Effects of Changes in the Levels of Damage-Associated Molecular Patterns Following Continuous Veno–Venous Hemofiltration Therapy on Outcomes in Acute Kidney Injury Patients With Sepsis

Background: We investigated the association of damage-associated molecular pattern (DAMP) removal with mortality in sepsis patients undergoing continuous veno–venous hemofiltration (CVVH).Methods: Circulating levels of DAMPs [mitochondrial DNA (mtDNA); nuclear DNA (nDNA); heat shock protein 70 (HSP70); and high mobility group box 1 (HMGB1)] and cytokines were measured at baseline, 6 and 12 h after initiation of CVVH. Urinary DNA levels were analyzed at baseline and end of CVVH. The expression of human leukocyte antigen (HLA)-DR was assayed at 0, 3, and 7 days after initiation of CVVH. Moreover, the effects of HSP70 and HMGB1 clearance on survival were analyzed.Results: We evaluated 43 patients with acute kidney injury (AKI) (33 sepsis patients). Twenty-two sepsis patients (67%) and three non-sepsis patients (30%) expired (P = 0.046). Significant reductions in the levels of circulating interleukin-6 (P = 0.046) and tumor necrosis factor-α (P = 0.008) were found in the sepsis group. The levels of mtDNA were increased (ND2, P = 0.035; D-loop, P = 0.003), whereas that of HSP70 was reduced (P = 0.000) in all patients during the first 12 h. The levels of DAMPs in the plasma were markedly increased after blood passage from the inlet through the dialyzer in survivor sepsis patients. The clearance rates of HSP70 and HMGB1 were good predictors of mortality [area under the curve (AUC) = 0.937, P = 0.000; AUC = 0.90, P = 0.001, respectively]. The level of HLA-DR was increased in response to higher HSP70 clearance (P = 0.006). Survival was significantly worse in groups with higher clearance rates of HSP70 and HMGB1 than the cut-off value (log-rank test: P = 0.000 for both). Higher HSP70 clearance was a significant independent predictor of mortality (odds ratio = 1.025, 95% confidence interval [CI]: 1.012–1.039, P = 0.000). The urinary nDNA (β-globin) level before CVVH was an independent risk factor for the duration of CVVH in patients with sepsis (sRE = 0.460, 95% CI: 1.720–8.857, P = 0.005).Conclusion: CVVH removes inflammatory factors, reduces urinary DAMPs, and removes plasma DAMPs. However, survival decreases in response to higher HSP70 clearance

Patterned nanostructure in AgCo/Pt/MgO(001) thin film

The formation of patterned nanostructure in AgCo/Pt/MgO(001) thin film is simulated by a technique of combining molecular dynamics and phase-field theory. The dislocation (strain) network existing in Pt/MgO is used as a template whose pattern is transferred to AgCo phase in spinodal decomposition, resulting in regular arrays of Co islands that are attracted by the dislocations. The influence of various factors, such as component concentration and film thickness, is studied. It is found that the spinodal decomposition of AgCo in this system is mainly characterized by a competition between a surface-directed layer structure and the strain-induced patterned structure, where the patterned Ag-Co structure only dominates in a small range near the interface (less than 10 atomic layers). However, if the interlayer diffusion can be minimized by controlling film growth conditions, it is shown that the patterned structure can be formed throughout the entire film.Comment: 8 pages, 12 figure

Design and Occupant-Protection Performance Analysis of a New Tubular Driver Airbag

An airbag is an effective protective device for vehicle occupant safety, but may cause unexpected injury from the excessive energy of ignition when it is deployed. This paper focuses on the design of a new tubular driver airbag from the perspective of reducing the dosage of gas generant. Three different dummies were selected for computer simulation to investigate the stiffness and protection performance of the new airbag. Next, a multi-objective optimization of the 50th percentile dummy was conducted. The results show that the static volume of the new airbag is only about 1/3 of the volume of an ordinary one, and the injury value of each type of dummy can meet legal requirements while reducing the gas dosage by at least 30%. The combined injury index (Pcomb) decreases by 22% and the gas dosage is reduced by 32% after optimization. This study demonstrates that the new tubular driver airbag has great potential for protection in terms of reducing the gas dosage. Keywords: New tubular airbag, Occupant protection, Multi-objective optimizatio

Tuning chemical short-range order for simultaneous strength and toughness enhancement in NiCoCr medium-entropy alloys

The pursuit of enhancing strength and toughness remains a critical endeavor in the field of structural materials. This study explores two distinct strategies to overcome the traditional strength-toughness trade-off. Specifically, we manipulate the chemical composition and shortrange order (SRO) of the NiCoCr medium-entropy alloy, which has shown remarkable fracture toughness in recent experiments. Utilizing molecular dynamics simulations, we uncover nanoscale deformation mechanisms during crack propagation. Our findings highlight that optimizing the SRO degree leads to improvements in both atomic scale strength and toughness defined as the area underneath stress-strain curves from MD simulations. In contrast, a trade-off between strength and toughness persists when only manipulating the Ni content in the NiCoCr alloy. Based on the simulation results, we establish a strong correlation between toughness, strength, surface energies, and unstable stacking fault energies. These factors are influenced by the chemical composition and SROs in NiCoCr, with SROs acting as strong obstacles to dislocations, thereby contributing to additional strength. The exceptional toughness of NiCoCr with SRO arises from a synergy of intrinsic and extrinsic mechanisms, including dislocation glide, nanobridging during nanovoid coalescence and zigzag crack path. It is found that, in the presence of SRO, intrinsic toughening mechanisms usually associated with crack tip blunting and dissipation can also facilitate the onset of extrinsic toughening mechanisms of nanobridging and zig-zag crack path associated with nanovoid formation and coalescence. This study emphasizes the importance of tailoring SRO in designing materials with enhanced strength and toughness

Molecular Simulations on Tuning the Interlayer Spacing of Graphene Nanoslits for C4H6/C4H10 Separation

There are great challenges in developing efficient membranes to replace the currently energy-intensive cryogenic distillation processes for purifying C4H6 from C4H6/C4H10 mixtures due to their similar physical and chemical properties. Here, we investigated the performance of graphene slits with different interlayer spacings for C4H6/C4H10 separation via molecular simulations. The results demonstrate that the 3.4-angstrom-interlayer-spacing graphene slit only allows the penetration of C4H6 due to the size sieving effect and the permeance of C4H6 is up to 2.09 x 10(6) GPU. When the interlayer spacing increases to 3.6-6.8 angstrom, the graphene slits still exhibit the preferential penetration for C4H6 over C4H10 due to the pi-pi adsorption interaction between graphene sheets and C4H6. Surprisingly, the graphene slits (>10.2 angstrom) exhibit the preferential penetration for C4H10 over C4H6 owing to the diffusivity of C4H10 being much larger than that of C4H6 under confined conditions. In conclusion, by fine-tuning the interlayer spacing of graphene slits, the dominant separation mechanism is switched in the order of size sieving, thermodynamic adsorption, and dynamic diffusion, thereby achieving the controllable regulation of the preferential permeation from C4H6 to C4H10. C4H10 -selective membranes are of great significance for energy saving. The tuning strategy is expected to be applied in different paraffin/olefin separation scenarios such as high-content and low-content olefin feedstocks

Antagonistic and Plant Growth-Promoting Properties of <i>Streptomyces</i> F2 Isolated from Vineyard Soil

Streptomyces can produce secondary metabolites with a wide range of activities and is often used in agriculture as a biocontrol strain to control soil-borne diseases. Screening and isolation from infected soil is an effective method to obtain active strains. In this study, the best antagonistic inter-root growth-promoting bacteria were isolated from grapevine inter-root soil samples, and strain F2 was identified as Streptomyces sp. based on morphological, physiological, and biochemical characteristics as well as 16S rDNA sequencing results. The results showed that the fermentation broth/liquid and sterile filtrate of strain F2 exhibited antagonistic effects against 10 plant pathogens, with an inhibition rate reaching up to 80%. Notably, two of them exhibited remarkable inhibitory effects against Phytophthora capsici with inhibition rates of 80.58% and 87.71%, respectively. The P. capsici leaf control experiment revealed that the control effect of strain F2 fermentation liquid on P. capsici filaments was 61.09%. Furthermore, indoor pot experiments demonstrated that the fermentation liquid of strain F2 had a significant inhibitory effect on pepper blight, with a maximum inhibition of 83.31%. Antagonistic factor analysis indicated that strain F2 had specific organophosphorus hydrolysis, nitrogen fixation, extracellular protease secretion, and IAA production capabilities. Additionally, root treatment with strain F2’s fermentation liquid significantly enhanced capsicum growth. Taking together, Streptomyces F2 not only exhibits a wide-spectrum antagonistic effect against plant pathogens but also promotes plant growth, which suggests that Streptomyces F2 can be used as an effective biological control resource and provides important theoretical support for the application of Streptomyces F2

What Can Facial Movements Reveal? Depression Recognition and Analysis Based on Optical Flow Using Bayesian Networks

Recent evidence have demonstrated that facial expressions could be a valid and important aspect for depression recognition. Although various works have been achieved in automatic depression recognition, it is a challenge to explore the inherent nuances of facial expressions that might reveal the underlying differences between depressed patients and healthy subjects under different stimuli. There is a lack of an undisturbed system that monitors depressive patients&#x2019; mental states in various free-living scenarios, so this paper steps towards building a classification model where data collection, feature extraction, depression recognition and facial actions analysis are conducted to infer the differences of facial movements between depressive patients and healthy subjects. In this study, we firstly present a plan of dividing facial regions of interest to extract optical flow features of facial expressions for depression recognition. We then propose facial movements coefficients utilising discrete wavelet transformation. Specifically, Bayesian Networks equipped with construction of Pearson Correlation Coefficients based on discrete wavelet transformation is learnt, which allows for analysing movements of different facial regions. We evaluate our method on a clinically validated dataset of 30 depressed patients and 30 healthy control subjects, and experiments results obtained the accuracy and recall of 81.7&#x0025;, 96.7&#x0025;, respectively, outperforming other features for comparison. Most importantly, the Bayesian Networks we built on the coefficients under different stimuli may reveal some facial action patterns of depressed subjects, which have a potential to assist the automatic diagnosis of depression