Key Branch Research Articles

Распространение заболеваний незаразной этиологии в различных отраслях животноводства в Российской Федерации

Animal husbandry in the Russian Federation is a key branch of agriculture, supplying the population with life-supporting, indispensable foodstuffs. The number of cattle in the Russian Federation over the past 3 years from 2020 to 2022 averaged 18,2 thousand heads, pigs – 26,0 thousand heads and small cattle – 21,432 thousand heads. From this livestock, only in 2021, milk was received – 24 976,3 thousand tons, cattle for slaughter in live weight – 1751,3 thousand tons, sheep and goats for slaughter – 237,5 thousand tons, as well as pigs for slaughter 3914,3 thousand tons. However, due to the intensification of the industry, diseases of non-contagious etiology are widespread, associated with violations of the technology of keeping and feeding animals, technological, thermal and other stresses, lack or insufficiency of exercise, a decrease in the immune status and resulting in large economic losses. Among such diseases in all considered areas of animal husbandry, diseases of the gastrointestinal tract, respiratory system, metabolic disorders and diseases of the reproductive organs in cattle are the most common.

Machine learning prediction of concrete compressive strength using rebound hammer test

Machine learning has become a key branch in artificial intelligence by providing unique predictive modeling solutions. Predicting the compressive strength of concrete determined using non-destructive test techniques (NDT) includes high levels of uncertainty. This uncertainty directly depends on the repeatability of the measurement and the variability of concrete properties. This study aims to evaluate the effect of mixture composition and age of concrete on the coefficient of variation (CV) of the rebound hammer index applied to various types of concrete. Several supervised machine learning models, including multivariate multiple regression (MMR), support vector machine (SVM), Gaussian process regression (GPR), and Regression tree (RT) were utilized to predict the compressive strength of concrete. A large dataset of 468 cubic concrete specimens was sorted into four categories and employed for simulation. Regardless of the selected dataset, it was concluded that GPR/SVM and RT yielded the most accurate model prediction metrics of compressive strength when using rebound hammer records over MMR model. The results of the adopted models were remarkably better when mixture proportion and age of concrete features (i.e., age and w/p) were considered in the simulation.

Multi-domain medical image translation generation for lung image classification based on generative adversarial networks

ObjectiveLung image classification-assisted diagnosis has a large application market. Aiming at the problems of poor attention to existing translation models, the insufficient ability of key transfer and generation, insufficient quality of generated images, and lack of detailed features, this paper conducts research on lung medical image translation and lung image classification based on generative adversarial networks. MethodsThis paper proposes a medical image multi-domain translation algorithm MI-GAN based on the key migration branch. After the actual analysis of the imbalanced medical image data, the key target domain images are selected, the key migration branch is established, and a single generator is used to complete the medical image multi-domain translation. The conversion between domains ensures the attention performance of the medical image multi-domain translation model and the quality of the synthesized images. At the same time, a lung image classification model based on synthetic image data augmentation is proposed. The synthetic lung CT medical images and the original real medical images are used as the training set together to study the performance of the auxiliary diagnosis model in the classification of normal healthy subjects, and also of the mild and severe COVID-19 patients. ResultsBased on the chest CT image dataset, MI-GAN has completed the mutual conversion and generation of normal lung images without disease, viral pneumonia and Mild COVID-19 images. The synthetic images GAN-test and GAN-train indicators reached, respectively 92.188% and 85.069%, compared with other generative models in terms of authenticity and diversity, there is a considerable improvement. The accuracy rate of pneumonia diagnosis of the lung image classification model is 93.85%, which is 3.1% higher than that of the diagnosis model trained only with real images; the sensitivity of disease diagnosis is 96.69%, a relative improvement of 7.1%. 1%, the specificity was 89.70%; the area under the ROC curve (AUC) increased from 94.00% to 96.17%. ConclusionIn this paper, a multi-domain translation model of medical images based on the key transfer branch is proposed, which enables the translation network to have key transfer and attention performance. It is verified on lung CT images and achieved good results. The required medical images are synthesized by the above medical image translation model, and the effectiveness of the synthesized images on the lung image classification network is verified experimentally.

Carotenoid analysis and functional characterization of lycopene cyclases in Zinnia elegans L.

Carotenoids, a group of essential pigments for petal coloration in many species, could be generally categorized into linear and cyclic groups. The cyclization of the linear substrate lycopene at both end groups by β- and ε-cyclases (LCYBs and LCYEs, respectively) is a key branching point of the biosynthesis of cyclic carotenoids in flowers. Common zinnia (Zinnia elegans L.), an Asteraceae family plant that has been widely used in landscape greening, is best known for its brilliant flower colors. However, the mechanism of its petal coloration is not well studied, especially with respect to carotenoid pigmentation. In this study, total carotenoid content and carotenoid compositions of petals were analyzed in two common zinnia cultivars, 'Dreamland Red’ (DRE) and 'Dreamland Yellow’ (DY). Despite the lighter color of DY petals, the total carotenoid content in DY flowers was significantly higher than that in DRE. Metabolomic analysis revealed that the major carotenoids of both cultivars are cyclic carotenoids, with β-carotene being the most abundant. In addition, one LCYB, LCYE, and capsanthin/capsorubin synthase (CCS) gene were identified from Z. elegans by homology-based search in transcriptome. After cloning and sequencing, full-length open reading frame of each gene is exactly the same between two cultivars. Bacterial pigment complementation experiments revealed that ZeLCYB and ZeCCS can cyclize lycopene at both ends to produce β-carotene. Unlike most LCYEs characterized from higher plants, ZeLCYE produced predominantly ε-carotene in E. coli system. However, ZeLCYE is likely to have a lower affinity for lycopene or lower activity compared with ZeLCYB. Gene expression analysis showed that DY has higher expression levels of ZeLCYB and ZeCCS than DRE at specific developmental stages, consistent with its higher total carotenoid content. This work would lay a solid foundation for future studies on carotenoid accumulation in Z. elegans.

Metabolic Rewiring of Kynurenine Pathway during Hepatic Ischemia-Reperfusion Injury Exacerbates Liver Damage by Impairing NAD Homeostasis.

Hepatic ischemia-reperfusion (IR) injury remains a common issue lacking effective strategy and validated pharmacological targets. Here, using an unbiased metabolomics screen, this study finds that following murine hepatic IR, liver 3-hydroxyanthranilic acid (3-HAA) and quinolinic acid (QA) decline while kynurenine and kynurenic acid (KYNA) increase. Kynurenine aminotransferases 2, functioning at the key branching point of the kynurenine pathway (KP), is markedly upregulated in hepatocytes during ischemia, shifting the kynurenine metabolic route from 3-HAA and QA to KYNA synthesis. Defects in QA synthesis impair de novo nicotinamide adenine dinucleotide (NAD) biosynthesis, rendering the hepatocytes relying on the salvage pathway for maintenance of NAD and cellular antioxidant defense. Blocking the salvage pathway following IR by the nicotinamide phosphoribosyltransferase inhibitor FK866 exacerbates liver oxidative damage and enhanced IR susceptibility, which can be rescued by the lipid peroxidation inhibitor Liproxstatin-1. Notably, nicotinamide mononucleotide administration once following IR effectively boosts NAD and attenuated IR-induced oxidative stress, inflammation, and cell death in the murine model. Collectively, the findings reveal that metabolic rewiring of the KP partitions it away from NAD synthesis in hepatic IR pathophysiology, and provide proof of concept that NAD augmentation is a promising therapeutic measure for IR-induced liver injury.

Single-cell transcriptomics reveals the cell fate transitions of human dopaminergic progenitors derived from hESCs

BackgroundMidbrain dopaminergic (DA) progenitors derived from human pluripotent stem cells are considered to be a promising treatment for Parkinson’s disease (PD). However, the differentiation process produces undesired cell types, which influence the in vivo evaluation of DA cells. In this paper, we analyze the cell fate choice during differentiation and provide valuable information on cell preparation.MethodsHuman embryonic stem cells were differentiated into DA progenitors. We applied single-cell RNA sequencing (scRNA-seq) of the differentiation cells at different time points and investigated the gene expression profiles. Based on the differentially expressed genes between DA and non-DA cells, we investigated the impact of LGI1 (DA enriched) overexpression on DA differentiation and the enrichment effect of CD99 (non-DA enriched) sorting.ResultsTranscriptome analyses revealed the DA differentiation trajectory as well as non-DA populations and three key lineage branch points. Using genetic gain- and loss-of-function approaches, we found that overexpression of LGI1, which is specific to EN1+ early DA progenitors, can promote the generation of TH+ neurons. We also found that choroid plexus epithelial cells and DA progenitors are major components of the final product (day 25), and CD99 was a specific surface marker of choroid plexus epithelial cells. Sorting of CD99− cells eliminated major contaminant cells and improved the purity of DA progenitors.ConclusionsOur study provides the single-cell transcriptional landscape of in vitro DA differentiation, which can guide future improvements in DA preparation and quality control for PD cell therapy.

Diadenosine tetraphosphate regulates biosynthesis of GTP in Bacillus subtilis.

Diadenosine tetraphosphate (Ap4A) is a putative second messenger molecule that is conserved from bacteria to humans. Nevertheless, its physiological role and the underlying molecular mechanisms are poorly characterized. We investigated the molecular mechanism by which Ap4A regulates inosine-5'-monophosphate dehydrogenase (IMPDH, a key branching point enzyme for the biosynthesis of adenosine or guanosine nucleotides) in Bacillus subtilis. We solved the crystal structure of BsIMPDH bound to Ap4A at a resolution of 2.45 Å to show that Ap4A binds to the interface between two IMPDH subunits, acting as the glue that switches active IMPDH tetramers into less active octamers. Guided by these insights, we engineered mutant strains of B. subtilis that bypass Ap4A-dependent IMPDH regulation without perturbing intracellular Ap4A pools themselves. We used metabolomics, which suggests that these mutants have a dysregulated purine, and in particular GTP, metabolome and phenotypic analysis, which shows increased sensitivity of B. subtilis IMPDH mutant strains to heat compared with wild-type strains. Our study identifies a central role for IMPDH in remodelling metabolism and heat resistance, and provides evidence that Ap4A can function as an alarmone.

Three birds with one stone: oxygen self-supply engineering palladium nanocluster/titanium carbide hybrid for single-NIR laser-triggered synergistic photodynamic-photothermal therapy

Abstract As a key branch of the cross-discipline biophotonics, phototherapy, including photodynamic therapy (PDT), and photothermal therapy (PTT), is promising in biomedicine and visible light-driving PDT has been applied to clinical treatment. However, extensive applications of phototherapy are limited by the hypoxic microenvironment, laser penetration depth, and potential complexity for combined PDT/PTT. Thus, NIR-responsive oxygen self-supply nanocomposites functionalized with photosensitizers for achieving simultaneous in-depth PDT/PTT are urgently required. Herein, a multifunctional platform has been fabricated by co-immobilizing monodispersed ultrasmall Pd nanoclusters and a photosensitizer 5,10,15,20-Tetrakis (4-Aminophenyl)-21H,23H Porphyrin (Thp) on the surface of Ti3C2T x MXene nanosheets, generating the Pd-Thp-Ti3C2T x nanocomposite. Material characterization demonstrated that Pd nanoclusters and Thp were well-distributed on the MXene surface while MXene maintained its photothermal conversion efficiency and broad absorption. In this nanoplatform, irradiated by the single 808 nm laser, Pd selectively catalyzed the decomposition of H2O2 to O2, and O2 was continuously supplied to Thp for enhanced NIR-driving PDT. The in vivo fluorescence and photothermal imaging demonstrated the pronounced accumulation of nanocomposites in the tumor site. Both in vitro and in vivo results clearly demonstrated the nanocomposite had good biocompatibility, and that the synergistic PTT and enhanced PDT made apoptosis of the tumor cell achievable. This work not only proves this Pd-Thp-Ti3C2T x nanocomposite serves a promising solution for tumor hypoxia by inducing apoptosis of tumor cells with synergistic PTT and PDT, but also broadens the application of promising optical materials in biomedical field.

Quantifying the capacity of tree branches for retaining airborne submicron particles

Human health risks brought by fine atmospheric particles raise scholarly and policy awareness about the role of urban trees as bio-filters of air pollution. While a large number of empirical studies have focused on the characteristics of vegetation leaves and their effects on atmospheric particle retention, the dry deposition of particles on branches, which plays a significant role in capturing and retaining particles during the defoliation period and contributes substantially to total removal of atmospheric particles, is under-investigated. To fill in this knowledge gap, this case study examined the dry deposition velocities (Vd) of submicron particulate matters (PM1) on the branches of six common deciduous species in Shanghai (China) using laboratory experiments. And the association between Vd and key branch anatomical traits (including surface roughness, perimeter, rind width proportion, lenticel density, peeling, and groove/ridge characteristics) was explored. It was found that surface roughness would increase Vd, as a rougher surface significantly increases turbulence, which is conducive to particle diffusion. By contrast, peeling, branch perimeter, and lenticel density would decrease Vd. Peeling represents the exfoliated remains on the branch surfaces which may flutter considerably with airflow, leading to particle resuspension and low Vd. When branch perimeter increases, the boundary layer of branches thickens and a wake area appears, increasing the difficulty of particles to reach branch surface, and reducing Vd. While lenticels can increase the roughness of branch surface, their pointy shape would uplift airflow and cause a leeward wake area, lowering Vd. This finely wrought study contributes to a better understanding of branch dry deposition during leaf-off seasons and potential of deciduous trees serving as nature-based air filters all year round in urban environments.

Pulsed Multifrequency Electron Paramagnetic Resonance Spectroscopy Reveals Key Branch Points for One- vs Two-Electron Reactivity in Mn/Fe Proteins.

Traditionally, the ferritin-like superfamily of proteins was thought to exclusively use a diiron active site in catalyzing a diverse array of oxygen-dependent reactions. In recent years, novel redox-active cofactors featuring heterobimetallic Mn/Fe active sites have been discovered in both the radical-generating R2 subunit of class Ic (R2c) ribonucleotide reductases (RNRs) and the related R2-like ligand-binding oxidases (R2lox). However, the protein-specific factors that differentiate the radical reactivity of R2c from the C-H activation reactions of R2lox remain unknown. In this work, multifrequency pulsed electron paramagnetic resonance (EPR) spectroscopy and ligand hyperfine techniques in conjunction with broken-symmetry density functional theory calculations are used to characterize the molecular and electronic structures of two EPR-active intermediates trapped during aerobic assembly of the R2lox Mn/Fe cofactor. A MnIII(μ-O)(μ-OH)FeIII species is identified as the first EPR-active species and represents a common state between the two classes of redox-active Mn/Fe proteins. The species downstream from the MnIII(μ-O)(μ-OH)FeIII state exhibits unique EPR properties, including unprecedented spectral breadth and isotope-dependent g-tensors, which are attributed to a weakly coupled, hydrogen-bonded MnIII(μ-OH)FeIII species. This final intermediate precedes formation of the MnIII/FeIII resting state and is suggested to be relevant to understanding the endogenous reactivity of R2lox.

Растениеводство Северо-Казахстанской области как основа сельскохозяйственного кластера и обеспечения продовольственной безопасности населения

The scientific article discusses the features of the development and location of crop production in the North Kazakhstan region, which is the main key branch of the agricultural cluster of the region and the basis for ensuring food security of the population. The purpose of the work is to identify the current state and trends in the development of the industry. Applying the economic and geographical method of research, the authors of the article conclude that ensuring food security both for the population of a particular region and for the country as a whole is possible by solving two main problems. This is a transition to an innovative way of development and acceleration of import products substitution. All this poses an important strategic task for the agro-industrial complex to increase the efficiency of production in agriculture, including crop production. The North Kazakhstan region, being one of the leading regions in the structure of agricultural production of the Republic of Kazakhstan, is the most interesting from a scientific point of view for studying the tasks set.

Stony coral tissue loss disease decimated Caribbean coral populations and reshaped reef functionality

Diseases are major drivers of the deterioration of coral reefs and are linked to major declines in coral abundance, reef functionality, and reef-related ecosystems services. An outbreak of a new disease is currently rampaging through the populations of the remaining reef-building corals across the Caribbean region. The outbreak was first reported in Florida in 2014 and reached the northern Mesoamerican Reef by summer 2018, where it spread across the ~450-km reef system in only a few months. Rapid spread was generalized across all sites and mortality rates ranged from 94% to <10% among the 21 afflicted coral species. Most species of the family Meandrinadae (maze corals) and subfamily Faviinae (brain corals) sustained losses >50%. This single event further modified the coral communities across the region by increasing the relative dominance of weedy corals and reducing reef functionality, both in terms of functional diversity and calcium carbonate production. This emergent disease is likely to become the most lethal disturbance ever recorded in the Caribbean, and it will likely result in the onset of a new functional regime where key reef-building and complex branching acroporids, an apparently unaffected genus that underwent severe population declines decades ago and retained low population levels, will once again become conspicuous structural features in reef systems with yet even lower levels of physical functionality.

Proteomic and metabolic disturbances in lignin-modified Brachypodium distachyon.

Lignin biosynthesis begins with the deamination of phenylalanine and tyrosine (Tyr) as a key branch point between primary and secondary metabolism in land plants. Here, we used a systems biology approach to investigate the global metabolic responses to lignin pathway perturbations in the model grass Brachypodium distachyon. We identified the lignin biosynthetic protein families and found that ammonia-lyases (ALs) are among the most abundant proteins in lignifying tissues in grasses. Integrated metabolomic and proteomic data support a link between lignin biosynthesis and primary metabolism mediated by the ammonia released from ALs that is recycled for the synthesis of amino acids via glutamine. RNA interference knockdown of lignin genes confirmed that the route of the canonical pathway using shikimate ester intermediates is not essential for lignin formation in Brachypodium, and there is an alternative pathway from Tyr via sinapic acid for the synthesis of syringyl lignin involving yet uncharacterized enzymatic steps. Our findings support a model in which plant ALs play a central role in coordinating the allocation of carbon for lignin synthesis and the nitrogen available for plant growth. Collectively, these data also emphasize the value of integrative multiomic analyses to advance our understanding of plant metabolism.

Inference of cell state transitions and cell fate plasticity from single-cell with MARGARET.

Despite recent advances in inferring cellular dynamics using single-cell RNA-seq data, existing trajectory inference (TI) methods face difficulty in accurately reconstructing the cell-state manifold and cell-fate plasticity for complex topologies. Here, we present MARGARET (https://github.com/Zafar-Lab/Margaret) for inferring single-cell trajectory and fate mapping for diverse dynamic cellular processes. MARGARET reconstructs complex trajectory topologies using a deep unsupervised metric learning and a graph-partitioning approach based on a novel connectivity measure, automatically detects terminal cell states, and generalizes the quantification of fate plasticity for complex topologies. On a diverse benchmark consisting of synthetic and real datasets, MARGARET outperformed state-of-the-art methods in recovering global topology and cell pseudotime ordering. For human hematopoiesis, MARGARET accurately identified all major lineages and associated gene expression trends and helped identify transitional progenitors associated with key branching events. For embryoid body differentiation, MARGARET identified novel transitional populations that were validated by bulk sequencing and functionally characterized different precursor populations in the mesoderm lineage. For colon differentiation, MARGARET characterized the lineage for BEST4/OTOP2 cells and the heterogeneity in goblet cell lineage in the colon under normal and inflamed ulcerative colitis conditions. Finally, we demonstrated that MARGARET can scale to large scRNA-seq datasets consisting of ∼ millions of cells.

Construction of a Linked Data Set of COVID-19 Knowledge Graphs: Development and Applications.

BackgroundWith the continuous spread of COVID-19, information about the worldwide pandemic is exploding. Therefore, it is necessary and significant to organize such a large amount of information. As the key branch of artificial intelligence, a knowledge graph (KG) is helpful to structure, reason, and understand data.ObjectiveTo improve the utilization value of the information and effectively aid researchers to combat COVID-19, we have constructed and successively released a unified linked data set named OpenKG-COVID19, which is one of the largest existing KGs related to COVID-19. OpenKG-COVID19 includes 10 interlinked COVID-19 subgraphs covering the topics of encyclopedia, concept, medical, research, event, health, epidemiology, goods, prevention, and character.MethodsIn this paper, we introduce the key techniques exploited in building COVID-19 KGs in a top-down manner. First, the schema of the modeling process for each KG in OpenKG-COVID19 is described. Second, we propose different methods for extracting knowledge from open government sites, professional texts, public domain–specific sources, and public encyclopedia sites. The curated 10 COVID-19 KGs are further linked together at both the schema and data levels. In addition, we present the naming convention for OpenKG-COVID19.ResultsOpenKG-COVID19 has more than 2572 concepts, 329,600 entities, 513 properties, and 2,687,329 facts, and the data set will be updated continuously. Each COVID-19 KG was evaluated, and the average precision was found to be above 93%. We have developed search and browse interfaces and a SPARQL endpoint to improve user access. Possible intelligent applications based on OpenKG-COVID19 for further development are also described.ConclusionsA KG is useful for intelligent question-answering, semantic searches, recommendation systems, visualization analysis, and decision-making support. Research related to COVID-19, biomedicine, and many other communities can benefit from OpenKG-COVID19. Furthermore, the 10 KGs will be continuously updated to ensure that the public will have access to sufficient and up-to-date knowledge.

Phosphorylation at Ser724 of the ER stress sensor IRE1α governs its activation state and limits ER stress–induced hepatosteatosis

Inositol-requiring enzyme 1 (IRE1) is an evolutionarily conserved sensor of endoplasmic reticulum (ER) stress and mediates a key branch of the unfolded protein response in eukaryotic cells. It is an ER-resident transmembrane protein that possesses Ser/Thr protein kinase and endoribonuclease (RNase) activities in its cytoplasmic region. IRE1 is activated through dimerization/oligomerization and autophosphorylation at multiple sites, acting through its RNase activity to restore the functional capacity of the ER. However, it remains poorly defined in vivo how the autophosphorylation events of endogenous IRE1 govern its dynamic activation and functional output. Here, we generated a mouse model harboring a S724A knock-in mutation (Ern1S724A/S724A) and investigated the importance of phosphorylation at Ser724 within the kinase activation loop of murine IRE1α. We found that in mouse embryonic fibroblast cells and in primary hepatocytes, S724A mutation resulted in markedly reduced IRE1α autophosphorylation in parallel with blunted activation of its RNase activity to catalyze X-box binding protein 1 (Xbp1) mRNA splicing. Furthermore, ablation of IRE1α phosphorylation at Ser724 exacerbated ER stress–induced hepatic steatosis in tunicamycin-treated Ern1S724A/S724A mice. This was accompanied by significantly decreased hepatic production of spliced XBP1 protein but increased CCAAT-enhancer–binding protein homologous protein (CHOP) level, along with suppressed expression of key metabolic regulators of fatty acid β-oxidation and lipid secretion. These results demonstrate a critical role of phosphorylation at Ser724 of IRE1α in dynamically controlling its kinase activity, and thus its autophosphorylation state, which is coupled to activation of its RNase activity in counteracting hepatic steatosis under ER stress conditions.

FERGCN: facial expression recognition based on graph convolution network.

Due to the problems of occlusion, pose change, illumination change, and image blur in the wild facial expression dataset, it is a challenging computer vision problem to recognize facial expressions in a complex environment. To solve this problem, this paper proposes a deep neural network called facial expression recognition based on graph convolution network (FERGCN), which can effectively extract expression information from the face in a complex environment. The proposed FERGCN includes three essential parts. First, a feature extraction module is designed to obtain the global feature vectors from convolutional neural networks branch with triplet attention and the local feature vectors from key point-guided attention branch. Then, the proposed graph convolutional network uses the correlation between global features and local features to enhance the expression information of the non-occluded part, based on the topology graph of key points. Furthermore, the graph-matching module uses the similarity between images to enhance the network’s ability to distinguish different expressions. Results on public datasets show that our FERGCN can effectively recognize facial expressions in real environment, with RAF-DB of 88.23%, SFEW of 56.15% and AffectNet of 62.03%.

Nanotechnology, Green Synthesis and Biological Activity Application of Zinc Oxide Nanoparticles Incorporated Argemone Mxicana Leaf Extract.

Nanomaterial is a rapidly growing area that is used to create a variety of new materials and nanotechnology applications from medical, pharmaceuticals, chemical, mechanical, electronics and several environmental industries including physical, chemical and biological nanoparticles are very important in our daily life. Nanoparticles with leaf extract from the healthy plant are important in the area of research using biosynthesis methods. Because of it’s used as an environmentally ecofriendly, other than traditional physical and chemical strategies. In particular, biologically synthesized nanoparticles have become a key branch of nanotechnology. The present work presents a synthesis of zinc oxide nanoparticles using an extract from the Argemone leaf Mexicana. Biosynthetic nanoparticles are characterized by X-ray diffraction (XRD), Ultraviolet visible (UV-vis) spectroscopy analysis, a Fourier Transform Infrared Spectroscopy analysis (FTIR) and a scanning electron microcopy (SEM), X-ray analysis with dispersive energy (EDAX). XRD is used to examine the crystalline size of zinc oxide nanoparticles. The FTIR test consists in providing evidence of the presence of targeted teams. UV is used for optical properties and calculates the energy of the bandwidth slot. The scanning microscope emission reveals the morphology of the surface and the energy dispersive X-ray analysis confirms the basic composition of zinc oxide nanoparticles. It is found that zinc nanoparticles are capable of achieving high anti-fungal efficacy and therefore have a high potential antimicrobial activity of ZnO NPs, like antibacterial and high antioxidant. Zinc Oxide nanoparticles from the Argemone Mexicana leaf extract have several antimicrobial applications, such as medical specialty, cosmetics, food, biotechnology, nano medicine and drug delivery system. ZnO nanoparticles are important because they provide many practical applications in industry. The most important use of nanoparticles of ZnO would be strong antibacterial and antioxidant activity with a simple and efficient biosynthesis method may be used for future work applications.

The PERK/ATF4/CHOP signaling branch of the unfolded protein response mediates cisplatin-induced ototoxicity in hair cells

Cisplatin is a widely used chemotherapeutic agent. However, its clinical application remains limited due to the high incidence of severe ototoxicity. It has been reported that the unfolded protein response (UPR) is involved in cisplatin-induced ototoxicity. However, the specific mechanism underlying its effect remains unclear. Therefore, the present study aimed to explore the sequential changes in the key UPR signaling branch and its potential pro-apoptotic role in cisplatin-induced ototoxicity. The hair cell-like OC-1 cells were treated with cisplatin for different periods and then the expression levels of the UPR- and apoptosis-related proteins were determined. The results showed that the apoptotic rate of cells was gradually increased with prolonged cisplatin treatment. Furthermore, the sequential changes in three UPR signaling branches were evaluated. The expression levels of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP) were gradually increased with up to 12 h of cisplatin treatment. The aforementioned expression profile was consistent with that observed for the apoptosis-related proteins. Subsequently, the proportion of apoptotic cells was notably decreased in CHOP-silenced hair cell-like OC-1 cells following treatment with cisplatin. Moreover, we found significant hair cells loss and a higher level of CHOP in cisplatin-treated cochlear explants in a time-dependent manner. Overall, the present study demonstrated that the protein kinase RNA‑like endoplasmic reticulum kinase (PERK)/ATF4/CHOP signaling branch could play an important role in cisplatin-induced cell apoptosis. Furthermore, the current study suggested that CHOP may be considered as a promising therapeutic target for cisplatin-induced ototoxicity.

Expression of p38MAPK and its regulation of apoptosis under high temperature stress in the razor clam Sinonovacula constricta

p38MAPK is a key branch of the MAPK (mitogen-activated protein kinase) pathway that plays an important role in physiological processes such as apoptosis, cell proliferation and growth. In this experiment, we screened and identified one p38MAPK gene in the razor clam Sinonovacula constricta, which encoded 359 amino acids and was widely expressed in various adult tissues. After 24 h of high temperature stress at 34 °C, the transcript expression of p38MAPK showed significant changes in all tested tissues. In particular in the gill and hepatopancreas tissues, where the expression increased 1.81 and 7.83 times compared with the control group, respectively (P < 0.01). Furthermore, we examined the expression of the apoptosis suppressor gene Bcl-2 and pro-apoptosis gene Bax by knock-down of p38MAPK with dsRNA interference in the gill and hepatopancreas tissues. The obvious up-regulation expression of Bcl-2 and significant suppression of Bax were observed, respectively (P < 0.01). Moreover, the TUNEL staining technique was used to detect apoptosis before and after interference. The degree of apoptosis in the gill and hepatopancreas tissues was reduced after interference with p38MAPK, and the ROS content was significantly reduced (P < 0.01). The results suggested that p38MAPK had a regulatory role in the heat tolerance of razor clams.