Important Value Research Articles

Thirteen complete chloroplast genomes of the costaceae family: insights into genome structure, selective pressure and phylogenetic relationships

BackgroundCostaceae, commonly known as the spiral ginger family, consists of approximately 120 species distributed in the tropical regions of South America, Africa, and Southeast Asia, of which some species have important ornamental, medicinal and ecological values. Previous studies on the phylogenetic and taxonomic of Costaceae by using nuclear internal transcribed spacer (ITS) and chloroplast genome fragments data had low resolutions. Additionally, the structures, variations and molecular evolution of complete chloroplast genomes in Costaceae still remain unclear. Herein, a total of 13 complete chloroplast genomes of Costaceae including 8 newly sequenced and 5 from the NCBI GenBank database, representing all three distribution regions of this family, were comprehensively analyzed for comparative genomics and phylogenetic relationships.ResultThe 13 complete chloroplast genomes of Costaceae possessed typical quadripartite structures with lengths from 166,360 to 168,966 bp, comprising a large single copy (LSC, 90,802 − 92,189 bp), a small single copy (SSC, 18,363 − 20,124 bp) and a pair of inverted repeats (IRs, 27,982 − 29,203 bp). These genomes coded 111 − 113 different genes, including 79 protein-coding genes, 4 rRNA genes and 28 − 30 tRNAs genes. The gene orders, gene contents, amino acid frequencies and codon usage within Costaceae were highly conservative, but several variations in intron loss, long repeats, simple sequence repeats (SSRs) and gene expansion on the IR/SC boundaries were also found among these 13 genomes. Comparative genomics within Costaceae identified five highly divergent regions including ndhF, ycf1-D2, ccsA-ndhD, rps15-ycf1-D2 and rpl16-exon2-rpl16-exon1. Five combined DNA regions (ycf1-D2 + ndhF, ccsA-ndhD + rps15-ycf1-D2, rps15-ycf1-D2 + rpl16-exon2-rpl16-exon1, ccsA-ndhD + rpl16-exon2-rpl16-exon1, and ccsA-ndhD + rps15-ycf1-D2 + rpl16-exon2-rpl16-exon1) could be used as potential markers for future phylogenetic analyses and species identification in Costaceae. Positive selection was found in eight protein-coding genes, including cemA, clpP, ndhA, ndhF, petB, psbD, rps12 and ycf1. Maximum likelihood and Bayesian phylogenetic trees using chloroplast genome sequences consistently revealed identical tree topologies with high supports between species of Costaceae. Three clades were divided within Costaceae, including the Asian clade, Costus clade and South American clade. Tapeinochilos was a sister of Hellenia, and Parahellenia was a sister to the cluster of Tapeinochilos + Hellenia with strong support in the Asian clade. The results of molecular dating showed that the crown age of Costaceae was about 30.5 Mya (95% HPD: 14.9 − 49.3 Mya), and then started to diverge into the Costus clade and Asian clade around 23.8 Mya (95% HPD: 10.1 − 41.5 Mya). The Asian clade diverged into Hellenia and Parahellenia at approximately 10.7 Mya (95% HPD: 3.5 − 25.1 Mya).ConclusionThe complete chloroplast genomes can resolve the phylogenetic relationships of Costaceae and provide new insights into genome structures, variations and evolution. The identified DNA divergent regions would be useful for species identification and phylogenetic inference in Costaceae.

Multifunctional sodium alginate-based self-healing edible cross-linked coating for banana preservation

Edible coating plays an important role in preventing fruit rot and prolonging the shelf life of fruit. However, a large amount of water will accumulate on the surface of the fruit through respiratory metabolism during storage, leading to the dissolution of the coating. Therefore, it is important to develop water-resistant coatings to extend the shelf life of bananas. In this work, gluconolactone (GDL) was used to slowly generate gluconic acid, which protonated the amino groups of the whey protein isolate (WPI) and enhanced the electrostatic interaction between WPI and sodium alginate (SA) to form a cross-linked composite coating. The introduction of WPI increased the water contact angle value of the films from 47.1° to 102.1°. The composite coating exhibited excellent mechanical properties, water resistance, UV shielding self-healing, and gas-selective transmission. The experiment of banana preservation proved that the composite coating could effectively slow down the water loss of bananas, retard the ripening and browning, and extend the shelf life of bananas for 6 days at 25 °C and 50% RH. Therefore, this multifunctional coating has important reference value for the design of self-healing coating, and shows good potential in the preservation of perishable fruits.

Optimizing drug combination and mechanism analysis based on risk pathway crosstalk in pan cancer

Combination therapy can greatly improve the efficacy of cancer treatment, so identifying the most effective drug combination and interaction can accelerate the development of combination therapy. Here we developed a computational network biological approach to identify the effective drug which inhibition risk pathway crosstalk of cancer, and then filtrated and optimized the drug combination for cancer treatment. We integrated high-throughput data concerning pan-cancer and drugs to construct miRNA-mediated crosstalk networks among cancer pathways and further construct networks for therapeutic drug. Screening by drug combination method, we obtained 687 optimized drug combinations of 83 first-line anticancer drugs in pan-cancer. Next, we analyzed drug combination mechanism, and confirmed that the targets of cancer-specific crosstalk network in drug combination were closely related to cancer prognosis by survival analysis. Finally, we save all the results to a webpage for query (http://bio-bigdata.hrbmu.edu.cn/oDrugCP/). In conclusion, our study provided an effective method for screening precise drug combinations for various cancer treatments, which may have important scientific significance and clinical application value for tumor treatment.

Community structure and regeneration capacity of mangrove forest

Mangrove forests play a vital role in the environment. They provide a number of ecosystem services for supporting marine biodiversity, humans, and other living organisms inhabiting the area. This study aimed to determine the community structure and regeneration capacity of mangrove forests in Lebak, Sultan Kudarat, Philippines. Community structure was determined through relative density, relative frequency, relative dominance, and importance value. Using the center point circular plot method, 13 plots with 40 m diameter were established in two sampling sites: natural stand and reforested. Shannon-Weiner diversity and evenness indexes were used to determine species diversity and distribution, respectively. This study recorded a total of 14 462 individuals within the 1256 m² sampling plots, having Rhizophoraceae as the most abundant family with seven species that cover about 71% of both mangrove ecosystems. The vegetation analysis revealed that Ceriops tagal (70.35%) and Rhizophora mucronata (96.51%) had the highest importance value in the natural stand and reforested mangrove forests, respectively. Furthermore, these two species were also accounted for having the highest regeneration contribution among all species in each site. Shannon-Weiner diversity index revealed that the natural stand was more diverse compared to the reforested mangrove forest. However, the Shannon-Weiner evenness index showed that species in the reforested mangrove forest are more evenly distributed than species in the natural stand. Natural mangrove stands in Lebak have complex community structure and have higher regeneration capacity than the reforested mangrove forest. With this, the study suggested continuing the best practices employed for mangrove conservation in the area and crafting a strategic plan for sustainable mangrove resource utilization.

Study on the Automatic Information Processing Strategy in L2 Reading

Reading is currently a prominent topic in L2 acquisition research, serving as an indicator of L2 learners’ overall language proficiency. However, there are still many challenges in reading for L2 learners. For example, there still exist some linguistic and non-linguistic problems, such as insufficient language ability, lack of cultural background knowledge, low reading efficiency, and poor reading habits. Effectively improving the information processing skills of L2 learners in reading posts a major challenge for researchers. This paper explores the effective strategies for L2 learners to obtain the ability of automatic reading information processing through the scale survey. It is found in the study that:1) L2 learners believe that they can reach the level of automatic reading processing through the automatic information processing strategy; 2) The automatic information processing strategy can be applied in L2 reading to effectively improve the level of L2 automatic processing. Various strategies, such as improving language proficiency, increasing cultural background knowledge, utilizing metacognitive strategies, and employing socio-emotional strategies, both linguistic and non-linguistic, have been identified to effectively improve the automatic information processing ability of L2 learners. This study has important theoretical and practical value for improving the reading ability of L2 learners.

Natural halloysite nanotubes decorated with organophosphorous for highly flame‐resistant epoxy composites

AbstractHighly flame‐resistant epoxy composites have important application value in many industrial fields. Unfortunately, epoxy resins (EPs) are inherently flammable materials and exhibit great fire hazard. In this study, the commercially available 9,10‐dihydro‐9‐oxa‐10‐phosphaphenanthrene‐10‐oxide (DOPO) was chemically immobilized on the surface of natural halloysite nanotubes (HNTs) via the linkage of vinyltrimethoxysilane to obtain a novel flame‐retardant VD@HNTs containing P/Si/Al elements. It was found that the flame‐retardant VD@HNTs can effectively improve the thermal stability and flame resistance of epoxy composites. Typically, when 10% of VD@HNTs is added in EP, the limiting oxygen index of as‐prepared VD@HNTs/EP composites reaches 30.3%, and it also successfully reaches V‐0 classification in the UL‐94 test. Besides, the ignition time of VD@HNTs/EP composites was enhanced from 42 s for pure EP to 60 s, and the maximum heat release rate was reduced from 1221 to 758 kW∙m−2. These great findings promise an innovative and efficient strategy for improving the fire safety of EP products and may also offer valuable insight toward fabricating various novel organic–inorganic flame retardants as well as highly flame‐resistant polymer composites.Highlights A novel flame‐retardant VD@HNTs containing P/Si/Al elements was prepared by the chemical decoration of HNTs with organophosphorous. The VD@HNT can effectively improve the thermal stability and flame resistance of epoxy composites. Synergistic flame‐retardant mechanism of phosphorus‐based flame retardants and natural HNTs was classified.

Impact of peripheral blood mononuclear cells preconditioned by activated platelet supernatant in managing gastric mucosal damage induced by zinc oxide nanoparticles in rats.

The world has witnessed tremendous advancements in nano-base applications. Zinc oxide nanoparticles (ZON) are widely used in food industry and medicine. Although their application is of important value, they may cause toxicity to body tissues. Peripheral blood mononuclear cells (PBMCs) proved its efficacy in tissue regeneration especially when it is preconditioned by activated platelet supernatant (APS). The aim of this study is to evaluate the effect of ZON on the gastric mucosa and the therapeutic role of the PBMCs preconditioned by APS in rats. Ten rats were donors and fifty rats were recipients. The recipients were divided into; control group, ZON group (10 mg/kg/day orally for five days) and preconditioned PBMCs group (1×107 once intravenously 24 hours after ZON). Gastric specimens were processed for histological, immunohistochemical, biochemical and quantitative real-time polymerase chain reaction studies. ZON group showed marked structural changes in the gastric mucosa. There was desquamation or deep ulceration of the epithelium. Cytoplasmic vacuoles and pyknotic nuclei were in glandular cells. Reduced proliferating cell nuclear antigen and increased tumor necrosis factor-α were in epithelial cells. There were significant elevation in malondialdahyde and reduction in glutathione, superoxide dismutase, and catalase. Enhancement in mRNA expression of nuclear factor kappa-B and cyclooxygenase-2 was detected. The preconditioned PBMCs group showed significant improvement of all parameters. So, ZON had cytotoxic effects on the gastric mucosa and the preconditioned PBMCs had a therapeutic effect on gastric mucosal damage after ZON.

Soil Moisture Prediction Model Based on Improved GRU Recurrent Neural Network

Soil moisture plays a crucial role in land water and energy cycles, and has a certain impact on weather and climate change. In agricultural production, crop moisture status can be determined based on soil moisture, and timely and effective irrigation strategies can be formulated to ensure grain yield while saving water resources, maximizing the value of agricultural water resource utilization, and achieving sustainable development. Therefore, the accuracy of soil moisture prediction has important research value for many fields such as agriculture and climate. In this paper, the super parameters of GRU Recurrent neural network are optimized by intelligent seagull optimization algorithm using a small number of influencing factors, namely, atmospheric temperature, atmospheric humidity, rainfall and soil moisture data, and a soil moisture prediction model is established. The model was used to predict soil moisture for the next 12 hours, 24 hours, 36 hours, and 48 hours, respectively. The final experiment showed that the model in this paper had better predictive effect on soil moisture, with the best predictive evaluation index data being MAPE (12h) = 4.4120%, R2 (12h) = 0.94605, and RMSE (12h) = 1.9998; By comparing the prediction results of multiple time steps vertically, it was found that the prediction accuracy of the model in this paper decreased more smoothly, meeting the requirements of soil moisture prediction.

Quantifying physiological contributions to yield loss in response to planting date in short-season cotton under a cotton[sbnd]wheat double-cropping system

Crop yield is primarily determined by physiological parameters, including light interception by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, little information is available about how these physiological parameters are impacted by planting date and what their contributions are to cotton yield loss. To evaluate the relative contribution of each physiological parameter to planting date-associated yield loss in cotton, an experiment was conducted during the 2019 to 2021 growing seasons at a field site in Anyang, Henan, China. Two contemporary cotton cultivars were grown in the field with four different planting dates (PDMAY10, PDMAY20, PDMAY30 and PDJUN10) for the growing seasons from 2019 to 2021. The measurements included climatic parameters, seed cotton yield, yield components, HI and biweekly leaf area index, light interception and biomass. First, seed cotton yield was significantly affected by the planting dates, with yields ranging from 1984 to 3388 kg ha−1, averaged across cultivars and years, while a significant difference between the first three planting dates was observed only in 2021. Second, the planting date significantly impacted the total light interception during the growing season (IPARtotal) and HI, while IPARtotal and HI decreased with the delayed planting date in all the years of the study. Compared to PDMAY10, IPARtotal was 0.34%, 13.2%, and 19.9% lower for PDMAY20, PDMAY30 and PDJUN10, respectively. Averaged across cultivars and years, PDMAY10 resulted in the highest HI value (0.28). The RUE gradually decreased as the planting date was delayed, but a significant difference in RUE between planting dates was observed only in 2021. Overall, among the three physiological yield-driving parameters, IPARtotal was a stronger contributor (46.9–47.0%) to the yield loss for PDJUN10 than PDMAY10 and PDMAY20. However, when compared to PDMAY30, HI was the greatest contributor, accounting for approximately 72.5% of the seed cotton yield loss for PDJUN10, followed by IPAR. We found that when cotton sowing in the Yellow River basin was postponed until June 10, the cotton yield was significantly reduced, and IPAR and HI were the main factors responsible for PDJUN10 yield loss on average. This study identified the most important functional traits for seed cotton yield response to planting date and has important reference value for stable cotton production.

A tunable multitasking renal function assessment biosensor predicated on cylindrical metastructure

Chronic renal disease has become one of the world’s most serious public health problems in recent decades, leading to physical degradation, and even death. Glucose and creatinine in body fluids are important indicators used to assess renal dysfunction, but current biosensors only focus on the detection and performance improvement of a single indicator. To break through the idea limitation, a cylindrical metastructure based on indium antimonide material is proposed in this paper. It innovatively realizes the tunable multitasking renal function assessment biosensor, which is more suitable for the application of multiple medical detection scenarios. Through the control of the external magnetic field strength, the glucose concentration of 0 ∼ 400 g/L and the serum creatinine concentration of 80.9 ∼ 85.28 μmol/L can be separately detected in real-time, unlabeled, and non-destructively, which own better performance than previous renal function assessment biosensors in terms of detection range, R2, quality factor, figure of merit, and detection limit. This proposal has important reference value for promoting the detection and treatment of renal diseases, and the research of multitasking biosensors.

Automatic detection of mild cognitive impairment based on deep learning and radiomics of MR imaging.

Early and rapid diagnosis of mild cognitive impairment (MCI) has important clinical value in improving the prognosis of Alzheimer's disease (AD). The hippocampus and parahippocampal gyrus play crucial roles in the occurrence of cognitive function decline. In this study, deep learning and radiomics techniques were used to automatically detect MCI from healthy controls (HCs). This study included 115 MCI patients and 133 normal individuals with 3D-T1 weighted MR structural images from the ADNI database. The identification and segmentation of the hippocampus and parahippocampal gyrus were automatically performed with a VB-net, and radiomics features were extracted. Relief, Minimum Redundancy Maximum Correlation, Recursive Feature Elimination and the minimum absolute shrinkage and selection operator (LASSO) were used to reduce the dimensionality and select the optimal features. Five independent machine learning classifiers including Support Vector Machine (SVM), Random forest (RF), Logistic Regression (LR), Bagging Decision Tree (BDT), and Gaussian Process (GP) were trained on the training set, and validated on the testing set to detect the MCI. The Delong test was used to assess the performance of different models. Our VB-net could automatically identify and segment the bilateral hippocampus and parahippocampal gyrus. After four steps of feature dimensionality reduction, the GP models based on combined features (11 features from the hippocampus, and 4 features from the parahippocampal gyrus) showed the best performance for the MCI and normal control subject discrimination. The AUC of the training set and test set were 0.954 (95% CI: 0.929-0.979) and 0.866 (95% CI: 0.757-0.976), respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high. The GP classifier based on 15 radiomics features of bilateral hippocampal and parahippocampal gyrus could detect MCI from normal controls with high accuracy based on conventional MR images. Our fully automatic model could rapidly process the MRI data and give results in 1 minute, which provided important clinical value in assisted diagnosis.

The Combination of University Students' Innovation Ability and Entrepreneurship Education

Under the background of current economic and social growth, innovation and entrepreneurship have become an important force to promote social progress and development. As the backbone of the future society, university students' innovative ability and entrepreneurial spirit are of great significance. This article aims to explore the combination mechanism of university students' innovation ability and enterprise education. Through in-depth theoretical analysis and empirical research, it is found that the combination of university students' innovation ability and enterprise education has important theoretical significance and practical value. It helps to cultivate innovative and entrepreneurial talents. By cultivating university students with innovative ability and entrepreneurial spirit, it can deliver more innovative talents and entrepreneurial strength to the society and promote the sustainable development of the national economy and society. At the same time, this study also reveals the problems and shortcomings of university students' innovation ability and enterprise education, and puts forward some specific combination mechanisms and optimization strategies. These conclusions provide reference for universities to carry out innovation and entrepreneurship education (IEE) and practical activities, and also provide new ideas and methods for future related research.

Study on the Diffusion and Optimization of Sucrose in Gaido Seak Based on Finite Element Analysis and Hyperspectral Imaging Technology.

As a traditional Chinese dish cutting technology process, Gaidao artificially create cuts embedded in the food surface by cutting through it with knife, a process that currently plays an important role in the beef marinating process. And different Gaidao processes directly affect the beef marination flavour and marination efficiency. This study is the first to propose the use of Hyperspectral imaging technology (HSI) combined with finite element analysis to investigate the effect of Gaidao process on the quality of marinated beef. The study was carried out by collecting spectral information of beef marinated with different sucrose concentrations and combining various pre-processing methods and algorithms such as PLS, BiPLS, iPLS, and SiPLS to establish a quantitative model of sucrose concentration in beef, and finally optimizing parameters such as the length, position and number of Gaidao by Finite Element Analysis (FEA), which showed that when marinated with 1.0 mol/m³ sucrose solution, the concentration of sucrose in all tissues in the Gaidao steak reached 0.8 mol/m³ and above, which greatly improved the diffusion effect of the marinade. This work provides new ideas and methods to optimize the beef marinade Gaidao process, which has important practical value and research significance.

Minimal clinically important differenceof fatigue severity scale in patients with chronic stroke

BackgroundOne of the most prevalent symptoms of stroke is fatigue. Fatigue severity scale is the most often used tool for evaluating fatigue in stroke patients, its minimal clinically important difference threshold has not been determined. This study aimed to identify the minimal clinically important difference of fatigue severity scale in stroke patients. MethodsAll study participants were examined using fatigue severity scale and multidimensional fatigue symptom inventory-short form before and after the intervention. The 6-week intervention combined graded activity training and pacing therapy employed to reduce fatigue severity. Participants reported changes in their fatigue severity after the intervention with the global rating of change and visual analog scale. The minimal clinically important difference of the fatigue severity scale calculated using both anchor- and distribution-based methods. ResultsA total of 117 stroke patients were included in the study. Using multidimensional fatigue symptom inventory-short form, global rating of change, and visual analog scale as an anchor, the minimal clinically important difference of fatigue severity scale was obtained at 3.5, 4.5, and 4.5, respectively. The minimal clinically important difference for fatigue severity scale varied from 4.28 to 12.90 using the distribution-based method, with SEM = 4.28 displaying the best sensitivity and specificity for use as minimal clinically important difference. ConclusionsThe minimal clinically important difference value for the fatigue severity scale was estimated at 3.5_12.90 using anchor-based and distribution-based methods. The study's results can be utilized to understand the effectiveness of fatigue interventions in stroke patients in clinical and research settings

Biomedical knowledge graph construction of Sus scrofa and its application in anti-PRRSV traditional Chinese medicine discovery

As a new data management paradigm, knowledge graphs can integrate multiple data sources and achieve quick responses, reasoning and better predictions in drug discovery. Characterized by powerful contagion and a high rate of morbidity and mortality, porcine reproductive and respiratory syndrome (PRRS) is a common infectious disease in the global swine industry that causes economically great losses. Traditional Chinese medicine (TCM) has advantages in low adverse effects and a relatively affordable cost of application, and TCM is therefore conceived as a possibility to treat PRRS under the current circumstance that there is a lack of safe and effective approaches. Here, we constructed a knowledge graph containing common biomedical data from humans and Sus Scrofa as well as information from thousands of TCMs. Subsequently, we validated the effectiveness of the Sus Scrofa knowledge graph by the t-SNE algorithm and selected the optimal model (i.e., transR) from six typical models, namely, transE, transR, DistMult, ComplEx, RESCAL and RotatE, according to five indicators, namely, MRR, MR, HITS@1, HITS@3 and HITS@10. Based on embedding vectors trained by the optimal model, anti-PRRSV TCMs were predicted by two paths, namely, VHC-Herb and VHPC-Herb, and potential anti-PRRSV TCMs were identified by retrieving the HERB database according to the pharmacological properties corresponding to symptoms of PRRS. Ultimately, Dan Shen's (Salvia miltiorrhiza Bunge) capacity to resist PRRSV infection was validated by a cell experiment in which the inhibition rate of PRRSV exceeded 90% when the concentrations of Dan Shen extract were 0.004, 0.008, 0.016 and 0.032 mg/mL. In summary, this is the first report on the Sus Scrofa knowledge graph including TCM information, and our study reflects the important application values of deep learning on graphs in the swine industry as well as providing accessible TCM resources for PRRS.

Forest Fuel Bed Variation in Tropical Coastal Freshwater Forested Wetlands Disturbed by Fire

Tropical coastal freshwater forested wetlands in coastal regions are rapidly disappearing as a result of various disturbance agents, mainly wildfires caused by high accumulations of forest fuels. The objective of this study was to characterize the structure and composition of fuel beds in tropical coastal freshwater forested wetlands with three levels of disturbance at El Castaño, La Encrucijada Biosphere Reserve. Seventeen sampling units were used to describe the structure of the forest’s fuel beds (canopy, sub-canopy, and understory). Fallen woody material and litter (surface and fermented) were characterized using the planar intersection technique. Diversity comprised eight species of trees, two shrubs, five lianas, and two herbaceous species. The vertical strata were dominated by trees between 2 and 22 m in height. The horizontal structure had a higher percentage of trees with normal diameter between 2.5 and 7.5 cm (61.4%) of the total. Sites with low disturbance had the highest arboreal density (2686 ind. ha−1). Diversity of species showed that the Fisher, Margalef, Shannon, and Simpson α indices were higher in the low disturbance sites. The Berger–Parker index exhibited greater dominance in the sites with high disturbance. Pachira aquatica Aubl. Showed the highest importance value index and was the largest contributor to fuel beds. Sites with the highest disturbance had the highest dead fuel load (222.18 ± 33.62 Mg ha−1), with woody fuels of classes 1, 10, and 1000 h (rotten) being the most representative. This study contributes to defining areas prone to fire in these ecosystems and designing prevention strategies.

Ethnobotanical study of medicinal plants used in the prevention and treatment of COVID-19 infection in the Tiaret region (Algeria)

The Corona Virus disease has spread widely over the world with a high mortality rate. This spread has prompted people to look for other ways to treator minimize the negative impact of this out break. During the pandemic, the Algerian population used medicinal plants for the prevention and treatment of COVID-19. The present work was carried out to identify the medicinal plants used during COVID-19 by the population of Tiaret region (Algeria). An ethnobotanical survey was conducted to collect data on the medicinal plants used, including the socio demographic parameters of the users and floristic characteristics of the plants. Information was obtained from 428 participants, of which 67.05% were women, aged between 16 and 88 years old. Most plant users were between 41 and 64 years old. The majority of participants have a high level of education (55.14% university and 20.32% secondary). Quantitative indices, namely, Frequency of Citation (FC), Relative Frequency of Citation (RFC) and Family Importance Value (FIV) were used to analyze the data. 27 species of medicinal plants belonging to 15 botanical families used during the COVID - 19 pandemic in our region. The most used species were Syzygium aromaticum, Zingiber officinale, Citrus limon and Aloysia citriodora.

Plant communities and potential phytoremediation species for resource utilization of abandoned drilling mud

Oil and gas development produces a large amount of abandoned drilling mud, which may be a source of pollution but may also be a potential resource. A quadrat sampling method was used in the Changqing Oilfield to investigate the plant community characteristics inside and outside abandoned drilling mud pits at different completion times. The importance value of plant showed that the natural succession of plant communities in the abandoned drilling mud pool could be divided into three stages: (1) 4–8 years after the completion of the well, Leymus secalinus, Calamagrostis epigeios with the importance values of more than 100, were dominant species in the initial construction stage; (2) 9–13 years after the succession, the intense competition stage of the plant community, although the importance value of plant inside the mud pit had decreased, it was still higher than the importance value of plant outside the mud pool. The importance values of L. secalinus and Artemisia scoparia outside the mud pool were 62.5 and 52.5, while those in the mud pool were 95 and 75, respectively; (3) 23–28 years after the succession, the gradual stabilization stage of the plant community, the importance value of plant was lower than that in the mud pool. Leymus secalinus, C. epigeios and A. scoparia could be used for phytoremediation of abandoned drilling soil for their higher importance values. Changes of Shannon–Wiener index, Pielou index, Community ecological dominance and vegetation biomass showed that the mud pit was suitable for the recovery and growth of the dominant species, improved the diversity of plant communities inside the mud pit compared with the stable plant community outside the mud pit. Abandoned drilling mud increased the content of nitrogen, potassium and trace elements in plants. While the variation coefficient of heavy metal content in plants inside and outside the mud pit was large, but the content of heavy metals in plants was within the normal range. Abandoned drilling mud has the potential for resource utilization on the premise of ensuring soil quality and safety. This study provides information on the comprehensive treatment, resource utilization, disposal economics and environmental safety of abandoned drilling mud.

Türk Onkoloji Hemşirelerinin Etik ve Profesyonel Değerleri

Aim
 This study aimed to determine the values that Turkish oncology nurses believe to be a guide for oncology nursing.
 Method 
 The study was conducted by Turkish Oncology Nursing Association members, attended oncology nursing certification courses or working in oncology clinics. Survey forms were sent to the participants to their postal and e-mail addresses in the association records, and the forms were also delivered by hand to the courses organized by the subject. A total of 880 forms were sent and 521 complete forms were received. As the first part of the questionnaire form, six values suggested for oncology nursing were obtained through a literature review and were included in the study along with their explanations. As the second part of the questionnaire, 10 values derived from the ethical codes of oncology nurses (National Nursing Ethical Codes) were included. The oncology nurses evaluate the importance of these values using a four-point Likert scale.
 Results 
 The study included 521 oncology nurses and reported the following values to be important: innovativeness, excellence, integrity, nurse advocacy, patient advocacy, and inclusiveness. Based on their preference, the participants reported the following ethical codes to be important for oncology nursing: innovativeness, informed consent, respect for individuals, loyalty, patient education, patient benefit, accurate information, respect for decisions, fair sharing, and honesty.
 Conclusion 
 The most important professional nursing values according to the perspectives of nurses in Türkiye were identified. It is advisable to update core values and ethical codes in future studies.

The correlation between sperm percentage with a small acrosome and unexplained in vitro fertilization failure

PurposeSince the unexplained in vitro fertilization failure occurs frequently, it is of great importance and clinical value to identify potential underlying predictors. This study aimed to explore whether the percentage of sperm with a small acrosome was correlated with unexplained in vitro fertilization failure.MethodsA new acrosomal function evaluation index (the percentage of sperm with a small acrosome) was introduced into the analysis of sperm morphology. The association between the index and acrosome function by acrosin activity detection test and acrosome reaction test was investigated. In addition, the correlation with unexplained in vitro fertilization failure was further explored. Finally, the ROC curve was used to analyze the diagnostic efficacy on the failure of in vitro fertilization and the cutoff value was calculated.ResultsAs the increasing of the percentage of sperm with a small acrosome, the value of acrosin activity, acrosome reaction rate, and in vitro fertilization rate were reduced, with a statistically significant difference (P < 0.05). The index in the low fertilization rate group was significantly higher than that in the normal fertilization rate group (P < 0.05). Finally, the results of ROC curve found that when the index was 43.5%, the sensitivity and specificity were 74.2% and 95.3%, respectively.ConclusionThe percentage of sperm with a small acrosome was positively correlated with unexplained in vitro fertilization failure, which could be potentially used as a prognostic index for the failure of in vitro fertilization.Trial registration[Ethics review acceptance No IIT20210339B]