Research on the Multiple Small Target Detection Methodology in Remote Sensing.

This study focuses on advancing the field of remote sensing image target detection, addressing challenges such as small target detection, complex background handling, and dense target distribution. We propose solutions based on enhancing the YOLOv7 algorithm. Firstly, we improve the multi-scale feature enhancement (MFE) method of YOLOv7, enhancing its adaptability and precision in detecting small targets and complex backgrounds. Secondly, we design a modified YOLOv7 global information DP-MLP module to effectively capture and integrate global information, thereby improving target detection accuracy and robustness, especially in handling large-scale variations and complex scenes. Lastly, we explore a semi-supervised learning model (SSLM) target detection algorithm incorporating unlabeled data, leveraging information from unlabeled data to enhance the model's generalization ability and performance. Experimental results demonstrate that despite the outstanding performance of YOLOv7, the mean average precision (MAP) can still be improved by 1.9%. Specifically, under testing on the TGRS-HRRSD-Dataset, the MFE and DP-MLP models achieve MAP values of 93.4% and 93.1%, respectively. Across the NWPU VHR-10 dataset, the three models achieve MAP values of 93.1%, 92.1%, and 92.2%, respectively. Significant improvements are observed across various metrics compared to the original model. This study enhances the adaptability, accuracy, and generalization of remote sensing image object detection.

MJ-GAN: Generative Adversarial Network with Multi-Grained Feature Extraction and Joint Attention Fusion for Infrared and Visible Image Fusion.

The challenging issues in infrared and visible image fusion (IVIF) are extracting and fusing as much useful information as possible contained in the source images, namely, the rich textures in visible images and the significant contrast in infrared images. Existing fusion methods cannot address this problem well due to the handcrafted fusion operations and the extraction of features only from a single scale. In this work, we solve the problems of insufficient information extraction and fusion from another perspective to overcome the difficulties in lacking textures and unhighlighted targets in fused images. We propose a multi-scale feature extraction (MFE) and joint attention fusion (JAF) based end-to-end method using a generative adversarial network (MJ-GAN) framework for the aim of IVIF. The MFE modules are embedded in the two-stream structure-based generator in a densely connected manner to comprehensively extract multi-grained deep features from the source image pairs and reuse them during reconstruction. Moreover, an improved self-attention structure is introduced into the MFEs to enhance the pertinence among multi-grained features. The merging procedure for salient and important features is conducted via the JAF network in a feature recalibration manner, which also produces the fused image in a reasonable manner. Eventually, we can reconstruct a primary fused image with the major infrared radiometric information and a small amount of visible texture information via a single decoder network. The dual discriminator with strong discriminative power can add more texture and contrast information to the final fused image. Extensive experiments on four publicly available datasets show that the proposed method ultimately achieves phenomenal performance in both visual quality and quantitative assessment compared with nine leading algorithms.

KnotAli: informed energy minimization through the use of evolutionary information.

BACKGROUND: Improving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Homology-based methods utilize structural similarities within a family to predict the structure. However, their prediction is limited to the consensus structure, and by the quality of the alignment. Minimum free energy (MFE) based methods, on the other hand, do not rely on familial information and can predict structures of novel RNA molecules. Their prediction normally suffers from inaccuracies due to their underlying energy parameters. RESULTS: We present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes a multiple RNA sequence alignment as input and uses covariation and thermodynamic energy minimization to predict possibly pseudoknotted secondary structures for each individual sequence in the alignment. We compared KnotAli's performance to that of three other alignment-based programs, two that can handle pseudoknotted structures and one control, on a large data set of 3034 RNA sequences with varying lengths and levels of sequence conservation from 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT). CONCLUSIONS: We found KnotAli's performance to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. While both KnotAli and Cacofold use background noise correction strategies, we found KnotAli's predictions to be less dependent on the alignment quality. KnotAli can be found online at the Zenodo image: https://doi.org/10.5281/zenodo.5794719.

Insights into the stability and substrate specificity of the E. coli aerobic ß-oxidation trifunctional enzyme complex.

Degradation of fatty acids by the ß-oxidation pathway results in the formation of acetyl-CoA which enters the TCA cycle for the production of ATP. In E. coli, the last three steps of the ß-oxidation are catalyzed by two heterotetrameric α2ß2 enzymes namely the aerobic trifunctional enzyme (EcTFE) and the anaerobic TFE (anEcTFE). The α-subunit of TFE has 2E-enoyl-CoA hydratase (ECH) and 3S-hydroxyacyl-CoA dehydrogenase (HAD) activities whereas the ß-subunit is a thiolase with 3-ketoacyl-CoA thiolase (KAT) activity. Recently, it has been shown that the two TFEs have complementary substrate specificities allowing for the complete degradation of long chain fatty acyl-CoAs into acetyl-CoA under aerobic conditions. Also, it has been shown that the tetrameric EcTFE and anEcTFE assemblies are similar to the TFEs of Pseudomans fragi and human, respectively. Here the properties of the EcTFE subunits are further characterized. Strikingly, it is observed that when expressed separately, EcTFE-α is a catalytically active monomer whereas EcTFE-ß is inactive. However, when mixed together active EcTFE tetramer is reconstituted. The crystal structure of the EcTFE-α chain is also reported, complexed with ATP, bound in its HAD active site. Structural comparisons show that the EcTFE hydratase active site has a relatively small fatty acyl tail binding pocket when compared to other TFEs in good agreement with its preferred specificity for short chain 2E-enoyl-CoA substrates. Furthermore, it is observed that millimolar concentrations of ATP destabilize the EcTFE complex, and this may have implications for the ATP-mediated regulation of ß-oxidation in E. coli.

The importance of mRNA structure in determining the pathogenicity of synonymous and non-synonymous mutations in haemophilia.

INTRODUCTION: Mutational analysis is commonly used to support the diagnosis and management of haemophilia. This has allowed for the generation of large mutation databases which provide unparalleled insight into genotype-phenotype relationships. Haemophilia is associated with inversions, deletions, insertions, nonsense and missense mutations. Both synonymous and non-synonymous mutations influence the base pairing of messenger RNA (mRNA), which can alter mRNA structure, cellular half-life and ribosome processivity/elongation. However, the role of mRNA structure in determining the pathogenicity of point mutations in haemophilia has not been evaluated. AIM: To evaluate mRNA thermodynamic stability and associated RNA prediction software as a means to distinguish between neutral and disease-associated mutations in haemophilia. METHODS: Five mRNA structure prediction software programs were used to assess the thermodynamic stability of mRNA fragments carrying neutral vs. disease-associated and synonymous vs. non-synonymous point mutations in F8, F9 and a third X-linked gene, DMD (dystrophin). RESULTS: In F8 and DMD, disease-associated mutations tend to occur in more structurally stable mRNA regions, represented by lower MFE (minimum free energy) levels. In comparing multiple software packages for mRNA structure prediction, a 101-151 nucleotide fragment length appears to be a feasible range for structuring future studies. CONCLUSION: mRNA thermodynamic stability is one predictive characteristic, which when combined with other RNA and protein features, may offer significant insight when screening sequencing data for novel disease-associated mutations. Our results also suggest potential utility in evaluating the mRNA thermodynamic stability profile of a gene when determining the viability of interchanging codons for biological and therapeutic applications.

Synthesis and characterization of MFe2O4 (M = Co, Ni, Mn) magnetic nanoparticles for modulation of angiogenesis in chick chorioallantoic membrane (CAM).

In this study, we report the synthesis and characterization studies of amine-functionalized MFe2O4 (Co, Ni, Mn) nanoparticles. The synthesis process was accomplished by refluxing metal chloride precursors in ethylene glycol in the presence of sodium acetate and ethanolamine. The average crystallite sizes of the synthesized particles are found to be in the range of 8-10 nm. The synthesized particles are characterized using X-ray diffraction, Brunauer-Emmett-Teller technique, FTIR, dynamic light scattering, Raman and UV-visible spectroscopy for crystal structure, average size, surface area, pore diameter and hydrodynamic diameter, phase and functional group determination. The surface morphology and elemental composition were studied by scanning electron microscope and X-ray fluorescence respectively. Magnetic behavior up to fields of 3 T at room temperature measured in Quantum Design Physical Property Measurement System (QD PPMS) magnetometer showed the superparamagnetic behavior of these particles. Modulation of angiogenesis by the nanoparticles was studied in a chick embryo chorioallantoic membrane model by analysis of blood vessel development and effect on hemoglobin level using imaging and colorimetric methods. An enhancement in the angiogenesis compared to the saline control was observed for all the ferrite nanoparticles with a relatively optimal activity in case of CoFe2O4 nanoparticles.

Local food-based complementary feeding recommendations developed by the linear programming approach to improve the intake of problem nutrients among 12-23-month-old Myanmar children.

Poor feeding practices result in inadequate nutrient intakes in young children in developing countries. To improve practices, local food-based complementary feeding recommendations (CFR) are needed. This cross-sectional survey aimed to describe current food consumption patterns of 12-23-month-old Myanmar children (n 106) from Ayeyarwady region in order to identify nutrient requirements that are difficult to achieve using local foods and to formulate affordable and realistic CFR to improve dietary adequacy. Weekly food consumption patterns were assessed using a 12-h weighed dietary record, single 24-h recall and a 5-d food record. Food costs were estimated by market surveys. CFR were formulated by linear programming analysis using WHO Optifood software and evaluated among mothers (n 20) using trial of improved practices (TIP). Findings showed that Ca, Zn, niacin, folate and Fe were 'problem nutrients': nutrients that did not achieve 100 % recommended nutrient intake even when the diet was optimised. Chicken liver, anchovy and roselle leaves were locally available nutrient-dense foods that would fill these nutrient gaps. The final set of six CFR would ensure dietary adequacy for five of twelve nutrients at a minimal cost of 271 kyats/d (based on the exchange rate of 900 kyats/USD at the time of data collection: 3rd quarter of 2012), but inadequacies remained for niacin, folate, thiamin, Fe, Zn, Ca and vitamin B6. TIP showed that mothers believed liver and vegetables would cause worms and diarrhoea, but these beliefs could be overcome to successfully promote liver consumption. Therefore, an acceptable set of CFR were developed to improve the dietary practices of 12-23-month-old Myanmar children using locally available foods. Alternative interventions such as fortification, however, are still needed to ensure dietary adequacy of all nutrients.

Thermodynamic matchers for the construction of the cuckoo RNA family.

RNA family models describe classes of functionally related, non-coding RNAs based on sequence and structure conservation. The most important method for modeling RNA families is the use of covariance models, which are stochastic models that serve in the discovery of yet unknown, homologous RNAs. However, the performance of covariance models in finding remote homologs is poor for RNA families with high sequence conservation, while for families with high structure but low sequence conservation, these models are difficult to built in the first place. A complementary approach to RNA family modeling involves the use of thermodynamic matchers. Thermodynamic matchers are RNA folding programs, based on the established thermodynamic model, but tailored to a specific structural motif. As thermodynamic matchers focus on structure and folding energy, they unfold their potential in discovering homologs, when high structure conservation is paired with low sequence conservation. In contrast to covariance models, construction of thermodynamic matchers does not require an input alignment, but requires human design decisions and experimentation, and hence, model construction is more laborious. Here we report a case study on an RNA family that was constructed by means of thermodynamic matchers. It starts from a set of known but structurally different members of the same RNA family. The consensus secondary structure of this family consists of 2 to 4 adjacent hairpins. Each hairpin loop carries the same motif, CCUCCUCCC, while the stems show high variability in their nucleotide content. The present study describes (1) a novel approach for the integration of the structurally varying family into a single RNA family model by means of the thermodynamic matcher methodology, and (2) provides the results of homology searches that were conducted with this model in a wide spectrum of bacterial species.

SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration.

MOTIVATION: Computational RNA secondary structure prediction by free energy minimization is indispensable for analyzing structural RNAs and their interactions. These methods find the structure with the minimum free energy (MFE) among exponentially many possible structures and have a restrictive time and space complexity ( O ( n 3 ) time and O ( n 2 ) space for pseudoknot-free structures) for longer RNA sequences. Furthermore, accurate free energy calculations, including dangle contributions can be difficult and costly to implement, particularly when optimizing for time and space requirements. RESULTS: Here we introduce a fast and efficient sparsified MFE pseudoknot-free structure prediction algorithm, SparseRNAFolD, that utilizes an accurate energy model that accounts for dangle contributions. While the sparsification technique was previously employed to improve the time and space complexity of a pseudoknot-free structure prediction method with a realistic energy model, SparseMFEFold, it was not extended to include dangle contributions due to the complexity of computation. This may come at the cost of prediction accuracy. In this work, we compare three different sparsified implementations for dangle contributions and provide pros and cons of each method. As well, we compare our algorithm to LinearFold, a linear time and space algorithm, where we find that in practice, SparseRNAFolD has lower memory consumption across all lengths of sequence and a faster time for lengths up to 1000 bases. CONCLUSION: Our SparseRNAFolD algorithm is an MFE-based algorithm that guarantees optimality of result and employs the most general energy model, including dangle contributions. We provide a basis for applying dangles to sparsified recursion in a pseudoknot-free model that has the potential to be extended to pseudoknots.

Synthetic biology approach revealed enhancement in haeme oxygenase-1 gene expression by codon pair optimization while reduction by codon deoptimization.

Haem oxygenase-1 (HO-1) is a ubiquitously expressed gene involved in cellular homoeostasis, and its imbalance in expression results in various disorders. To alleviate such disorders, HO-1 gene expression needs to be modulated. Codon usage bias results from evolutionary forces acting on any nucleotide sequence and determines the gene expression. Like codon usage bias, codon pair bias also exists, playing a role in gene expression. In the present study, HO-1 gene was recoded by manipulating codon and codon pair bias, and four such constructs were made through codon/codon pair deoptimization and codon/codon pair optimization to reduce and enhance the HO-1 gene expression. Codon usage analysis was done for these constructs for four tissues brain, heart, pancreas and liver. Based on codon usage in different tissues, gene expression of these tissues was determined in terms of the codon adaptation index. Based on the codon adaptation index, minimum free energy, and translation efficiency, constructs were evaluated for enhanced or decreased HO-1 expression. The analysis revealed that for enhancing gene expression, codon pair optimization, while for reducing gene expression, codon deoptimization is efficacious. The recoded constructs developed in the study could be used in gene therapy regimens to cure HO-1 over or underexpression-associated disorders.

Combined small RNA and degradome sequencing reveals microRNA regulation during immature maize embryo dedifferentiation.

Genetic transformation of maize is highly dependent on the development of embryonic calli from the dedifferentiated immature embryo. To better understand the regulatory mechanism of immature embryo dedifferentiation, we generated four small RNA and degradome libraries from samples representing the major stages of dedifferentiation. More than 186 million raw reads of small RNA and degradome sequence data were generated. We detected 102 known miRNAs belonging to 23 miRNA families. In total, we identified 51, 70 and 63 differentially expressed miRNAs (DEMs) in the stage I, II, III samples, respectively, compared to the control. However, only 6 miRNAs were continually up-regulated by more than fivefold throughout the process of dedifferentiation. A total of 87 genes were identified as the targets of 21 DEM families. This group of targets was enriched in members of four significant pathways including plant hormone signal transduction, antigen processing and presentation, ECM-receptor interaction, and alpha-linolenic acid metabolism. The hormone signal transduction pathway appeared to be particularly significant, involving 21 of the targets. While the targets of the most significant DEMs have been proved to play essential roles in cell dedifferentiation. Our results provide important information regarding the regulatory networks that control immature embryo dedifferentiation in maize.

Decoupling the effects of nutrition, age, and behavioral caste on honey bee physiology, immunity, and colony health.

Nutritional stress, especially a dearth of pollen, has been linked to honey bee colony losses. Colony-level experiments are critical for understanding the mechanisms by which nutritional stress affects individual honey bee physiology and pushes honey bee colonies to collapse. In this study, we investigated the impact of pollen restriction on key markers of honey bee physiology, main elements of the immune system, and predominant honey bee viruses. To achieve this objective, we uncoupled the effects of behavior, age, and nutritional conditions using a new colony establishment technique designed to control size, demography, and genetic background. Our results showed that the expression of storage proteins, including vitellogenin (vg) and royal jelly major protein 1 (mrjp1), were significantly associated with nursing, pollen ingestion, and older age. On the other hand, genes involved in hormonal regulation including insulin-like peptides (ilp1 and ilp2) and methyl farnesoate epoxidase (mfe), exhibited higher expression levels in young foragers from colonies not experiencing pollen restriction. In contrast, pollen restriction induced higher levels of insulin-like peptides in old nurses. On the other hand, we found a strong effect of behavior on the expression of all immune genes, with higher expression levels in foragers. In contrast, the effects of nutrition and age were significant only the expression of the regulatory gene dorsal. We also found multiple interactions of the experimental variables on viral titers, including higher Deformed wing virus (DWV) titers associated with foraging and age-related decline. In addition, nutrition significantly affected DWV titers in young nurses, with higher titers induced by pollen ingestion. In contrast, higher levels of Black queen cell virus (BQCV) were associated with pollen restriction. Finally, correlation, PCA, and NMDS analyses proved that behavior had had the strongest effect on gene expression and viral titers, followed by age and nutrition. These analyses also support multiple interactions among genes and virus analyzed, including negative correlations between the expression of genes encoding storage proteins associated with pollen ingestion and nursing (vg and mrjp1) with the expression of immune genes and DWV titers. Our results provide new insights into the proximal mechanisms by which nutritional stress is associated with changes in honey bee physiology, immunity, and viral titers.

Pseudomonas fluorescens MFE01 uses 1-undecene as aerial communication molecule.

Bacterial communication is a fundamental process used to synchronize gene expression and collective behavior among the bacterial population. The most studied bacterial communication system is quorum sensing, a cell density system, in which the concentration of inductors increases to a threshold level allowing detection by specific receptors. As a result, bacteria can change their behavior in a coordinated way. While in Pseudomonas quorum sensing based on the synthesis of N-acyl homoserine lactone molecules is well studied, volatile organic compounds, although considered to be communication signals in the rhizosphere, are understudied. The Pseudomonas fluorescens MFE01 strain has a very active type six secretion system that can kill some competitive bacteria. Furthermore, MFE01 emits numerous volatile organic compounds, including 1-undecene, which contributes to the aerial inhibition of Legionella pneumophila growth. Finally, MFE01 appears to be deprived of N-acyl homoserine lactone synthase. The main objective of this study was to explore the role of 1-undecene in the communication of MFE01. We constructed a mutant affected in undA gene encoding the enzyme responsible for 1-undecene synthesis to provide further insight into the role of 1-undecene in MFE01. First, we studied the impacts of this mutation both on volatile organic compounds emission, using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry and on L. pneumophila long-range inhibition. Then, we analyzed influence of 1-undecene on MFE01 coordinated phenotypes, including type six secretion system activity and biofilm formation. Next, to test the ability of MFE01 to synthesize N-acyl homoserine lactones in our conditions, we investigated in silico the presence of corresponding genes across the MFE01 genome and we exposed its biofilms to an N-acyl homoserine lactone-degrading enzyme. Finally, we examined the effects of 1-undecene emission on MFE01 biofilm maturation and aerial communication using an original experimental set-up. This study demonstrated that the ΔundA mutant is impaired in biofilm maturation. An exposure of the ΔundA mutant to the volatile compounds emitted by MFE01 during the biofilm development restored the biofilm maturation process. These findings indicate that P. fluorescens MFE01 uses 1-undecene emission for aerial communication, reporting for the first time this volatile organic compound as bacterial intraspecific communication signal.

Primary Failure Eruption: Genetic Investigation, Diagnosis and Treatment: A Systematic Review.

AIM: The aim of this systematic review is to explore the pathology, diagnosis, treatment, and genetic basis of Primary Failure of Eruption (PFE) in the field of pediatric dentistry and orthodontics. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed for this review. The databases PubMed, Science Direct, Scopus, and Web of Science were searched from 1 July 2013 to 1 July 2023, using keywords "primary failure of tooth eruption" OR "primary failure of eruption" OR "tooth eruption failure" OR "PFE" AND "orthodontics". The study selection process involved screening articles based on the inclusion and exclusion criteria. RESULTS: A total of 1151 results were obtained from the database search, with 14 papers meeting the inclusion criteria. The review covers various aspects of PFE, including its clinical features, diagnosis, treatment options, and genetic associations with mutations in the PTH1R gene. Differentiation between PFE and Mechanical Failure of Eruption (MFE) is crucial for accurate treatment planning. Orthodontic and surgical interventions, along with multidisciplinary approaches, have been employed to manage PFE cases. Genetic testing for PTH1R mutations plays a significant role in confirming the diagnosis and guiding treatment decisions, although some cases may not be linked to this mutation. CONCLUSIONS: This systematic review provides valuable insights into the diagnosis, treatment, and genetic basis of PFE. Early diagnosis and personalized treatment planning are crucial for successful management. Genetic testing for PTH1R mutations aids in accurate diagnosis and may influence treatment decisions. However, further research is needed to explore the complex genetic basis of PFE fully and improve treatment outcomes for affected individuals.

Rapid degradation of tetracycline in aqueous solution by Fe/Cu catalysis enhanced by H2O2 activation.

Tetracycline (TC) is widely detected in the environment because of its abuse and persistence. There is an urgent need to efficiently treat TC due to its potential threat to the ecosystem and human health. In this study, microscale Fe/Cu bimetallic particles' (mFe/Cu) catalysis enhanced by H2O2 was proposed to remove TC in an aqueous solution. Based on the pre-experiment, the effect of theoretical Cu mass loading (TMLCu) and some key operating parameters on the TC removal efficiency were investigated thoroughly. The degradation rates of TC by mFe/Cu with different TMLCu followed the pseudo-first-order kinetics model, and the optimal TMLCu (0.34 g Cu/g Fe) was obtained. The optimal operating parameters of mFe/Cu dosage, concentration of H2O2, initial concentration of TC, stirring speed and operating temperature were 5 g/L, 50 mM, 50 ppm, 400 r/min, and 55°C, respectively. Compared with the control system, the system of mFe/Cu catalysis enhanced by H2O2 (mFe/Cu-H2O2) presented excellent performance due to its synergistic effect. Also, the fresh and reacted mFe/Cu was characterized by scanning electron microscope, which showed the surface of mFe/Cu was rougher after reaction, indicating mFe/Cu participated in the degradation reaction. Besides, with the presence of inorganic anions, the degradation of TC in mFe/Cu-H2O2 system did not change much. And mFe/Cu presented good stability and recyclability after 10 repeated tests. Therefore, mFe/Cu-H2O2 system had a great potential for cost-effective removal of antibiotics in wastewater.

Analysis of the Compositional Features and Codon Usage Pattern of Genes Involved in Human Autophagy.

Autophagy plays an intricate role in paradigmatic human pathologies such as cancer, and neurodegenerative, cardiovascular, and autoimmune disorders. Autophagy regulation is performed by a set of autophagy-related (ATG) genes, first recognized in yeast genome and subsequently identified in other species, including humans. Several other genes have been identified to be involved in the process of autophagy either directly or indirectly. Studying the codon usage bias (CUB) of genes is crucial for understanding their genome biology and molecular evolution. Here, we examined the usage pattern of nucleotide and synonymous codons and the influence of evolutionary forces in genes involved in human autophagy. The coding sequences (CDS) of the protein coding human autophagy genes were retrieved from the NCBI nucleotide database and analyzed using various web tools and software to understand their nucleotide composition and codon usage pattern. The effective number of codons (ENC) in all genes involved in human autophagy ranges between 33.26 and 54.6 with a mean value of 45.05, indicating an overall low CUB. The nucleotide composition analysis of the autophagy genes revealed that the genes were marginally rich in GC content that significantly influenced the codon usage pattern. The relative synonymous codon usage (RSCU) revealed 3 over-represented and 10 under-represented codons. Both natural selection and mutational pressure were the key forces influencing the codon usage pattern of the genes involved in human autophagy.

Can Dairy Slurry Application to Stubble, without Incorporation into the Soil, Be Sustainable?

In many countries, livestock slurry must be injected or incorporated into the soil to reduce nitrogen losses. However, when the injection is not feasible, farmers adopting conservation practices discard the use of slurry as fertilizer. New approaches related to slurry treatment or application management can stimulate the use of slurry in conservation agriculture (CA). This study aimed to evaluate the agronomic effects of some new management strategies to use dairy slurry for fertilization of ryegrass grown on stubble-covered soil, using as reference standard practices (slurry injection and mineral fertilizer application). The following treatments were considered: (i) bare soil: control (CB), mineral fertilizer (MB), injection (IN); (ii) stubble: control (CS), acidified dairy slurry (ADS), raw dairy slurry (RDS), irrigation following RDS (IR), mineral fertilizer (MS), RDS placed under the stubble (US), raw slurry applied 16 days after sowing (RDS T16). Effects on ryegrass yield, apparent nutrient recovery (ANR) and soil chemical properties were assessed. ADS reached 94% equivalence to MS and performed similarly to IN for productivity, ANR and soil parameters showing to be a sustainable alternative to replace mineral nitrogen and a potential solution to enable dairy slurry application in CA without injection or incorporation into the soil.

Design of a Toolbox of RNA Thermometers.

RNA thermometers are RNA regulatory elements that convert temperature into a functional biological response through a temperature-induced conformational change. These regulatory elements have been investigated in numerous natural contexts and have been designed for synthetic biology as well. A basic challenge has been the design of an RNA thermometer whose final activity in response to temperature matches a prespecified response, in terms of its sensitivity, threshold, and leakiness. This chapter provides a methodology for the design of a toolbox of RNA thermometers. We describe considerations for the conceptual design, a computational assessment, and strategies for experimental synthesis and measurement.

Effect of insilico predicted and designed potential siRNAs on inhibition of SARS-CoV-2 in HEK-293 cells.

Objectives: The COVID-19 was identified for the first time from the sea food market, Wuhan city, China in 2019 and the pathogenic organism was identified as SARS-CoV-2. Currently, this virus has spread to 223 countries and territories and known as a serious issue for the global human community. Many vaccines have been developed and used for immunization. Methods: We have reported the insilico prediction, designing, secondary structure prediction, molecular docking analysis, and in vitro assessment of siRNAs against SARS-CoV-2. The online bioinformatic approach was used for siRNAs selection and designing. The selected siRNAs were evaluated for antiviral efficacy by using Lipofectamine 2000 as delivery agent to HEK-293 cells. The MTT assay was used for cytotoxicity determination. The antiviral efficacy of potential siRNAs was determined based on the Ct value of q-RT-PCR and the data analysis was done by Prism-GraphPad software. Results: The analyzed data resulted in the selection of only three siRNAs out of twenty-six siRNAs generated by online software. The secondary structure prediction and molecular docking analysis of siRNAs revealed the efficient binding to the target. There was no cellular toxicity observed in the HEK-293 cells at any tested concentrations of siRNAs. The purification of RNA was completed from inoculated cells and subjected to q-RT-PCR. The highest Ct value was observed in siRNA 3 than the others. The results offered valuable evidence and invigorated us to assess the potency of siRNAs by using alone or in combination in other human cells. Conclusion: The data generated from this study indicates the significance of in silico prediction and narrow down the potential siRNA' against SARS-CoV-2, and molecular docking investigation offered the effective siRNAs binding with the target. Finally, it is concluded that the online bioinformatics approach provided the prediction and selection of siRNAs with better antiviral efficacy. The siRNA-3 was observed to be the best for reduction of viral RNA in cells.

Toehold switch based biosensors for sensing the highly trafficked rosewood Dalbergia maritima.

Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains, from pathogen detection to single cell transcriptomics analysis. The many applications of nucleic acid detection and identification are mostly carried out by PCR techniques, sequencing, and their derivatives used at large scale. However, these methods' limitations on speed, cost, complexity and specificity have motivated the development of innovative detection methods among which nucleic acid biosensing technologies seem promising. Toehold switches are a particular class of RNA sensing devices relying on a conformational switch of secondary structure induced by the pairing of the detected trigger RNA with a de novo designed synthetic sensing mRNA molecule. Here we describe a streamlined methodology enabling the development of such a sensor for the RNA-mediated detection of an endangered plant species in a cell-free reaction system. We applied this methodology to help identify the rosewood Dalbergia maritima, a highly trafficked wood, whose protection is limited by the capacity of the authorities to distinguish protected logs from other unprotected but related species. The streamlined pipeline presented in this work is a versatile framework enabling cheap and rapid development of new sensors for custom RNA detection.