Pervaporation Dehydration Mechanism and Performance of High-Aluminum ZSM-5 Zeolite Membranes for Organic Solvents.

Membrane-based pervaporation (PV) for organic solvent dehydration is of great significance in the chemical and petrochemical industries. In this work, high-aluminum ZSM-5 zeolite membranes were synthesized by a fluoride-assisted secondary growth on α-alumina tubular supports using mordenite framework inverted (MFI) nanoseeds (~110 nm) and a template-free synthesis solution with a low Si/Al ratio of 10. Characterization by XRD, EDX, and SEM revealed that the prepared membrane was a pure-phase ZSM-5 zeolite membrane with a Si/Al ratio of 3.8 and a thickness of 2.8 µm. Subsequently, two categories of PV performance parameters (i.e., flux versus separation factor and permeance versus selectivity) were used to systematically examine the effects of operating conditions on the PV dehydration performance of different organic solvents (methanol, ethanol, n-propanol, and isopropanol), and their PV mechanisms were explored. Employing permeance and selectivity effectively disentangles the influence of operating conditions on PV performance, thereby elucidating the inherent contribution of membranes to separation performance. The results show that the mass transfer during PV dehydration of organic solvents was mainly dominated by the adsorption-diffusion mechanism. Furthermore, the diffusion of highly polar water and methanol molecules within membrane pores had a strong mutual slowing-down effect, resulting in significantly lower permeance than other binary systems. However, the mass transfer process for water/low-polar organic solvent (ethanol, n-propanol, and isopropanol) mixtures was mainly controlled by competitive adsorption caused by affinity differences. In addition, the high-aluminum ZSM-5 zeolite membrane exhibited superior PV dehydration performance for water/isopropanol mixtures.

EnzyACT: A Novel Deep Learning Method to Predict the Impacts of Single and Multiple Mutations on Enzyme Activity.

Enzyme engineering involves the customization of enzymes by introducing mutations to expand the application scope of natural enzymes. One limitation of that is the complex interaction between two key properties, activity and stability, where the enhancement of one often leads to the reduction of the other, also called the trade-off mechanism. Although dozens of methods that predict the change of protein stability upon mutations have been developed, the prediction of the effect on activity is still in its early stage. Therefore, developing a fast and accurate method to predict the impact of the mutations on enzyme activity is helpful for enzyme design and understanding of the trade-off mechanism. Here, we introduce a novel approach, EnzyACT, a deep learning method that fuses graph technique and protein embedding to predict activity changes upon single or multiple mutations. Our model combines graph-based techniques and language models to predict the activity changes. Moreover, EnzyACT is trained on a new curated data set including both single- and multiple-point mutations. When benchmarked on multiple independent data sets, it shows uniform performance on problems affected by mutations. This work also provides insights into the impact of distant mutations within activity design, which could also be useful for predicting catalytic residues and developing improved enzyme-engineering strategies.

Imparting Ultrahigh Strength to Polymers via a New Concept Strategy of Construction of up to Duodecuple Hydrogen Bonding among Macromolecular Chains.

Interconnecting macromolecules via multiple hydrogen bonds (H-bonds) can simultaneously strengthen and toughen polymers, but material synthesis becomes extremely difficult with increasing number of H-bonding donors and acceptors; therefore, most reports are limited to triple and quadruple H-bonds. Herein, this bottleneck is overcome by adopting a quartet-wise approach of constructing H-bonds instead of the traditional pairwise method. Thus, large multiple hydrogen bonds can be easily established, and the supramolecular interactions are further reinforced. Especially, when such multiple H-bond motifs are embedded in polymers, four macromolecular chains-rather than two as usual-are tied, distributing the applied stress over a larger volume and more significantly improving the overall mechanical properties. Proof-of-concept studies indicate that the proposed intermolecular multiple H-bonds (up to duodecuple) are readily introduced in polyurethane. A record-high tensile strength (105.2 MPa) is achieved alongside outstanding toughness (352.1 MJ m-3), fracture energy (480.7 kJ m-2), and fatigue threshold (2978.4 J m-2). Meantime, the polyurethane has acquired excellent self-healability and recyclability. This strategy is also applicable to nonpolar polymers, such as polydimethylsiloxane, whose strength (15.3 MPa) and toughness (50.3 MJ m-3) are among the highest reported to date for silicones. This new technique has good expandability and can be used to develop even more and stronger polymers.

Will greenhouse gas emissions increase with mining depth in coal mines? An analysis of gas occurrence under varying in-situ stress conditions.

The rapid development of the economy leads to the high demand for deep coal resources, which further poses the potential problem of deep gas (or methane) emissions. The clarification of deep gas occurrence law for coal mines provides theoretical and data support for methane emission predictions, and assists industrial and mining enterprises in planning targeted emission reduction measures. This study defined and verified the existence of a critical depth for the deep gas occurrence in coal mines based on a multiple-scale case study of how the gas occurrence is associated with depth and stress status changes in the Pingdingshan No.8 Coal Mine. In addition, 882 sets of gas content data from 7 major mining areas in China were collected and their gas content distributions among various depths were statistically analyzed to prove the universal existence of critical depth. The results show that the critical depth of Pingdingshan No.8 Coal Mine is 509 m, and the critical depth of other Chinese areas is about 400 to 1000 m. Significant differences were observed in the pore space, surface, and gas desorption characteristics for coal samples with different depths and stress states. The pore structure in the critical depth area is relatively developed, and gas is easily accumulated. The gas occurrence of both normal and abnormal gas gradually increases with the depth's increase in areas above the critical depth, whereas the gas occurrence gradually decreases for areas below the critical depth, showing that the existence of critical depth lead to significant deviations in gas emission predictions. The results provide a fundamental reference for gas emission prediction, greenhouse effect assessment, and carbon emission factor calculation and indicate that using the traditional linear method may be misleading for evaluating deep gas occurrence and emission.

Thermal self-crosslink after etching for regulated preparation of Ti3C2 type MXene membrane and its preliminary gas separation.

We present an innovative methodology for the synthesis of MXene membranes through a dual-stage process involving etching and subsequent thermal self-crosslinking. A molar ratio of 1 (Al3+):9 (F-) using HCl/LiF was employed to convert raw Ti3AlC2 (MAX phase) into MXene within 48 h at 40 °C. This procedure predominantly yielded monolayers distinguished by diameters exceeding 500 nm, elevated crystallinity and a high overall yield. Advanced characterization techniques, including FESEM, TEM, HRTEM, AFM, XPS, and FTIR, were utilized. Instrumental analysis confirmed the formation of MXene exhibiting a single-flake morphology with diameters exceeding 500 nm. These monolayers were intact and continuous, with smooth peripheries and a uniform thickness of 2.1 nm. The surfaces were predominantly composed of carbon (C), oxygen (O), and titanium (Ti) atoms, interconnected by chemical bonds such as C-Ti-O, C-Ti-OH, C-C, C-O, and Ti-O. In the subsequent phase, vacuum filtration facilitated the assembly of a self-supporting MXene membrane. Thermal treatment at 170 °C for 30 h resulted in the reinforcement of C-Ti-O bonds within the nanosheets, increasing their prevalence to 43.14 % and 19.47 %, respectively. This thermal regulation reduced the interlayer d-spacing from 4.33 to 3.54 Å, which significantly improved the gas separation efficiency beyond the Knudsen diffusion limit, as demonstrated by the αH2/CF4 value exceeding 23.0.

Peroxymonosulfate enhanced photocatalytic degradation of organic dye by metal-free TpTt-COF under visible light irradiation.

Recently, the activation of persulfate (PDS) by non-metallic photocatalysts under visible light has attracted significant interest in applications in environmental remediation. This study presents a pioneering investigation into the combined application of the TpTt-COF and PMS for visible light degradation of organic dyes. Synthesized orange TpTt-COF monomers exhibit exceptional crystallinity, a 2D structure, and notable stability in harsh conditions. The broad visible light absorption around a wavelength of 708 nm. The TpTt-COF emerges as a promising candidate for photocatalytic dye degradation. The study addresses high charge recombination in the TpTt-COF, highlighting the crucial role of its electron donor and acceptor for the PMS activation. Comparative analyses against traditional photocatalytic materials, such as the metal-free carbon-based material g-C3N4 and transition metal-containing TiO2, demonstrate TpTt-COF's superior performance, generating diverse free radicals. In simulated experiments, the TpTt-COF's degradation rate surpasses PMS-combined g-C3N4 by 13.9 times. and 1.6 times higher than the TpTt-COF alone. Remarkably, the TpTt-COF maintains high activity under harsh environments. Investigations into the degradation mechanism and the TpTt-COF's reusability reveal its efficiency and stability. Under visible light, TpTt-COF facilitates efficient electron-hole separation. Combining the TpTt-COF with PMS produces various radicals, ensuring effective separation and a synergistic effect. Radical quenching experiments confirm the pivotal role of O2-· radicals, while ·OH and SO4-· radicals intensify the degradation. After five cycles, TpTt-COF maintains an impressive 83.2% degradation efficiency. This study introduces an efficient photocatalytic system mediated by PMS and valuable insights into governing mechanisms for organic pollutant degradation in water environments.

Role of Copper Nanoparticles in the Thermal and Mechanical Properties of Expanded Graphite-Reinforced Epoxy Hybrids.

Epoxy resin is extensively applied in the electronics and electrical fields because of its outstanding comprehensive performance. However, the low thermal conductivity (TC) limits its application in thermal interface materials. In the present work, epoxy-based hybrid composites with high TC were prepared by using expanded graphite (EG) and copper (Cu) nanoparticles as thermally conductive hybrid fillers via hot blending and compression-curing processes. Additionally, the influence of the Cu content on the thermal properties, mechanical properties, and morphology of each epoxy/EG/Cu composite was investigated. According to the results, the epoxy/EG/Cu composite showed a maximum TC of 9.74 W/(m·K) at a fixed EG content of 60 wt % owing to the addition of 10 wt % Cu. After the addition of 10 wt % Cu, the flexural strength, flexural modulus, and impact strengths of epoxy/EG/Cu composites were improved from 27.9 MPa, 9.72 GPa, and 0.81 kJ/m2 to 37.5 MPa, 10.88 GPa, and 0.91 kJ/m2, respectively. Hence, this study offers a feasible strategy for the design of epoxy hybrid composites with excellent TC that can be applied to thermal interface materials.

Synthesis optimization and separation mechanism of ZSM-5 zeolite membranes for pervaporation dehydration of organic solvents.

Pervaporation (PV), as an energy-efficient mixture separation technology, plays an important role in the chemical industry. In this work, no organic templates were needed to produce high-performance ZSM-5 membranes with an extremely low Si/Al ratio of 3.3 on α-Al2O3 tubular supports using 100 nm nanoseeds. The effects of preparation parameters on the crystalline phase structures, micromorphologies, and PV separation performance of ZSM-5 membranes were comprehensively investigated. The results revealed that the Si/Al ratio of gels significantly affected both the Si/Al ratio and the crystal orientation of the final ZSM-5 membrane. The optimized ZSM-5 membrane with a thickness of 1.8 µm was utilized to dehydrate various organic solvents via PV, and the influence of the operating parameters on PV dehydration performance was evaluated and is described herein. Furthermore, the permeation behaviors of single gases and PV were examined using permeate molecules within a similar size range to reveal the PV mechanism of the ZSM-5 membrane. The results demonstrated that gas permeation followed Knudsen diffusion, while PV permeation was decreased with decreases in the affinity of molecules, revealing an adsorption-diffusion mechanism that dominated PV dehydration through the ZSM-5 membrane. Moreover, the as-synthesized ZSM-5 membrane had good water permselectivity for water/acetone (e.g., total flux = 1.03 kg/(m2 h), α = 307) and for water/isopropanol (e.g., total flux = 1.49 kg/(m2 h), α = 1070) mixtures compared with other membranes reviewed in the literature. The synthesized ZSM-5 membrane also exhibited excellent reproducibility, high stability, and attractive PV separation performance, demonstrating its significant potential application in the PV dehydration of organic solvents.

Current landscape of preoperative neoadjuvant therapies for initial resectable colorectal cancer liver metastasis.

Colorectal cancer liver metastasis (CRLM) presents a clinical challenge, and optimizing treatment strategies is crucial for improving patient outcomes. Surgical resection, a key element in achieving prolonged survival, is often linked to a heightened risk of recurrence. Acknowledging the potential benefits of preoperative neoadjuvant chemotherapy in managing resectable liver metastases, this approach has gained attention for its role in tumor downsizing, assessing biological behavior, and reducing the risk of postoperative recurrence. However, the use of neoadjuvant chemotherapy in initially resectable CRLM sparks ongoing debates. The balance between tumor reduction and the risk of hepatic injury, coupled with concerns about delaying surgery, necessitates a nuanced approach. This article explores recent research insights and draws upon the practical experiences at our center to address critical issues regarding considerations for initially resectable cases. Examining the criteria for patient selection and the judicious choice of neoadjuvant regimens are pivotal areas of discussion. Striking the right balance between maximizing treatment efficacy and minimizing adverse effects is imperative. The dynamic landscape of precision medicine is also reflected in the evolving role of gene testing, such as RAS/BRAF and PIK3CA, in tailoring neoadjuvant regimens. Furthermore, the review emphasizes the need for a multidisciplinary approach to navigate the complexities of CRLM. Integrating technical expertise and biological insights is crucial in refining neoadjuvant strategies. The management of progression following neoadjuvant chemotherapy requires a tailored approach, acknowledging the diverse biological behaviors that may emerge. In conclusion, this review aims to provide a comprehensive perspective on the considerations, challenges, and advancements in the use of neoadjuvant chemotherapy for initially resectable CRLM. By combining evidence-based insights with practical experiences, we aspire to contribute to the ongoing discourse on refining treatment paradigms for improved outcomes in patients with CRLM.

AbImmPred: An immunogenicity prediction method for therapeutic antibodies using AntiBERTy-based sequence features.

Due to the unnecessary immune responses induced by therapeutic antibodies in clinical applications, immunogenicity is an important factor to be considered in the development of antibody therapeutics. To a certain extent, there is a lag in using wet-lab experiments to test the immunogenicity in the development process of antibody therapeutics. Developing a computational method to predict the immunogenicity at once the antibody sequence is designed, is of great significance for the screening in the early stage and reducing the risk of antibody therapeutics development. In this study, a computational immunogenicity prediction method was proposed on the basis of AntiBERTy-based features of amino sequences in the antibody variable region. The AntiBERTy-based sequence features were first calculated using the AntiBERTy pre-trained model. Principal component analysis (PCA) was then applied to reduce the extracted feature to two dimensions to obtain the final features. AutoGluon was then used to train multiple machine learning models and the best one, the weighted ensemble model, was obtained through 5-fold cross-validation on the collected data. The data contains 199 commercial therapeutic antibodies, of which 177 samples were used for model training and 5-fold cross-validation, and the remaining 22 samples were used as an independent test dataset to evaluate the performance of the constructed model and compare it with other prediction methods. Test results show that the proposed method outperforms the comparison method with 0.7273 accuracy on the independent test dataset, which is 9.09% higher than the comparison method. The corresponding web server is available through the official website of GenScript Co., Ltd., https://www.genscript.com/tools/antibody-immunogenicity.

Molecular mechanism of Jianpiyifei II granules in the treatment of chronic obstructive pulmonary disease: Network pharmacology analysis, molecular docking, and experimental assessment.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is defined by persistent airway and lung inflammation, excessive mucus production, remodeling of the airways, and damage to the alveolar tissue. Based on clinical experience, it has been observed that Jianpiyifei II (JPYF II) granules exhibit a significant therapeutic impact on individuals suffering from stable COPD. Nevertheless, the complete understanding of JPYF II's potential mode of action against COPD remains to be further clarified. PURPOSE: To further investigate the underlying mechanism of JPYF II for treating COPD and clarify the role of the IL-17 pathway in the treatment. METHODS: A variety of databases were utilized to acquire JPYF II's bioactive components, as well as related targets of JPYF II and COPD. Cytoscape was utilized to establish multiple interaction networks for the purpose of topological analyses and core-target screening. The Metascape was utilized to identify the function of target genes and crucial signaling pathways. To evaluate the interactions between bioactive ingredients and central target proteins, molecular docking simulations were conducted. Following that, a sequence of experiments was conducted both in the laboratory and in living organisms, which included analyzing the cell counts in bronchoalveolar lavage fluid (BALF), examining lung tissue for histopathological changes, conducting immunohistochemistry, RT‒qPCR, ELISA, and Western blotting. RESULTS: In JPYF II, 88 bioactive ingredients were predicted to have a total of 342 targets. After conducting Venn analysis, it was discovered that 284 potential targets of JPYF II were linked to the provision of defensive benefits against COPD. The PPI network yielded a total of twenty-four core targets. The findings from the analysis of enrichment and gene‒pathway network suggested that JPYF II targeted Hsp90, MAPKs, ERK, AP-1, TNF-α, IL-6, COX-2, CXCL8, and MMP-9 as crucial elements for COPD treatment through the IL-17 pathway. Additionally, JPYF II might modulate MAPK signaling pathways and the downstream transcription factor AP-1 via IL-17 regulation. According to the findings from molecular docking, it was observed that the 24 core target proteins exhibited robust binding affinities towards the top 10 bioactive compounds. Furthermore, the treatment of COPD through the regulation of MAPKs in the IL-17 pathway was significantly influenced by flavonoids and sterols found in JPYF II. In vitro, these observations were further confirmed. In vivo results demonstrated that JPYF II reduced inflammatory cell infiltration in pulmonary tissues and the quantity of inflammatory cells in BALF obtained from LPS- and CS-stimulated mice. Moreover, the administration of JPYF II resulted in the inhibition of IL-17 mRNA and protein levels, phosphorylation levels of MAPK proteins, and expression of phosphorylated AP-1 proteins. It also suppressed the expression of downstream effector genes and proteins associated with the IL-17/MAPK/AP-1 signaling axis in lung tissues and BALF. CONCLUSION: This research reveals that JPYF II improves COPD by controlling the IL-17/MAPK/AP-1 signaling axis within the IL-17 pathway for the first time. These findings offer potential approaches for the creation of novel medications that specifically target IL-17 and proteins involved in the IL-17 pathway to address COPD.

Multigenerational paternal obesity enhances the susceptibility to male subfertility in offspring via Wt1 N6-methyladenosine modification.

There is strong evidence that obesity is a risk factor for poor semen quality. However, the effects of multigenerational paternal obesity on the susceptibility to cadmium (a reproductive toxicant)-induced spermatogenesis disorders in offspring remain unknown. Here, we show that, in mice, spermatogenesis and retinoic acid levels become progressively lower as the number of generations exposed to a high-fat diet increase. Furthermore, exposing several generations of mice to a high fat diet results in a decrease in the expression of Wt1, a transcription factor upstream of the enzymes that synthesize retinoic acid. These effects can be rescued by injecting adeno-associated virus 9-Wt1 into the mouse testes of the offspring. Additionally, multigenerational paternal high-fat diet progressively increases METTL3 and Wt1 N6-methyladenosine levels in the testes of offspring mice. Mechanistically, treating the fathers with STM2457, a METTL3 inhibitor, restores obesity-reduced sperm count, and decreases Wt1 N6-methyladenosine level in the mouse testes of the offspring. A case-controlled study shows that human donors who are overweight or obese exhibit elevated N6-methyladenosine levels in sperm and decreased sperm concentration. Collectively, these results indicate that multigenerational paternal obesity enhances the susceptibility of the offspring to spermatogenesis disorders by increasing METTL3-mediated Wt1 N6-methyladenosine modification.

ProtT5 and random forests-based viscosity prediction method for therapeutic mAbs.

Viscosity is a key characteristic of therapeutic antibodies for subcutaneous administration which requires low volume and high concentration formulations. It would be highly beneficial to accurately predict the viscosity of newly developed therapeutic antibodies in the early stages of development. In this work, a ProtT5-XL-UniRef50 (ProtT5) and Random Forests (RF)-based prediction method was proposed for accurately predicting the viscosity of monoclonal antibodies, with only corresponding sequences needed. Starting from the given heavy and light chain V-region sequences, corresponding features were first extracted from the ProtT5 pretrained model. Kernel principal analysis (Kernel-PCA) was then used for reducing the extracted 2048-D (1024-D for each sequence) feature vector to a reasonable level for efficient training of the RF-regressor. Then, the RF model was constructed on 40 commercially available therapeutic antibodies and tested with 3-folds cross-validation. Test results show that the model could reproduce the viscosity value at a high level (Pearson correlation coefficient (PCC) = 0.928). Performance on classifying high (>30 cP) and low (<30 cP) viscosity is much more satisfactory, the Accuracy (ACC) and the area under precision-recall curve (AUC) of the classification model from validation tests are 0.975 and 1.000, respectively. Compared to 5 existing state-of-the-art viscosity prediction methods, the proposed method performs best which would facilitate high concentration antibody viscosity high-throughput screening.

Enhanced Electrical Properties and Impact Strength of Phenolic Formaldehyde Resin Using Silanized Graphene and Ionic Liquid.

In this study, to improve the electrical properties and impact strength of phenolic formaldehyde (PF) resin, PF-based composites were prepared by mixing graphene and the ionic liquid 3-decyl-bis(1-vinyl-1H-imidazole-3-ium-bromide) (C10[VImBr]2) via hot blending and compression-curing processes. The graphene surface was modified using a silane coupling agent. The synergistic effect of graphene and C10[VImBr]2 on the electrical properties, electromagnetic shielding efficiency, thermal stability, impact strength, and morphology of PF/graphene and PF/graphene/C10[VImBr]2 composites was then investigated. It was found that the electrical conductivity of the composites significantly increased from 2.3 × 10-10 to 4.14 × 10-3 S/m with an increase in the graphene content from 0 to 15 wt %, increasing further to 0.145 S/m with the addition of 5 wt % C10[VImBr]2. The electromagnetic shielding efficiency of the composite increased from 4.70 to 28.64 dB with the addition of 15 wt % graphene, while the impact strength of the composites rose significantly from 0.59 to 1.13 kJ/m2 with an increase in the graphene content from 0 to 15 wt %, reaching 1.53 kJ/m2 with the addition of 5 wt % C10[VImBr]2. Scanning electron microscopy images of the PF/GNP/C10[VImBr]2 composites revealed a rough morphology with numerous microcracks.

ProSTAGE: Predicting Effects of Mutations on Protein Stability by Using Protein Embeddings and Graph Convolutional Networks.

Protein thermodynamic stability is essential to clarify the relationships among structure, function, and interaction. Therefore, developing a faster and more accurate method to predict the impact of the mutations on protein stability is helpful for protein design and understanding the phenotypic variation. Recent studies have shown that protein embedding will be particularly powerful at modeling sequence information with context dependence, such as subcellular localization, variant effect, and secondary structure prediction. Herein, we introduce a novel method, ProSTAGE, which is a deep learning method that fuses structure and sequence embedding to predict protein stability changes upon single point mutations. Our model combines graph-based techniques and language models to predict stability changes. Moreover, ProSTAGE is trained on a larger data set, which is almost twice as large as the most used S2648 data set. It consistently outperforms all existing state-of-the-art methods on mutation-affected problems as benchmarked on several independent data sets. The protein embedding as the prediction input achieves better results than the previous results, which shows the potential of protein language models in predicting the effect of mutations on proteins. ProSTAGE is implemented as a user-friendly web server.

Echinacoside exerts neuroprotection via suppressing microglial α-synuclein/TLR2/NF-κB/NLRP3 axis in parkinsonian models.

BACKGROUND: Echinacoside (ECH), a natural active compound, was found to exert neuroprotection in Parkinson's disease (PD). However, the underlying molecular mechanisms remain controversial. PURPOSE: This study aimed to explore the roles of ECH in PD and its engaged mechanisms. CONCLUSION: In vivo, MPTP was adapted to construct subacute PD mouse model to explore the regulation of ECH on NLRP3 inflammasome. In vitro, α-synuclein (α-syn)/MPP+ was used to mediate the activation of NLRP3 inflammasome in BV2 cells, and the mechanism of ECH regulation of it was explored with molecular docking, immunofluorescence, Western blotting, and small molecule inhibitors. CONCLUSION: The activation of microglial NLRP3 inflammasome could be evoked by MPTP in vitro, but its toxic metabolite MPP+ alone cannot trigger the activation of NLRP3 inflammasome in vitro, which requires α-synuclein (α-syn) priming. Exogenous α-syn could evoke microglial TLR2/NF-κB/NLRP3 axis, playing the priming role in MPP+ -mediated NLRP3 inflammasome activation. ECH can suppress the upregulation of α-syn in MPTP-treated mice and BV2 microglia. It can also suppress the activation of the TLR2/NF-κB/NLRP3 axis induced by α-syn. CONCLUSION: ECH exerts neuroprotective effects by downregulating the TLR2/NF-κB/NLRP3 axis via reducing the expression of α-syn in the PD models.

Hydrological characteristics of the Bering Sea in the summer of 2019.

Based on the data of three CTD sections in the northern, northeastern and western Bering Sea of 2019 voyage of Chinese National Arctic Research Expedition (CHINARE), this paper analyzes and studies the hydrological characteristics of the water mass distribution, layered structure, and cline characteristics in different sea areas of the Bering Sea. The results indicate that the hydrological characteristics of the Bering Sea in the summer of 2019 are different from those in the past and that the water mass is warming in many locations. The maximum water temperature reaches 11.13 °C, and the maximum thickness of the warm water is about 32 m. The water mass composition and characteristics of the north-northeast-west sections are significantly different: the BL section has the highest salinity, while the BS section has the lowest salinity, and both the lowest temperature and the largest temperature variation appear in the BL section. The stratification characteristics in all sea areas are noteworthy. In the deep-water seas, there are three types of water masses: upper water (BSW), middle water (BIW) and deep water (BDW) from top to bottom, while two main water masses appear in the shelf waters with the Alaska Coastal Water (ACW) overlies the Bering Sea Shelf Water (BSW). Along the Bering Sea Slope Current (BSC), the water mass is essentially steady. Statically unstable hydrological inversion structure appears near the bottom of the three stations at the northern end of the BL section.

High-Performance FAU Zeolite Membranes Derived from Nano-Seeds for Gas Separation.

In this study, high-performance FAU (NaY type) zeolite membranes were successfully synthesized using small-sized seeds of 50 nm, and their gas separation performance was systematically evaluated. Employing nano-sized NaY seeds and an ultra-dilute reaction solution with a molar composition of 80 Na2O: 1Al2O3: 19 SiO2: 5000H2O, the effects of synthesis temperature, crystallization time, and porous support (α-Al2O3 or mullite) on the formation of FAU membranes were investigated. The results illustrated that further extending the crystallization time or increasing the synthesis temperature led to the formation of a NaP impurity phase on the FAU membrane layer. The most promising FAU membrane with a thickness of 2.7 µm was synthesized on an α-Al2O3 support at 368 K for 8 h and had good reproducibility. The H2 permeance of the membrane was as high as 5.34 × 10-7 mol/(m2 s Pa), and the H2/C3H8 and H2/i-C4H10 selectivities were 183 and 315, respectively. The C3H6/C3H8 selectivity of the membrane was as high as 46, with a remarkably high C3H6 permeance of 1.35 × 10-7 mol/(m2 s Pa). The excellent separation performance of the membrane is mainly attributed to the thin, defect-free membrane layer and the relatively wide pore size (0.74 nm).

Index of consciousness monitoring during general anesthesia may effectively enhance rehabilitation in elderly patients undergoing laparoscopic urological surgery: a randomized controlled clinical trial.

BACKGROUND: Based on electroencephalogram (EEG) analysis, index of consciousness (IoC) monitoring is a new technique for monitoring anesthesia depth. IoC is divided into IoC1 (depth of sedation) and IoC2 (depth of analgesia). The potential for concurrent monitoring of IoC1 and IoC2 to expedite postoperative convalescence remains to be elucidated. We investigated whether combined monitoring of IoC1 and IoC2 can effectively enhances postoperative recovery compared with bispectral index (BIS) in elderly patients undergoing laparoscopic urological surgery under general anesthesia. METHODS: In this prospective, controlled, double-blinded trail, 120 patients aged 65 years or older were arbitrarily assigned to either the IoC group or the control group (BIS monitoring). All patients underwent blood gas analysis at T1 (before anesthesia induction) and T2 (the end of operation). The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were administered to all patients at T0 (1 day before surgery) and T4 (7 days after surgery). Serum concentrations of C-reactive protein (CRP) and glial fibrillary acid protein (GFAP) were assessed at T1, T2, and T3 (24 h after surgery). Postoperative complications and the duration of hospitalization were subjected to comparative evaluation. RESULTS: The incidence of postoperative cognitive dysfunction (POCD) was notably lower in the IoC group (10%) than in the control group (31.7%) (P = 0.003). Postoperative serum CRP and GFAP concentrations exhibited significant differences at time points T2 (CRP: P = 0.000; GFAP: P = 0.000) and T3 (CRP: P = 0.003; GFAP: P = 0.008). Postoperative blood glucose levels (P = 0.000) and the overall rate of complications (P = 0.037) were significantly lower in Group IoC than in Group control. CONCLUSION: The employment of IoC monitoring for the management of elderly surgical patients can accelerate postoperative convalescence by mitigating intraoperative stress and reducing peripheral and central inflammatory injury. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR1900025241 (17/08/2019).

Incidence, prevention, risk factors, and prediction of venous thromboembolism in Chinese patients after colorectal cancer surgery: a prospective, multicenter cohort study.

BACKGROUND: Venous thromboembolism (VTE) is a common and serious complication after colorectal cancer (CRC) surgery. Few large-sample studies have reported VTE incidence and management status after CRC surgery in China. This study aimed to investigate the incidence and prevention of VTE in Chinese patients after CRC surgery, identify risk factors for developing VTE, and construct a new scoring system for clinical decision-making and care planning. METHODS: Participants were recruited from 46 centers in 17 provinces in China. Patients were followed up for 1 month postoperatively. The study period was from May 2021 to May 2022. The Caprini score risk stratification and VTE prevention and incidence were recorded. The predictors of the occurrence of VTE after surgery were identified by multivariate logistic regression analysis, and a prediction model (CRC-VTE score) was developed. RESULTS: A total of 1836 patients were analyzed. The postoperative Caprini scores ranged from 1 to 16 points, with a median of 6 points. Of these, 10.1% were classified as low risk (0-2 points), 7.4% as moderate risk (3-4 points), and 82.5% as high risk (≥5 points). Among these patients, 1210 (65.9%) received pharmacological prophylaxis, and 1061 (57.8%) received mechanical prophylaxis. The incidence of short-term VTE events after CRC surgery was 11.2% (95% CI 9.8-12.7), including deep venous thrombosis (DVT) (11.0%, 95% CI 9.6-12.5) and pulmonary embolism (PE) (0.2%, 95% CI 0-0.5). Multifactorial analysis showed that age (≥70 years), history of varicose veins in the lower extremities, cardiac insufficiency, female sex, preoperative bowel obstruction, preoperative bloody/tarry stool, and anesthesia time at least 180 min were independent risk factors for postoperative VTE. The CRC-VTE model was developed from these seven factors and had good VTE predictive performance ( C -statistic 0.72, 95% CI 0.68-0.76). CONCLUSIONS: This study provided a national perspective on the incidence and prevention of VTE after CRC surgery in China. The study offers guidance for VTE prevention in patients after CRC surgery. A practical CRC-VTE risk predictive model was proposed.