and low systemic toxicity may be used as a promising platform for enhanced tumor therapy