Adaptation Index Research Articles

Selection on synonymous codon usage in soybean (Glycine max) WRKY genes

The WRKY transcription factor gene family in soybean [Glycine max (L.) Merr.] (GmWRKY) is critical for the plant’s development and stress responses. This study examines the evolutionary dynamics of the GmWRKY gene family, focusing on its synonymous codon usage bias (CUB) in a comprehensive set of 179 coding sequences. CUB was analyzed using various indices, revealing a preference for A/T-ending codons and relatively low codon bias. Codon adaptation index (CAI) analysis suggested that these genes are optimized for efficient translation despite relatively low bias, reflecting a balance between codon diversity and translation efficiency. Neutrality and NC plots indicated that selective forces dominate over mutational forces in shaping codon usage, while selection signature analysis showed purifying selection being prevalent across the gene family. However, episodic positive selection was also detected in certain clades, highlighting potential adaptive diversification in response to environmental stress. Additionally, promoter binding site analysis uncovered correlations between codon usage and transcriptional regulation, indicating a context-dependent relationship between CUB and gene expression. Phylogenetic analysis identified 11 well-supported clades in the modern GmWRKY gene family and ancestral sequence reconstruction revealed more relaxed codon preferences and reduced selection constraints in modern GmWRKY genes, potentially linked to neofunctionalization and adaptation to environmental changes. These findings provide a framework for optimizing gene expression in transgenic soybean crops with resilience. Further functional validation of positively selected genes is recommended to elucidate their role in stress responses.

Bridging One Health: Computational design of a multi-epitope messenger RNA vaccine for cross-species immunization against Nipah virus

Background and Aim: Nipah virus (NiV) poses a threat to human and animal health, particularly swine, which serve as primary vectors for human transmission. Despite its severe risks, no NiV vaccine currently exists for humans or animal hosts; thus, innovative vaccine development approaches that address cross-species transmission are required. This study was computationally designed to evaluate a multi-epitope messenger RNA (mRNA) vaccine targeting NiV for human and swine immunization. Materials and Methods: B and T lymphocyte epitopes were identified from NiV structural proteins using multiple epitope prediction tools. All epitopes were linked to form a multi-epitope construct, and various adjuvant combinations were analyzed for physicochemical properties and immune simulation. Molecular docking and dynamics were employed to visualize the construct’s interaction with a host immune receptor. Signal peptides were added to the construct, and mRNA sequences were generated using LinearDesign. The minimum free energies (MFEs) and codon adaptation indices (CAI) were used to select the final mRNA sequence of the vaccine construct. Results: Computational tools predicted 10 epitopes within NiV structural proteins that can be recognized by human and swine immune receptors. The construct with β-defensin 2 adjuvant was selected as the final immunogenic region after showing favorable immunogenicity profiles and physicochemical properties. The final vaccine sequence had higher MFE and CAI compared to the BioNTech/Pfizer BNT162b2 and Moderna mRNA-1273 vaccines. Conclusion: The multi-epitope mRNA vaccine designed in this study shows promising results as a potential NiV vaccine candidate. Further in vivo and in vitro studies are required to confirm the efficacy. Keywords: computational design, cross-species immunization, messenger RNA vaccine, multi-epitope, Nipah virus.

Comprehensive Analysis of Codon Usage Bias in Human Papillomavirus Type 51.

Human papillomavirus type 51 (HPV-51) is associated with various cancers, including cervical cancer. Examining the codon usage bias of the organism can offer valuable insights into its evolutionary patterns and its relationship with the host. This study comprehensively analyzed codon usage bias in HPV-51 by examining 64 complete genome sequences sourced from the NCBI GenBank database. Our analysis revealed no noteworthy preference for codon usage in HPV-51 overall. However, there was a noticeable bias towards A/T-ending codons, accompanied by GC3s below 32%. Dinucleotide frequency analysis revealed reduced frequencies for ApA, CpG, and TpC dinucleotides, while CpA and TpG dinucleotides were more frequent than others. Relative Synonymous Codon Usage analysis revealed 30 favored codons, primarily concluding with A/T nucleotides. Further analysis using Parity Rule 2, Effective Number of Codons plot, and neutrality plot indicated a balance between mutational pressure and natural selection, with natural selection being the primary force shaping codon usage bias. The Isoacceptor tRNA Pool analysis indicates that HPV-51 has a higher translation efficiency within the human cellular translational system. Moreover, the Codon Adaptation Index and Relative Codon Deoptimization Index analyses suggested a moderate adaptation of HPV-51 to human codon preferences. Our discoveries offer valuable perspectives on how HPV-51 evolves and uses genetic codes, contributing to a deeper comprehension of its endurance and disease-causing potential.

Novel dual-pathogen multi-epitope mRNA vaccine development for Brucella melitensis and Mycobacterium tuberculosis in silico approach.

Brucellosis and Tuberculosis, both of which are contagious diseases, have presented significant challenges to global public health security in recent years. Delayed treatment can exacerbate the conditions, jeopardizing patient lives. Currently, no vaccine has been approved to prevent these two diseases simultaneously. In contrast to traditional vaccines, mRNA vaccines offer advantages such as high efficacy, rapid development, and low cost, and their applications are gradually expanding. This study aims to develop multi-epitope mRNA vaccines argeting Brucella melitensis and Mycobacterium tuberculosis H37Rv (L4 strain) utilizing immunoinformatics approaches. The proteins Omp25, Omp31, MPT70, and MPT83 from the specified bacteria were selected to identify the predominant T- and B-cell epitopes for immunological analysis. Following a comprehensive evaluation, a vaccine was developed using helper T lymphocyte epitopes, cytotoxic T lymphocyte epitopes, linear B-cell epitopes, and conformational B-cell epitopes. It has been demonstrated that multi-epitope mRNA vaccines exhibit increased antigenicity, non-allergenicity, solubility, and high stability. The findings from molecular docking and molecular dynamics simulation revealed a robust and enduring binding affinity between multi-epitope peptides mRNA vaccines and TLR4. Ultimately, Subsequently, following the optimization of the nucleotide sequence, the codon adaptation index was calculated to be 1.0, along with an average GC content of 54.01%. This indicates that the multi-epitope mRNA vaccines exhibit potential for efficient expression within the Escherichia coli(E. coli) host. Analysis through immune modeling indicates that following administration of the vaccine, there may be variation in immunecell populations associated with both innate and adaptive immune reactions. These types encompass helper T lymphocytes (HTL), cytotoxic T lymphocytes (CTL), regulatory T lymphocytes, natural killer cells, dendritic cells and various immune cell subsets. In summary, the results suggest that the newly created multi-epitope mRNA vaccine exhibits favorable attributes, offering novel insights and a conceptual foundation for potential progress in vaccine development.

Host-dependent C-to-U RNA editing in SARS-CoV-2 creates novel viral genes with optimized expressibility.

Rampant C-to-U RNA editing drives the mutation and evolution of SARS-CoV-2. While much attention has been paid to missense mutations, the C-to-U events leading to AUG and thus creating novel ORFs were uninvestigated. By utilizing the public time-course mutation data from the worldwide SARS-CoV-2 population, we systematically identified the "AUG-gain mutations" caused by C-to-U RNA editing. Synonymous mutations were of special focus. A total of 58 synonymous C-to-U sites are able to create out-of-frame AUG in coding sequence (CDS). These 58 synonymous sites showed significantly higher allele frequency (AF) and increasing rate (dAF/dt) than other C-to-U synonymous sites in the SARS-CoV-2 population, suggesting that these 58 AUG-gain events conferred additional benefits to the virus and are subjected to positive selection. The 58 predicted new ORFs created by AUG-gain events showed the following advantages compared to random expectation: they have longer lengths, higher codon adaptation index (CAI), higher Kozak scores, and higher tRNA adaptation index (tAI). The 58 putatively novel ORFs have high expressibility and are very likely to be functional, providing an explanation for the positive selection on the 58 AUG-gain mutations. Our study proposed a possible mechanism of the emergence of de novo genes in SARS-CoV-2. This idea should be helpful in studying the mutation and evolution of SARS-CoV-2.

Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst.

Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner's mental state in real-time, resulting in less optimized learning experiences. This research aimed to explore the effect on the learning experience of a novel EEG-based Brain-Computer Interface (BCI) that adjusts the speed of information presentation in real-time during a learning task according to the learner's cognitive load. We also explored how motivation moderated these effects. In accordance with three experimental groups (non-adaptive, adaptive, and adaptive with motivation), participants performed a calibration task (n-back), followed by a memory-based learning task concerning astrological constellations. Learning gains were assessed based on performance on the learning task. Self-perceived mental workload, cognitive absorption and satisfaction were assessed using a post-test questionnaire. Between-group analyses using Mann-Whitney tests suggested that combining BCI and motivational factors led to more significant learning gains and an improved learning experience. No significant difference existed between the BCI without motivational factor and regular non-adaptive interface for overall learning gains, self-perceived mental workload, and cognitive absorption. However, participants who undertook the experiment with an imposed learning pace reported higher overall satisfaction with their learning experience and a higher level of temporal stress. Our findings suggest BCI's potential applicability and feasibility in improving memorization-based learning experiences. Further work should seek to optimize the BCI adaptive index and explore generalizability to other learning contexts.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species.

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

Full-field amplitude speckle decorrelation angiography.

We propose a new simple and cost-effective optical imaging technique, full-field amplitude speckle decorrelation angiography (FASDA), capable of visualizing skin microvasculature with high resolution, and sensitive to small, superficial vessels with slow blood flow and larger, deeper vessels with faster blood flow. FASDA makes use of a laser source with limited temporal coherence, can be implemented with cameras with conventional frame rates, and does not require raster scanning. The proposed imaging technique is based on the simultaneous evaluation of two metrics: the blood flow index, a contrast-based metric used in laser speckle contrast imaging, and the adaptive speckle decorrelation index (ASDI), a new metric that we defined based on the second-order autocorrelation function that considers the limited speckle modulation that occurs in partially-coherent imaging. We demonstrate excellent delineation of small, superficial vessels with slow blood flow in skin nevi using ASDI and larger, deeper vessels with faster blood flow using BFI, providing a powerful new tool for the imaging of microvasculature with significantly lower hardware complexity and cost than other optical imaging techniques.

Comparative analyses of plastomes in Allaeanthus and Malaisia: structure, evolution, and phylogeny.

The small genera Allaeanthus and Malaisia within the Moraceae have important edible, medicinal, and economic value. However, complete plastome blueprints and a well-resolved evolutionary history of these two genera are still lack, thereby limiting their conservation and application. The recent discovery of a new distribution of Allaeanthus kurzii in Hainan, China, marked by the collection of two unique samples, alongside three samples of Malaisia scandens, has opened new avenues for research. This study aimed to compare the Allaeanthus and Malaisia plastomes of Hainan Province samples with those of samples from other regions, focusing on plastome structure, codon usage bias, natural selection, and the evolutionary history of A. kurzii and M. scandens. The results showed that both species had a quadripartite plastome structure, with sizes ranging from 162,134 to 162,170bp for A. kurzii and 161,235 to 162,134bp for M. scandens. Both species displayed loss of the infA gene and reduction of the rpl22 gene. Two highly variable regions (petD-trnD-GUC and rpl20-clpP) and three highly variable genes (rpl20, petB, and rpl16) were identified in A. kurzii, while two highly variable regions (ycf2-ndhB and ccsA-ndhE) and three highly variable genes (psbT, rpl36, and ycf2) were found in M. scandens. The protein-coding sequences (CDSs) of the Allaeanthus and Malaisia plastomes exhibited similar patterns of adaptive indices and codon usage frequencies. The genes associated with photosynthesis underwent strong purifying selection. Phylogenetic analysis revealed that Allaeanthus, Broussonetia, and Malaisia constituted a monophyletic group, with Malaisia being more closely related to Broussonetia. Broussonetia diversified approximately 19.78 million years ago, Malaisia approximately 4.74 million years ago, and Allaeanthus approximately 16.18 million years ago. These new plastome-based discoveries will guide conservation planners and medicinal plant breeders and genetic resource development for these species in the region.

Rhizosphere bacterial community influence on <i>Deschampsia antarctica</i> È Desv. adaptability in context of temperature near plants in local spatial scales of Galindez Island, Argentine Islands (the maritime Antarctic)

The effect of rhizosphere bacterial community index (Irbi) influence on the nine populations of Antarctic hair grass (Deschampsia antarctica) adaptability was studied in the Galindez Island (summer season 2017/18). Moreover, the corresponding influence indices Irbi (i=1÷9) and Irbpi (p=1÷5 for the most common bacteria) were evaluated as well. The objective was to compare the Irbi and Irbpi series with the united temperature influence index on plant populations (It1i(z)) series and the united quality latent index of adaptability Iq1i. The study used data on the rhizosphere metagenome composition based on 16S RNA analysis. Methods determining the plant number in populations, and measuring the morphometric indices of D. antarctica populations were used. Reserve and protective seed proteins spectra were studied by polyacrylamide gel electrophoresis. Method of extreme grouping the spatial variables of these indices was applied for nine populations to obtain a Iq1I and It1i and Irbi, Irbpi. Sets of united indices were compared by regression technique. A comparative statistical analysis of the It1i and Irbi, Irbpi sets in this season was carried out. This possible influence appeared to be individual for each D. antarctica studied population. In each population, part of the plants reacted positively to the bacteria influence, while the other part either did not react or reacted negatively. Dependence of the plant adaptation indices on rhizospheric bacterial communities z(x) is shown in our data. This means that the rhizosphere bacterial community and temperature-dependent rhizosphere bacteria (x) can play an active role in plant adaptation of D. antarctica populations (z) to individual temperature conditions in the microscale of Galindez Island from a biological point of view.

Construction of English corpus oral instant translation model based on information security and deep learning

In order to improve the quality of translation, avoid translation ambiguity and accurately present the content of the source language, supported by the concept of deep learning and guaranteed by information security, an instant oral translation model is constructed for English corpus. The aim of this study is to enhance the efficiency and accuracy of oral translation systems through the application of deep learning algorithms. Specifically, we employ a sample training mechanism tailored to the unique characteristics of oral translation, allowing for separate training of system interaction and translation data. Furthermore, by redesigning the interaction hardware, this research comprehensively redefines the hardware structure of the translation system, marking a significant step towards improving the usability and performance of such systems. After obtaining and processing effective security sensitive information, language resources are managed by using database management system, which fundamentally improves the level of network information security. The performance of the existing oral automatic translation system (Test Group 1) and the system designed in this paper (Test Group 2) is tested by experiments, and the results are as follows: (1) The translation system designed here has better interactive performance, and it is better than Test Group 1. (2) The adaptive index value of Test Group 1 is 1, and that of Test Group 2 is 0.5, which proves that the adaptive ability of system algorithm of Test Group 2 is better than that of Test Group 1. (3) When comparing the translation speed, the translation time of Test Group 2 is only 70.7 s, while that of Test Group 1 is 130.6 s, so the proposed translation system is obviously superior to that of Test Group 1.

A novel statistical framework of drought projection by improving ensemble future climate model simulations under various climate change scenarios.

Unlike other natural disasters, drought is one of the most severe threats to all living beings globally. Due to global climate change, the frequency and duration of droughts have increased in many parts of the world. Therefore, accurate prediction and forecasting of droughts are essential for effective mitigation policies and sustainable research. In recent research, the use of ensemble global climate models (GCMs) for simulating precipitation data is common. The objective of this research is to enhance the multi-model ensemble (MME) for improving future drought characterizations. In this research, we propose the use of relative importance metric (RIM) to address collinearity effects and point-wise discrepancy weights (PWDW) in GCMs. Consequently, this paper introduces a new statistical framework for weighted ensembles called the discrepancy-enhanced beta weighting ensemble (DEBWE). DEBWE enhances the weighted ensemble data of precipitation simulated by multiple GCMs. In DEBWE, we addressed uncertainties in GCMs arising from collinearity and outliers. To evaluate the effectiveness of the proposed weighting framework, we compared its performance with the simple average multi-model ensemble (SAMME), Taylor skill score ensemble (TSSE), and mutual information ensemble (MIE). Based on the Kling-Gupta efficiency (KGE) metric, DEBWE outperforms all competitors across all evaluation criteria. These inferences are based on the analysis of historical simulated data from 22 GCMs in the CMIP6 project. The quantitative performance indicators strongly support the superiority of DEBWE. The median and mean KGE values for DEBWE are 0.2650 and 0.2429, compared to SAMME (0.1000, 0.0991), TSSE (0.2600, 0.2397), and MIE (0.1550, 0.1511). For drought assessment, we computed the adaptive standardized precipitation index (SPI) for three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The steady-state probabilities suggest that normal drought (ND) is the most frequent condition, with extreme events (dry or wet) being less probable.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Features of Ukrainian cultural sphere adaptation to the conditions of the Russo-Ukrainian War (based on data of UCF survey)

Since the problems of the Ukrainian cultural sphere in the context of war are usually studied in relation to consumers of cultural products, the article emphasizes the expediency of studying the state of culture from the point of view of its direct creators. Using the author’s methodology and on the basis of empirical study, the article highlights the peculiarities of the Ukrainian cultural organizations and cultural figures’ adaptation to the сrisis provoked by russia’s armed aggression. The key factors of cultural organizations and creative industries’ successful adaptation to the war conditions are identified. The survival strategy of cultural workers and institutions can be described as cost savings, along with maintaining activities, creating new products and services, and taking active measures to attract additional funding. It is concluded that adaptation does not always take active forms and is not necessarily associated with positive changes in the organization. Often, adaptability is only the result of passive adaptation to the conditions of war. Special attention is paid to the analysis of changes in the level of adaptability of cultural organizations in the dynamics (from November 2022 to December 2023). Despite the fact that the adaptability index tends to increase in comparison with 2022, there is an increase in neutral assessments of the prospects of their organizations and a decrease in positive expectations among respondents. Based on the respondents’ answers, matrices of motivational and demotivational factors of adaptability were constructed. This allowed us to distinguish adapted and non-adapted organizations and workers and the primary obstacles to adaptation. The results of the study show that cultural institutions need support from the state but the specifics of the request depend on the legal form of the organizations. Groups with high and low levels of adaptability were identified, which requires the development of additional support programs for vulnerable cultural organizations and cultural figures.

High-Resolution Structuring of Silica-Based Nanocomposites for the Fabrication of Transparent Multicomponent Glasses with Adjustable Properties.

Silicate-based multicomponent glasses are of high interest for technical applications due to their tailored properties, such as an adaptable refractive index or coefficient of thermal expansion. However, the production of complex structured parts is associated with high effort, since glass components are usually shaped from high-temperature melts with subsequent mechanical or chemical postprocessing. Here for the first time the fabrication of binary and ternary multicomponent glasses using doped nanocomposites based on silica nanoparticles and photocurable metal oxide precursors as part of the binder matrix is presented. The doped nanocomposites are structured in high resolution using UV-casting and additive manufacturing techniques, such as stereolithography and two-photon lithography. Subsequently, the composites are thermally converted into transparent glass. By incorporating titanium oxide, germanium oxide, or zirconium dioxide into the silicate glass network, multicomponent glasses are fabricated with an adjustable refractive index nD between 1.4584-1.4832 and an Abbe number V of 53.85-61.13. It is further demonstrated that by incorporating 7wt% titanium oxide, glasses with ultralow thermal expansion can be fabricated with so far unseen complexity. These novel materials enable for the first time high-precision lithographic structuring of multicomponent silica glasses with applications from optics and photonics, semiconductors as well as sensors.

How Far Bangladesh Is Adapted to Climate Change? Evidence from Coastal Areas Applying Climate Change Adaptation Index

How Far Bangladesh Is Adapted to Climate Change? Evidence from Coastal Areas Applying Climate Change Adaptation Index

Revealing Molecular Patterns of Alzheimer's Disease Risk Gene Expression Signatures in COVID-19 Brains.

Various virus infections are known to predispose to Alzheimer's disease (AD), and a linkage between COVID-19 and AD has been established. COVID-19 infection modulates the gene expression of the genes implicated in progression of AD. Determination of molecular patterns and codon usage and context analysis for the genes that are modulated during COVID-19 infection and are implicated in AD was the target of the study. Our study employed a comprehensive array of research methods, including relative synonymous codon usage, Codon adaptation index analysis, Neutrality and parity analysis, Rare codon analyses, and codon context analysis. This meticulous approach was crucial in determining the molecular patterns present in genes up or downregulated during COVID-19 infection. G/C ending codons were preferred in upregulated genes while not in downregulated genes, and in both gene sets, longer genes have high expressivity. Similarly, T over A nucleotide was preferred, and selection was the major evolutionary force in shaping codon usage in both gene sets. Apart from stops codons, codons CGU - Arg, AUA - Ile, UUA - Leu, UCG - Ser, GUA - Val, and CGA - Arg in upregulated genes, while CUA - Leu, UCG - Ser, and UUA - Leu in downregulated genes were present below the 0.5%. Glutamine-initiated codon pairs have high residual values in upregulated genes. Identical codon pairs GAG-GAG and GUG-GUG were preferred in both gene sets. The shared and unique molecular features in the up- and downregulated gene sets provide insights into the complex interplay between COVID-19 infection and AD. Further studies are required to elucidate the relationship of these molecular patterns with AD pathology.

In-silico identification of putatively functional intergenic small open reading frames in the cucumber genome and their predicted response to biotic and abiotic stresses.

The availability of high-throughput sequencing technologies increased our understanding of different genomes. However, the genomes of all living organisms still have many unidentified coding sequences. The increased number of missing small open reading frames (sORFs) is due to the length threshold used in most gene identification tools, which is true in the genic and, more importantly and surprisingly, in the intergenic regions. Scanning the cucumber genome intergenic regions revealed 420 723 sORF. We excluded 3850 sORF with similarities to annotated cucumber proteins. To propose the functionality of the remaining 416 873 sORF, we calculated their codon adaptation index (CAI). We found 398 937 novel sORF (nsORF) with CAI ≥ 0.7 that were further used for downstream analysis. Searching against the Rfam database revealed 109 nsORFs similar to multiple RNA families. Using SignalP-5.0 and NLS, identified 11 592 signal peptides. Five predicted proteins interacting with Meloidogyne incognita and Powdery mildew proteins were selected using published transcriptome data of host-pathogen interactions. Gene ontology enrichment interpreted the function of those proteins, illustrating that nsORFs' expression could contribute to the cucumber's response to biotic and abiotic stresses. This research highlights the importance of previously overlooked nsORFs in the cucumber genome and provides novel insights into their potential functions.

Climate Change Adaptation and Economic Vulnerability of Small Scale Fishermen in the Spermonde Islands, Indonesia

The general objectives of the research are: 1) To investigates the economic hardships faced by fishermen households in the Spermonde Islands due to climate change., and 2) To examine the adoption of diversified livelihoods as a tactic for confronting and adjusting to climate change among fishermen in the Spermonde Islands. Meanwhile, the specific objectives of the research are: 1) Calculating the economic vulnerability of fishermen to climate change, 2) Determining the adaptive capacity index (ACI), 3) Determining possible scenarios taken by fishermen in making decisions related to the impact of climate change on fishermen's income and 4) Determine co-development scenarios for adaptation to climate change. The research method uses in-depth interviews with small-scale fishermen on four islands in Makassar City (Barrang Lompo Island and Kodingareng Lompo) and Pangkep Regency (Ballang Lompo and Badi Islands) and data analysis to understand the impact of climate change on fishermen's livelihoods and the factors that influence vulnerability. their economy. The research results show that fishermen in the Spermonde Islands face various challenges due to climate change, including increased frequency and intensity of extreme weather, changes in seasonal patterns, and rising sea levels. This impact negatively impacts their production and income, and threatens the sustainability of their livelihoods. A factor that most influenced the economic vulnerability of fishing households in the Spermonde Archipelago was the existence an alternative income for a fishermen.

Synonymous codon usage influences the transmission of peste des petits ruminants (PPR) virus in camels.

Peste des petits ruminants virus (PPRV) is an infectious pathogen; causing highly contagious, acute febrile, and economically important disease of small ruminants. The virus is known to have intrinsic ability to adapt new hosts and to cross the species barrier. The incidence of PPR has already been reported in unusual host species such as camels, bovines, and wild animals from spill-over or natural infection. Still, there are elementary gaps in our knowledge of the extent of susceptibility of camel to PPRV and the adaptability of PPRV to camel. The present study delineates the potential role of preferential codon usage patterns responsible for adaptation, host immune evasion, and transmission of PPRV to unusual hosts like old world camel species namely, dromedary and bactrian camel. The results indicate codon usage of the PPRV genome is functioned by an interplay of mutational pressure and natural selection to exhort the adaptation and fitness of PPRV in probable hosts. The indices of natural selection like the relative codon deoptimization index (RCDI) and codon adaptation index (CAI) predict the ability of PPRV to adapt and evolve in camel species. The analysis also depicts the potential role of the CpG depletion mechanism employed by PPRV to evade host adaptive immune response. The report emphasizes the need for a comprehensive national PPR surveillance plan in unusual hosts like camels for the successful implementation of the PPR Global Eradication Programme (PPR- GEP).