Proteome and Glycoproteome Analyses Reveal Regulation of Protein Glycosylation Site-Specific Occupancy and Lysosomal Hydrolase Maturation by N-Glycan-Dependent ER-Quality Control.

N-Glycan-dependent endoplasmic reticulum quality control (ERQC) primarily mediates protein folding, which determines the fate of the polypeptide. Monoglucose residues on N-glycans determine whether the nascent N-glycosylated proteins enter into and escape from the calnexin (CANX)/calreticulin (CALR) cycle, which is a central system of the ERQC. To reveal the impact of ERQC on glycosylation and protein fate, we performed comprehensive quantitative proteomic and glycoproteomic analyses using cells defective in N-glycan-dependent ERQC. Deficiency of MOGS encoding the ER α-glucosidase I, CANX, or/and CALR broadly affected protein expression and glycosylation. Among the altered glycoproteins, the occupancy of oligomannosidic N-glycans was significantly affected. Besides the expected ER stress, proteins and glycoproteins involved in pathways for lysosome and viral infection are differentially changed in those deficient cells. We demonstrated that lysosomal hydrolases were not correctly modified with mannose-6-phosphates on the N-glycans and were directly secreted to the culture medium in N-glycan-dependent ERQC mutant cells. Overall, the CANX/CALR cycle promotes the correct folding of glycosylated peptides and influences the transport of lysosomal hydrolases.

Defect-Enabled Superior Negative Thermal Quenching in Palmierite Ba9La(VO4)7:Eu3+ for WLED In Situ Temperature Measuring.

Negative thermal quenching (NTQ) of the phosphors is critically important for both scientific research and practical applications, but the design of efficient NTQ phosphors is still a challenging task. Herein, we report a new strategy for developing NTQ materials by cation-vacancy engineering. Specifically, a new color-tunable Ba9La1-x(VO4):xEu3+ (BLVO:xEu3+) phosphor with abundant intrinsic cation vacancy was developed, exhibiting superior NTQ behavior under 365 nm excitation. The NTQ performance can be modulated via adjusting Eu3+ doping levels, and the emission intensity of Eu3+ ions in the BLVO:0.20Eu3+ phosphor increased by 275% at 473 K compared to room temperature. Furthermore, the reported material emitting bright white light under 365 nm excitation was well-suited for use in white light-emitting diode (WLED) phosphor and fluorescent temperature sensors, exhibiting outstanding color-rendering index (90.1) in lighting and high sensitivity (Sa = 11.83% K-1, Sr = 2.33% K-1) in temperature detecting. Lastly, the operating temperature of WLED at different currents can be monitored and displayed in real time through emission spectroscopy. All of the results demonstrated that the designed NTQ BLVO:xEu3+ can be used as a single-phase white phosphor and optical thermometry. This work provides a fresh perspective for designing high-efficient NTQ phosphors and expands the application of phosphors in WLED in situ temperature detection.

Small mass limit for stochastic interacting particle systems with Lévy noise and linear alignment force.

We study the small mass limit in mean field theory for an interacting particle system with non-Gaussian Lévy noise. When the Lévy noise has a finite second moment, we obtain the limit equation with convergence rate ε+1/εN, by taking first the mean field limit N→∞ and then the small mass limit ε→0. If the order of the two limits is exchanged, the limit equation remains the same but has a different convergence rate ε+1/N. However, when the Lévy noise is α-stable, which has an infinite second moment, we can only obtain the limit equation by taking first the small mass limit and then the mean field limit, with the convergence rate 1/Nα-1+1/Np2+εp/α where p∈(1,α). This provides an effectively limit model for an interacting particle system under a non-Gaussian Lévy fluctuation, with rigorous error estimates.

Carbon Dioxide Pressure and Catalyst Quantity Dependencies in Artificial Photosynthesis of Hydrocarbon Chains on Nanostructured Co/CoO Surfaces.

In this study, we investigated the influence of pressure and the quantity of Co/CoO catalyst on an artificial photosynthesis process that converts CO2 and H2O into hydrocarbons (CnH2n+2, where n ≤ 18). The adsorption of CO2 and H2O on Co/CoO surfaces proved to be pivotal in this photo-catalytic reaction. Photoexcited carbon dioxide and water molecules ((CO2)* and (H2O)*) generated by illuminating the catalyst surface led to the formation of alkene hydrocarbon molecules with carbon numbers following an approximate Poisson distribution. The optimal pressure was found to be 0.40 MPa. Pressure less than 0.40 MPa resulted in low CO2 adsorption, impeding excitation for photosynthesis. At greater pressure, oil/wax accumulation on Co/CoO surfaces hindered CO2 adsorption, limiting further photosynthesis reactions. The average number of carbon atoms in the hydrocarbons and hydrocarbon yield were correlated. The amount of Co/CoO was also found to affect the hydrocarbon yield. Our study contributes to the understanding of Co/CoO-catalyzed photosynthesis and suggests that an open-flow system could potentially enhance the productivity of long-chain hydrocarbons.

Coherent perfect absorption in Tavis-Cummings models.

We theoretically study the conditions under which two laser fields can undergo Coherent Perfect Absorption (CPA) when shined on a single-mode bi-directional optical cavity coupled with two two-level quantum emitters (natural atoms, artificial atoms, quantum dots, qubits, etc.). In addition to being indirectly coupled through the cavity-mediated field, in our Tavis-Cummings model, the two quantum emitters (QEs) are allowed to interact directly via the dipole-dipole interaction (DDI). Under the mean-field approximation and low-excitation assumption, in this work, we particularly focus on the impact of DDI on the existence of CPA in the presence of decoherence mechanisms (spontaneous emission from the QEs and the leakage of photons from the cavity walls). We also present a dressed-state analysis of the problem to discuss the underlying physics related to the allowed polariton state transitions in the Jaynes-Tavis-Cummings ladder. As a key result, we find that in the strong-coupling regime of cavity quantum electrodynamics, the strong DDI and the emitter-cavity detuning can act together to achieve the CPA at two laser frequencies tunable by the inter-atomic separation which are not possible to attain with a single QE in the presence of detuning. Our CPA results are potentially applicable in building quantum memories that are an essential component in long-distance quantum networking.

Electroplating Cobalt Films on Silicon Nanostructures for Sensing Molecules.

In this study, we electroplated Co and Cu on nano-spiked silicon substrates that were treated with femtosecond laser irradiations. With energy-dispersive X-ray (EDX) analysis by a scanning electron microscope (SEM), it was found that both Co and Cu are primarily coated on the spike surfaces without changing the morphology of the nanospikes. We also found that nanoscale bridges were formed, connecting the Co-coated silicon spikes. The formation of these bridges was studied and optimized through a series of time-controlled electroplating and oxidizing processes. The bridges are related to the oxidation of Co in the air. When it is irradiated with visible light, this special structure has shown a capability of interactions with carbon monoxide and carbon dioxide molecules. The electroplated cobalt may be used for gas sensors.

Topological kink states in graphene.

Due to the unique band structure, graphene exhibits a number of exotic electronic properties that have not been observed in other materials. Among them, it has been demonstrated that there exist the one-dimensional valley-polarized topological kink states localized in the vicinity of the domain wall of graphene systems, where a bulk energy gap opens due to the inversion symmetry breaking. Notably, the valley-momentum locking nature makes the topological kink states attractive to the property manipulation in valleytronics. This paper systematically reviews both the theoretical research and experimental progress on topological kink states in monolayer graphene, bilayer graphene and graphene-like classical wave systems. Besides, various applications of topological kink states, including the valley filter, current partition, current manipulation, Majorana zero modes and etc, are also introduced.

Formulation of stochastic contact Hamiltonian systems.

In this work, we devise a stochastic version of contact Hamiltonian systems and show that the phase flows of these systems preserve contact structures. Moreover, we provide a sufficient condition under which these stochastic contact Hamiltonian systems are completely integrable. This establishes an appropriate framework for investigating stochastic contact Hamiltonian systems.

Information upper bound for McKean-Vlasov stochastic differential equations.

We develop an information-theoretic framework to quantify information upper bound for the probability distributions of the solutions to the McKean-Vlasov stochastic differential equations. More precisely, we derive the information upper bound in terms of Kullback-Leibler divergence, which characterizes the entropy of the probability distributions of the solutions to McKean-Vlasov stochastic differential equations relative to the joint distributions of mean-field particle systems. The order of information upper bound is also figured out.

RNA sequencing reveals the role of splicing polymorphisms in regulating human gene expression.

Expression levels of many human genes are under the genetic control of expression quantitative trait loci (eQTLs). Despite technological advances, the precise molecular mechanisms underlying most eQTLs remain elusive. Here, we use deep mRNA sequencing of two CEU individuals to investigate those mechanisms, with particular focus on the role of splicing control loci (sQTLs). We identify a large number of genes that are differentially spliced between the two samples and associate many of those differences with nearby single nucleotide polymorphisms (SNPs). Subsequently, we investigate the potential effect of splicing SNPs on eQTL control in general. We find a significant enrichment of alternative splicing (AS) events within a set of highly confident eQTL targets discovered in previous studies, suggesting a role of AS in regulating overall gene expression levels. Next, we demonstrate high correlation between the levels of mature (exonic) and unprocessed (intronic) RNA, implying that ∼75% of eQTL target variance can be explained by control at the level of transcription, but that the remaining 25% may be regulated co- or post-transcriptionally. We focus on eQTL targets with discordant mRNA and pre-mRNA expression patterns and use four examples: USMG5, MMAB, MRPL43, and OAS1, to dissect the exact downstream effects of the associated genetic variants.

[Preliminary experiences of "Waffle cone" technique for the treatment of intracranial aneurysm].

OBJECTIVE: To explore the preliminary experiences of "Waffle cone" technique for the treatment of intracranial aneurysm. METHODS: Retrospective data analyses were performed for patients with intracranial aneurysms embolized by the "Waffle cone" technique from stent-assisted coiling at our hospital from December 2010 to November 2012. RESULTS: Six patients used the "Waffle cone" technique from 138 stent-assisted coiling. All had complex wide-neck bifurcation cerebral aneurysms. And the angles between parental artery and distal vessels were acute. Six rupture aneurysms were at the terminus of basilar artery (BA) (n = 2), right anterior communicating artery (AcomA) (n = 3) and trifurcation middle cerebral artery (MCA) (n = 1). All stents were of Solitaire with specification 4×15 mm (ev3, USA) .Four patients had Raymond classification Class I while another 2 Class II. No perioperative complication occurred. The average follow-up period was 6 months. CONCLUSION: This technique is safe, time-saving, simple and effective for complex, wide-necked bifurcation aneurysms with acute angles between parental artery and distal vessels.Long-term follow-ups are needed to further evaluate its efficacy.

Application of observed data denoising based on variational mode decomposition in groundwater pollution source recognition.

Groundwater pollution source recognition (GPSR) is a prerequisite for subsequent pollution remediation and risk assessment work. The actual observed data are the most important known condition in GPSR, but the observed data can be contaminated with noise in real cases. This may directly affect the recognition results. Therefore, denoising is important. However, in different practical situations, the noise attribute (e.g., noise level) and observed data attribute (e.g., observed frequency) may be different. Therefore, it is necessary to study the applicability of denoising. Current studies have two deficiencies. First, when dealing with complex nonlinear and non-stationary situations, the effect of previous denoising methods needs to be improved. Second, previous attempts to analyze the applicability of denoising in GPSR have not been comprehensive enough because they only consider the influence of the noise attribute, while overlooking the observed data attribute. To resolve these issues, this study adopted the variational mode decomposition (VMD) to perform denoising on the noisy observed data in GPSR for the first time. It further explored the influence of different factors on the denoising effect. The tests were conducted under 12 different scenarios. Then, we expanded the study to include not only the noise attribute (noise level) but also the observed data attribute (observed frequency), thus providing a more comprehensive analysis of the applicability of denoising in GPSR. Additionally, we used a new heuristic optimization algorithm, the collective decision optimization algorithm, to improve the recognition accuracy. Four representative scenarios were adopted to test the ideas. The results showed that the VMD performed well under various scenarios, and the denoising effect diminished as the noise level increased and the observed frequency decreased. The denoising was more effective for GPSR with high noise levels and multiple observed frequencies. The collective decision optimization algorithm had a good inversion accuracy and strong robustness.

An ensemble optimizer with a stacking ensemble surrogate model for identification of groundwater contamination source.

The application of the simulation-optimization method for groundwater contamination source identification (GCSI) encounters two main challenges: the substantial time cost of calling the simulation model, and the limitations on the accuracy of identification results due to the complexity, nonlinearity, and ill-posed nature of the inverse problem. To address these issues, we have innovatively developed an inversion framework based on ensemble learning strategies. This framework comprises a stacking ensemble model (SEM), which integrates three distinct machine learning models (Extremely Randomized Trees, Adaptive Boosting, and Bidirectional Gated Recurrent Unit), and an ensemble optimizer (E-GKSEEFO), which combines two newly proposed swarm intelligence optimizers (Genghis Khan Shark Optimizer and Electric Eel Foraging Optimizer). Specifically, the SEM serves as a surrogate model for the groundwater numerical simulation model. Compared to the original simulation model, it significantly reduces time cost while maintaining accuracy. The E-GKSEEFO, functioning as the search strategy for the optimization model, greatly enhances the accuracy of the optimization results. We have verified the performance of the SEM-E-GKSEEFO ensemble inversion framework through two hypothetical scenarios derived from an actual coal gangue pile. The results are as follows. (1) The SEM exhibits improved fitting performance compared to single machine learning models when dealing with high-dimensional nonlinear data from GCSI. (2) The E-GKSEEFO achieves significantly higher accuracy in the identification results of GCSI than individual optimizers. These findings affirm the effectiveness and superiority of the proposed SEM-E-GKSEEFO ensemble inversion framework.

Associations of urinary phytoestrogens with all-cause and cardiovascular mortality in adults: a population-based cohort study.

Background: The overall understanding of the correlations between mortality risk and phytoestrogens in general population remains limited. We examined the association between urinary phytoestrogen levels and all-cause and cardiovascular mortality based on the National Health and Nutrition Examination Survey (NHANES). Methods: Weighted Cox proportional hazard regression models were employed to calculate adjusted hazard ratios (HRs) and their 95% confidence intervals (CIs). Nonlinear relationships were assessed using multivariable-adjusted restricted cubic splines (RCS). Results: In the fully adjusted model, the highest quartiles of urinary genistein levels were correlated with significantly elevated all-cause (HR = 1.36, 95%CI: 1.16-1.59) and cardiovascular (HR = 1.58, 95%CI: 1.20-2.09) mortality. Urinary enterolactone levels in the third quartile were associated with reduced all-cause (HR = 0.77, 95%CI: 0.65-0.90) and cardiovascular (HR = 0.74, 95%CI: 0.55-0.99) mortality. In the highest quartiles of urinary daidzein levels, the cardiovascular mortality was significantly increased (HR = 1.44, 95%CI: 1.09-1.90). RCS showed an non-linear relationship between urinary daidzein levels and all-cause mortality (P = 0.04). Conclusion: In the context of a nationally representative sample, genistein exhibited associations with elevated all-cause and cardiovascular mortality, whereas enterolactone showed an association with reduced mortality. The dose-response relationship between urinary daidzein levels and all-cause mortality as well as sex-specific disparities in the impact of phytoestrogen levels should be considered.

Molecular insights into the interactions of theaflavin and epicatechin with different lipid bilayer membranes by molecular dynamics simulation.

At present, consumers increasingly favored the natural food preservatives with fewer side-effects on health. The green tea catechins and black tea theaflavins attracted considerable interest, and their antibacterial effects were extensively reported in the literature. Epicatechin (EC), a green tea catechin without a gallate moiety, showed no bactericidal activity, whereas the theaflavin (TF), also lacking a gallate moiety, exhibited potent bactericidal activity, and the antibacterial effects of green tea catechins and black tea theaflavins were closely correlated with their abilities to disrupt the bacterial cell membrane. In our present study, the mechanisms of membrane interaction modes and behaviors of TF and EC were explored by molecular dynamics simulations. It was demonstrated that TF exhibited markedly stronger affinity for the POPG bilayer compared to EC. Additionally, the hydrophobic interactions of tropolone/catechol rings with the acyl chain part could significantly contribute to the penetration of TF into the POPG bilayer. It was also found that the resorcinol/pyran rings were the key functional groups in TF for forming hydrogen bonds with the POPG bilayer. We believed that the findings from our current study could offer useful insights to better understand the stronger antibacterial effects of TF compared to EC.

The application of a 4D-printed chitosan-based stem cell carrier for the repair of corneal alkali burns.

BACKGROUND: Corneal alkali burns can lead to ulceration, perforation, and even corneal blindness due to epithelial defects and extensive cell necrosis, resulting in poor healing outcomes. Previous studies have found that chitosan-based in situ hydrogel loaded with limbal epithelium stem cells (LESCs) has a certain reparative effect on corneal alkali burns. However, the inconsistent pore sizes of the carriers and low cell loading rates have resulted in suboptimal repair outcomes. In this study, 4D bioprinting technology was used to prepare a chitosan-based thermosensitive gel carrier (4D-CTH) with uniform pore size and adjustable shape to improve the transfer capacity of LESCs. METHODS: Prepare solutions of chitosan acetate, carboxymethyl chitosan, and ß-glycerophosphate sodium at specific concentrations, and mix them in certain proportions to create a pore-size uniform scaffold using 4D bioprinting technology. Extract and culture rat LESCs (rLESCs) in vitro, perform immunofluorescence experiments to observe the positivity rate of deltaNp63 cells for cell identification. Conduct a series of experiments to validate the cell compatibility of 4D-CTH, including CCK-8 assay to assess cell toxicity, scratch assay to evaluate the effect of 4D-CTH on rLESCs migration, and Calcein-AM/PI cell staining experiment to examine the impact of 4D-CTH on rLESCs proliferation and morphology. Establish a severe alkali burn model in rat corneas, transplant rLESCs onto the injured cornea using 4D-CTH, periodically observe corneal opacity and neovascularization using a slit lamp, and evaluate epithelial healing by fluorescein sodium staining. Assess the therapeutic effect 4D-CTH-loaded rLESCs on corneal alkali burn through histological evaluation of corneal tissue paraffin sections stained with hematoxylin and eosin, as well as immunofluorescence staining of frozen sections. RESULTS: Using the 4D-CTH, rLESCs were transferred to the alkali burn wounds of rats. Compared with the traditional treatment group (chitosan in situ hydrogel encapsulating rLESCs), the 4D-CTH-rLESC group had significantly higher repair efficiency of corneal injury, such as lower corneal opacity score (1.2 ± 0.4472 vs 0.4 ± 0.5477, p < 0.05) and neovascularization score (5.5 ± 1.118 vs 2.6 ± 0.9618, p < 0.01), and significantly higher corneal epithelial wound healing rate (72.09 ± 3.568% vs 86.60 ± 5.004%, p < 0.01). CONCLUSION: In summary, the corneas of the 4D-CTH-rLESC treatment group were similar to the normal corneas and had a complete corneal structure. These findings suggested that LESCs encapsulated by 4D-CTH significantly accelerated corneal wound healing after alkali burn and can be considered as a rapid and effective method for treating epithelial defects.

Dry tribological properties of textured PMMA composites by embedding microspheres with different thermal conductivities.

Textured surfaces were prepared by embedding microspheres with different thermal conductivities of brass microspheres (BS), 304 stainless steel microspheres (SS), and polyoxymethylene microspheres (PS) on the surface of polymethyl methacrylate (PMMA). The effects of surface texture and filling modification on the dry tribological properties of BS/PMMA, SS/PMMA, and PS/PMMA composites were studied by ring-on-disc contact. Based on the finite element analysis of friction heat, the wear mechanisms of BS/PMMA, SS/PMMA, and PS/PMMA composites were analyzed. The results show that regular surface texture can be achieved by embedding microspheres on the PMMA surface. The friction coefficient and wear depth of the SS/PMMA composite are both the lowest. The worn surfaces of BS/PMMA, SS/PMMA, and PS/PMMA composites are divided into three micro-wear-regions. The wear mechanisms of different micro-wear-regions are different. Finite element analysis shows that thermal conductivity and thermal expansion coefficient affect the wear mechanisms of BS/PMMA, SS/PMMA, and PS/PMMA composites.

Simultaneous identification of groundwater contaminant source and hydraulic parameters based on multilayer perceptron and flying foxes optimization.

Groundwater contaminant source identification (GCSI) has practical significance for groundwater remediation and liability. However, when applying the simulation-optimization method to precisely solve GCSI, the optimization model inevitably encounters the problems of high-dimensional unknown variables to identify, which might increase the nonlinearity. In particular, to solve such optimization models, the well-known heuristic optimization algorithms might fall into a local optimum, resulting in low accuracy of inverse results. For this reason, this paper proposes a novel optimization algorithm, namely, the flying foxes optimization (FFO) to solve the optimization model. We perform simultaneous identification of the release history of groundwater pollution sources and hydraulic conductivity and compare the results with those of the traditional genetic algorithm. In addition, to alleviate the massive computational load caused by the frequent invocation of the simulation model when solving the optimization model, we utilized the multilayer perception (MLP) to establish a surrogate model of the simulation model and compared it with the method of backpropagation algorithm (BP). The results show that the average relative error of the results of FFO is 2.12%, significantly outperforming the genetic algorithm (GA); the surrogate model of MLP can replace the simulation model for calculation with fitting accuracy of more than 0.999, which is better than the commonly used surrogate model of BP.

Site- and Structure-Specific Glycosylation Signatures of Bovine, Caprine, Porcine, and Human Milk-Derived Extracellular Vesicles.

Extracellular vesicles (EVs) are membrane-bound vesicles released by living cells. As vesicles for macromolecule transmission and intercellular communication, EVs are broadly applied in clinical diagnosis and biomimetic drug delivery. Milk-derived EVs (MEVs) are an ideal choice for scale-up applications because they exhibit biocompatibility and are easily obtained. Herein, intact glycopeptides in MEVs from bovines, caprines, porcines, and humans were comprehensively analyzed by high-resolution mass spectrometry using the sceHCD, followed by the EThcD fragment method, revealing that protein glycosylation is abundant and heterogeneous in MEVs. The dominant glycans in all MEVs were sialic acid-modified N-linked glycans (over 50%). A couple of species-specific glycans were also characterized, which are potentially markers of different original EVs. Interestingly, the Neu5Gc-modified glycans were enriched in caprine milk-derived EVs (58 ± 2%). Heterogeneity of MEV protein glycosylation was observed for glycosites and glycan compositions, and the structural heterogeneity of protein glycosylation was also identified and validated. The glycosignatures of EV biogenesis- and endocytosis-related proteins (CD63 and MFGE8) were significantly different in these four species. Overall, we comprehensively characterized the glycosylation signature of MEVs from four different species and provided insight into protein glycosylation related to drug target delivery.

Measuring Encapsulation Efficiency in Cell-Mimicking Giant Unilamellar Vesicles.

One of the main drivers within the field of bottom-up synthetic biology is to develop artificial chemical machines, perhaps even living systems, that have programmable functionality. Numerous toolkits exist to generate giant unilamellar vesicle-based artificial cells. However, methods able to quantitatively measure their molecular constituents upon formation is an underdeveloped area. We report an artificial cell quality control (AC/QC) protocol using a microfluidic-based single-molecule approach, enabling the absolute quantification of encapsulated biomolecules. While the measured average encapsulation efficiency was 11.4 ± 6.8%, the AC/QC method allowed us to determine encapsulation efficiencies per vesicle, which varied significantly from 2.4 to 41%. We show that it is possible to achieve a desired concentration of biomolecule within each vesicle by commensurate compensation of its concentration in the seed emulsion. However, the variability in encapsulation efficiency suggests caution is necessary when using such vesicles as simplified biological models or standards.