Chemical stability of carbon pool in peatlands dominated by different plant types in Jilin province (China) and its potential influencing factors

IntroductionThe peat carbon pool stores 30% of the total global soil carbon accounting for 3–4% of the global land surface. The stability of the peatland carbon pool is a key factor affecting global carbon cycling that is seriously disturbed by climate change and regional human activities. However, the impact of these factors on carbon pool stability remains poorly understood.MethodsBased on the physicochemical properties and carbon compounds of 973 peat samples from Jilin Province (China), which are widely distributed in different altitude regions of the Changbai Mountains, we investigated the stability of the carbon pool in different dominant plants and degradation types of peatlands and assessed the effects of regional environmental factors on the peatland carbon pool.Results and DiscussionOur results showed that the carbohydrate content of peat soils in different peatland types ranged from 33.2 ± 6.9% to 40.5 ± 4.8%, and the aromatic content ranged from 19.8 ± 1.2% to 22.7 ± 2.3%. Bulk density is the most important physicochemical factor, and annual average temperature is the most important environmental factor that influences carbon stability. The effects of selected environmental factors on the peatland carbon pool covered by different plants were different, and the carbon stability in shrub peatlands is more sensitive to climate characteristics than in peatlands dominated by the other two plant types. Peatland degradation decreases the carbon stability in herb and herb/shrub peatlands and increases the carbon stability in shrub peatlands, leading the peatland carbon pool to be more easily influenced by regional human activities than natural peatlands

Full genome characterization and evolutionary analysis of Banna virus isolated from Culicoides, mosquitoes and ticks in Yunnan, China

IntroductionBanna virus (BAV), a potential pathogen that may cause human encephalitis, is the prototype species of genus Seadornaviru within the family Reoviridae, and has been isolated from a variety of blood-sucking insects and mammals in Asia.MethodsCulicoides, Mosquitoes, and Ticks were collected overnight in Yunnan, China, during 2016-2023 using light traps. Virus was isolated from these collected blood-sucking insects and grown using Aedes albopictus (C6/36) cells. Preliminary identification of the virus was performed by agarose gel electrophoresis (AGE). The full genome sequences of the BAVs were determined by full-length amplification of cDNAs (FLAC) and sequenced using next-generation sequencing.ResultsIn this study, 13 strains BAV were isolated from Culicoides, Mosquitoes and Ticks. Their viral genome consisted of 12 segments of double-stranded RNA (dsRNA), and with three distinct distribution patterns. Sequence analysis showed that Seg-5 of four strains (SJ_M46, SJ_M49, JC_M19-13 and JC_C24-13) has 435 bases nucleotide sequence insertions in their ORF compared to other BAVs, resulting in the length of Seg-5 up to 2128 nt. There are 34 bases sequence deletion in Seg-9 of 3 strains (WS_T06, MS_M166 and MS_M140). Comparison of the coding sequences of VP1, VP2, VP5, VP9 and VP12 of the 13 BAV strains, the results show that VP1, VP2 and VP12 are characterised by high levels of sequence conservation, while VP9 is highly variable, under great pressure to adapt and may be correlated with serotype. While also variable, VP5 appears to be under less adaptive pressure than VP9. Additionally, phylogenetic analysis indicates that the 13 BAV strains locate in the same evolutionary cluster as BAVs isolated from various blood-sucking insects, and are clustered according to geographical distribution.ConclusionThe data obtained herein would be beneficial for the surveillance of evolutionary characteristics of BAV in China and neighboring countries as well as extend the knowledge about its genomic diversity and geographic distribution

Gut Symbionts alleviate Mash Through a Secondary Bile acid Biosynthetic Pathway

The gut microbiota has been found to play an important role in the progression of metabolic dysfunction-associated steatohepatitis (MASH), but the mechanisms have not been established. Here, by developing a click-chemistry-based enrichment strategy, we identified several microbial-derived bile acids, including the previously uncharacterized 3-succinylated cholic acid (3-sucCA), which is negatively correlated with liver damage in patients with liver-tissue-biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD). By screening human bacterial isolates, we identified Bacteroides uniformis strains as effective producers of 3-sucCA both in vitro and in vivo. By activity-based protein purification and identification, we identified an enzyme annotated as β-lactamase in B. uniformis responsible for 3-sucCA biosynthesis. Furthermore, we found that 3-sucCA is a lumen-restricted metabolite and alleviates MASH by promoting the growth of Akkermansia muciniphila. together, our data offer new insights into the gut microbiota-liver axis that may be leveraged to augment the management of MASH

Analysis between ABO blood group and clinical outcomes in COVID-19 patients and the potential mediating role of ACE2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the most common coronavirus that causes large-scale infections worldwide. Currently, several studies have shown that the ABO blood group is associated with coronavirus disease 2019 (COVID-19) infection and some studies have also suggested that the infection of COVID-19 may be closely related to the interaction between angiotensin-converting enzyme 2 (ACE2) and blood group antigens. However, the relationship between blood type to clinical outcome in critically ill patients and the mechanism of action is still unclear. The current study aimed to examine the correlation between blood type distribution and SARS-CoV-2 infection, progression, and prognosis in patients with COVID-19 and the potential mediating role of ACE2. With 234 patients from 5 medical centers and two established cohorts, 137 for the mild cohort and 97 for the critically ill cohort, we found that the blood type A population was more sensitive to SARS-CoV-2, while the blood type distribution was not relevant to acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and mortality in COVID-19 patients. Further study showed that the serum ACE2 protein level of healthy people with type A was significantly higher than that of other blood groups, and type O was the lowest. The experimental results of spike protein binding to red blood cells also showed that the binding rate of people with type A was the highest, and that of people with type O was the lowest. Our finding indicated that blood type A may be the biological marker for susceptibility to SARS-CoV-2 infection and may be associated with potential mediating of ACE2, but irrelevant to the clinical outcomes including ARDS, AKI, and death. These findings can provide new ideas for clinical diagnosis, treatment, and prevention of COVID-19

Temporal Prediction of Landslide-GeneratedWaves Using a Theoretical–Statistical Combined Method.

For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship between the wave characteristics and slide features. We gave specific insights into impulse waves generated by snow avalanches and mimicked them using a buoyant material called Carbopol whose density is close to that of water. Using the particle image velocimetry (PIV) technique, the slide’s temporal velocity field and thickness, as well as the temporal free water surface fluctuation, were determined experimentally. Using a statistical method denoted as panel data analysis, we quantified the temporal wave amplitude from the time series data of the thickness and depth-averaged velocity of the sliding mass at the shoreline. Then, the slide’s temporal thickness and velocity at the shoreline were estimated from the parameters of the stationary slide at the initial position, based on the viscoplastic theory. Combining the panel data analysis and the viscoplastic theory, the temporal wave amplitudes were estimated from the initial slide parameters. In the end, we validated the proposed theoretical–statistical combined predictive method with the support of experimental data.LH

Temporal Prediction of Landslide-Generated Waves Using a Theoretical–Statistical Combined Method

For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship between the wave characteristics and slide features. We gave specific insights into impulse waves generated by snow avalanches and mimicked them using a buoyant material called Carbopol whose density is close to that of water. Using the particle image velocimetry (PIV) technique, the slide’s temporal velocity field and thickness, as well as the temporal free water surface fluctuation, were determined experimentally. Using a statistical method denoted as panel data analysis, we quantified the temporal wave amplitude from the time series data of the thickness and depth-averaged velocity of the sliding mass at the shoreline. Then, the slide’s temporal thickness and velocity at the shoreline were estimated from the parameters of the stationary slide at the initial position, based on the viscoplastic theory. Combining the panel data analysis and the viscoplastic theory, the temporal wave amplitudes were estimated from the initial slide parameters. In the end, we validated the proposed theoretical–statistical combined predictive method with the support of experimental data

The Momentum Transfer Mechanism of a Landslide Intruding a Body of Water

Landslide-generated waves occur as a result of the intrusion of landslides such as mud flows and debris flows into bodies of water such as lakes and reservoirs. The objective of this study was to determine how the momentum is transferred from the sliding mass to the body of water on the basis of theoretical analysis and physical model experiments. Considering the viscoplastic idealization of natural landslides, the theoretical model was established based on the momentum and mass conservation of a two-phase flow in a control volume. To close the theoretical equations, slide thickness and velocity passing through the left boundary of the control volume were estimated by lubrication theory, and the interaction forces between the slide phase and water phase, including hydrostatic force and drag force, were given by semiempirical equations fitted with experimental data obtained using the particle image velocimetry (PIV) technique. The near-field velocity fields of both the sliding mass and the body of water, as well as the air–water–slide interfaces, were determined from the experiments. The theoretical model was validated by comparing the theoretical and experimental data of the slide thickness and slide velocity, as well as the momentum variations of the two phases in the control volume

Effect of Er on Microstructure and Corrosion Behavior of Al–Zn–Mg–Cu–Sc–Zr Aluminum Alloys

In this study, the influence of Er addition on the microstructure, type transformation of second phases, and corrosion resistance of an Al–Zn–Mg–Cu alloy were explored. The results revealed that the added Er element could significantly refine the alloy grains and change the second-phase composition at the grain boundary of the alloy. In the as-cast state, the Er element significantly enhanced the corrosion resistance of the alloy due to its refining effect on the grains and second phases at the grain boundary. The addition of the alloying element Er to the investigated alloy changed the type of corrosion attack on the alloy’s surface. In the presence of Er, the dominant type of corrosion attack is pitting corrosion, while the alloy without Er is prone to intergranular corrosion attack. After a solution treatment, the Al8Cu4Er phase was formed, in which the interaction with the Cu element and the competitive growth relation to the Al3Er phase were the key factors influencing the corrosion resistance of the alloy. The anodic corrosion mechanism of the Al8Cu4Er and Al3Er phases evidently lowered the alloy corrosion rate, and the depth of the corrosion pit declined from 197 μm to 155 μm; however, further improvement of corrosion resistance was restricted by the morphology and size of the Al8Cu4Er phase after its formation and growth; therefore, adjusting the matching design of the Cu and Er elements can allow Er to improve the corrosion resistance of the Al–Zn–Mg–Cu aluminum alloy to the greatest extent

Preparation and Characterization of Polysaccharide-Based Hydrogels for Cutaneous Wound Healing

Natural hydrogels are growing in interest as a priority for wound healing. Plant polysaccharides have a variety of biological pharmacological activities, and chitosan hydrogels have proven strong antimicrobial effects, but hydrogels prepared with polysaccharides alone have certain deficiencies. Polysaccharides from flowers of Lonicera japonica Thunb. (LP) and the aerial parts of Mentha canadensis L. (MP) were extracted and oxidized by sodium periodate (NaIO4) and then cross-linked with oxidized-carboxymethylated chitosan (O-CCS) to develop oxidized plant- polysaccharides-chitosan hydrogels (OPHs). SEM observation showed that OPHs had porous interior structures with interconnecting pores. The OPHs showed good swelling, water-retention ability, blood coagulation, cytocompatibility properties, and low cytotoxicity (classed as grade 1 according to United States Pharmacopoeia), which met the requirements for wound dressings. Then the cutaneous wound-healing effect was evaluated in BALB/C mice model, after 7 days treatment, the wound-closure rate of OPHs groups were all greater than 50%, and after 14 days, all were greater than 90%, while the value of the control group was only 72.6%. Of them, OPH-2 and OPH-3 were more favorable to the wound-healing process, as the promotion was more significant. The plant polysaccharides and CS-based hydrogel should be a candidate for cutaneous wound dressings

Coupling Fault Diagnosis Based on Dynamic Vertex Interpretable Graph Neural Network

Mechanical equipment is composed of several parts, and the interaction between parts exists throughout the whole life cycle, leading to the widespread phenomenon of fault coupling. The diagnosis of independent faults cannot meet the requirements of the health management of mechanical equipment under actual working conditions. In this paper, the dynamic vertex interpretable graph neural network (DIGNN) is proposed to solve the problem of coupling fault diagnosis, in which dynamic vertices are defined in the data topology. First, in the date preprocessing phase, wavelet transform is utilized to make input features interpretable and reduce the uncertainty of model training. In the fault topology, edge connections are made between nodes according to the fault coupling information, and edge connections are established between dynamic nodes and all other nodes. Second the data topology with dynamic vertices is used in the training phase and in the testing phase, the time series data are only fed into dynamic vertices for classification and analysis, which makes it possible to realize coupling fault diagnosis in an industrial production environment. The features extracted in different layers of DIGNN interpret how the model works. The method proposed in this paper can realize the accurate diagnosis of independent faults in the dataset with an accuracy of 100%, and can effectively judge the coupling mode of coupling faults with a comprehensive accuracy of 88.3%