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Under the combined influences of climate and vegetation change, land–atmosphere interactions have enhanced, and precipitation recycling is an important part of this. Previous studies of the precipitation recycling process have focused on calculating the precipitation recycling rate (PRR) and analyzing the influencing factors. However, the climate-driven and vegetation-induced precipitation recycling process variations were not quantified. This study has systematically examined the precipitation recycling process in a typical arid region using the Eltahir and Bras model, random forest algorithm, and partial least-squares structural equation modeling. During 1982–2018, the leaf area index (LAI) and evapotranspiration (ET) rate both increased significantly, with growth rates of 0.06 m2m−2/decade and 13.99 mm/decade, respectively. At the same time, the average PRR in Xinjiang was 13.92% and experienced significant growth at a rate of 1.28%/decade. The climate-driven and vegetation-induced PRR variations were quantified, which contributed 79.12% and 20.88%, respectively. In addition, the positive effects of both of these on PRR variations through ET did not increase with the increase in ET, but rather decreased sharply and then stabilized. This study can provide favorable theoretical support for mitigating the contradiction in water use and balancing economic development and ecological security by quantifying the regulation of precipitation by vegetation.

Background: Angiogenesis is essential for various physiological and pathological processes, such as embryonic development and cancer cell proliferation, migration, and invasion. Long noncoding RNAs (lncRNAs) play pivotal roles in normal homeostasis and disease processes by regulating gene expression through various mechanisms, including competing endogenous RNAs (ceRNAs) of target microRNAs (miRNAs). The lncRNA MYU is known to promote prostate cancer proliferation via the miR-184/c-Myc regulatory axis and to be upregulated in vascular endothelial cells under hypoxic conditions, which often occurs in solid tumors. In the present study, we investigated whether MYU might affect cancer growth by regulating angiogenesis in vascular endothelial cells under hypoxia. Methods: The expression of MYU-regulated miR-23a-3p and interleukin-8 (IL-8) in HUVEC cell lines was examined using qRT-PCR. The CCK-8 assay, EdU assay, wound-healing assay, and tube-formation assay were used to assess the effects of MYU on cell proliferation, migration, and tube formation of HUVEC cells in vitro. The dual-luciferase reporter assay was performed to examine the effects of miR-23a-3p on MYU and IL-8 expression. Results: We found that the overexpression of MYU and knockdown of miR-23a-3p in human umbilical vein endothelial cells (HUVECs) under hypoxia promoted cell proliferation, migration, and tube formation. Mechanistically, MYU was shown to bind competitively to miR-23a-3p, thereby preventing miR-23a-3p binding to the 3′ untranslated region of IL-8 mRNA. In turn, increased production of pro-angiogenic IL-8 promoted HUVEC proliferation, migration, and tube formation under hypoxia. Conclusion: This study identified a new role for lncRNA MYU as a ceRNA for miR-23a-3p and uncovered a novel MYU–miR-23a-3p–IL-8 regulatory axis for angiogenesis. MYU and/or miR-23a-3p may thus represent new targets for the treatment of hypoxia-related diseases by promoting angiogenesis.

This study presents an in-depth investigation into the intersection of Building Information Modeling (BIM) and green building practices within China’s rapidly evolving construction industry. As China intensifies its efforts to mitigate environmental impacts and promote sustainable growth, the integration of BIM into green building practices emerges as a crucial area of study. A qualitative research method was adopted in this research. In the first step, utilizing semi-structured interviews with a diverse array of industry professionals, this research provides nuanced insights into the current state and prospects of BIM in the green building landscape. Secondly, thematic analysis is used to formalize the views and points from interviewees. Finally, a novel conceptual framework is proposed, addressing these challenges through technological innovation, supportive policies, cultural and educational reform, economic incentives, and collaborative dynamics. This study contributes a systematic approach to amalgamate BIM with sustainable construction, offering insights for industry professionals and policymakers to promote environmentally conscious building practices in China.

In recent years, railway safety accidents have repeatedly occurred. Any omission in the process of management or operation can easily have very serious consequences. This study aimed to examine the causes and transmission mechanisms of safety risks in railway engineering departments. First, the multi-objective particle swarm optimization algorithm was employed to determine the key risk factors, allowing for indicator screening that was in line with the requirements of practical applications. Then, Bayesian networks were used, and their structure was optimized to analyze the propagation diagnosis and probability of key risk indicators, obtaining the causal logic chain that produces accidents and, from that, the four aspects (human, machine, environment, management) of the corresponding prevention of risk recommendations. Finally, in this article, it is shown that combining the indicators and Bayesian networks can improve the accuracy of risk prediction and provide more accurate results than using existing research and, hence, it can fill the gap in research on railway safety risks in risk transmission mechanisms.

In order to reduce the effect of nonlinear friction and time-varying factors on the servo system of a computer numerical control (CNC) machine tool and improve its motion control accuracy, this paper uses an adaptive sliding mode control (ASMC) method based on model reference adaptive control (MRAC). The method adopts ASMC in the control outer loop and obtains the optimal control parameters by making the sliding mode control (SMC) law continuous and adaptively estimating the control parameters. At the same time, MRAC is used in the control inner loop to enhance the “invariance” of the controlled object so that the switching gain of SMC can satisfy the disturbance matching condition even under lesser conditions. Simulation and experimental results show that compared with the traditional SMC, the ASMC based on MRAC proposed in this paper effectively reduces the influence of nonlinear friction on the system performance, and the reduction in following error reaches 71.2%, which significantly improves the motion control accuracy of the control system. The spectral analysis of the following errors shows that the maximum magnitude reduction rate of the high-frequency chattering is 89.02%, which significantly reduces the effect of the high-frequency chattering and effectively improves the stability performance of the control system.

Hail, known as an agricultural meteorological disaster, can substantially constrain the growth of the apple industry. Presently, apple orchards use a variety of colored (photo-selective) hail nets as a preventative measure. However, it is unclear which color proves most effective for apple orchards. This study provides a systematic investigation of the impact of four photo-selective colored hail nets (white, blue, black, and green; with white being the control) on the microenvironment of apple orchards, fruit tree development, fruit quality, and yield over a two-year period (2020–2021). Different photo-selective nets do not evidently alter the intensity of light, although the nets’ shading effects decrease in the order from black to green to blue. Among them, blue nets increased the proportion of blue light, while green nets enhanced the proportion of green light. On the other hand, black, green, and blue nets diminished the proportion of red and far-red light. Such photo-selective nets effectively lowered soil temperature but did not have an impact on relative humidity and air temperature. Encasing apple trees with blue nets promoted growth, increasing shoot length, thickness, leaf area, and water content, while simultaneously decreasing leaf thickness. Black nets had comparable effects, although the impacts of green nets were inconsistent. Different photo-selective nets did not significantly influence the leaf shape index or overall chlorophyll content. However, black and green nets reduced the chlorophyll a/b ratio, while blue nets slightly boosted this ratio. Additionally, blue nets proved beneficial for apple trees’ photosynthesis. With the employment of a principal component analysis and comprehensive evaluation, this study concludes that blue nets offer the most favorable environmental conditions for apple growth while protecting apple orchards against hail, compared to black, white, and green nets.

As a class of highly dynamic organelles, lipid droplets (LDs) are involved in numerous physiological functions, and the changes in polarity of LDs are closely related to a variety of diseases. In this work, we developed two polarity-sensitive fluorescent probes (CC-CH and CC-Cl) based on curcumin analogs. CC-CH and CC-Cl with a donor–acceptor–donor (D–A–D) structure exhibited the property of intramolecular charge transfer (ICT); thus, their fluorescence emissions were significantly attenuated with increasing ambient polarity. Cell experiments indicated that CC-CH and CC-Cl showed excellent photostability, a low cytotoxicity, and a superior targeting ability regarding LDs. After treatment with oleic acid (OA) and methyl-β-cyclodextrin (M-β-CD), the polarity changes of LDs in living cells could be visualized by using CC-CH and CC-Cl. In addition, CC-CH and CC-Cl could monitor polarity changes of LDs in different pathological processes, including inflammatory responses, nutrient deprivation, and H2O2-induced oxidative stress. Therefore, CC-CH and CC-Cl are promising potential fluorescent probes for tracking intracellular LD polarity changes.

Central Asia is a drought-prone region that is sensitive to global climate change. The increased actual evapotranspiration intensifies the drought impacts in this area. However, little is known about the similarities and differences between various types of drought in Central Asia, as well as the relative importance of water income and consumption processes during drought events. Therefore, this study evaluates the trends and characteristics of meteorological, agricultural, and hydrological droughts in Central Asia using precipitation, soil moisture, and terrestrial water storage as indicators; explores the temporal correlation of and spatial similarity between various types of drought; and quantitatively assesses the contribution of water balance variables to drought intensity. The results indicate that drought has intensified in Central Asia, and the trends of precipitation, soil moisture, and terrestrial water storage in this region were −0.75 mm·yr−1 (p = 0.36), −0.0003 m3·m−3 yr−1 (p < 0.01), and −0.3742 cm·yr−1 (p < 0.001), respectively. Severe droughts are typically short in duration and high in intensity. Three various types of drought have low temporal correlation and spatial similarity. Furthermore, agricultural and hydrological droughts were primarily driven by actual evapotranspiration, accounting for relative contributions of 64.38% and 51.04% to these drought types, respectively. Moreover, the extent of increased actual evapotranspiration expanded to cover 49.88% of the region, exacerbating agricultural and hydrological droughts in 23.88% and 35.14% of the total study area, respectively. The study findings demonstrate that actual evapotranspiration plays a critical role in causing droughts. This study establishes a theoretical foundation to carry out drought assessment, the construction of multivariate drought indices, and water resource management in Central Asia.

Deep learning techniques for gaze estimation usually determine gaze direction directly from images of the face. These algorithms achieve good performance because face images contain more feature information than eye images. However, these image classes contain a substantial amount of redundant information that may interfere with gaze prediction and may represent a bottleneck for performance improvement. To address these issues, we model long-distance dependencies between the eyes via Strip Pooling and Multi-Criss-Cross Attention Networks (SPMCCA-Net), which consist of two newly designed network modules. One module is represented by a feature enhancement bottleneck block based on fringe pooling. By incorporating strip pooling, this residual module not only enlarges its receptive fields to capture long-distance dependence between the eyes but also increases weights on important features and reduces the interference of redundant information unrelated to gaze. The other module is a multi-criss-cross attention network. This module exploits a cross-attention mechanism to further enhance long-range dependence between the eyes by incorporating the distribution of eye-gaze features and providing more gaze cues for improving estimation accuracy. Network training relies on the multi-loss function, combined with smooth L1 loss and cross entropy loss. This approach speeds up training convergence while increasing gaze estimation precision. Extensive experiments demonstrate that SPMCCA-Net outperforms several state-of-the-art methods, achieving mean angular error values of 10.13° on the Gaze360 dataset and 6.61° on the RT-gene dataset.

At present, marine autonomous surface ships (MASSs) play a huge role in marine shipping, surveying and mapping, safeguarding the rights and interests of marine space, and other maritime tasks. The cooperative operation of a swarm of MASSs can extend the scope of operation of the MASSs, and thus allow them to carry out more complex tasks. Path tracking is an important problem for the control of a swarm of MASSs. In this paper, the control of underactuated MASSs is decoupled, to control the heading and speed, respectively. First of all, in the path tracking, the improved arc LOS guidance law is introduced, and the heading torque controller is designed, so that the MASS can track the reference path efficiently and accurately. Then the single-path guided path tracking without formation of the swarm of MASSs is studied, the reference path of the swarm center tracking is defined, and the heave thrust controller of the swarm of MASSs is designed based on consensus theory, so that the surge velocity of the MASS can tend towards consistentcy, and finally converge to the desired speed. Finally, the effectiveness of the proposed control strategy is verified by two groups of simulation experiments.

This study aimed to identify biomarkers for pork quality evaluation. Firstly, the correlation between indicators of pork quality evaluation was investigated. The pH of pork meat at 45 min post slaughter showed a significant negative correlation with meat color indicators (r: −0.4868–−0.3040). Subsequently, porcine plasma samples were further divided into low pH (pH = 6.16 ± 0.22) or high pH (pH = 6.75 ± 0.08) groups. Plasma metabolites in both sample groups were investigated using untargeted metabolomics. In total, 90 metabolites were recognized as differential metabolites using partial least squares discriminant analysis. Pathway enrichment analysis indicated these differential metabolites were enriched in amino acid metabolism and energy metabolism. Correlation analysis revealed that creatinine, L-carnitine, D-sphingosine, citraconic acid, and other metabolites may constitute novel plasma biomarkers with the pH value of pork meat. The current study provides important insights into plasma biomarkers for predicting pork quality based on pH value.

The intestine is a tubular organ with multiple functions such as digestion absorption and immunity, but the functions of each intestinal segments are different. Intestinal regionalization is necessary for normal physiological function, but it also means the research results obtained at specific sites may not be applicable to other intestinal segments. In order to comprehensively describe the functional changes in the intestine, different intestinal segments and their contents (duodenum, jejunum, ileum, cecum, colon, and rectum) of guinea pigs were collected for RNA seq and 16S rRNA seq, respectively. The results showed differential genes of each intestinal segment mainly involve mucosa, digestion, absorption, and immunity. The gene sets related to fat, bill salts, vitamins, aggregates, amino acids, and water absorption were highly expressed in the small intestine, and the gene sets related to metal ions, nucleotides, and SCFAs were highly expressed in the large intestine. In terms of immunity, the CD8+ T, Th1, eosinophils, pDCs, and natural killer (NK) T cells in the small intestine showed higher scores than those in the large intestine, while the pattern-recognition receptor signaling pathway-related genes are highly expressed in the large intestine. In terms of microbial composition, Proteobacteria and Actinobacteria are abundant in the small intestine, while Firmicutes and Spirochaete are abundant in large intestine. The correlation analysis showed a high correlation between intestinal microorganisms and gene modules related to digestion and absorption. In addition, cross-species analysis showed the SCFA metabolism gene expression trends in human and rodent intestine were different. In conclusion, we analyzed the changes in substance transport, immune and microbial composition between different intestinal segments of guinea pigs, and explored the relationship between intestinal transcriptome and microorganisms, our research will provides a reference for subsequent intestinal-related research.

Hydropower is at the backbone of low-carbon clean energy, while large hydroelectric generators play a key role in hydropower systems. In this paper, the tightness detection of stator trough wedges in the offline state of large hydroelectric generators is mainly studied. The offline state means that the generator stops running but does not need to move the stator and rotor. The traditional detection of generator stator wedges has problems, such as long maintenance intervals and low work efficiency. According to the structural characteristics of the generator, a generator maintenance robot device based on the track mechanism is designed. The device can simultaneously visualize the internal of the generator and detect the tightness of the stator slot wedge, effectively improving the maintenance efficiency. According to the electromagnetic magnitude of the stator rod in the alternating magnetic field, different stator slot wedge models are built for tightening, slightly tightening and loosening. For the conventional slot wedge loosen detection, there is a problem that the characteristic parameter is single, and the state of the slot wedge cannot be fully fed back. In this paper, a method for extracting the Linear Prediction Cepstrum Coefficient (LPCC) and Mel Frequency Cepstrum Coefficient (MFCC) of percussion sound signal is proposed, and the tightness recognition of the stator slot wedge is realized by combining the BP neural network algorithm. Experimental results show that the proposed method can effectively identify stator slot wedges in different states.

Value creation is the primary motivation for public-private cooperation. The development of urban rail transit (URT) projects requires heavy investment and abundant construction and management experience. Thus, public-private partnership (PPP) is usually adopted in URT project development to benefit the public and private sectors. However, with the high-quality development of PPP projects, the value creation of URT PPP projects is not only about achieving basic project objectives but also relying on partner synergy to achieve value-added. Based on the extended connotation of value creation, this study intends to systematically identify the influencing factors of value creation of URT PPP projects in China. The grounded theory approach was adopted to deduce the influencing factors of value creation through analyzing the various types of articles related to Chinese URT PPP projects. Resources complementarity among stakeholders, cooperation environment, and partnership synergy were identified as the main influencing factors. Meanwhile, a theoretical model that described how these influencing factors combined to promote value creation during public-private sectors cooperation of URT projects was established. This research helps broaden the understanding of how public and private sectors should cooperate and collaborate in URT projects to realize value maximization and promote the sustainable development of URT PPP projects and provides a model for further empirical examination.

Accurate and stable wind speed prediction is crucial for the safe operation of large-scale wind power grid connections. Existing methods are typically limited to a certain fixed area when learning the information of the wind speed sequence, which cannot make full use of the spatiotemporal correlation of the wind speed sequence. To address this problem, in this paper we propose a new wind speed prediction method based on collaborative filtering against a virtual edge expansion graph structure in which virtual edges enrich the semantics that the graph can express. It is an effective extension of the dataset, connecting wind turbines of different wind farms through virtual edges to ensure that the spatial correlation of wind speed sequences can be effectively learned and utilized. The new collaborative filtering on the graph is reflected in the processing of the wind speed sequence. The wind speed is preprocessed from the perspective of pattern mining to effectively integrate various information, and the k-d tree is used to match the wind speed sequence to achieve the purpose of collaborative filtering. Finally, a model with long short-term memory (LSTM) as the main body is constructed for wind speed prediction. By taking the wind speed of the actual wind farm as the research object, we compare the new approach with four typical wind speed prediction methods. The mean square error is reduced by 16.40%, 11.78%, 9.57%, and 18.36%, respectively, which demonstrates the superiority of the proposed new method.

Knowledge representation learning achieves the automatic completion of knowledge graphs (KGs) by embedding entities into continuous low-dimensional vector space. In knowledge graph completion (KGC) tasks, the inter-dependencies and hierarchical information in KGs have gained attention. Existing methods do not well capture the latent dependencies between all components of entities and relations. To address this, we introduce the mathematical theories of octonion, a more expressive generalized form of complex number and quaternion, and propose a translation-based KGC model with octonion (TransO). TransO models entities as octonion coordinate vectors, relations as the combination of octonion component matrices and coordinate vectors, and uses specific grouping calculation rules to interact between entities and relations. In addition, since hyperbolic Poincaré space in non-Euclidean mathematics can represent hierarchical data more accurately and effectively than traditional Euclidean space, we propose a Poincaré-extended TransO model (PTransO). PTransO transforms octonion coordinate vectors into hyperbolic embeddings by exponential mapping, and integrates the Euclidean-based calculations into hyperbolic space by operations such as Möbius addition and hyperbolic distance. The experimental results of link prediction indicate that TransO outperforms other translation-based models on the WN18 benchmark, and PTransO further achieves state-of-the-art performance in low-dimensional space on the well-established WN18RR and FB15k-237 benchmarks.

Cardiovascular disease is the leading cause of death worldwide. Traditional autologous transplantation has become a severe issue due to insufficient donors. Artificial blood vessel is an effective method for the treatment of major vascular diseases, such as heart and peripheral blood vessel diseases. However, the traditional single-material printing technology has been unable to meet the users’ demand for product functional complexity, which is not only reflected in the field of industrial manufacturing, but also in the field of functional vessel-like structure regeneration. In order to achieve the printing and forming of multi-layer vessel-like structures, this paper carries out theoretical and experimental research on the printing and forming of a multi-layer vessel-like structure based on multi-material 3D bioprinting technology. Firstly, theoretical analysis has been explored to research the relationship among the different parameters in the process of vessel forming, and further confirm the synchronous relationship among the extrusion rate of material, the tangential speed of the rotating rod, and the movement speed of the platform. Secondly, sodium alginate and gelatin have been used as the experimental materials to manufacture the vessel-like structure, and the corrected parameter of the theoretical analysis is further verified. Finally, the cell-loaded materials have been printed and analyzed, and cell viability is more than 90%, which provides support for the research of multi-layer vessel-like structure printing.

To improve the control performance of the CNC machine tool feed servo system with nonlinear disturbances, a model reference adaptive control (MRAC) based on PID control is proposed. The method is based on the traditional three-loop control, the output signal of the speed loop controller is used as the input signal of the model reference adaptive controller, and the adaptive law is derived on the basis of Lyapunov stability theory. To verify the effectiveness, this paper analyzed the method through simulation and experiment. Results showed that the following error caused by nonlinear friction was significantly reduced when the speed was reversed, and the influence of noise and mechanical resonance was effectively suppressed. The proposed control method in this paper improves the motion-control accuracy and anti-interference ability of the control system.

Self-supervised method has proven to be a suitable approach for despeckling on synthetic aperture radar (SAR) images. However, most self-supervised despeckling methods are trained by noisy-noisy image pairs, which are constructed by using natural images with simulated speckle noise, time-series real-world SAR images or generative adversarial network, limiting the practicability of these methods in real-world SAR images. Therefore, in this paper, a novel self-supervised despeckling algorithm with an enhanced U-Net is proposed for real-world SAR images. Firstly, unlike previous self-supervised despeckling works, the noisy-noisy image pairs are generated from real-word SAR images through a novel generation training pairs module, which makes it possible to train deep convolutional neural networks using real-world SAR images. Secondly, an enhanced U-Net is designed to improve the feature extraction and fusion capabilities of the network. Thirdly, a self-supervised training loss function with a regularization loss is proposed to address the difference of target pixel values between neighbors on the original SAR images. Finally, visual and quantitative experiments on simulated and real-world SAR images show that the proposed algorithm notably removes speckle noise with better preserving features, which exceed several state-of-the-art despeckling methods.

As the medium of material exchange between mother and fetus, umbilical cord blood is closely connected with fetal development. microRNA (miRNA) has a wide range of biological functions and has high flow characteristics. Small RNA sequencing of pig umbilical venous blood (UVB) and umbilical arterial blood (UAB) revealed that a total of 302 miRNAs were identified, and 106 and 22 miRNAs were specifically expressed in the UVB and UAB, respectively. Using the two methods of differential expression multiple and differential expression percentage, it is found that only 35% of the highly expressed miRNAs in the UVB by the two analysis modes overlap, but 56.25% of the enriched signal pathways are the same. Only 20% of the highly expressed miRNAs in the UAB overlap, but 62.07% of the signal pathways are the same. Further analysis revealed that miR-423 can be used as a characteristic miRNA of UVB and has the potential to treat muscle-related diseases. miR-122-5p can be used as a characteristic miRNA of UAB and may help to improve liver- and brain-related diseases. In summary, these results enrich understanding of miRNA in mother–fetal communication and provide a reference for the development and application of porcine cord blood products.

miRNA is a small non-coding RNA, which plays an important role in diverse biological processes. In the present study, we explore the effect of ssc-miR-451 on porcine adipose development and meat quality. We observed that ssc-miR-451 was downregulated during porcine primary adipocyte differentiation. Overexpression of ssc-miR-451 inhibited adipogenic differentiation, while inhibition of ssc-miR-451 promoted adipogenic differentiation. The dual luciferase reporter system indicated Acetyl-CoA carboxylase alpha (ACACA) as a target gene of ssc-miR-451. Correlation analysis negatively correlated miR-451 expression with intramuscular fat content (IMF) and positively correlated ACACA expression with IMF. Further analysis of fatty acid composition revealed that pigs with high expression of ssc-miR-451 had higher monounsaturated fatty acid (MUFA) and lower polyunsaturated fatty acid (PUFA). Taken together, our study suggests that ssc-miR-451 regulates lipid deposition and fatty acid composition by targeting ACACA, and ssc-miR-451 may serve as a potential genetic marker to improve pork quality.

Manipulating the light emission direction and boosting its directivity have essential importance in integrated nanophotonic devices. Here, we theoretically propose a single dielectric silicon nanoblock as an efficient, multifunctional and ultracompact all-dielectric nanoantenna to direct light into a preferential direction. Unidirectional scattering of a plane wave as well as switchable directive emission fed by a localized emitter are demonstrated within the nanoantenna. The high directionalities are revealed to originate from a variety of mechanisms that can coexist within a single nanoblock, which contribute to the far-field radiation patterns of the outcoming light, thanks to the wealth of multipolar electric and magnetic resonances. The efficient beam redirections are also observed, which are sensitive to the local configurations of the emitter antenna coupled system. The designed antenna, with extreme geometry simplicity, ultracompact and low-loss features, could be favorable for highly sensitive sensing as well as applications in optical nanocircuits.

Cardiac hypertrophy is a common pathological condition and an independent risk factor that triggers cardiovascular morbidity. As an important epigenetic regulator, miRNA is widely involved in many biological processes. In this study, miRNAs expressed in rat hearts that underwent isoprenaline-induced cardiac hypertrophy were identified using high-throughput sequencing, and functional verification of typical miRNAs was performed using rat primary cardiomyocytes. A total of 623 miRNAs were identified, of which 33 were specifically expressed in cardiac hypertrophy rats. The enriched pathways of target genes of differentially expressed miRNAs included the FoxO signaling pathway, dopaminergic synapse, Wnt signaling pathway, MAPK (mitogen-activated protein kinase) signaling pathway, and Hippo signaling pathway. Subsequently, miR-144 was the most differentially expressed miRNA and was subsequently selected for in vitro validation. Inhibition of miR-144 expression in primary myocardial cells caused up-regulation of cardiac hypertrophy markers atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP). The dual luciferase reporter system showed that ANP may be a target gene of miR-144. Long non-coding RNA myocardial infarction associated transcript (LncMIAT) is closely related to heart disease, and here, we were the first to discover that LncMIAT may act as an miR-144 sponge in isoproterenol-induced cardiac hypertrophy. Taken together, these results enriched the understanding of miRNA in regulating cardiac hypertrophy and provided a reference for preventing and treating cardiac hypertrophy.

Indigenous pig breeds are important biological resources and their diversity has been severely damaged. The Liangshan pig is a typical mountain-type local pig breed in southwest China. Here, the meat quality, amino acid, and fatty acid composition of Liangshan pigs were compared at seven stages within the weight range of 50–90 kg. A score for comprehensive factors of meat quality was maintained after rising and kept in a plateau within 74.9–91.5 kg of body weight. The total amount of amino acids in the longissimus dorsi muscle remained stable, and the total fatty acids showed an upward trend. Amino acid composition analysis revealed that as the body weight of Liangshan pigs increased, umami, basic, and acidic amino acid contents decreased, while the essential amino acids (EAA) content and the ratio of basic amino acids to acidic amino acids increased. Fatty acid composition analysis revealed that as body weight increased, the content of polyunsaturated fatty acids (PUFA) exhibited a downward trend, while the content of saturated fatty acids (SFA) exhibited an upward trend. This study is a primary step towards the development and utilization of Liangshan pigs and provides useful information for local pork processing and genetic improvement.

Black spot disease, which is caused by the pathogenic fungal Ceratocystis fimbriata, seriously affects the production of sweet potato and its quality during postharvest storage. In this study, the preliminary identification of the rhizosphere actinomycete strain SPS-33, and its antifungal activity of volatiles in vitro and in vivo was investigated. Based on morphological identification and phylogenetic analysis of the 16S rRNA gene sequence, strain SPS-33 was identified as Streptomyces lavendulae. Volatile organic compounds (VOCs) emitted by SPS-33 inhibited mycelial growth and sporulation of C. fimbriata in vitro and also induced a series of observable hyphae morphological changes. In an in vivo pathogenicity assay, exposure to SPS-33 significantly decreased the lesion diameter and water loss rate in sweet potato tuberous roots (TRs) inoculated with C. fimbriata. It increased the antioxidant enzymes’ activities of peroxidase, catalase, and superoxide dismutase as well as decreased malondialdehyde and increased total soluble sugar. In the VOC profile of SPS-33 detected by a headspace solid-phase micro extraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS), heptadecane, tetradecane, and 3-methyl-1-butanol were the most abundant compounds. 2-Methyl-1-butanol, 3-methyl-1-butanol, pyridine, and phenylethyl alcohol showed strong antifungal effects against C. fimbriata. These findings suggest that VOCs from S. lavendulae SPS-33 have the potential for pathogen C. fimbriata control in sweet potato postharvest storage by fumigant action.

Adipogenesis is a complex biological process and the main cause of obesity. Recently, microRNAs (miRNAs), a class of small endogenous non-coding RNAs, have been proven to play an important role in adipogenesis by the post-transcriptional regulation of target genes. In this current study, we observed an increment of miR-152 expression during the process of 3T3-L1 cell audiogenic differentiation. A functional analysis indicated that the overexpression of miR-152 inhibited pre-adipocyte proliferation and suppressed the expression of some cell cycle-related genes. Moreover, the overexpression of miR-152 promoted lipid accumulation in 3T3-L1 preadipocytes accompanied by increase of the expression of some pro-audiogenic genes. Additionally, a dual-luciferase reporter assay demonstrated lipoprotein lipase (LPL) was a direct target gene of miR-152 during preadipocyte differentiation. Further analysis showed that miR-152 was positively correlated with adipogenesis and intramuscular fat formation in vivo. Taken together, our findings suggest that miR-152 could suppress 3T3-L1 preadipocyte proliferation, whereas it could promote 3T3-L1 preadipocyte differentiation by negatively regulating LPL. The findings indicate that miR-152 might have a therapeutic significance for obesity and obesity-related metabolic syndrome.

tRNA-derived fragments (tRFs), a novel type of non-coding RNA derived from tRNAs, play an important part in governing gene expressions at a post-transcriptional level. To date, the regulatory mechanism of tRFs governing fat deposition and adipogenesis is completely unknown. In this study, high fat diet was employed to induce an obese rat model, and tRFs transcriptome sequencing was conducted to identify differentially expressed tRFs that response to obesity. We found out that tRFGluTTC, which promoted preadipocyte proliferation by increasing expressions of cell cycle regulatory factors, had the highest fold change in the 296 differentially expressed tRFs. Moreover, tRFGluTTC also suppressed preadipocyte differentiation by reducing triglyceride content and lipid accumulation, and by decreasing expressions of genes that related to fatty acid synthesis. According to results of luciferase activity analysis, tRFGluTTC directly targeted Kruppel-like factor (KLF) 9, KLF11, and KLF12, thus significantly suppressing mRNA expressions of these target genes. Moreover, tRFGluTTC suppressed adipogenesis, accompanying by suppressing expressions of adipogenic transcription factors (aP2, PPARγ, and C/EBPα). In conclusion, these results imply that tRFGluTTC may act as a novel epigenetic molecule regulating adipogenesis and could provide a new strategy for the intervention treatment of obesity.

Measurement is a key method to obtain information from the real world and is widely used in human life. A unified model of measurement systems is critical to the design and optimization of measurement systems. However, the existing models of measurement systems are too abstract. To a certain extent, this makes it difficult to have a clear overall understanding of measurement systems and how to implement information acquisition. Meanwhile, this also leads to limitations in the application of these models. Information entropy is a measure of information or uncertainty of a random variable and has strong representation ability. In this paper, an information entropy-based modeling method for measurement system is proposed. First, a modeling idea based on the viewpoint of information and uncertainty is described. Second, an entropy balance equation based on the chain rule for entropy is proposed for system modeling. Then, the entropy balance equation is used to establish the information entropy-based model of the measurement system. Finally, three cases of typical measurement units or processes are analyzed using the proposed method. Compared with the existing modeling approaches, the proposed method considers the modeling problem from the perspective of information and uncertainty. It focuses on the information loss of the measurand in the transmission process and the characterization of the specific role of the measurement unit. The proposed model can intuitively describe the processing and changes of information in the measurement system. It does not conflict with the existing models of the measurement system, but can complement the existing models of measurement systems, thus further enriching the existing measurement theory.

tRNA-derived fragments (tRFs) are a new class of non-coding RNA that play an important role in regulating cellular RNA processing and protein translation. However, there is currently no study reporting the influence of tRFs on myocardial hypertrophy. In this study, we used an isoproterenol (ISO)-induced myocardial hypertrophy rat model. Small RNA (

Excessive accumulation of adipose tissue is a main cause of obesity or overweight, which is significantly involved in increasing the risk of diseases. Recently, numerous studies have proved that microRNAs (miRNAs) play important roles in adipogenesis by negatively regulating gene expression at posttranscriptional levels. In this study, we showed that miR-125a-5p was expressed at lower levels in the adipose tissues of high-fat diet (HFD)-fed mice than the normal chow (NCW)-fed mice. MiR-125a-5p expression were strongly up-regulated by nearly five-fold, when 3T3-L1 preadipocyte were induced and differentiated into mature adipocytes. Functional analysis indicated that overexpression of miR-125a-5p promoted 3T3-L1 preadipocyte proliferation and inhibited its differentiation. By contrast, inhibition of miR-125a-5p repressed 3T3-L1 preadipocyte proliferation and accelerated its differentiation. Furthermore, a dual-luciferase reporter assay demonstrated that signal transducer and activator of transcription 3 (STAT3) is a direct target gene of miR-125a-5p during 3T3-L1 preadipocyte differentiation. Further analysis confirmed that the process of miR-125a-5p inhibiting 3T3-L1 preadipocyte differentiation might be associated with the regulation of fatty acid metabolism related genes. Taken together, our results indicated that miR-125a-5p might promote 3T3-L1 preadipocyte proliferation, whereas inhibiting 3T3-L1 preadipocyte differentiation by negatively regulating STAT3.