Linyi University

Abiotic stresses are one of the major constraints to crop production and food security worldwide. The situation has aggravated due to the drastic and rapid changes in global climate. Heat and drought are undoubtedly the two most important stresses having huge impact on growth and productivity of the crops. It is very important to understand the physiological, biochemical, and ecological interventions related to these stresses for better management. A wide range of plant responses to these stresses could be generalized into morphological, physiological, and biochemical responses. Interestingly, this review provides a detailed account of plant responses to heat and drought stresses with special focus on highlighting the commonalities and differences. Crop growth and yields are negatively affected by sub-optimal water supply and abnormal temperatures due to physical damages, physiological disruptions, and biochemical changes. Both these stresses have multi-lateral impacts and therefore, complex in mechanistic action. A better understanding of plant responses to these stresses has pragmatic implication for remedies and management. A comprehensive account of conventional as well as modern approaches to deal with heat and drought stresses have also been presented here. A side-by-side critical discussion on salient responses and management strategies for these two important abiotic stresses provides a unique insight into the phenomena. A holistic approach taking into account the different management options to deal with heat and drought stress simultaneously could be a win-win approach in future.

Abnormal enzymatic activities are directly related to the development of cancers. Identifying the location and expression levels of these enzymes in live cancer cells have considerable importance in early-stage cancer diagnoses and monitoring the efficacy of therapies. Small-molecule fluorescent probes have become a powerful tool for the detection and imaging of enzymatic activities in biological systems by virtue of their higher sensitivity, nondestructive fast analysis, and real-time detection abilities. Moreover, due to their structural tailorability, numerous small-molecule enzymatic fluorescent probes have been developed to meet various demands involving real-time tracking and visualizing different enzymes in live cancer cells or in vivo. In this review, we provide an overview of recent advances in small-molecule enzymatic fluorescent probes mainly during the past decade, including the design strategies and applications for various enzymes in live cancer cells. We also highlight the challenges and opportunities in this rapidly developing field of small-molecule fluorescent probes for interventional surgical imaging, as well as cancer diagnosis and therapy.

Programmed cell death (PCD) refers to the way in which cells die depending on specific genes encoding signals or activities. Apoptosis, autophagy, and pyroptosis are all mechanisms of PCD. Among these mechanisms, pyroptosis is mediated by the gasdermin family, accompanied by inflammatory and immune responses. The relationship between pyroptosis and cancer is complex, and the effects of pyroptosis on cancer vary in different tissues and genetic backgrounds. On one hand, pyroptosis can inhibit the occurrence and development of tumors; on the other hand, as a type of proinflammatory death, pyroptosis can form a suitable microenvironment for tumor cell growth and thus promote tumor growth. In addition, the induction of tumor pyroptosis is also considered a potential cancer treatment strategy. Studies have shown that DFNA5 (nonsyndromic hearing impairment protein 5)/GSDME (Gasdermin-E) mRNA methylation results in lower expression levels of DFNA5/GSDME in most tumor cells than in normal cells, making it difficult to activate the pyroptosis in most tumor cells. During the treatment of malignant tumors, appropriate chemotherapeutic drugs can be selected according to the expression levels of DFNA5/GSDME, which can be upregulated in tumor cells, thereby increasing the sensitivity to chemotherapeutic drugs and reducing drug resistance. Therefore, induced pyroptosis may play a predominant role in the treatment of cancer. Here, we review the latest research on the anti- and protumor effects of pyroptosis and its potential applications in cancer treatment.

Developing powerful, simple and low-cost DNA amplification techniques is of great significance to bioanalysis and biomedical research. Thus far, many signal amplification strategies have been developed, such as polymerase chain reaction (PCR), rolling circle amplification (RCA), and DNA strand displacement amplification (SDA). In particular, hybridization chain reaction (HCR), a type of toehold-mediated strand displacement (TMSD) reaction, has attracted great interest because of its enzyme-free nature, isothermal conditions, simple protocols, and excellent amplification efficiency. In a typical HCR, an analyte initiates the cross-opening of two DNA hairpins, yielding nicked double helices that are analogous to alternating copolymers. As an efficient amplification platform, HCR has been utilized for the sensitive detection of a wide variety of analytes, including nucleic acids, proteins, small molecules, and cells. In recent years, more complicated sets of monomers have been designed to develop nonlinear HCR, such as branched HCR and even dendritic systems, achieving quadratic and exponential growth mechanisms. In addition, HCR has attracted enormous attention in the fields of bioimaging and biomedicine, including applications in fluorescence in situ hybridization (FISH) imaging, live cell imaging, and targeted drug delivery. In this review, we introduce the fundamentals of HCR and examine the visualization and analysis techniques for HCR products in detail. The most recent HCR developments in biosensing, bioimaging, and biomedicine are subsequently discussed with selected examples. Finally, the review provides insight into the challenges and future perspectives of HCR.

In recent years, the concept of the Metaverse has attracted considerable attention. This article provides a comprehensive overview of the Metaverse. First, the development status of the Metaverse is presented. We summarize the policies of various countries, companies, and organizations relevant to the Metaverse, as well as statistics on the number of Metaverse-related publications. Characteristics of the Metaverse are identified: 1) multitechnology convergence; 2) sociality; and 3) hyper-spatio-temporality. For the multitechnology convergence of the Metaverse, we divide the technological framework of the Metaverse into five dimensions. For the sociality of the Metaverse, we focus on the Metaverse as a virtual social world. Regarding the characteristic of hyper-spatio-temporality, we introduce the Metaverse as an open, immersive, and interactive 3-D virtual world which can break through the constraints of time and space in the real world. The challenges of the Metaverse are also discussed.

Abstract Facebook is a popular social networking site. It, like many other new technologies, has potential for teaching and learning because of its unique built‐in functions that offer pedagogical, social and technological affordances. In this study, the Facebook group was used as a learning management system (LMS) in two courses for putting up announcements, sharing resources, organizing weekly tutorials and conducting online discussions at a teacher education institute in Singapore. This study explores using the Facebook group as an LMS and the students' perceptions of using it in their courses. Results showed that students were basically satisfied with the affordances of Facebook as the fundamental functions of an LMS could be easily implemented in the Facebook group. However, using the Facebook group as an LMS has certain limitations. It did not support other format files to be uploaded directly, and the discussion was not organized in a threaded structure. Also, the students did not feel safe and comfortable as their privacy might be revealed. Constraints of using the Facebook group as an LMS, implications for practice and limitations of this study are discussed. Practitioner notes What is already known about this topic Facebook has been popularly used by tertiary students, but many students do not want their teachers to be friends on Facebook Teacher's self‐disclosure on Facebook can promote classroom atmosphere, teacher's credibility and student–teacher relationship Commercial learning management systems (LMSs) have limitations What this paper adds The Facebook group can be used an LMS as it has certain pedagogical, social and technological affordances Students are satisfied with the way of using the Facebook group as an LMS Younger students are more acceptable with the idea of using the Facebook group as an LMS Using the Facebook group as an LMS has limitations: it does not support other format files; its discussions are not listed in threads; and it is not perceived as a safe environment Implications for practice and/or policy The Facebook group can be used an LMS substitute or supplement Third‐party applications are needed to extend the capability of the Facebook group as an LMS Using Facebook seems to be more appropriate for young learners than adults Teachers do not have to be students' friends on Facebook.

Terpenoids, the most abundant compounds in natural products, are a set of important secondary metabolites in plants with diverse structures. Terpenoids play key roles in plant growth and development, response to the environment, and physiological processes. As raw materials, terpenoids were also widely used in pharmaceuticals, food, and cosmetics industries. Terpenoids possess antitumor, anti-inflammatory, antibacterial, antiviral, antimalarial effects, promote transdermal absorption, prevent and treat cardiovascular diseases, and have hypoglycemic activities. In addition, previous studies have also found that terpenoids have many potential applications, such as insect resistance, immunoregulation, antioxidation, antiaging, and neuroprotection. Terpenoids have a complex structure with diverse effects and different mechanisms of action. Activities and mechanisms of terpenoids were reviewed in this paper. The development and application prospect of terpenoid compounds were also prospected, which provides a useful reference for new drug discovery and drug design based on terpenoids.

Adsorptive separation of acetylene (C2H2) from carbon dioxide (CO2) promises a practical way to produce high-purity C2H2 required for industrial applications. However, challenges exist in the pore environment engineering of porous materials to recognize two molecules due to their similar molecular sizes and physical properties. Herein, we report a strategy to optimize pore environments of multivariate metal–organic frameworks (MOFs) for efficient C2H2/CO2 separation by tuning metal components, functionalized linkers, and terminal ligands. The optimized material UPC-200(Al)-F-BIM, constructed from Al3+ clusters, fluorine-functionalized organic linkers, and benzimidazole terminal ligands, demonstrated the highest separation efficiency (C2H2/CO2 uptake ratio of 2.6) and highest C2H2 productivity among UPC-200 systems. Experimental and computational studies revealed the contribution of small pore size and polar functional groups on the C2H2/CO2 selectivity and indicated the practical C2H2/CO2 separation of UPC-200(Al)-F-BIM.

Previous investigations [H. L. Zhuang and R. G. Hennig, J. Phys. Chem. C, 2013, 117, 20440-20445; J. Kang, S. Tongay, J. Zhou, J. Li and J. Wu, Appl. Phys. Lett., 2013, 102, 012111] demonstrated that molybdenum disulfide (MoS2) is a potential photocatalyst for water splitting. However, the photogenerated electron-hole pairs in MoS2 remain in the same spatial regions, resulting in a high rate of recombination. Using first-principles calculations, we designed a MoS2-based heterostructure by stacking MoS2 on two-dimensional zinc oxide (ZnO) and investigated its structural, electronic, and optical properties. The interaction at the MoS2/ZnO interface was found to be dominated by van der Waals (vdW) forces. The energy levels of both water oxidation and reduction lie within the bandgap of the MoS2/ZnO vdW heterostructure, which guarantee their occurrence for water splitting. Moreover, a type-II band alignment and a large built-in electric field are formed at the MoS2/ZnO interface, which ensure the enhanced separation of the photogenerated electron-hole pairs. In addition, strong optical absorption in the visible region was also found in the MoS2/ZnO vdW heterostructure, indicating that it has potential for application in photovoltaic and photocatalytic devices.

Agroforestry integrates woody perennials with arable crops, livestock, or fodder in the same piece of land, promoting the more efficient utilization of resources as compared to monocropping via the structural and functional diversification of components. This integration of trees provides various soil-related ecological services such as fertility enhancements and improvements in soil physical, biological, and chemical properties, along with food, wood, and fodder. By providing a particular habitat, refugia for epigenic organisms, microclimate heterogeneity, buffering action, soil moisture, and humidity, agroforestry can enhance biodiversity more than monocropping. Various studies confirmed the internal restoration potential of agroforestry. Agroforestry reduces runoff, intercepts rainfall, and binds soil particles together, helping in erosion control. This trade-off between various non-cash ecological services and crop production is not a serious constraint in the integration of trees on the farmland and also provides other important co-benefits for practitioners. Tree-based systems increase livelihoods, yields, and resilience in agriculture, thereby ensuring nutrition and food security. Agroforestry can be a cost-effective and climate-smart farming practice, which will help to cope with the climate-related extremities of dryland areas cultivated by smallholders through diversifying food, improving and protecting soil, and reducing wind erosion. This review highlighted the role of agroforestry in soil improvements, microclimate amelioration, and improvements in productivity through agroforestry, particularly in semi-arid and degraded areas under careful consideration of management practices.

Abstract The shortage of fresh water in the world has brought upon a serious crisis to human health and economic development. Solar‐driven interfacial photothermal conversion water evaporation including evaporating seawater, lake water, or river water has been recognized as an environmentally friendly process for obtaining clean water in a low‐cost way. However, water transport is restricted by itself by solar energy absorption capacity's limits, especially for finite evaporation rates and insufficient working life. Therefore, it is important to seek photothermal conversion materials that can efficiently absorb solar energy and reasonably design solar‐driven interfacial photothermal conversion water evaporation devices. This paper reviews the research progress of carbon‐based photothermal conversion materials and the mechanism for solar‐driven interfacial photothermal conversion water evaporation, as well as the summary of the design and development of the devices. Based on the research progress and achievements of photothermal conversion materials and devices in the fields of seawater desalination and photothermal electric energy generation in recent years, the challenges and opportunities faced by carbon‐based photothermal conversion materials and devices are discussed. The prospect of the practical application of solar‐driven interfacial photothermal conversion evaporation technology is foreseen, and theoretical guidance is provided for the further development of this technology.

Phthalic acid esters (PAEs) are a class of lipophilic chemicals widely used as plasticizers and additives to improve various products’ mechanical extensibility and flexibility. At present, synthesized PAEs, which are considered to cause potential hazards to ecosystem functioning and public health, have been easily detected in the atmosphere, water, soil, and sediments; PAEs are also frequently discovered in plant and microorganism sources, suggesting the possibility that they might be biosynthesized in nature. In this review, we summarize that PAEs have not only been identified in the organic solvent extracts, root exudates, and essential oils of a large number of different plant species, but also isolated and purified from various algae, bacteria, and fungi. Dominant PAEs identified from natural sources generally include di-n-butyl phthalate, diethyl phthalate, dimethyl phthalate, di(2-ethylhexyl) phthalate, diisobutyl phthalate, diisooctyl phthalate, etc. Further studies reveal that PAEs can be biosynthesized by at least several algae. PAEs are reported to possess allelopathic, antimicrobial, insecticidal, and other biological activities, which might enhance the competitiveness of plants, algae, and microorganisms to better accommodate biotic and abiotic stress. These findings suggest that PAEs should not be treated solely as a “human-made pollutant” simply because they have been extensively synthesized and utilized; on the other hand, synthesized PAEs entering the ecosystem might disrupt the metabolic process of certain plant, algal, and microbial communities. Therefore, further studies are required to elucidate the relevant mechanisms and ecological consequences.

Long non-coding RNA (lncRNA) and microRNA (miRNA) are two typical types of non-coding RNAs (ncRNAs), their interaction plays an important regulatory role in many biological processes. Exploring the interactions between unknown lncRNA and miRNA can help us better understand the functional expression between lncRNA and miRNA. At present, the interactions between lncRNA and miRNA are mainly obtained through biological experiments, but such experiments are often time-consuming and labor-intensive, it is necessary to design a computational method that can predict the interactions between lncRNA and miRNA. In this paper, we propose a method based on graph convolutional neural (GCN) network and conditional random field (CRF) for predicting human lncRNA-miRNA interactions, named GCNCRF. First, we construct a heterogeneous network using the known interactions of lncRNA and miRNA in the LncRNASNP2 database, the lncRNA/miRNA integration similarity network, and the lncRNA/miRNA feature matrix. Second, the initial embedding of nodes is obtained using a GCN network. A CRF set in the GCN hidden layer can update the obtained preliminary embeddings so that similar nodes have similar embeddings. At the same time, an attention mechanism is added to the CRF layer to reassign weights to nodes to better grasp the feature information of important nodes and ignore some nodes with less influence. Finally, the final embedding is decoded and scored through the decoding layer. Through a 5-fold cross-validation experiment, GCNCRF has an area under the receiver operating characteristic curve value of 0.947 on the main dataset, which has higher prediction accuracy than the other six state-of-the-art methods.

The uplift history of south-eastern Tibet is crucial to understanding processes driving the tectonic evolution of the Tibetan Plateau and surrounding areas. Underpinning existing palaeoaltimetric studies has been regional mapping based in large part on biostratigraphy that assumes a Neogene modernization of the highly diverse, but threatened, Asian biota. Here, with new radiometric dating and newly collected plant-fossil archives, we quantify the surface height of part of the south-eastern margin of Tibet in the latest Eocene (∼34 Ma) to be ∼3 km and rising, possibly attaining its present elevation (3.9 km) in the early Oligocene. We also find that the Eocene-Oligocene transition in south-eastern Tibet witnessed leaf-size diminution and a floral composition change from sub-tropical/warm temperate to cool temperate, likely reflective of both uplift and secular climate change, and that, by the latest Eocene, floral modernization on Tibet had already taken place, implying modernization was deeply rooted in the Palaeogene.

Molecularly imprinted polymers (MIPs) with trinitrophenol (TNP) as a dummy template molecule capped with CdTe quantum dots (QDs) were prepared using 3-aminopropyltriethoxy silane (APTES) as the functional monomer and tetraethoxysilane (TEOS) as the cross linker through a seed-growth method via a sol-gel process (i.e., DMIP@QDs) for the sensing of 2,4,6-trinitrotoluene (TNT) on the basis of electron-transfer-induced fluorescence quenching. With the presence and increase of TNT in sample solutions, a Meisenheimer complex was formed between TNT and the primary amino groups on the surface of the QDs. The energy of the QDs was transferred to the complex, resulting in the quenching of the QDs and thus decreasing the fluorescence intensity, which allowed the TNT to be sensed optically. DMIP@QDs generated a significantly reduced fluorescent intensity within less than 10 min upon binding TNT. The fluorescence-quenching fractions of the sensor presented a satisfactory linearity with TNT concentrations in the range of 0.8-30 μM, and its limit of detection could reach 0.28 μM. The sensor exhibited distinguished selectivity and a high binding affinity to TNT over its possibly competing molecules of 2,4-dinitrophenol (DNP), 4-nitrophenol (4-NP), phenol, and dinitrotoluene (DNT) because there are more nitro groups in TNT and therefore a stronger electron-withdrawing ability and because it has a high similarity in shape and volume to TNP. The sensor was successfully applied to determine the amount of TNT in soil samples, and the average recoveries of TNT at three spiking levels ranged from 90.3 to 97.8% with relative standard deviations below 5.12%. The results provided an effective way to develop sensors for the rapid recognition and determination of hazardous materials from complex matrices.

Metabolism is the process by which an organism continuously replaces old substances with new substances. It plays an important role in maintaining human life, body growth and reproduction. More and more researchers have shown that the concentrations of some metabolites in patients are different from those in healthy people. Traditional biological experiments can test some hypotheses and verify their relationships but usually take a considerable amount of time and money. Therefore, it is urgent to develop a new computational method to identify the relationships between metabolites and diseases. In this work, we present a new deep learning algorithm named as graph convolutional network with graph attention network (GCNAT) to predict the potential associations of disease-related metabolites. First, we construct a heterogeneous network based on known metabolite-disease associations, metabolite-metabolite similarities and disease-disease similarities. Metabolite and disease features are encoded and learned through the graph convolutional neural network. Then, a graph attention layer is used to combine the embeddings of multiple convolutional layers, and the corresponding attention coefficients are calculated to assign different weights to the embeddings of each layer. Further, the prediction result is obtained by decoding and scoring the final synthetic embeddings. Finally, GCNAT achieves a reliable area under the receiver operating characteristic curve of 0.95 and the precision-recall curve of 0.405, which are better than the results of existing five state-of-the-art predictive methods in 5-fold cross-validation, and the case studies show that the metabolite-disease correlations predicted by our method can be successfully demonstrated by relevant experiments. We hope that GCNAT could be a useful biomedical research tool for predicting potential metabolite-disease associations in the future.

Atomically thin 2D carbon nitride sheets (CNS) are promising materials for photocatalytic applications due to their large surface area and very short charge-carrier diffusion distance from the bulk to the surface. However, compared to their bulk counterpart, CNS' applications always suffer from an enlarged bandgap and thus narrowed solar absorption range. Here, an approach to significantly increase solar absorption of the atomically thin CNS via fluorination followed by thermal defluorination is reported. This approach can greatly increase the visible-light absorption of CNS by extending the absorption edge up to 578 nm. The modulated CNS loaded with Pt cocatalyst as a photocatalyst shows a superior photocatalytic hydrogen production activity under visible-light irradiation to Pt-CNS. Combining experimental characterization with theoretical calculations shows that this approach can introduce cyano groups into the framework of CNS as well as the accompanied nitrogen vacancies at the edges, which leads to both narrowing the bandgap and changing the charge distribution. This study will provide an effective strategy to increase solar absorption of carbon-nitride-based photocatalysts for solar energy conversion applications.

Abstract The structural, electronic, and optical properties of heterostructures formed by transition metal dichalcogenides MX 2 (M = Mo, W; X = S, Se) and graphene-like zinc oxide (ZnO) were investigated using first-principles calculations. The interlayer interaction in all heterostructures was characterized by van der Waals forces. Type-II band alignment occurs at the MoS 2 /ZnO and WS 2 /ZnO interfaces, together with the large built-in electric field across the interface, suggesting effective photogenerated-charge separation. Meanwhile, type-I band alignment occurs at the MoSe 2 /ZnO and WSe 2 /ZnO interfaces. Moreover, all heterostructures exhibit excellent optical absorption in the visible and infrared regions, which is vital for optical applications.

Pythagorean fuzzy sets (PFSs), originally proposed by Yager, are a new tool to deal with vagueness with the square sum of the membership degree and the nonmembership degree equal to or less than 1, which have much stronger ability than Atanassov's intuitionistic fuzzy sets to model such uncertainty. In this paper, we modify the existing score function and accuracy function for Pythagorean fuzzy number to make it conform to PFSs. Associated with the given operational laws, we define some novel Pythagorean fuzzy weighted geometric/averaging operators for Pythagorean fuzzy information, which can neutrally treat the membership degree and the nonmembership degree, and investigate the relationships among these operators and those existing ones. At length, a practical example is provided to illustrate the developed operators and to make a comparative analysis.

Increased levels of greenhouse gases in the atmosphere and associated climatic variability is primarily responsible for inducing heat waves, flooding and drought stress. Among these, water scarcity is a major limitation to crop productivity. Water stress can severely reduce crop yield and both the severity and duration of the stress are critical. Water availability is a key driver for sustainable cotton production and its limitations can adversely affect physiological and biochemical processes of plants, leading towards lint yield reduction. Adaptation of crop husbandry techniques suitable for cotton crop requires a sound understanding of environmental factors, influencing cotton lint yield and fiber quality. Various defense mechanisms e.g. maintenance of membrane stability, carbon fixation rate, hormone regulation, generation of antioxidants and induction of stress proteins have been found play a vital role in plant survival under moisture stress. Plant molecular breeding plays a functional role to ascertain superior genes for important traits and can offer breeder ready markers for developing ideotypes. This review highlights drought-induced damage to cotton plants at structural, physiological and molecular levels. It also discusses the opportunities for increasing drought tolerance in cotton either through modern gene editing technology like clustered regularly interspaced short palindromic repeat (CRISPR/Cas9), zinc finger nuclease, molecular breeding as well as through crop management, such as use of appropriate fertilization, growth regulator application and soil amendments.