Net Selection Research Articles

Offshore Submerged Aquaculture Flow-Net Interaction Simulation: A Numerical Approach for the Hydrodynamic Characteristics of Nets Produced from Different Materials

The mechanical and hydrodynamic characteristics of single-piece nets are key to the design and optimization of offshore aquaculture net cages. A numerical approach for offshore submerged aquaculture net materials based on the Morison equations and finite element is proposed, simulating the hydrodynamic characteristics of single-piece nets under varying parameters such as wire diameter, mesh size, and flow velocity, and simulating the impact of marine organism attachment on nets by modifying the drag coefficient. The simulation results of nets made from materials such as Copper–Zinc Alloy (Cu-Zn), Zinc–Aluminum Alloy (Zn-Al), Semi-Rigid Polyethylene Terephthalate (PET), and Ultra-High Molecular Weight Polyethylene (UHMWPE) are compared, which provides a theoretical basis for optimizing design parameters and selecting materials for nets based on force conditions and hydrodynamic characteristics. The simulation results indicate that the current force on the net is positively correlated with flow velocity; the maximum displacement of the net is also positively correlated with the flow rate. Compared to other materials, the Cu-Zn net is subjected to the greatest water flow force, while the UHMWPE net experiences the greatest displacement; the larger the diameter of the netting twine, the greater the current force on the net; the mesh size is inversely related to the current force on the net. With increasing drag coefficient, both the maximum displacement of the net and the current force experiences increase, and UHMWPE material nets are more sensitive to increases in the drag coefficient, which indicates a greater impact from the attachment of marine organisms. The density and elastic modulus of the netting material affect the rate of increase in force on the net. The research results can provide a basis for further research on material selection and design of deep-sea aquaculture nets.

Meta-analysis reveals global variations in plant diversity effects on productivity.

Positive effects of plant diversity on productivity have been globally demonstrated and explained by two main effects: complementarity effects and selection effects1-4. However, plant diversity experiments have shown substantial variation in these effects, with driving factors poorly understood4-6. On the basis of a meta-analysis of 452 experiments across the globe, we show that productivity increases on average by 15.2% from monocultures to species mixtures with an average species richness of 2.6; net biodiversity effects are stronger in grassland and forest experiments and weaker in container, cropland and aquatic ecosystems. Of the net biodiversity effects, complementarity effects and selection effects contribute 65.6% and 34.4%, respectively. Complementarity effects increase with phylogenetic diversity, the mixing of nitrogen-fixing and non-nitrogen-fixing species and the functional diversity of leaf nitrogen contents, which indicate the key roles of niche partitioning, biotic feedback and abiotic facilitation in complementarity effects. More positive selection effects occur with higher species biomass inequality in their monocultures. Complementarity effects increase over time, whereas selection effects decrease over time, and they remain consistent across global variations in climates. Our results provide key insights into understanding global variations in plant diversity effects on productivity and underscore the importance of integrating both complementarity and selection effects into strategies for biodiversity conservation and ecological restoration.

Erçek Gölü’nde farklı ağ göz genişliğine sahip multifilament fanyalı uzatma ağlarının seçiciliği

This study was conducted in Lake Erçek, located in the Van Lake basin. The study examined the selectivity of multifilament trammel nets used in the fishing of pearl mullet (Alburnus tarichi, Güldenstädt, 1814) in the lake. The efficiency of nets with mesh sizes of 22 mm, 24 mm, and 26 mm was evaluated in the research. A total of 5.336 pearl mullets were caught in the study carried out between October 2021 and April 2022. 1.296, 1.721 and 2.319 fish were caught from nets with mesh sizes of 22. 24 and 26 mm, respectively. The aim of the study was to determine the most suitable mesh size for sustainable pearl mullet fishing in Lake Erçek. The Holt (1963) method was used to calculate the selectivity parameters. This method considers the fish length and mesh size to determine which size of fish can be caught by the nets. The calculations showed that nets with a 26 mm mesh size had the highest efficiency and contributed to the preservation of fish stocks by allowing smaller fish to escape. The optimum catch lengths for the 22 mm, 24 mm, and 26 mm nets were calculated as 21.15 cm, 22.47 cm, and 23.69 cm, respectively. It was particularly noted that nets with a 22 mm mesh size caught fish below the legal catch size, which could negatively affect the sustainability of the fish stocks. As a result, it was concluded that nets with a 26 mm mesh size are the most suitable option for sustainable fishing in Lake Erçek. The findings of the study provide important data for the conservation of pearl mullet stocks and for the sustainable management of fishing practices.

Sex-Specific Dominance of Gene Expression in Seed Beetles.

When different alleles are favored in different environments, dominance reversal where alternate alleles are dominant in the environment in which they are favored can generate net balancing selection. The sexes represent two distinct genetic environments and sexually antagonistic (SA) selection can maintain genetic variation, especially when the alleles involved show sex-specific dominance. Sexual dimorphism in gene expression is pervasive and has been suggested to result from SA selection. Yet, whether gene-regulatory variation shows sex-specific dominance is poorly understood. We tested for sex-specific dominance in gene expression using three crosses between homozygous lines derived from a population of a seed beetle, where a previous study documented a signal of dominance reversal for fitness between the sexes. Overall, we found that the dominance effects of variants affecting gene expression were positively correlated between the sexes (r = 0.33 to 0.44). Yet, 586 transcripts showed significant differences in dominance between the sexes. Sex-specific dominance was significantly more common in transcripts with more sex-biased expression, in two of three of our crosses. Among transcripts showing sex-specific dominance, lesser sexual dimorphism in gene expression among heterozygotes was somewhat more common than greater. Gene ontology enrichment analyses showed that functional categories associated with known SA phenotypes in Callosobruchus maculatus were overrepresented among transcripts with sex-specific dominance, including genes involved in metabolic processes and the target-of-rapamycin pathway. Our results support the suggestion that sex-specific dominance of regulatory variants contributes to the maintenance of genetic variation in fitness mediated by SA selection in this species.

STOCK SELECTION AND MARKET TIMING ABILITY OF FUND MANAGERS: ANALYSIS OF SELECTED INDIAN EQUITY FUNDS

Collective investment plans, which combine investors' resources to engage in various fund schemes, play an important role in the economy by utilising funds in various sectors such as the stock market and bond market. Since its start, the sector has seen major changes and challenges. Within the context of this research, the performance of managers controlling banking and financial funds is evaluated in terms of their ability to identify investments and their market timing abilities from April 2016 to March 2021. In this study, the Bank Nifty index acts as the benchmark. Esteemed models such as Jensen alpha, Fama net selectivity, the Traynor & Mazuy model, and the Henrikson & Merton model are used to evaluate their performance. According to the study's findings, most of the schemes examined had positive alpha, suggesting favourable performance. Furthermore, while a large proportion of fund managers have high selectivity abilities, the vast majority lack acceptable market timing skills.

Fish Stock Status and Its Clues on Stocking: A Case Study of Acanthopagrus schlegelii from Zhanjiang Coastal Waters, China

Global fisheries face overfishing challenges, endangering fish stock and biodiversity. While hatchery release stocking programs aim to bolster fish populations, their effectiveness remains uncertain due to challenges in data acquisition, such as obtaining stocking details and differentiating between wild and stocked individuals. This study evaluates the stock status of black sea bream (Acanthopagrus schlegelii) released in Chinese hatchery programs since the 1980s. Samples from Zhanjiang fish markets (January 2019–October 2021) underwent analysis using the length–weight relationship (LWR), length-based spawning potential ratio (LBSPR), and length-based Bayesian (LBB) methods. The male and female LWRs were W = 0.0188L2.9725 and W = 0.016L3.0284, respectively, and the observed condition factors indicated good health. The estimates imply that the region is conducive to species survival and can sustain its stocking programs. The LBSPR (SPR = 0.21 (0.17–0.25)) and LBB (B/BMSY = 1.1 (0.718–1.34), B/B0 = 0.37 (0.253–0.473)) results suggest a rebuilding population capable of replenishing to more sustainable levels. However, F/M and net selectivity estimates indicate that fishing practices target juvenile fish, limiting the reproductive potential of A. schlegelii. These findings underline the need for enhanced management strategies, including delayed harvesting and the use of size-specific fishing gear, to ensure the long-term sustainability of the species.

Early-life variation in migration is subject to strong fluctuating survival selection in a partially migratory bird.

Population dynamic and eco-evolutionary responses to environmental variation and change fundamentally depend on combinations of within- and among-cohort variation in the phenotypic expression of key life-history traits, and on corresponding variation in selection on those traits. Specifically, in partially migratory populations, spatio-seasonal dynamics depend on the degree of adaptive phenotypic expression of seasonal migration versus residence, where more individuals migrate when selection favours migration. Opportunity for adaptive (or, conversely, maladaptive) expression could be particularly substantial in early life, through the initial development of migration versus residence. However, within- and among-cohort dynamics of early-life migration, and of associated survival selection, have not been quantified in any system, preventing any inference on adaptive early-life expression. Such analyses have been precluded because data on seasonal movements and survival of sufficient young individuals, across multiple cohorts, have not been collected. We undertook extensive year-round field resightings of 9359 colour-ringed juvenile European shags Gulosus aristotelis from 11 successive cohorts in a partially migratory population. We fitted Bayesian multi-state capture-mark-recapture models to quantify early-life variation in migration versus residence and associated survival across short temporal occasions through each cohort's first year from fledging, thereby quantifying the degree of adaptive phenotypic expression of migration within and across years. All cohorts were substantially partially migratory, but the degree and timing of migration varied considerably within and among cohorts. Episodes of strong survival selection on migration versus residence occurred both on short timeframes within years, and cumulatively across entire first years, generating instances of instantaneous and cumulative net selection that would be obscured at coarser temporal resolutions. Further, the magnitude and direction of selection varied among years, generating strong fluctuating survival selection on early-life migration across cohorts, as rarely evidenced in nature. Yet, the degree of migration did not strongly covary with the direction of selection, indicating limited early-life adaptive phenotypic expression. These results reveal how dynamic early-life expression of and selection on a key life-history trait, seasonal migration, can emerge across seasonal, annual, and multi-year timeframes, yet be substantially decoupled. This restricts the potential for adaptive phenotypic, microevolutionary, and population dynamic responses to changing seasonal environments.

Optimal mesh size of traps for marbled flounder (Pseudopleuronectes yokohamae) based on biological and economic factors

AbstractGear selectivity is crucial in fisheries management because it influences the size and species of fish caught, with traditional methods often basing optimal mesh size on the mature length of a target species. However, to ensure sustainable fisheries, both biological aspects of resource protection and fishing operation efficiency must be considered. This study aimed to determine the ideal mesh size for trap fishing of marbled flounder (Pseudopleuronectes yokohamae) in Gyeongsangnam‐do, South Korea, by using biological and economic factors for sustainable fisheries management. We sampled fish caught in traps of varying mesh sizes (35, 50, 65, 80, and 100 mm) and developed two models based on fish maturity, bycatch ratio, and CPUE. Model 1 used a maturity criterion of 17.8 cm, and Model 2 used the legal minimum length limit of 20 cm. Net selectivity curves indicated that the optimal mesh size ranged 50–65 mm based only on a minimum mature body length of 17.8 cm. In contrast, the optimal mesh size based on both biological and economic factors ranged 57.5–90 mm. Our findings could guide policymakers in enhancing marble flounder population management strategies through policy adjustments in mesh size and gear restrictions.

Legume choice and planting configuration influence intercrop nutrient and yield gains through complementarity and selection effects in legume-based wheat intercropping systems

CONTEXTBy exploiting the complementarities between intercrops, cereal/legume intercropping provides an opportunity to increase legume production with sustained cereal yield. However, little is known about how legume choice and spatial configurations affect the performance and economic viability of legume-based wheat intercropping, especially in arid-irrigated conditions. OBJECTIVEWe conducted this study to investigate the complementarity of three different legumes (chickpea, soybean, and pea) with wheat and determine the appropriate strip width for intercrops. METHODSA three-year study (2021−2023) was conducted to evaluate the effects of legume choice and spatial configuration (narrow strips of 0.6 m (NS) and partially wide strips of 1.2 m (pWS) for each intercrop) on wheat/soybean, wheat/pea, and wheat/chickpea intercropping, and results were compared with their sole systems for dry matter, nitrogen (N) and phosphorus (P) uptake, yield, and economic returns. We also quantified the intensity of the net biodiversity effect (NE), complementarity effect (CE), and selection effect (SE) for yield, N (NEN, CEN, and SEN), and P (NEP, CEP, and SEP) gains of legume-based wheat intercropping systems. RESULTS AND CONCLUSIONSOur results show that intercrops achieved the highest dry matter, nutrient uptake, and grain yield with pWS compared to NS. The intercropped chickpea, soybean, and pea achieved 67–71%, 55–62%, and 62–70% of their sole system yield. The intercropped wheat with chickpea, soybean, and pea produced 66–69%, 57–62%, and 62–66% of sole wheat yield, respectively. Results also confirmed a positive NE with both NS and pWS, mainly due to the higher CE, which ranges from 37% to 104% of NE under all intercropping systems. The nutrient uptake gain with NS and pWS ranged from −3.4 kg ha−1 to 101.5 kg ha−1 (NEN) and − 0.2 kg ha−1 to 13.8 kg ha−1 (NEP). On average, maximum LER (1.36), NE (1012 kg ha−1), NEN (86 kg ha−1), and NEP (12 kg ha−1) were obtained with pWS in wheat/chickpea, followed by wheat/pea and wheat/soybean intercropping. Overall, wheat/pea intercropping with pWS generated the highest net profit (2014, 1533, and 1394 USD ha−1 in 2021, 2022, and 2023, respectively), which was primarily linked to the high market price of pea than chickpea and soybean. SIGNIFICANCEThese results imply that legume choice and spatial configurations influenced complementary and facilitation interactions between intercrops, and wheat/chickpea and wheat/pea intercropping with pWS could be adopted as a productive cropping strategy for obtaining higher and diverse crop yields with reduced land and nutrients than the sole wheat system.

Selection favours high spread and asymmetry of flower opening dates within plant individuals

Abstract Natural selection on traits expressed repeatedly by individuals is usually investigated with a focus on mean values, although within‐individual trait distributions often differ also in other aspects, such as their spread and shape. In plants producing multiple flowers during a season, there might not be a single optimal flowering time, but rather an optimal distribution of flower opening dates. This optimal distribution might depend on both resource allocation patterns and interactions with the abiotic and biotic environment. In this study, we quantified mean, variance, skewness and kurtosis of 495 individual flowering schedules (5287 flowers) over 3 years, and assessed phenotypic selection on these aspects of the within‐individual distribution of opening dates in the perennial herb Lathyrus vernus. We also explored how selection on within‐individual variation in flowering schedules was related to effects on two fitness components: fruit set and the proportion of seeds escaping pre‐dispersal predation. Within‐individual variation in phenology was larger than, or at least similar to, among‐individual variation in all years. We found phenotypic selection on several aspects of individual flowering schedules. In 1 year, selection favoured plants with higher variance in opening dates, and this coincided with a higher fruit set in plants with an increased spread of the flowering schedule. In two of the study years, selection favoured a higher asymmetry of the flowering schedule, and plants with more right‐skewed distributions had higher fruit set and higher proportions of seeds escaping predation. Both fruit set and seed predation increased with an earlier mean flowering, resulting in no net selection on mean flowering date. Synthesis: Our results suggest that phenotypic selection on the spread and shape of flower opening date distributions might be at least as important as selection on the mean flowering date. In a broad sense, this implies that we should consider the entire trait distribution if we aim to understand the evolution of traits that are expressed multiple times within individuals.

The genome-wide signature of short-term temporal selection

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multigenerational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a 10-y population-genomic survey of the microcrustacean Daphnia pulex. The genome sequences of [Formula: see text]800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the following: the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals); the preponderance of weak positive selection operating on minor alleles; and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that interannual fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the further development of theoretical expressions for the interpretation of population-genomic data.

Bridging the gap between the evolutionary dynamics and the molecular mechanisms of meiosis: A model based exploration of the PRDM9 intra-genomic Red Queen.

Molecular dissection of meiotic recombination in mammals, combined with population-genetic and comparative studies, have revealed a complex evolutionary dynamic characterized by short-lived recombination hotspots. Hotspots are chromosome positions containing DNA sequences where the protein PRDM9 can bind and cause crossing-over. To explain these fast evolutionary dynamic, a so-called intra-genomic Red Queen model has been proposed, based on the interplay between two antagonistic forces: biased gene conversion, mediated by double-strand breaks, resulting in hotspot extinction (the hotspot conversion paradox), followed by positive selection favoring mutant PRDM9 alleles recognizing new sequence motifs. Although this model predicts many empirical observations, the exact causes of the positive selection acting on new PRDM9 alleles is still not well understood. In this direction, experiment on mouse hybrids have suggested that, in addition to targeting double strand breaks, PRDM9 has another role during meiosis. Specifically, PRDM9 symmetric binding (simultaneous binding at the same site on both homologues) would facilitate homology search and, as a result, the pairing of the homologues. Although discovered in hybrids, this second function of PRDM9 could also be involved in the evolutionary dynamic observed within populations. To address this point, here, we present a theoretical model of the evolutionary dynamic of meiotic recombination integrating current knowledge about the molecular function of PRDM9. Our modeling work gives important insights into the selective forces driving the turnover of recombination hotspots. Specifically, the reduced symmetrical binding of PRDM9 caused by the loss of high affinity binding sites induces a net positive selection eliciting new PRDM9 alleles recognizing new targets. The model also offers new insights about the influence of the gene dosage of PRDM9, which can paradoxically result in negative selection on new PRDM9 alleles entering the population, driving their eviction and thus reducing standing variation at this locus.

Selectivity-based management for reversing overexploitation of demersal fisheries in North-western Mediterranean Sea

Bottom trawling in the Mediterranean Sea has compromised the availability of demersal fishery resources, primarily due to decades of overexploitation beyond sustainability thresholds. Low selective bottom trawl nets have exacerbated this situation by catching large numbers of under-sized or immature individuals of targeted and not-targeted commercial species that are subsequently discarded. EU legislation requires EU Mediterranean countries to recover demersal fish stocks to sustainable levels by January 2025. This is a challenging requirement under current management scenarios that mainly focus on reducing fishing hours, compromising the activity of the fleets. While social networks among fishing fleets and fisherman associations are essential for facilitating the transition to sustainable exploitation, improving the selectivity of bottom trawl gears is proposed as a viable option beyond reducing fishing hours. This study presents the benefits of improving bottom trawlers net selectivity in multi-species NW Mediterranean coastal and deep-sea fisheries to reduce the catch of non-commercial sizes and discards. Data from selectivity experiments and literature review, fish market landings and a regional monitoring program in the FAO geographical sub-area 6 were used. Results indicate that in the short term, enhanced selectivity leads to an increase in the proportion of fish that are closer to their minimum conservation reference sizes or sizes at maturity, while minimising the impact on commercial catches. Sustainability may be achieved, though beyond 2025, with measures complementing selectivity. These include the adoption of semi-pelagic otter doors to mitigate the impact of trawlers on the seabed and the expansion of no-take marine reserves to ensure habitat recovery and spillover effects.

Range control-based class imbalance and optimized granular elastic net regression feature selection for credit risk assessment

Range control-based class imbalance and optimized granular elastic net regression feature selection for credit risk assessment

Explainable Early Prediction of Gestational Diabetes Biomarkers by Combining Medical Background and Wearable Devices: A Pilot Study With a Cohort Group in South Africa.

This study aims to explore the potential of Internet of Things (IoT) devices and explainable Artificial Intelligence (AI) techniques in predicting biomarker values associated with GDM when measured 13-16 weeks prior to diagnosis. We developed a system that forecasts biomarkers such as LDL, HDL, triglycerides, cholesterol, HbA1c, and results from the Oral Glucose Tolerance Test (OGTT) including fasting glucose, 1-hour, and 2-hour post-load glucose values. These biomarker values are predicted based on sensory measurements collected around week 12 of pregnancy, including continuous glucose levels, short physical movement recordings, and medical background information. To the best of our knowledge, this is the first study to forecast GDM-associated biomarker values 13 to 16 weeks prior to the GDM screening test, using continuous glucose monitoring devices, a wristband for activity detection, and medical background data. We applied machine learning models, specifically Decision Tree and Random Forest Regressors, along with Coupled-Matrix Tensor Factorisation (CMTF) and Elastic Net techniques, examining all possible combinations of these methods across different data modalities. The results demonstrated good performance for most biomarkers. On average, the models achieved Mean Squared Error (MSE) between 0.29 and 0.42 and Mean Absolute Error (MAE) between 0.23 and 0.45 for biomarkers like HDL, LDL, cholesterol, and HbA1c. For the OGTT glucose values, the average MSE ranged from 0.95 to 2.44, and the average MAE ranged from 0.72 to 0.91. Additionally, the utilisation of CMTF with Alternating Least Squares technique yielded slightly better results (0.16 MSE and 0.07 MAE on average) compared to the well-known Elastic Net feature selection technique. While our study was conducted with a limited cohort in South Africa, our findings offer promising indications regarding the potential for predicting biomarker values in pregnant women through the integration of wearable devices and medical background data in the analysis. Nevertheless, further validation on a larger, more diverse cohort is imperative to substantiate these encouraging results.

An Overview of Gillnet and Trammel Net Size Selectivity in the Turkish Inland Fisheries

An Overview of Gillnet and Trammel Net Size Selectivity in the Turkish Inland Fisheries

The Role of (Co)variation in Shaping the Response to Selection in New World Leaf-Nosed Bats.

AbstractUnderstanding and predicting the evolutionary responses of complex morphological traits to selection remains a major challenge in evolutionary biology. Because traits are genetically correlated, selection on a particular trait produces both direct effects on the distribution of that trait and indirect effects on other traits in the population. The correlations between traits can strongly impact evolutionary responses to selection and may thus impose constraints on adaptation. Here, we used museum specimens and comparative quantitative genetic approaches to investigate whether the covariation among cranial traits facilitated or constrained the response to selection during the major dietary transitions in one of the world's most ecologically diverse mammalian families-the phyllostomid bats. We reconstructed the set of net selection gradients that would have acted on each cranial trait during the major transitions to feeding specializations and decomposed the selection responses into their direct and indirect components. We found that for all transitions, most traits capturing craniofacial length evolved toward adaptive directions owing to direct selection. Additionally, we showed instances of dietary transitions in which the complex interaction between the patterns of covariation among traits and the strength and direction of selection either constrained or facilitated evolution. Our work highlights the importance of considering the within-species covariation estimates to quantify evolvability and to disentangle the relative contribution of variational constraints versus selective causes for observed patterns.

Increasing trammel mesh size reduces biomass removal, mitigates discards and increases economic revenue in artisanal fisheries

Small-scale fishing plays a major role in regional economies worldwide and, with a large number of small vessels involved, it provides employment and livelihood to coastal communities. Generally recognized as more selective than other fishing practices, small-scale fishery can nevertheless be subjected to high rates of discards of both non-target species and small-sized individuals, which in turn could lead to both decreased incomes for fishers and increased depletion of fish stocks. However, if the relationship between fish size and price has long been assessed, the effect of enhanced size-selectivity of fishing gears and consequent economic gains has been little investigated. This study, set in the Porto Cesareo Marine Protected Area (Italy, Ionian Sea), aimed at testing effective strategies to improve trammel net selectivity, reducing discards and maximizing the income for fishers. Different mesh sizes (20, 22 and 24 mm) trammel nets were employed. The study consisted in 72 fishing days from July 2012 to September 2013 and each day involved experimental fishing with the three mesh sizes. A total of 16008 specimens (103 species) were collected but the analysis focused on the 18 most common species in the area for a total of 12782 individuals. Mesh size trammel nets of 20 mm and 22 mm yielded most of the biomass, 324.8 and 321.5 kg respectively, while the 24 mm mesh yielded 280.7 kg. The 24 mm mesh, even if accounted for lower income compared to the 22 mm mesh (2383.9 € vs 2590.5 €, respectively), provided significant 50% reduction of discards compared to the 20 and 22 mm mesh. The use of 24 mm mesh size was found to be an effective strategy to reduce the number of discarded organisms and, consequently, the pressure exerted on local fish stocks with associated higher revenue for fishers. The results of this study demonstrated that trammel net selectivity can improve and support conservation measures and concurrently increase profitability of local fishery.

A machine learning model to predict therapeutic inertia in type 2 diabetes using electronic health record data.

To estimate the therapeutic inertia prevalence for patients with type 2 diabetes, develop and validate a machine learning model predicting therapeutic inertia, and determine the added predictive value of area-level social determinants of health (SDOH). This prognostic study with a retrospective cohort design used OneFlorida data (linked electronic health records (EHRs) from 1240 practices/clinics in Florida). The study cohort included adults (aged ≥ 18) with type 2 diabetes, HbA1C ≥ 7% (53mmol/mol), ≥one ambulatory visit, and ≥one antihyperglycemic medication prescribed (excluded patients prescribed insulin before HbA1C). The outcome was therapeutic inertia, defined as absence of treatment intensification within six months after HbA1C ≥ 7% (53mmol/mol). The predictors were patient, provider, and healthcare system factors. Machine learning methods included gradient boosting machines (GBM), random forests (RF), elastic net (EN), and least absolute shrinkage and selection operator (LASSO). The DeLong test compared the discriminative ability (represented by C-statistics) between models. The cohort included 31,087 patients with type 2 diabetes (mean age = 58.89 (SD = 13.27)years, 50.50% male, 58.89% White). The therapeutic inertia prevalence was 39.80% among the 68,445 records. GBM outperformed (C-statistic from testing sample = 0.84, 95% CI = 0.83-0.84) RF (C-statistic = 0.80, 95% CI = 0.79-0.80), EN (C-statistic = 0.80, 95% CI = 0.80-0.81), and LASSO (C-statistic = 0.80, 95% CI = 0.80-0.81), p < 0.05. Area-level SDOH significantly increased the discriminative ability versus models without SDOH (C-statistic for GBM = 0.84, 95% CI = 0.84-0.85 vs. 0.84, 95% CI = 0.83-0.84), p < 0.05. Using EHRs of patients with type 2 diabetes from a large state, machine learning predicted therapeutic inertia (prevalence = 40%). The model's ability to predict patients at high risk of therapeutic inertia is clinically applicable to diabetes care.

Identification of natural antimicrobial peptides mimetic to inhibit Ca2+ influx DDX3X activity for blocking dengue viral infectivity.

Viruses are microscopic biological entities that can quickly invade and multiply in a living organism. Each year, over 36,000 people die and nearly 400 million are infected with the dengue virus (DENV). Despite dengue being an endemic disease, no targeted and effective antiviral peptide resource is available against the dengue species. Antiviral peptides (AVPs) have shown tremendous ability to fight against different viruses. Accelerating antiviral drug discovery is crucial, particularly for RNA viruses. DDX3X, a vital cell component, supports viral translation and interacts with TRPV4, regulating viral RNA metabolism and infectivity. Its diverse signaling pathway makes it a potential therapeutic target. Our study focuses on inhibiting viral RNA translation by blocking the activity of the target gene and the TRPV4-mediated Ca2+ cation channel. Six major proteins from camel milk were first extracted and split with the enzyme pepsin. The antiviral properties were then analyzed using online bioinformatics programs, including AVPpred, Meta-iAVP, AMPfun, and ENNAVIA. The stability of the complex was assessed using MD simulation, MM/GBSA, and principal component analysis. Cytotoxicity evaluations were conducted using COPid and ToxinPred. The top ten AVPs, determined by optimal scores, were selected and saved for docking studies with the GalaxyPepDock tools. Bioinformatics analyses revealed that the peptides had very short hydrogen bond distances (1.8 to 3.6Å) near the active site of the target protein. Approximately 76% of the peptide residues were 5-11 amino acids long. Additionally, the identified peptide candidates exhibited desirable properties for potential therapeutic agents, including a net positive charge, moderate toxicity, hydrophilicity, and selectivity. In conclusion, this computational study provides promising insights for discovering peptide-based therapeutic agents against DENV.