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.

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.

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.

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.

Computational identification and characterization of conserved miRNAs and their target genes in garlic (Allium sativum L.) expressed sequence tags

The endogenous small non-coding functional microRNAs (miRNAs) are short in size, range from ~21 to 24 nucleotides in length, play a pivotal role in gene expression in plants and animals by silencing genes either by destructing or blocking of translation of homologous mRNA. Although various high-throughput, time consuming and expensive techniques like forward genetics and direct cloning are employed to detect miRNAs in plants but comparative genomics complemented with novel bioinformatic tools pave the way for efficient and cost-effective identification of miRNAs through homologous sequence search with previously known miRNAs. In this study, an attempt was made to identify and characterize conserved miRNAs in garlic expressed sequence tags (ESTs) through computational means. For identification of novel miRNAs in garlic, a total 3227 known mature miRNAs of plant kingdom Viridiplantae were searched for homology against 21,637 EST sequences resulting in identification of 6 potential miRNA candidates belonging to 6 different miRNA families. The psRNATarget server predicted 33 potential target genes and their probable functions for the six identified miRNA families in garlic. Most of the garlic miRNA target genes seem to encode transcription factors as well as genes involved in stress response, metabolism, plant growth and development. The results from the present study will shed more light on the understanding of molecular mechanisms of miRNA in garlic which may aid in the development of novel and precise techniques to understand some post-transcriptional gene silencing mechanism in response to stress tolerance.

Identification and characterization of microRNAs in the crab-eating macaque (Macaca fascicularis) using transcriptome analysis

MicroRNAs (miRNAs), with an average length between 16 nt and 26 nt, are small non-coding RNAs that can repress gene expression on the post-transcriptional level. Macaca fascicularis (M. fascicularis), one of the most important nonhuman primate animal models, is widely used in basic and applied preclinical research, especially in studies that involve neuroscience and disease. However, due to the lack of a complete genome sequence, the miRNAs in M. fascicularis have not been completely characterized. In this study, 86 putative M. fascicularis miRNAs were identified using a strategy of our design. The expression of some of these miRNAs in the tissue was confirmed by qRT-PCR. The function and pathway of their targeted genes were analyzed to reveal the potential relevance of miRNA regulation on diseases and physiological processes. The current study provides insight into potential miRNAs and forms a useful knowledge base for the future understanding of the function of miRNAs in M. fascicularis.

Profiling microRNAs and their targets in an important fleshy fruit: tomato (Solanum lycopersicum)

Tomato (Solanum lycopersicum) is an important and the most useful plant based diet. It is widely used for its antioxidant property. Presently, only two digits, tomato microRNAs (miRNAs) are reported in miRBase: a miRNA database. This study is aimed to profile and characterize more miRNAs and their targets in tomato. A comprehensive comparative genomic approach is applied and a total of 109 new miRNAs belonging to 106 families are identified and characterized from the tomato expressed sequence tags (ESTs). All these potential miRNAs are profiled for the first time in tomato. The profiled miRNAs are also observed with stable stem-loop structures (Precursor-miRNAs), whose length ranges from 45 to 329 nucleotides (nt) with an average of 125 nt. The mature miRNAs are found in the stem of pre-miRNAs and their length ranges from 19 to 24 nt with an average of 21 nt. Furthermore, twelve miRNAs are randomly selected and experimentally validated through RT-PCR. A total of 406 putative targets are also predicted for the newly 109 tomato miRNAs. These targets are involved in structural protein, metabolism, transcription factor, growth & development, stress related, signaling pathways, storage proteins and other vital processes. Some important proteins like; 9-cisepoxycarotenoid dioxygenase (NCED), transcription factor MYB, ATP-binding cassette transporters, terpen synthase, 14-3-3 and TIR-NBS proteins are also predicted as putative targets for tomato miRNAs. These findings improve a baseline data of miRNAs and their targets in tomato. This baseline data can be utilized to fine tune this important fleshy fruit for nutritional & antioxidant properties and also under biotic & abiotic stresses.

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.

Association of perceived health and depression with older adults' subjective memory complaints: contrasting a specific questionnaire with general complaints questions

The objectives of this paper were to evaluate the association of subjective memory complaints (SMC) with perceived state of health, mood and episodic memory (associative and everyday memory). We studied these areas using two different complaint assessment methods (three general questions and a validated scale). The study included 269 older adults (aged 65-87) with age-related memory changes, but without cognitive impairment. They were evaluated with Mini-cognitive Exam, Rivermead Behavioural Memory Test (a test of everyday memory), Paired Associates Learning Test, Memory Failures of Everyday Questionnaire, three memory complaints questions, Nottingham Health Profile and Geriatric Depression Scale. The results indicated that memory for everyday performance, mood and perceived health were independent predictors of SMC, with mood and perceived health being stronger predictors than actual memory performance. Age was not associated with subjective memory and, with regard to level of education, only the illiterate level was associated with SMC. A specific questionnaire on subjective memory was found to be preferable to an aggregate of complaints questions on self-reported memory; only health profile was found to predict the outcomes on memory complaints questions. Our conclusion is that a group of underlying factors other than everyday memory were playing a role in SMC; these SMC of subjects with age-related memory changes were mainly associated with subjective evaluations of their health.

A new Atp2b2 deafwaddler allele, dfw(i5), interacts strongly with Cdh23 and other auditory modifiers

Tight regulation of calcium (Ca2+) concentrations in the stereocilia bundles of auditory hair cells of the inner ear is critical to normal auditory transduction. The plasma membrane Ca2+ ATPase 2 (PMCA2), encoded by the Atp2b2 gene, is the primary mechanism for clearance of Ca2+ from auditory stereocilia, keeping intracellular levels low, and also contributes to maintaining adequate levels of extracellular Ca2+ in the endolymph. This study characterizes a novel null Atp2b2 allele, dfw(i5), by examining cochlear anatomy, vestibular function and auditory physiology in mutant mice. Loss of auditory function in PMCA2 mutants can be attributed to dysregulation of intracellular Ca2+ inside the stereocilia bundles. However, extracellular Ca2+ ions surrounding the stereocilia are also required for rigidity of cadherin 23, a component of the stereocilia tip-link encoded by the Cdh23 gene. This study further resolves the interaction between Atp2b2 and Cdh23 in a gene dosage and frequency-dependent manner, and finds that low frequencies are significantly affected by the interaction. In +/dfw(i5) mice, one mutant copy of Cdh23 is sufficient to cause broad frequency hearing impairment. Additionally, we report another modifying interaction with Atp2b2 on auditory sensitivity, possibly caused by an unidentified hearing loss gene in mice.