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Purpose: This study elucidates the rationale, implementation, values, and challenges of the Synergized Quality Improvement Program in Teacher Education (SQIPTE)--the first policy specifically dedicated to the development of teaching staff since the founding of the People's Republic of China. Design/Approach/Methods: After introducing the primary structure and rationale of the SQIPTE, this study reviews the existing data and research to explain why the program focuses on local normal colleges and determine how it could be implemented more effectively. Findings: In establishing group-based assistance under the principle of "1 + M + N" (M [greater than or equal to] N), the SQIPTE seeks to make normal colleges the primary force in the education of rural teachers and explores a collaborative operating mechanism to this end. Evidence suggests that this innovative program will provide new practical experience for the collaborative development and quality improvement of teachers. Originality/Value: This study reviews the SQIPTE as a new Chinese intervention to improve the quality of rural teachers. There is strong evidence to suggest that this innovative program will inspire the construction of collaborative operating mechanisms incorporating multiple resources for teacher education systems across different areas.

Abstract The mud carp (Cirrhinus molitorella) is an important economic farmed fish, mainly distributed in South China and Southeast Asia due to its strong adaptability and high yield. Despite its economic importance, the paucity of genomic information has constrained detailed genetic research and breeding efforts. In this study, we utilized PacBio HiFi long-read sequencing and Hi-C technologies to generate a meticulously assembled chromosome-level genome of the mud carp. This assembly spans 1,033.41 Mb, with an impressive 99.82% distributed across 25 chromosomes. The contig N50 and scaffold N50 are 33.29 Mb and 39.86 Mb, respectively. The completeness of the mud carp genome assembly is highlighted by a BUSCO score of 98.05%. We predict 25,865 protein-coding genes, with a BUSCO score of 96.54%, and functional annotations for 91.83% of these genes. Approximately 52.21% of the genome consists of repeat elements. This high-fidelity genome assembly is a vital resource for advancing molecular breeding, comparative genomics, and evolutionary studies of the mud carp and related species.

Abstract Background Aging often leads to changes in hormone levels, particularly testosterone, which is thought to significantly affect bone health in older males. Objective This study aimed to explore the link between testosterone levels and bone mineral density in men aged 60 and above. Methods Data from the National Health and Nutrition Examination Survey 2013–2014 were used. Weighted multivariable linear regression models were employed to study the association between testosterone and bone mineral density. Furthermore, a weighted generalized additive model and smooth curve fitting were used to address potential nonlinear patterns in the data. Results The analysis included 621 elderly men. After accounting for various factors, the study uncovered a Inverted U-shaped correlation between testosterone levels and femoral neck density. Notably, a turning point was identified at the testosterone level of 406.4 ng/dL. Further examination, using different models, showed that testosterone levels in the third quartile (group Q3) were positively linked to bone density. However, contrasting trends were observed in the first (group Q1) and fourth quartiles (group Q4), where testosterone levels displayed a negative relationship with bone density. Conclusion The results indicate a complex interplay between testosterone levels and bone mineral density in elderly men. The U-shaped trend suggests that both low and high testosterone levels could negatively impact bone health. These findings highlight the importance of maintaining testosterone levels within an optimal range to preserve bone health in aging men.

Abstract Transition metal carbide shows excellent performance in selective hydrogenation of acetylene, however, the carburization of Pd-based intermetallic compounds remains infeasible. Here we report the successful synthesis of an unprecedented Pd3ZnCx intermetallic carbide, via co-infiltration of zinc and carbon in one-step carburization by syngas. Utilizing state-of-the-art in situ characterizations and theoretical calculation, we unveil the dynamic evolution of Pd3ZnCx during carburization, forming a Pd3Zn like cubic phase carbide structure. A unique transitional state (Pdt) with low content of Zn/C co-infiltration is clearly identified facilitating phase transition and sustain incorporation of carbon and zinc at elevated temperatures. The Pd3ZnCx carbide shows by far the best catalytic performance in the selective hydrogenation of acetylene with a high selectivity (>90%) even at a high H2/C2H2 ratio. Our results therefore provide a co-infiltration strategy and dynamic insights for the one-step synthesis of Pd based intermetallic carbides, towards high-performance intermetallic compound for selective hydrogenation of acetylene.

Abstract To study the influence of different geological and mining factors on the decompression effect of protective layer mining, a numerical simulation was carried out using FLAC3D numerical software. Taking the Hulusu coal mine as the engineering background, numerical simulation studies were carried out under different mining heights, working face lengths, interlayer lithologies and layer spacing by using FLAC3D numerical software, and the effects of different geological and mining factors on the degree of decompression and the scope of decompression were quantitatively investigated through the control of single‐factor variables. The results show that: the stress at the critical depth of impact ground pressure is 16.44 MPa, and the coefficient of unloading degree C = 0.5 is the indicator of sufficient unloading; the unloading effect of the protected layer decreases with the increase of layer spacing, lithological strength, and length of the working face, and increases with the increase of mining height; the geological and mining parameters of the protected layer show a functional relationship with the critical depth of the unloading, and the order of the influence of pressure relief effect is layer spacing > mining height > interlayer lithology > working face length. The results of the study are very important for the determination of the mining parameters of the protective layer, the estimation of the protective effect, and the design of the management programme of impact pressure.

Abstract Human action understanding (HAU) is a broad topic that involves specific tasks, such as action localisation, recognition, and assessment. However, most popular HAU datasets are bound to one task based on particular actions. Combining different but relevant HAU tasks to establish a unified action understanding system is challenging due to the disparate actions across datasets. A large‐scale and comprehensive benchmark, namely SkatingVerse is constructed for action recognition, segmentation, proposal, and assessment. SkatingVerse focus on fine‐grained sport action, hence figure skating is chosen as the task object, which eliminates the biases of the object, scene, and space that exist in most previous datasets. In addition, skating actions have inherent complexity and similarity, which is an enormous challenge for current algorithms. A total of 1687 official figure skating competition videos was collected with a total of 184.4 h, exceeding four times over other datasets with a similar topic. SkatingVerse enables to formulate a unified task to output fine‐grained human action classification and assessment results from a raw figure skating competition video. In addition, SkatingVerse can facilitate the study of HAU foundation model due to its large scale and abundant categories. Moreover, image modality is incorporated for human pose estimation task into SkatingVerse. Extensive experimental results show that (1) SkatingVerse significantly helps the training and evaluation of HAU methods, (2) the performance of existing HAU methods has much room to improve, and SkatingVerse helps to reduce such gaps, and (3) unifying relevant tasks in HAU through a uniform dataset can facilitate more practical applications. SkatingVerse will be publicly available to facilitate further studies on relevant problems.

Abstract Background Oocytes, the largest cells in mammals, harbor numerous mitochondria within their cytoplasm. These highly dynamic organelles are crucial for providing energy resources and serving as central regulators during oogenesis. Mitochondrial dynamics ensure proper energy distribution for various cellular processes involved in oocyte maturation. Previous studies have used alterations in mitochondrial distribution as a biomarker to assess the oocyte health. However, there are discrepancies between studies regarding mitochondrial distribution profiles in healthy oocytes. Consequently, a comprehensive mitochondrial distribution profile in oocytes during maturation has not been fully characterized. Additionally, there is a lack of objective, quantitative methods to evaluate alterations in mitochondrial distribution profiles in oocytes. Methods This study aims to provide an in-depth overview of mitochondrial distribution profiles in mouse oocytes at different maturation stages: germinal vesicle (GV) stage, metaphase I (MI), and mature metaphase II (MII). Freshly collected mouse GV, MI and MII oocytes were stained with MitoTracker Red. Confocal microscopy was used to obtain images of mitochondrial distribution profiles in these oocytes. Using the Imaris software, we reconstructed three-dimensional (3D) surface renderings of each oocyte and quantitatively illustrated the mitochondrial distribution profiles. Results At the GV stage, mitochondria in oocytes were evenly distributed throughout the ooplasm. As oocytes progressed to MI and MII stages, mitochondria aggregated and formed clusters, the mean size of mitochondrial clusters and the proportions of clustered mitochondria increased along with the maturation of oocytes. Conclusions Our findings reveal that mitochondria in mouse oocytes are highly dynamic, undergoing significant reorganizations during oocyte maturation. We for the first time provided comprehensive mitochondrial distribution profiles in mouse oocytes at the GV, MI and MII stages. These mitochondrial distribution profiles were further quantitatively evaluated. Our methods provide an objective and standardized approach for evaluating alterations in mitochondrial dynamics, which can be used as biomarkers to monitor oocyte conditions during maturation.

Abstract Intermetallic nanoparticles (NPs) possess significant potentials for catalytic applications, yet their production presents challenges as achieving the disorder-to-order transition during the atom ordering process involves overcoming a kinetic energy barrier. Here, we demonstrate a robust approach utilizing atomic gas-migration for the in-situ synthesis of stable and homogeneous intermetallic alloys for propane dehydrogenation (PDH). This approach relies on the physical mixture of two separately supported metal species in one reactor. The synthesized platinum-zinc intermetallic catalysts demonstrate exceptional stability for 1300 h in continuous propane dehydrogenation under industrially relevant industrial conditions, with extending 95% propylene selectivity and propane conversions approaching thermodynamic equilibrium values at 550–600 oC. In situ characterizations and density functional theory/molecular dynamics simulation reveal Zn atoms adsorb on the particle surface and then diffuse inward, aiding in the formation of ultrasmall and highly ordered intermetallic alloys. This in-situ gas-migration strategy is applicable to a wide range of intermetallic systems.

Abstract Low-cost, efficient catalyst high-throughput screening is crucial for future renewable energy technology. Interpretable machine learning is a powerful method for accelerating catalyst design by extracting physical meaning but faces huge challenges. This paper describes an interpretable descriptor model to unify activity and selectivity prediction for multiple electrocatalytic reactions (i.e., O2/CO2/N2 reduction and O2 evolution reactions), utilizing only easily accessible intrinsic properties. This descriptor, named ARSC, successfully decouples the atomic property (A), reactant (R), synergistic (S), and coordination effects (C) on the d-band shape of dual-atom sites, which is built upon our developed physically meaningful feature engineering and feature selection/sparsification (PFESS) method. Driven by this descriptor, we can rapidly locate optimal catalysts for various products instead of over 50,000 density functional theory calculations. The model’s universality has been validated by abundant reported works and subsequent experiments, where Co-Co/Ir-Qv3 are identified as optimal bifunctional oxygen reduction and evolution electrocatalysts. This work opens the avenue for intelligent catalyst design in high-dimensional systems linked with physical insights.

Abstract Background Blotched snakehead (Channa maculata) displays significant sexual dimorphism, with males exhibiting faster growth rates and larger body sizes compared to females. The cultivation of the all-male population of snakeheads holds substantial economic and ecological value. Nonetheless, the intricate processes governing the development of bipotential gonads into either testis or ovary in C. maculata remain inadequately elucidated. Therefore, it is necessary to determine the critical time window of sex differentiation in C. maculata, providing a theoretical basis for sex control in production practices. Methods The body length and weight of male and female C. maculata were measured at different developmental stages to reveal when sexual dimorphism in growth initially appears. Histological observations and spatiotemporal comparative transcriptome analyses were performed on ovaries and testes across various developmental stages to determine the crucial time windows for sex differentiation in each sex and the sex-related genes. Additionally, qPCR and MG2C were utilized to validate and locate sex-related genes, and levels of E2 and T were quantified to understand sex steroid synthesis. Results Sexual dimorphism in growth became evident starting from 90 dpf. Histological observations revealed that morphological sex differentiation in females and males occurred between 20 and 25 dpf or earlier and 30–35 dpf or earlier, respectively, corresponding to the appearance of the ovarian cavity or efferent duct anlage. Transcriptome analyses revealed divergent gene expression patterns in testes and ovaries after 30 dpf. The periods of 40–60 dpf and 60–90 dpf marked the initiation of molecular sex differentiation in females and males, respectively. Male-biased genes (Sox11a, Dmrt1, Amh, Amhr2, Gsdf, Ar, Cyp17a2) likely play crucial roles in male sex differentiation and spermatogenesis, while female-biased genes (Foxl2, Cyp19a1a, Bmp15, Figla, Er) could be pivotal in ovarian differentiation and development. Numerous biological pathways linked to sex differentiation and gametogenesis were also identified. Additionally, E2 and T exhibited sexual dimorphism during sex differentiation and gonadal development. Based on these results, it is hypothesized that in C. maculata, the potential male sex differentiation pathway, Sox11a–Dmrt1–Sox9b, activates downstream sex-related genes (Amh, Amhr2, Gsdf, Ar, Cyp17a2) for testicular development, while the antagonistic pathway, Foxl2/Cyp19a1a, activates downstream sex-related genes (Bmp15, Figla, Er) for ovarian development. Conclusions This study provides a comprehensive overview of gonadal dynamic changes during sex differentiation and gametogenesis in C. maculata, establishing a scientific foundation for sex control in this species.

Background Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development. Purpose This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Abstract Background The RNA N 6-methyladenosine (m6A) modification has become an essential hotspot in epigenetic modulation. Serine–arginine protein kinase 1 (SRPK1) is associated with the pathogenesis of various cancers. However, the m6A modification of SRPK1 and its association with the mechanism of in lung adenocarcinoma (LUAD) remains unclear. Methods Western blotting and polymerase chain reaction (PCR) analyses were carried out to identify gene and protein expression. m6A epitranscriptomic microarray was utilized to the assess m6A profile. Loss and gain-of-function assays were carried out elucidate the impact of METTL3 and SRPK1 on LUAD glycolysis and tumorigenesis. RNA immunoprecipitation (RIP), m6A RNA immunoprecipitation (MeRIP), and RNA stability tests were employed to elucidate the SRPK1’s METTL3-mediated m6A modification mechanism in LUAD. Metabolic quantification and co-immunoprecipitation assays were applied to investigate the molecular mechanism by which SRPK1 mediates LUAD metabolism. Results The epitranscriptomic microarray assay revealed that SRPK1 could be hypermethylated and upregulated in LUAD. The main transmethylase METTL3 was upregulated and induced the aberrant high m6A levels of SRPK1. Mechanistically, SRPK1’s m6A sites were directly methylated by METTL3, which also stabilized SRPK1 in an IGF2BP2-dependent manner. Methylated SRPK1 subsequently promoted LUAD progression through enhancing glycolysis. Further metabolic quantification, co-immunoprecipitation and western blot assays revealed that SRPK1 interacts with hnRNPA1, an important modulator of PKM splicing, and thus facilitates glycolysis by upregulating PKM2 in LUAD. Nevertheless, METTL3 inhibitor STM2457 can reverse the above effects in vitro and in vivo by suppressing SRPK1 and glycolysis in LUAD. Conclusion It was revealed that in LUAD, aberrantly expressed METTL3 upregulated SRPK1 levels via an m6A-IGF2BP2-dependent mechanism. METTL3-induced SRPK1 fostered LUAD cell proliferation by enhancing glycolysis, and the small-molecule inhibitor STM2457 of METTL3 could be an alternative novel therapeutic strategy for individuals with LUAD.

Abstract Virus‒host protein‒lncRNA interaction (VHPLI) predictions are critical for decoding the molecular mechanisms of viral pathogens and host immune processes. Although VHPLI interactions have been predicted in both plants and animals, they have not been extensively studied in viruses. For the first time, we propose a new deep learning-based approach that consists mainly of a convolutional neural network and bidirectional long and short-term memory network modules in combination with transfer learning named CBIL‒VHPLI to predict viral–host protein‒lncRNA interactions. The models were first trained on large and diverse datasets (including plants, animals, etc.). Protein sequence features were extracted using a k-mer method combined with the one-hot encoding and composition–transition–distribution (CTD) methods, and lncRNA sequence features were extracted using a k-mer method combined with the one-hot encoding and Z curve methods. The results obtained on three independent external validation datasets showed that the pre-trained CBIL‒VHPLI model performed the best with an accuracy of approximately 0.9. Pretraining was followed by conducting transfer learning on a viral protein–human lncRNA dataset, and the fine-tuning results showed that the accuracy of CBIL‒VHPLI was 0.946, which was significantly greater than that of the previous models. The final case study results showed that CBIL‒VHPLI achieved a prediction reproducibility rate of 91.6% for the RIP-Seq experimental screening results. This model was then used to predict the interactions between human lncRNA PIK3CD-AS2 and the nonstructural protein 1 (NS1) of the H5N1 virus, and RNA pull-down experiments were used to prove the prediction readiness of the model in terms of prediction. The source code of CBIL‒VHPLI and the datasets used in this work are available at https://github.com/Liu-Lab-Lnu/CBIL-VHPLI for academic usage.

Abstract The lncRNA NEAT1 has been shown to promote the progression of several cancers, containing laryngeal squamous cell carcinoma (LSCC). However, the precise mechanism by which it promotes LSCC progression remains unclear. In this study, we verified the high expression of lncRNA NEAT1 in LSCC tissues and cells using RT-qPCR. Analysis of clinical data exhibited that high expression of lncRNA NEAT1 was associated with a history of smoking, worse T stage, lymph node metastasis, and later TNM stage in patients with LSCC. The promotion effect of lncRNA NEAT1 on LSCC cell proliferation, migration, invasion, and tumor growth in vivo was verified by CCK-8, plate clone formation, Transwell, and nude mouse tumorigenicity assays. Bioinformatics prediction and double luciferase reporter gene assay verified the binding of miR-411-3p to lncRNA NEAT1 and FZD3 mRNA, and inhibition of miR-411-3p reversed the inhibitory effect of lncRNA NEAT1 on FZD3 expression in LSCC cells. We also verified that lncRNA NEAT1-mediated FZD3 activation in the Wnt pathway affects LSCC development. In conclusion, we demonstrate that lncRNA NEAT1 promotes the progression of LSCC, and propose that the lncRNA NEAT1/miR-411-3p/FZD3 axis may be an effective target for LSCC therapy.

Abstract Nickel (Ni) and copper (Cu) contamination have become major threats to plant survival worldwide. 24-epibrassinolide (24-EBR) and melatonin (MT) have emerged as valuable treatments to alleviate heavy metal-induced phytotoxicity. However, plants have not fully demonstrated the potential mechanisms by which these two hormones act under Ni and Cu stress. Herein, this study investigated the impact of individual and combined application of 24-EBR and MT on the growth and physiological traits of Primula forbesii Franch. subjected to stress (200 μmol L–1 Ni and Cu). The experiments compared the effects of different mitigation treatments on heavy metal (HM) stress and the scientific basis and practical reference for using these exogenous substances to improve HM resistance of P. forbesii in polluted environments. Nickel and Cu stress significantly hindered leaf photosynthesis and nutrient uptake, reducing plant growth and gas exchange. However, 24-EBR, MT, and 24-EBR + MT treatments alleviated the growth inhibition caused by Ni and Cu stress, improved the growth indexes of P. forbesii, and increased the gas exchange parameters. Exogenous MT effectively alleviated Ni stress, and 24-EBR + MT significantly alleviated the toxic effects of Cu stress. Unlike HM stress, MT and 24-EBR + MT activated the antioxidant enzyme activity (by increasing superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT)), significantly reduced reactive oxygen species (ROS) accumulation, and regulated ascorbate and glutathione cycle (AsA-GSH) efficiency. Besides, the treatments enhanced the ability of P. forbesii to accumulate HMs, shielding plants from harm. These findings conclusively illustrate the capability of 24-EBR and MT to significantly bolster the tolerance of P. forbesii to Ni and Cu stress.

Abstract Background To compare the repeatability and reproducibility of corneal and corneal epithelial thickness mapping using anterior segment optical coherence tomography (AS-OCT) according to tear film break-up time (TBUT). Methods The included eyes were divided into three subgroups according to TBUT (group 1: TBUT ≤ 5 s, group 2: 5 s 10 s). All eyes were imaged separately thrice by two operators to obtain the thickness maps (TMs) of the cornea and corneal epithelium based on spatial zones encompassing a 9-mm-diameter area. Each TM consisted of 25 areas. Intraoperator (repeatability) and interoperator (reproducibility) standard deviations (Sws), coefficients of variation (CoVs), and intraclass correlation coefficients (ICCs) among the tests were calculated and compared in all the areas. Results Altogether, 132 eyes of 67 subjects were included (50, 47, and 35 eyes in groups 1, 2, and 3; respectively). The ICCs of corneal epithelial thickness and corneal thickness were > 0.75 in most of the areas. Pairwise comparisons showed that AS-OCT exhibited lower repeatability in group 1 than in groups 2 and 3 (P

The first pandemic wave of coronavirus disease 2019 (COVID-19) induced a considerable increase in several antivirals and antibiotics in surface water. The common symptoms of COVID-19 are viral and bacterial infections, while comorbidities (e.g., hypertension and diabetes) and mental shock (e.g., insomnia and anxiety) are nonnegligible. Nevertheless, little is known about the long-term impacts of comorbidities and mental shock on organic micropollutants (OMPs) in surface waters. Herein, we monitored 114 OMPs in surface water and wastewater treatment plants (WWTPs) in Wuhan, China, between 2019 and 2021. The pandemic-induced OMP pollution in surface water was confirmed by significant increases in 26 OMP concentrations. Significant increases in four antihypertensives and one diabetic drug suggest that the treatment of comorbidities may induce OMP pollution. Notably, cotinine (a metabolite of nicotine) increased 155 times to 187 ng·L−1, which might be associated with increased smoking. Additionally, the increases in zolpidem and sulpiride might be the result of worsened insomnia and depression. Hence, it is reasonable to note that mental-health protecting drugs/behavior also contributed to OMP pollution. Among the observed OMPs, telmisartan, lopinavir, and ritonavir were associated with significantly higher ecological risks because of their limited WWTP-removal rate and high ecotoxicity. This study provides new insights into the effects of comorbidities and mental shock on OMPs in surface water during a pandemic and highlights the need to monitor the fate of related pharmaceuticals in the aquatic environment and to improve their removal efficiencies in WWTPs.

Abstract Ubiquitous moisture is of particular interest for sustainable power generation and self‐powered electronics. However, current moisture electric generators (MEGs) can only harvest moisture energy in the air, which tremendously limits the energy harvesting efficiency and practical application scenarios. Herein, the operationality of MEG from air to underwater environment, through a sandwiched engineered‐hydrogel device with an additional waterproof breathable membrane layer allowing water vapor exchange while preventing liquid water penetration, is expanded. Underwater environment, the device can spontaneously deliver a voltage of 0.55 V and a current density of 130 µA cm−2 due to the efficient ion separation assisted by negative ions confinement in hydrogel networks. The output can be maintained even under harsh underwater environment with 10% salt concentration, 1 m s−1 disturbing flow, as well as >40 kPa hydraulic pressure. The engineered hydrogel used for MEG also exhibits excellent self‐healing ability, flexibility, and biocompatibility. As the first demonstration of practical applications in self‐powered underwater electronics, the MEG device is successfully powering a wireless emitter for remote communication in water. This new type of MEG offers an innovative route for harvesting moisture energy underwater and holds promise in the creation of a new range of innovative electronic devices for marine Internet‐of‐Things.

Abstract Incorporation of CO into substrates to construct high‐value carbonyl compounds is an intensive industrial carbonylation procedure, however, high toxicity and wide explosion limits (12.5–74.0 vol% in air) of CO limit its application in industrial production. The development of a CO‐free catalytic system for carbonylation is one of ideal methods, but full of challenge. Herein, this study reports the CO‐free aminocarbonylation conversion of terminal alkynes synergistically catalyzed by a unique Co(ІІ)/Ag(І) metal–organic framework (MOF), in which the combination of isocyanides and O2 is employed as safe and green source of aminocarbonyl. This reaction has broad substrate applicability in terminal alkyne and isocyanides components with 100% atom economy. The bimetal MOF catalyst can be recycled at least five times without substantial loss of catalytic activities. Mechanistic investigations demonstrate that the synergistic effect between Ag(I) and Co(II) sites can efficiently activate terminal alkyne and isocyanides, respectively. Free radical capture experiments, FT‐IR analysis and theoretical explorations further reveal that terminal alkynes and isocyanides can be catalytically transformed into an anionic intermediate through heterolysis pathways. This work provides secure and practical access to carbonylation as well as a new approach to aminocarbonylation of terminal alkynes.

Abstract Based on plasma observations from Juno's Jovian Auroral Distributions Experiment instrument and forward modeling, we investigate the dawn‐dusk asymmetries within Jupiter's magnetosphere between 10 and 40 RJ. On the dawnside, the flux tubes are depleted characterized by low density and near rigid‐corotation velocity, with a low temperature and thin plasma sheet. On the duskside, the flux tubes are assimilated characterized by high density and sub‐corotation velocity, with a hotter and thicker plasma sheet. Super‐corotating hot inflows originating from reconnection events are identified in the pre‐dawn sector. These observations are consistent with the Vasyliūnas cycle, suggesting it operates in a region closer to Jupiter than previous studies suggested. Outflows are locally coupled with swept‐back magnetic fields and are frequently observed near midnight. Inflows are locally coupled with swept‐forward fields with higher temperatures. The discernible temperature difference between inflows and outflows reveals their distinct origins. Plasma beta increases with radial distance, suggesting increased instabilities at larger distances.

This study aimed to investigate the impact of acute velocity stress on the exercise physiology of mandarin fish (Siniperca chuatsi). Initially, the relative critical swimming speed (U’crit) was estimated to be around 4.87 body lengths per second (bl/s), while the relative burst swimming speed (U’burst) reached approximately 8.60 bl/s. Then, the results showed that as the flow velocity increased, the oxygen consumption rate (MO2) of mandarin fish gradually elevated, while the cost of transport (COT) displayed a decreasing trend. Subsequently, four groups were established for the experiment, including control group (0 %Ucrit), low flow velocity (20 %Ucrit), medium flow velocity (50 %Ucrit) and high flow velocity (80 %Ucrit). The results showed that with the increase of flow velocity, the content of muscle glycogen decreased gradually and the content of muscle lactate increased significantly. Furthermore, the results of serum myocardial enzymes and antioxidant enzymes showed that the levels of creatine kinase (CK), total antioxidant capacity (T-AOC) and glutathione peroxidase (GSH-Px) exhibited an initial increase followed by a decrease. During the examination of the gills, the highest level of Na+-K+-ATPase was reached at 80 %Ucrit, while the content of malondialdehyde (MDA) was significantly reduced. Additionally, transcriptomic sequencing was conducted on 0 %Ucrit and 80 %Ucrit groups, resulting in the identification of 101 upregulated genes and 116 downregulated genes. KEGG enrichment analysis revealed that the differentially expressed genes (DEGs) were significantly enriched in lipid metabolism and signal transduction. Finally, it was observed that the MAPK signaling pathway within the signaling transduction pathway exhibited the highest number of annotated DEGs. In general, it can be inferred that mandarin fish may regulate lipid peroxidation levels, and MAPK signaling pathway as an adaptive response to mitigate the effects induced by acute velocity stress. The above research is of great significance for improving the farming method of mandarin fish.

Yuanbaoshancha (YBSC) is characterized as a new wild tea relative morphologically and phytochemically distinguished from the closest wild tea plants Rongjiangcha (Camellia yungkiangensis, RJC) and Tulecha (Camellia costata, TLC). YBSC young leaves contain higher tea polyphenol and theobromine contents but lower caffeine and theanine as compared with RJC, TLC, and other tea landraces and modern cultivars. The major alkaloid detected in YBSC, TLC, and RJC is theobromine while caffeine is a minor; the primary catechins in YBSC leaves are non-galloylated catechins, significantly different from Camellia sinensis and other low-caffeine tea resources. The unique phytochemical profiles featured YBSC black tea with extremely lower caffeine and higher theobromine, as well as unique flavors and health benefits. This botanical characterization of YBSC and two related low-caffeine wild tea resources lays a foundation for future better utilization for the production of a highly valuable natural low-caffeine/high-theobromine tea. Chemical compounds: Caffeine (PubChem CID: 2519); Theobromine (PubChem CID: 5429); Catechins (PubChem CID: 9064); Epigallocatechin gallate (PubChem CID: 65064); Theanine (PubChem CID: 439378); Jasmone (PubChem CID: 1549018); cis-3-Hexenyl hexanoate (PubChem CID: 5352543); Hexyl 2-methylbutanoate (PubChem CID: 24838).

Inflammation of the central nervous system (CNS) is a common feature of neurological disorders and infections, playing a crucial role in the development of CNS-related conditions. CNS inflammation is primarily regulated by glial cells, with astrocytes being the most abundant type in the mammalian CNS. Numerous studies have demonstrated that astrocytes, as immunocompetent cells, perform diverse and complex functions in both health and disease. Glycosylation, a critical post-translational modification of proteins, regulates numerous biological functions. The expression and activity of glycosyltransferases, the enzymes responsible for glycosylation, are closely associated with the pathogenesis of various diseases. β-1,4-GalTI, a mammalian glycosyltransferase, plays a significant role in cell-cell interactions, adhesion, and migration. Although many studies have focused on β-1,4-GalTI, few have explored its effects on astrocyte function. In this study, we constructed lentiviral vectors for both interference and overexpression of β-1,4-GalTI and discovered that β-1,4-GalTI knockdown inhibited astrocyte migration and proliferation, while its overexpression promoted these processes. Concurrently, β-1,4-GalTI knockdown reduced the expression of TNF-α, IL-1β, and IL-6, whereas overexpression enhanced the expression of these cytokines. These findings suggest that modulating β-1,4-GalTI activity can influence the molecular functions of astrocytes and provide a theoretical foundation for further research into β-1,4-GalTI as a potential therapeutic target in astrocyte-mediated inflammation.