Total Synthesis of (±)-Rubriflordilactone A.

A new and efficient synthesis of rubriflordilactone A has been realized. The key transformations include the following: (1) an intramolecular Prins cyclization to establish the seven-membered ring containing two contiguous stereocenters; (2) a Mukaiyama hydration/oxa-Michael cascade to construct the B-ring; and (3) an unprecedented stereocontrol intermolecular o-QM type [4 + 2]-cycloaddition to rapidly assemble core structure of rubriflordilactone A.

High-Density CoSe2 Sites Embedded within 2D Porous N-Doped Carbon for High-Performance Oxygen Reduction Reaction Electrocatalysis.

Designing and fabricating efficient and stable nonprecious metal-based oxygen reduction reaction (ORR) electrocatalysts is a pressing and challenging task for the pursuit of sustainable new energy devices. Herein, porous P-CoSe2@NC electrocatalysts with high-density carbon-coated CoSe2 sites were successfully fabricated based on a pyridyl-porphyrinic metal-organic framework (Co-TPyP MOF) via a molten salt-assisted synthesis method. The hierarchical pore and N-doping carbon substrate of P-CoSe2@NC promotes mass transfer and electron-transfer efficiency, which is beneficial to maximize CoSe2 site utilization. Well-designed P-CoSe2@NC exhibits efficient ORR catalytic activity with a high half-wave potential of 0.863 V and excellent catalytic stability. Meanwhile, rechargeable aqueous primary/quasi-solid-state ZABs based on a P-CoSe2@NC air cathode show a high peak power density and exceptional operating stability, catering to the demands of practical applications. The qualified performance and structure stability of the electrocatalytic system may be mainly attributed to the protection of the CoSe2 nanoparticle by the coated carbon layer. Given the rational design of the structure and the component of the electrocatalyst with enhanced ORR activity, we believe that this work has provided a reliable pathway to the development of high-performance transition-metal chalcogenides for energy-storage and -conversion devices.

Evolutionary novelties underlie sound production in baleen whales.

Baleen whales (mysticetes) use vocalizations to mediate their complex social and reproductive behaviours in vast, opaque marine environments1. Adapting to an obligate aquatic lifestyle demanded fundamental physiological changes to efficiently produce sound, including laryngeal specializations2-4. Whereas toothed whales (odontocetes) evolved a nasal vocal organ5, mysticetes have been thought to use the larynx for sound production1,6-8. However, there has been no direct demonstration that the mysticete larynx can phonate, or if it does, how it produces the great diversity of mysticete sounds9. Here we combine experiments on the excised larynx of three mysticete species with detailed anatomy and computational models to show that mysticetes evolved unique laryngeal structures for sound production. These structures allow some of the largest animals that ever lived to efficiently produce frequency-modulated, low-frequency calls. Furthermore, we show that this phonation mechanism is likely to be ancestral to all mysticetes and shares its fundamental physical basis with most terrestrial mammals, including humans10, birds11, and their closest relatives, odontocetes5. However, these laryngeal structures set insurmountable physiological limits to the frequency range and depth of their vocalizations, preventing them from escaping anthropogenic vessel noise12,13 and communicating at great depths14, thereby greatly reducing their active communication range.

NiCoP cocatalyst modified g-C3N4 as ohmic junction photocatalyst for efficient degradation of tetracycline under visible light.

Increasing the electron-hole recombination rate in g-C3N4 can effectively improve its photocatalytic performance. In this work, NiCoP/g-C3N4 (NCP/PCN) composites with ohmic junction were formed by embedding granular NiCoP in irregularly porous g-C3N4. There was almost no barrier between the metal and the semiconductor in ohmic junction, which made it easier for electrons to slip from PCN to NCP along the curved energy band, and NCP acted as an electron collector to rapidly capture the slipping electrons. In addition, porous g-C3N4 prepared by supramolecular self-assembly could provide a shorter diffusion path for electrons. Thus, the electron-hole was effectively separated and the photocatalytic performance was improved. The band electronic structure and existence of ohmic junction in 7-NCP/PCN composite were demonstrated by XPS, ESR and DFT calculation. Finally, a reasonable photocatalytic degradation mechanism and possible tetracycline degradation path were proposed. This work has significant potential for providing an effective method for the design of non-precious metal photocatalysts.

Macro-Meso Damage Analysis of Tunnel Lining Concrete under Thermal-Mechanical Coupling Based on CT Images.

The mechanical properties and failure modes of concrete are controlled by its mesoscopic material composition and structure; therefore, it is necessary to study the deterioration characteristics of tunnel lining concrete under fire from a mesoscopic perspective. However, previous studies mostly analyzed the damage and failure process from a macro-homogeneous perspective, which has certain limitations. In this paper, a thermal-mechanical coupling test device was modified to simulate the state of concrete under tunnel fire conditions. Combined with CT technology, the macroscopic properties and mesoscopic characteristics of concrete were observed. Features were obtained, such as the change in compressive strength under fire, as well as mesoscopic deterioration characteristics. The damage variable D was defined to quantify mesoscopic damage, and the link between mesoscopic deterioration characteristics and macroscopic performance was established, which can be used to predict compressive strength loss through mesoscopic characteristics.

A self-centering and stiffness-controlled MEMS accelerometer.

This paper presents a high-performance MEMS accelerometer with a DC/AC electrostatic stiffness tuning capability based on double-sided parallel plates (DSPPs). DC and AC electrostatic tuning enable the adjustment of the effective stiffness and the calibration of the geometric offset of the proof mass, respectively. A dynamical model of the proposed accelerometer was developed considering both DC/AC electrostatic tuning and the temperature effect. Based on the dynamical model, a self-centering closed loop is proposed for pulling the reference position of the force-to-rebalance (FTR) to the geometric center of DSPP. The self-centering accelerometer operates at the optimal reference position by eliminating the temperature drift of the readout circuit and nulling the net electrostatic tuning forces. The stiffness closed-loop is also incorporated to prevent the pull-in instability of the tuned low-stiffness accelerometer under a dramatic temperature variation. Real-time adjustments of the reference position and the DC tuning voltage are utilized to compensate for the residue temperature drift of the proposed accelerometer. As a result, a novel controlling approach composed of a self-centering closed loop, stiffness-closed loop, and temperature drift compensation is achieved for the accelerometer, realizing a temperature drift coefficient (TDC) of approximately 7 µg/°C and an Allan bias instability of less than 1 µg.

Exploring the importance of m5c in the diagnosis and subtype classification of COPD using the GEO database.

BACKGROUND: 5-Methylcytosine (m5C) is an mRNA modifier that is associated with the occurrence and development of viral infection, pulmonary fibrosis, lung cancer, and other diseases. However, the role of m5C regulators in chronic obstructive pulmonary disease (COPD) remains unknown. METHODS: In this study, by analysing the GSE42057 dataset, the differential expression of m5c regulators in the COPD group and control group was obtained, and a correlation analysis was conducted. The random forest model and support vector machine model were used to predict the occurrence of COPD. A nomogram model was also constructed to predict the prevalence of COPD. The COPD patients were divided into subtypes by consistent cluster analysis based on m5c methylation regulators. Immune cell infiltration was performed on the m5c methylation subtypes. Differentially expressed genes (DEGs) between m5c methylation subtypes were screened, and the DEGs were analysed by Gene Ontology (GO) Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, we verified the expression of several m5C regulators and related pathways using a COPD cell model. RESULTS: Seven m5c methylation regulators were differentially expressed. The random forest model based on the above genes was the most accurate for predicting the occurrence of COPD. A nomogram model based on the above genes could also accurately predict the prevalence of COPD, and the implementation of these models could benefit COPD patients. The consistent cluster analysis divided the COPD patients into two subtypes (Cluster A and Cluster B). The main component analysis algorithm determined the m5c methylation subtypes and found that patients in Cluster A had a higher m5c score than those in Cluster B. GO analysis of the DEGs between the m5c methylation COPD patient subtypes revealed that DEGS were mainly enriched in leukocyte-mediated immunity and regulation of T-cell activation. KEGG analysis revealed that DEGS were mainly enriched in Th1 and Th2 cell differentiation, neutrophil extracellular trap formation, and the NF-κB signalling pathway. Immunocyte correlation analysis revealed that Cluster B was associated with neutrophil- and macrophage-mediated immunity, while Cluster A was associated with CD4 + T-cell- and CD8 + T-cell-mediated immunity. Cell experiments have also verified some of the above research results. CONCLUSION: The diagnosis and subtype classification of COPD patients based on m5c regulators may provide a new strategy for the diagnosis and treatment of COPD.

Porous carboxymethyl cellulose nanocrystalline imprinted composite aerogels for selective adsorption of gadolinium.

Gadolinium is widely applied in medical and high-tech materials because of special magnetic properties. Recovery of gadolinium from waste rare earth products has both economic and environmental value. In this experiment, honeycomb porous composite aerogels were constructed using sericin and sodium alginate mixed with functionally modified carboxymethylated cellulose nanocrystals for the adsorption and separation of gadolinium ions. There were large numbers of carboxyl groups as well as hydroxyl groups on the surface of sodium alginate and filamentous protein, which provided more sites for the adsorption of gadolinium ions. Besides, a stable honeycomb structure appeared on the surface of composite aerogels when the mixture of filamentous protein and sodium alginate was 1:1, which increased the specific surface area of materials to 140.65 m2 g-1. Additionally, the imprinted composite aerogels Ic-CNC/SSA were prepared by virtue of the imprinting technology, enhancing the adsorption selectivity of composite aerogels for gadolinium. The adsorption experiments revealed that the maximum adsorption capacity of Ic-CNC/SSA reached 93.41 mg g-1 at pH 7.0, indicating good selective adsorption of gadolinium ions. In summary, such composite aerogels provide great potential and reference value for the selective adsorption of gadolinium ions in industry.

Low-Temperature Vapor-Phase Growth of 2D Metal Chalcogenides.

2D metal chalcogenides (MCs) have garnered significant attention from both scientific and industrial communities due to their potential in developing next-generation functional devices. Vapor-phase deposition methods have proven highly effective in fabricating high-quality 2D MCs. Nevertheless, the conventionally high thermal budgets required for synthesizing 2D MCs pose limitations, particularly in the integration of multiple components and in specialized applications (such as flexible electronics). To overcome these challenges, it is desirable to reduce the thermal energy requirements, thus facilitating the growth of various 2D MCs at lower temperatures. Numerous endeavors have been undertaken to develop low-temperature vapor-phase growth techniques for 2D MCs, and this review aims to provide an overview of the latest advances in low-temperature vapor-phase growth of 2D MCs. Initially, the review highlights the latest progress in achieving high-quality 2D MCs through various low-temperature vapor-phase techniques, including chemical vapor deposition (CVD), metal-organic CVD, plasma-enhanced CVD, atomic layer deposition (ALD), etc. The strengths and current limitations of these methods are also evaluated. Subsequently, the review consolidates the diverse applications of 2D MCs grown at low temperatures, covering fields such as electronics, optoelectronics, flexible devices, and catalysis. Finally, current challenges and future research directions are briefly discussed, considering the most recent progress in the field.

Selective Adsorption of Gadolinium by Nitrogen-Doped Carboxymethylated Cellulose Nanocrystalline Carbon Aerogels Functionalized in the Ammonia-Urea System.

In this paper, an ammonia-urea system was developed to induce the shedding of carboxymethylcellulose carbon aerogels to form defects, and the specific surface area of the aerogels was significantly increased after carbonization, and the three-dimensional disordered pore structure of cellulose was preserved. The material showed the selective adsorption of gadolinium ions using the carboxylate active sites provided by carboxymethylation and the microporous or mesoporous structures formed after carbon burning. The successful synthesis of the material was demonstrated by relevant characterization, and the results of static adsorption experiments showed that the material was more consistent with the quasi second-order kinetic model at pH = 5.0. The maximum adsorption capacity was 99.65 mg g-1. The material showed a high adsorption capacity for gadolinium ions in the presence of competing ions and maintained 84.07% of the adsorption performance after five adsorption cycles. The simple use of urea ensured that the cellulose maintained its pore structure, and the specific surface area was greatly increased after carbonization, which provided a feasible direction for the industrial adsorption and recycling of rare-earth elements for reuse.

Cascaded compression of size distribution of nanopores in monolayer graphene.

Monolayer graphene with nanometre-scale pores, atomically thin thickness and remarkable mechanical properties provides wide-ranging opportunities for applications in ion and molecular separations1, energy storage2 and electronics3. Because the performance of these applications relies heavily on the size of the nanopores, it is desirable to design and engineer with precision a suitable nanopore size with narrow size distributions. However, conventional top-down processes often yield log-normal distributions with long tails, particularly at the sub-nanometre scale4. Moreover, the size distribution and density of the nanopores are often intrinsically intercorrelated, leading to a trade-off between the two that substantially limits their applications5-9. Here we report a cascaded compression approach to narrowing the size distribution of nanopores with left skewness and ultrasmall tail deviation, while keeping the density of nanopores increasing at each compression cycle. The formation of nanopores is split into many small steps, in each of which the size distribution of all the existing nanopores is compressed by a combination of shrinkage and expansion and, at the same time as expansion, a new batch of nanopores is created, leading to increased nanopore density by each cycle. As a result, high-density nanopores in monolayer graphene with a left-skewed, short-tail size distribution are obtained that show ultrafast and ångström-size-tunable selective transport of ions and molecules, breaking the limitation of the conventional log-normal size distribution9,10. This method allows for independent control of several metrics of the generated nanopores, including the density, mean diameter, standard deviation and skewness of the size distribution, which will lead to the next leap in nanotechnology.

Preparation of imprinted bacterial cellulose aerogel with intelligent modulation of thermal response stimulation for selective adsorption of Gd(III) from wastewater.

Research on recycling of used rare earth elements has been of great interest. Adsorption is one of the advantageous methods to recover gadolinium with high value. In the process of adsorption and separation of gadolinium from materials, the selectivity of materials for gadolinium can be significantly improved by using ion imprinting technique. However, gadolinium elution process is a traditional pickling process, which may affect the construction of imprinting sites. In this study, bacterial cellulose with three-dimensional spatial structure was used as the base material of aerogel material, and functional materials containing a large number of carboxyl groups were introduced by chemical grafting method. In combination with ion imprinting technology and N-polyacrylamide as intelligent temperature control valve, intelligent imprinting aerogel (PNBC-IIPS) with specific selectivity to gadolinium was prepared. The properties of aerogel materials were analyzed by SEM, FT-IR, and BET characterization. The experimental analysis shows that the desorption of gadolinium can be achieved by controlling the temperature change. The adsorption experiments show that PNBC-IIPS can selectively adsorb gadolinium ions from aqueous solution. The maximum adsorption capacity reached 95.51 mg g-1. Compared with unimprinted aerogel, the maximum adsorption capacity of gadolinium ion is significantly increased, which proves that the introduced ion imprinting technique plays a key role in the adsorption process. Cyclic experiments show that the adsorption capacity of PNBC-IIPS can still maintain 88% of the original adsorption capacity after 5 times of adsorption and desorption. In conclusion, PNBC-IIPS is a green adsorbent for selective recovery of gadolinium ions.

The Effects of Negative Pressure Induced by Flow Separation Vortices on Vocal Fold Dynamics during Voice Production.

This study used a two-dimensional flow-structure-interaction computer model to investigate the effects of flow-separation-vortex-induced negative pressure on vocal fold vibration and flow dynamics during vocal fold vibration. The study found that negative pressure induced by flow separation vortices enhances vocal fold vibration by increasing aeroelastic energy transfer during vibration. The result showed that the intraglottal pressure was predominantly negative after flow separation before gradually recovering to zero at the glottis exit. When the negative pressure was removed, the vibration amplitude and flow rate were reduced by up to 20%, and the closing speed, flow skewness quotient, and maximum flow declination rate were reduced by up to 40%. The study provides insights into the complex interactions between flow dynamics, vocal fold vibration, and energy transfer during voice production.

Deciphering the connection between upstream obstacles, wake structures, and root signals in seal whisker array sensing using interpretable neural networks.

This study presents a novel method that combines a computational fluid-structure interaction model with an interpretable deep-learning model to explore the fundamental mechanisms of seal whisker sensing. By establishing connections between crucial signal patterns, flow characteristics, and attributes of upstream obstacles, the method has the potential to enhance our understanding of the intricate sensing mechanisms. The effectiveness of the method is demonstrated through its accurate prediction of the location and orientation of a circular plate placed in front of seal whisker arrays. The model also generates temporal and spatial importance values of the signals, enabling the identification of significant temporal-spatial signal patterns crucial for the network's predictions. These signal patterns are further correlated with flow structures, allowing for the identification of important flow features relevant for accurate prediction. The study provides insights into seal whiskers' perception of complex underwater environments, inspiring advancements in underwater sensing technologies.

Combined Temperature Compensation Method for Closed-Loop Microelectromechanical System Capacitive Accelerometer.

This article describes a closed-loop detection MEMS accelerometer for acceleration measurement. This paper analyzes the working principle of MEMS accelerometers in detail and explains the relationship between the accelerometer zero bias, scale factor and voltage reference. Therefore, a combined compensation method is designed via reference voltage source compensation and terminal temperature compensation of the accelerometer, which comprehensively improves the performance over a wide temperature range of the accelerometer. The experiment results show that the initial range is reduced from 3679 ppm to 221 ppm with reference voltage source compensation, zero-bias stability of the accelerometer over temperature is increased by 14.3% on average and the scale factor stability over temperature is increased by 88.2% on average. After combined compensation, one accelerometer zero-bias stability over temperature was reduced to 40 µg and the scale factor stability over temperature was reduced to 16 ppm, the average value of the zero-bias stability over temperature was reduced from 1764 µg to 36 µg, the average value of the scale factor stability over temperature was reduced from 2270 ppm to 25 ppm, the average stability of the zero bias was increased by 97.96% and the average stability of the scale factor was increased by 98.90%.

Research on a Method to Improve the Temperature Performance of an All-Silicon Accelerometer.

This paper presents a novel method for the performance of an all-silicon accelerometer by adjusting the ratio of the Si-SiO2 bonding area, and the Au-Si bonding area in the anchor zone, with the aim of eliminating stress in the anchor region. The study includes the development of an accelerometer model and simulation analysis which demonstrates the stress maps of the accelerometer under different anchor-area ratios, which have a strong impact on the performance of the accelerometer. In practical applications, the deformation of the comb structure fixed by the anchor zone is influenced by the stress in the anchor region, causing a distorted nonlinear response signal. The simulation results demonstrate that when the area ratio of the Si-SiO2 anchor zone to the Au-Si anchor zone decreases to 0.5, the stress in the anchor zone decreases significantly. Experimental results reveal that the full-temperature stability of zero-bias is optimized from 133 µg to 46 µg when the anchor-zone ratio of the accelerometer decreases from 0.8 to 0.5. At the same time, the full-temperature stability of the scale factor is optimized from 87 ppm to 32 ppm. Furthermore, zero-bias full-temperature stability and scale factor full-temperature stability are improved by 34.6% and 36.8%, respectively.

A solvent-template ethyl cellulose-polydimethylsiloxane crosslinking sponge for rapid and efficient oil adsorption.

Lipophilic adsorbents for oil-water separation are usually synthesized using the template method, in which hydrophobic materials are coated on a ready-made sponge. Herein, a novel solvent-template technique is used to directly synthesize a hydrophobic sponge, by crosslinking polydimethylsiloxane (PDMS) with ethyl cellulose (EC) which plays a vital role in the formation of 3D porous structure. The as-prepared sponge has advantages of strong hydrophobility, high elasticity, as well as excellent adsorption performance. In addition, the sponge can be readily decorated by nano-coatings. After the sponge was simply dipped in nanosilica, the water contact angle increases from 139.2° to 144.5°, and the maximum adsorption capacity for chiroform rises from 25.6 g/g to 35.4 g/g. The adsorption equilibrium can be reached within 3 min, and, the sponge can be regenerated by squeezing, without any change in hydrophobility or evident decline in capacity. The simulation tests of emulsion separation and oil-spill cleanup demonstrate that the sponge has great potential in oil-water separation.

Gut microbial GABAergic signaling improves stress-associated innate immunity to respiratory viral infection.

INTRODUCTION: Epidemiological evidences reveal that populations with psychological stress have an increased likelihood of respiratory viral infection involving influenza A virus (IAV) and SARS-CoV-2. OBJECTIVES: This study aims to explore the potential correlation between psychological stress and increased susceptibility to respiratory viral infections and how this may contribute to a more severe disease progression. METHODS: A chronic restraint stress (CRS) mouse model was used to infect IAV and estimate lung inflammation. Alveolar macrophages (AMs) were observed in the numbers, function and metabolic-epigenetic properties. To confirm the central importance of the gut microbiome in stress-exacerbated viral pneumonia, mice were conducted through microbiome depletion and gut microbiome transplantation. RESULTS: Stress exposure induced a decline in Lactobacillaceae abundance and hence γ-aminobutyric acid (GABA) level in mice. Microbial-derived GABA was released in the peripheral and sensed by AMs via GABAAR, leading to enhanced mitochondrial metabolism and α-ketoglutarate (αKG) generation. The metabolic intermediator in turn served as the cofactor for the epigenetic regulator Tet2 to catalyze DNA hydroxymethylation and promoted the PPARγ-centered gene program underpinning survival, self-renewing, and immunoregulation of AMs. Thus, we uncover an unappreciated GABA/Tet2/PPARγ regulatory circuitry initiated by the gut microbiome to instruct distant immune cells through a metabolic-epigenetic program. Accordingly, reconstitution with GABA-producing probiotics, adoptive transferring of GABA-conditioned AMs, or resumption of pulmonary αKG level remarkably improved AMs homeostasis and alleviated severe pneumonia in stressed mice. CONCLUSION: Together, our study identifies microbiome-derived tonic signaling tuned by psychological stress to imprint resident immune cells and defensive response in the lungs. Further studies are warranted to translate these findings, basically from murine models, into the individuals with psychiatric stress during respiratory viral infection.

Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks.

Tissue dynamics play critical roles in many physiological functions and provide important metrics for clinical diagnosis. Capturing real-time high-resolution 3D images of tissue dynamics, however, remains a challenge. This study presents a hybrid physics-informed neural network algorithm that infers 3D flow-induced tissue dynamics and other physical quantities from sparse 2D images. The algorithm combines a recurrent neural network model of soft tissue with a differentiable fluid solver, leveraging prior knowledge in solid mechanics to project the governing equation on a discrete eigen space. The algorithm uses a Long-short-term memory-based recurrent encoder-decoder connected with a fully connected neural network to capture the temporal dependence of flow-structure-interaction. The effectiveness and merit of the proposed algorithm is demonstrated on synthetic data from a canine vocal fold model and experimental data from excised pigeon syringes. The results showed that the algorithm accurately reconstructs 3D vocal dynamics, aerodynamics, and acoustics from sparse 2D vibration profiles.

The Influence of Fiber Orientation of the Conus Elasticus in Vocal Fold Modeling.

While the conus elasticus is generally considered a part of continuation of the vocal ligament, histological studies have revealed different fiber orientations that fibers are primarily aligned in the superior-inferior direction in the conus elasticus and in the anterior-posterior direction in the vocal ligament. In this work, two continuum vocal fold models are constructed with two different fiber orientations in the conus elasticus: the superior-inferior direction and the anterior-posterior direction. Flow-structure interaction simulations are conducted at different subglottal pressures to investigate the effects of fiber orientation in the conus elasticus on vocal fold vibrations, aerodynamic and acoustic measures of voice production. The results reveal that including the realistic fiber orientation (superior-inferior) in the conus elasticus yields smaller stiffness and larger deflection in the coronal plane at the junction of the conus elasticus and ligament and subsequently leads to a greater vibration amplitude and larger mucosal wave amplitude of the vocal fold. The smaller coronal-plane stiffness also causes a larger peak flow rate and higher skewing quotient. Furthermore, the voice generated by the vocal fold model with a realistic conus elasticus has a lower fundamental frequency, smaller first harmonic amplitude, and smaller spectral slope.