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Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity 1 – 4 . Sparse taxon sampling has previously been proposed to confound phylogenetic inference 5 , and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families—including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confidently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specific variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will offer new perspectives on evolutionary processes in cross-species comparative analyses and assist in efforts to conserve species. A dataset of the genomes of 363 species from the Bird 10,000 Genomes Project shows increased power to detect shared and lineage-specific variation, demonstrating the importance of phylogenetically diverse taxon sampling in whole-genome sequencing.

Information on a study which investigates the effects of Zelnate, a DNA immunostimulant, administered to calves upon arrival, on morbidity and mortality, growth performance, and producer costs is presented. Crossbred male beef calves (steers and bulls) were acquired from multiple auction markets and transported to the University of Arkansas stocker unit for a 42-d backgrounding period. Calves were randomly allocated to chute side into treatment groups: 1) Control (CON) in which no immunostimulant was administered or 2) Zelnate (ZEL), DNA immunostimulant administered. Animals were checked daily for signs of morbidity and treated with preplanned antibiotics. Records for morbidity and mortality were kept in addition to body temperature, clinical score, and body weight at the time of treatment.

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain’s base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system’s potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.

In this study, the photophysical properties of thin films of an Eu3+ dye, namely europium tetrakis(dibenzoylmethide) triethylammonium (EuD4TEA), within deoxyribonucleic acid (DNA) biopolymer functionalized with hexadecyltrimethylammonium chloride (CTMA) were extensively investigated and compared with those of thin films of the same dye embedded in more conventional polymers, like poly(methyl methacrylate) and polycarbonate. The new materials obtained have good optical properties, as shown by their absorption and emission spectra. Remarkably, a large enhancement in photoluminescence was observed upon the interaction of EuD4TEA with DNA-CTMA (2- and 17-fold increase in luminescence quantum yield with respect to PMMA and PC). Photophysical analyses suggest that the emission enhancement was mainly due to the increase in the sensitization efficiency (ηsens) from the ligands to the Eu3+ ion along with the suppression of the vibrational deactivation upon immobilization onto the DNA-CTMA matrix, as the concentration of the complex increased from 20 to 50%. These phenomena are primarily driven by the transformation of the Eu3+ micro-environments, which are created by the interactions between complex ligands and the DNA-CTMA matrix.

The deoxyribonucleic acid (DNA) damage response (DDR) is a major feature in the maintenance of genome integrity and in the suppression of tumorigenesis. PALB2 (Partner and Localizer of Breast Cancer 2 (BRCA2)) plays an important role in maintaining genome integrity through its role in the Fanconi anemia (FA) and homologous recombination (HR) DNA repair pathways. Since its identification as a BRCA2 interacting partner, PALB2 has emerged as a pivotal tumor suppressor protein associated to hereditary cancer susceptibility to breast and pancreatic cancers. In this review, we discuss how other DDR proteins (such as the kinases Ataxia Telangiectasia Mutated (ATM) and ATM- and Rad3-Related (ATR), mediators BRCA1 (Breast Cancer 1)/BRCA2 and effectors RAD51/DNA Polymerase η (Polη) interact with PALB2 to orchestrate DNA repair. We also examine the involvement of PALB2 mutations in the predisposition to cancer and the role of PALB2 in stimulating error-free DNA repair through the FA/HR pathway.

Transcription factors (TFs) are fundamental regulators of gene expression and perform diverse functions in cellular processes. The management of 3-dimensional (3D) genome conformation and gene expression relies primarily on TFs. TFs are crucial regulators of gene expression, performing various roles in biological processes. They attract transcriptional machinery to the enhancers or promoters of specific genes, thereby activating or inhibiting transcription. Identifying these TFs is a significant step towards understanding cellular gene expression mechanisms. Due to the time-consuming and labor-intensive nature of experimental methods, the development of computational models is essential. In this work, we introduced a two-layer prediction framework based on a support vector machine (SVM) using the latent space representation of a protein language model, ProtBert. The first layer of the method reliably predicts and identifies transcription factors (TFs), and in the second layer, the proposed method predicts and identifies transcription factors that prefer binding to methylated deoxyribonucleic acid (TFPMs). In addition, we also tested the proposed method on an imbalanced database. In detecting TFs and TFPMs, the proposed model consistently outperformed state-of-the-art approaches, as demonstrated by performance comparisons via empirical cross-validation analysis and independent tests.

A novel color image encryption algorithm based on dynamic deoxyribonucleic acid (DNA) encoding and chaos is presented. A three-neuron fractional-order discrete Hopfield neural network (FODHNN) is employed as a pseudo-random chaotic sequence generator. Its initial value is obtained with the secret key generated by a five-parameter external key and a hash code of the plain image. The external key includes both the FODHNN discrete step size and order. The hash is computed with the SHA-2 function. This ensures a large secret key space and improves the algorithm sensitivity to the plain image. Furthermore, a new three-dimensional projection confusion method is proposed to scramble the pixels among red, green, and blue color components. DNA encoding and diffusion are used to diffuse the image information. Pseudo-random sequences generated by FODHNN are employed to determine the encoding rules for each pixel and to ensure the diversity of the encoding methods. Finally, confusion II and XOR are used to ensure the security of the encryption. Experimental results and the security analysis show that the proposed algorithm has better performance than those reported in the literature and can resist typical attacks.

Interfacial assembly has been intensively investigated in fabricating biomaterials and nanodevices for various applications. Recently, due to the precise sequence programmability, unique molecular recognition ability, and good biocompatibility, deoxyribonucleic acid (DNA) has been explored as superior building blocks to assemble at bio-interface for manipulating biological entities. To the best of our knowledge, the advances in this area have not been systematically summarized. To provide an overview of the area, in this review, the recently developed DNA assembly strategies on bio-interfaces were well summarized, and their representative works are exampled to illustrate how to rationally and elaborately design DNA molecules to realize functional integration and emerging of novel biological functionalities with high controllability and programmability. Furthermore, the biomedical applications of DNA assembly at bio-interface are categorially elaborated. The fascinating and unique advantages of DNA assembly systems are fully discussed in the exemplified applications to show the distinguished perspective of DNA in the future development. At the end of this review, the current limitations and challenges in applications and potential improvement strategies for DNA assembly at bio-interface are fully discussed. The future development direction is deliberated. We envision that this review will help scientists in the interdisciplinary fields gain a more comprehensive understanding of the DNA assembly at bio-interface, and therefore jointly promote the advances in this field.

Nowadays, digital medical images have become an essential source for the grand success of e-health technology. At the same time, the massive storage also plays a vital role. One of cloud storage’s main objectives is the affordable and easily accessible storage of vast amounts of multi-structured data. The cloud paradigm gives an illusion of infinite storage of data. The future of Cyber-Physical Systems (CPS) relies upon technologies like cloud computing to thrive. However, the major lacuna is data security. This paper deals with the Confidentiality Integrity Availability (CIA) aspects required for cloud-based medical image repositories. Since it is for the medical image, the Region of Interest (RoI) is separated, and the integrity check is applied for RoI. A two-tier security for the medical image has been proposed, including an additional security layer for RoI. A 3-D Lorenz chaotic attractor has been used to generate the key where the keyspace is widely increased. Deoxyribonucleic Acid (DNA) based image diffusion in different stages of cryptosystem offered an average entropy of 7.98042 and a correlation of 0.002864 for RoI only and for ciphered medical image an average entropy of 7.99724 and a correlation of − 0.00063. Text encryption is performed over metadata to ensure the privacy of client authentication. Encrypted metadata and 320 bits have been generated for the RoI part embedded in an image’s Non-Region of Interest (NRoI) part in the random pixel indexes obtained using a 1D Tent map. This proposed approach also gives a Graphical User Interface developed using Python 3.8 to support non-technical persons or medical practitioners. The proposed security framework provides a complete CIA triad for medical image repositories in the cloud.