Background: Childhood anaemia remains a significant public health challenge, particularly in low- and middle-income countries like Nigeria, where the prevalence among children under five is alarmingly high. This study aims to identify the key determinants of childhood anaemia, develop an accurate predictive model using advanced machine learning techniques, and assess the model’s performance across different demographic groups to ensure equitable risk prediction. Methods: Data from 13,136 children aged 6-59 months from the 2018 National Demographic Health Survey (NDHS) were analysed. Sixteen machine learning algorithms were evaluated based on their ability to predict childhood anaemia using a wide range of individual, community, and environmental factors. The Extra Trees (ET) classifier, demonstrating the highest predictive performance, was used to identify the top ten predictors of childhood anaemia. A fairness and demographic bias assessment framework was incorporated to evaluate the model’s performance across different regions, wealth index categories, ethnic groups, and gender. Results: The ET classifier outperformed all other algorithms, achieving an area under the curve (AUC) of 0.8319, accuracy of 0.7565, and a recall of 0.7565. The top ten predictors identified by the ET model included the number of under-five children in the household, birth order, child age, media access, maternal health-seeking behaviour, child gender, proximity to water, money problems, day land surface temperature, and all population count. The demographic bias assessment revealed variations in model performance across different subgroups, with the lowest AUCs observed in the North-East region (0.79), the poorest wealth index category (0.80), and the Hausa/Fulani ethnic group (0.81). Conclusion: This study demonstrates the potential of machine learning techniques to accurately predict childhood anaemia in Nigeria and identify key risk factors that inform targeted interventions. Future research should focus on refining the predictive model, exploring integrated interventions, and deploying AI-based tools to combat childhood anaemia in Nigeria and beyond.

Global change and urbanisation profoundly alter wildlife habitats, driving native animals into novel habitats while increasing the co-occurrence between native and invasive species. Host-microbiome associations are shaped by host traits and environmental features, but little is known about their plasticity in co-occurring native and invasive species across urban-rural gradients. Here, we explored gut microbiomes of four sympatric small mammal species along an urban-rural ecotone in Borneo, one of the planet’s oldest rainforest regions experiencing recent urban expansion. Host species identity was the strongest determinant of microbiome composition, while land use and spatial proximity shaped microbiome similarity within and among the three rat species. The urban-dwelling rat Rattus rattus had a microbiome composition more similar to that of the native, urban-adapted rat Sundamys muelleri (R. rattus’ strongest environmental niche overlap), than to the closely related urban-dwelling R. norvegicus. The urban-dwelling shrew Suncus murinus presented the most distinct microbiome. The microbiome of R. norvegicus was the most sensitive to land use intensity, exhibiting significant alterations in composition and bacterial abundance across the ecotone. Our findings suggest that environmental niche overlap among native and invasive species promotes similar gut microbiomes. Even for omnivorous urban-dwellers with a worldwide distribution like R. norvegicus, gut microbiomes may change across fine-scale environmental gradients. Future research needs to confirm whether land use intensity can be a strong selective force on mammalian gut microbiomes, influencing the way in which native and invasive species are able to exploit novel environments.

Mast seeding, the variable and intermittent production of seeds, has cascading effects on ecosystem functioning. This study explores its influence on the brown bear populations in the Italian Alps, focusing on beechnuts (Fagus sylvatica L.), the primary food source for bears in the region. Using historical data and field sampling we estimated and mapped the annual seed biomass from 2007 to 2021 for the province of Trento. The energy content of beechnuts was assessed through high heating values (HHV), providing the caloric resources available. Data on beechnuts production, records of damages and GPS data from 16 Eurasian brown bears, were integrated to perform a temporal and spatial analysis at home range and at landscape level. Standardised damages to beehive and livestock decreased during mast years, suggesting that bears met their trophic needs through natural food sources. In fact, bears used more agricultural areas and less beech forest during years of crop failure then in mast years. At landscape level, agriculture and pasture areas, close to beech forests and distant from cities showed higher risk of damage providing a tool to anticipate management actions.. This work provides insights on the ecological dynamics and conservation implications of brown bear in the study area by mapping the spatial and temporal aspects of mast seeding and bear related damages.

Over the past two decades, numerous studies have emphasised the importance of including organic matter (OM) in land surface models (LSMs) to accurately represent soil thermal and hydrological properties. This is particularly relevant in Arctic regions, where organic-rich soils are widespread. Consequently, most LSMs incorporate parameterisations that account for OM effects, although these implementations are often simplified. Recent advancements in global soil datasets now enable more precise modelling of soil properties by providing detailed inputs for soil composition and physical characteristics. This study enhances the ORCHIDEE LSM by refining the representation of soil organic and mineral content, as well as improving parameterisations of heat capacity, thermal conductivity, and porosity, using data from the SoilGrids 250m v2.0 database. The updated model is evaluated across multiple Arctic sites and compared against two earlier versions: (1) a Bulk version that neglects OM effects and (2) a simplified version with a basic OM prescription. Results show that incorporating OM into thermal process modelling significantly improves soil temperature simulations, particularly at greater depths. For some sites, root mean square errors (RMSE) are reduced by up to 25% compared to the Bulk version, especially during the snow-free summer months. These findings highlight the value of high-resolution soil datasets, such as SoilGrids, for improving simulations of thermal dynamics in carbon-rich Arctic soils.

Accurate, spatiotemporally continuous total precipitable water (TPW) data under all-weather conditions are crucial for understanding water and energy cycles. This study introduces TPWDiff, a novel deep learning-based TPW retrieval model that employs a generative diffusion model. TPWDiff effectively estimates TPW under all-weather conditions by leveraging thermal infrared observations from the Advanced Himawari Imager (AHI) aboard Himawari-8. Compared to ERA5 TPW, TPW retrieved by TPWDiff shows excellent correspondence, achieving nearly the same accuracy under cloudy conditions as in clear-sky conditions. When validated against radiosonde TPW, TPWDiff achieves a correlation coefficient (R) of 0.97 and a root mean square error (RMSE) of 4.61 mm. TPWDiff excels in learning the TPW distribution and demonstrates robustness in spatiotemporal retrievals, outperforming traditional machine learning method. These results demonstrate the high accuracy of TPWDiff and its potential for applications in weather and climate research.

To effectively reduce the negative impact of impact load during pyrotechnic launch, this paper proposes a new type of vibration-damping method of knitted stainless steel metal wire mesh damper (MWMD) and analyzes its mechanical behavior and cushioning performance. The effects of MWMD wire diameter d and relative density ρ on the mechanical and rebound characteristics of MWMD were studied by quasi-static cyclic compression experiments. The results show that the smaller the diameter d and the smaller the relative density ρ , the more cyclic loading times and the better the resilience of MWMD. On this basis, the finite element simulation model of MWMD is established, and the mechanical behavior of MWMD under cyclic impact load is studied by numerical simulation analysis. The simulation results show that when the wire diameter range is 0.15 mm~0.23 mm and the relative density range is 1.35 g/cm 3~1.79 g/cm 3, the MWMD with smaller wire diameter and larger relative density has a good buffer energy absorption capacity, and the energy absorption efficiency reaches 37.11%. With the increase in the number of cyclic impacts, the energy absorption capacity of MWMD decreases. MWMDs with smaller wire diameters and higher relative densities exhibit more stable mechanical properties under multiple impact loads and show stronger resistance to repetitive impacts.

A secondary hyperparathyroidism revealed by a mandibular radiolucency: case reportAuthors: Mohamed Beh1 , Wahbi Ben Salha1, Ghada Bouslama2, Lamia Oualha2, Eya Moussaoui11Dental medicine, Sahloul University Hospital, Sousse, Tunisia2Dental medicine, Farhat Hached University Hospital, Sousse, TunisiaCorresponding author: Mohamed BehSousse, 4054 Tunisia+216 22372110mohamedbeh55@yahoo.comWahbi Ben Salha: Email address: bensalhawahbi@gmail.comGhada Bouslama: Email address: bouslama.ghada@yahoo.frLamia Oualha: Email address: lamia.oualha@gmail.comEya Moussaoui: Email address: eyamouss@live.frAuthor Contributions:Author 1: Conceptualization, Writing – Original Draft PreparationAuthor 2: Conceptualization, Writing – Original Draft PreparationAuthor 3: Methodology, Writing – Review & EditingAuthor 4: Investigation, Writing – Review & EditingAuthor 5: Formal analysis, Writing – Review & EditingPatient consent: Written informed consent to participate was obtained from the patient.AcknowledgmentConflict of Interest Statement: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.Statements:Data availability statement: Not applicableFunding statement: This research received no specific grant from any funding agency.Manuscript Type: Case reportKeywords: brown tumor, jaw, hyperparathyroidism, parathormone, bone remodeling, enucleation

Fusarium head blight (FHB), a devastating disease of barley caused primarily by the fungus Fusarium graminearum, causes significant yield losses and grain contamination with mycotoxins. Enhancing resistance to FHB and the resultant accumulation of mycotoxins, such as deoxynivalenol (DON), is an effective and economical method of reducing losses caused by this disease. A diverse panel of 234 barley accessions from world-wide origins was assembled and evaluated in head-to-head comparisons over multi-year and multi-environment field trials to identify those that perform consistently well with respect to FHB resistance and DON accumulation under Upper Midwest conditions. In addition to these two traits, row type (RT), heading date (HD), plant height (HT), kernel density (KD), and node density (ND) assessments were also recorded to investigate the relationship between these agro-morphological traits and both DON concentration and FHB severity. Accessions were genotyped with a barley 50K single nucleotide polymorphism (SNP) microarray in order to assess their population structure and genetic relationships and also investigate patterns of disease resistance. Several accessions originating from diverse backgrounds were identified as having moderately high resistance to FHB and/or DON accumulation. However, most accessions with low disease severity and mycotoxin accumulation also had undesirable agro-morphological traits, a challenge to breeding for FHB resistance in barley. The data generated in this study will serve as a valuable resource for resistance breeding and genetic mapping of resistance to FHB and DON accumulation.

Introduction: There were some reports on superior vena cava isolation (SVCI) by the pentaspline pulsed-field ablation (PFA) catheter, however, this report presents case series of superior vena cava (SVC) fibrillation that was successfully treated using a circular multielectrode array PFA catheter. Methods: We performed SVCI using a PulseSelect PFA catheter in 11 cases. SVCI was performed when the earliest activation during ectopy was inside the SVC. In the second session, SVCI was routinely performed if the myocardial sleeves were of sufficient length. Results: The mean number of PFA deliveries was 7.8±2.1 applications. The acute success of SVC isolation was achieved in all patients. Importantly, no cases of sinus node dysfunction or persistent phrenic nerve palsy were observed in this study. Conclusions: A circular multielectrode array PFA catheter is useful and safe for treating non-PV foci triggered by SVC.

Current genotoxicity testing strategies face several challenges, including a high incidence of misleading positive results that lead to unnecessary animal testing, limited mechanistic insights, insufficient integration of innovative methodologies, and a lack of quantitative assessment. Despite rapid advancements in technology and scientific understanding, genotoxicity testing batteries have remained largely unchanged for years. To modernize genotoxicity assessment and incorporate innovative approaches, the development of Integrated Approaches for Testing and Assessment (IATAs) is essential. These frameworks combine existing knowledge with data from New Approach Methodologies (NAMs) aiming to reduce or eliminate reliance on in vivo testing. Genotoxicity is particularly well-suited for IATA development as numerous cutting-edge, non-animal methods have emerged in recent years, including 3D test systems, Prediscreen®, MultiFlow®, ToxTracker®, and transcriptomic-based biomarkers such as GENOMARK and TGx-DDI. However, the integration of NAMs into IATAs must be systematic and scientifically robust. In this process, the Adverse Outcome Pathway (AOP) framework plays a crucial role by linking molecular-level events to adverse health effects, thereby supporting the structured selection of NAMs. This article explores the key challenges and gaps within the current European regulatory frameworks for chemical compound genotoxicity assessment and discuss how an AOP-based IATA can address these issues. Additionally, we present a global AOP network for permanent DNA damage, designed to guide IATA development and improve regulatory decision-making. This integrated approach has the potential to enhance the accuracy, efficiency, and ethical standards of genotoxicity assessment while reducing reliance on animal testing.

Introduction: Left bundle branch area pacing (LBBAP) is typically performed using the lumenless (LLL) Medtronic SelectSecure TM Model 3830 pacing lead. Stylet driven leads (SDL) for LBBAP were recently introduced. Objective: To compare the Abbott Tendril STS TM 2088TC SDL and CPS Locator TM 3D delivery system to the Medtronic LLL and delivery system acutely and chronically. Methods: Fifty consecutive patients who received SDL using the CPS Locator TM 3D delivery system for standard pacing indications were included in this study. A comparison was made with 229 LLL patients from a retrospective database, evaluating baseline characteristics, procedural outcomes, lead and system performance, and follow-up data. Results: LBBAP was successful in 84% of SDL and 79% of LLL patients (p = 0.55), with no significant differences in procedural characteristics or complications. Minor pacing differences were noted. CPS Locator TM 3D performed similarly to C315His ® delivery system with a trend for less lead placement attempts. Conduction system capture (CSC) pattern at implant did not differ between both groups. CSC maintenance was similar between SDL and LLL. However, follow-up QRS duration was significantly longer in SDL group (154ms vs 129ms, p=0.004) suggesting a possibility of CSC loss in some patients. Conclusion: SDL is a viable alternative to LLL demonstrating comparable acute and mid-term pacing parameters. CPS Locator TM 3D delivery system showed comparable performance and excellent safety profile. Acute CSC with SDL and LLL is similar, but its long-term maintenance will require further study.

Background: Guidelines advise for the implementation of patient-reported outcomes (PROMs). Our objective is to identify the utilization patterns of PROMs, together with the reasons for their usage and the barriers to their adoption among practitioners managing patients with asthma, allergic rhinitis (AR), and rhinosinusitis (RS). Methods: This was a cross-sectional observational study using a questionnaire encompassing all pertinent PROMs and disseminated to practitioners associated with the ARIA, UCARE, ADCARE, and ACARE networks. Individuals unfamiliar with PROMS or lacking prior experience with it were eliminated. Descriptive and analytical data were utilized, categorized by the frequency and type of PROMs applied. Stata 18.0 was utilized, with p<0.05 indicating statistical significance. Results: A total of 439 practitioners participated, with PROMs predominantly utilized by physicians certified for over 30 years and by respiratory specialists (16.67% and 12.46%, respectively; p<0.05). Pulmonologists exhibited the greatest utilization of asthma PROMs at 86%, while allergists predominantly employed AR and RS PROMs at 38.42% and 33.33%, respectively (p < 0.001). ACT (66.74%), RCAT (27.79%), and SNOTT22 (15.26%) were the predominant PROMs utilized primarily for asthma (79.19%), AR (51.23%), and RS (57.26%), respectively (p<0.001). The foremost purposes for their application were disease control monitoring (93.39%) and evaluation of performance of therapy approaches (90.2%). The most significant barrier identified was time constraint, rated at 75.40% (p>0.05 across all groups). Conclusions: The use of PROMs is suboptimal, primarily due to time limitations. It is imperative that methods be swiftly implemented to include these techniques into the therapeutic environment to attain enhanced outcomes.

Background Influenza A Viruses (IAV) are emerging pathogens of public health concern. Wild birds and mammals are important reservoirs that contribute to the evolving genetic diversity of influenza viruses and represent an important transmission interface that may facilitate mammalian adaptation of IAV. Detection of IAV within wild mammalian species provides important insights to potential mechanisms of interspecies transmission and adaptation. Methods A novel H3N6 IAV was recovered from a stranded harbor seal (Phoca vitulina) in Alaska. The virus was sequenced, isolated, and tested for replication in mouse and ferret models. Results Analysis of the full genome sequence suggested the novel seal derived H3N6 IAV was derived from a reassortment of H3N8 and H4N6 circulating in dabbling ducks in the Pacific flyway. Assessment of replication and virulence phenotypes in mouse and ferret models of influenza provided evidence of replication in mammals despite minimal disease. Conclusions. We report the first identification of H3N6 within marine mammals with capacity for replication within mammalian hosts despite the absence of previously described adaptations. Field surveillance studies combined with risk assessment pipelines that incorporate phylogenetic analysis and in vitro and in vivo characterization are essential for understanding mammalian adaptation.

Bacterial ferredoxins are small iron-sulfur binding proteins that function as soluble electron shuttles between redox enzymes in the cell. Their simple 2x(β-α-β) fold, central metabolic function, and ubiquity across all kingdoms of life have led to the proposal that ferredoxins were likely among the earliest proteins. Today, ferredoxin-like folds are embedded in large, multidomain enzymes, suggesting ancient gene duplication and fusion events. In some cases, these embedded domains may have scant sequence or even structural homology to soluble counterparts, challenging the use of traditional phylogenetic tools to establish evolutionary relationships. In this study, we identify fragments of bacterial ferredoxins within larger oxidoreductases by integrating comparative sequence, structure, and dynamical attributes. Dynamics are computed using an elastic network model and analyzed for similarity of major normal modes. Using comparative dynamics, fragments of ferredoxin domains are found within larger proteins, even in cases of limited structural homology. This study also reveals a non-linear relationship between dynamical and structural similarities, suggesting that protein dynamics are more constrained than structure through evolutionary time. We propose that dynamical similarity is indicative of functional similarity. And, since nature selects for function, that the inclusion of dynamical similarity, in addition to sequence and structure similarities, provides a more robust framework for inferring homology. Inclusion of dynamical attributes in comparative analysis will lead to a greater understanding of the deep-time evolution of modern protein nanomachines.

Motivation: Developing a de facto method to generate synthetic protein sequences is a challenging task that ensures confidence in protein engineering, provides functional insights, and aids in target identification. We highlight the protein sequence design, focusing on optimizing the synthetic sequences and their validity by encouraging the immense potential in various domains. Methods: In this framework, first we create the Ramachandran plot, which has been designed to identify the conformational region space for protein. Then, the model is tailored to generate synthetic proteins using Bernoulli data distribution that preserve essential structural or sequence features to ensure the diversity in the training data set. The adversarial loss is evaluated to differentiate between generator-discriminator optimizations. The probability of a protein being real or synthetic is encouraged by the FID score. Results: Our experimental results demonstrate the potential of a GAN model for protein data augmentation to expand the datasets significantly. The model generalizes to a native approach; we evaluate the discriminator loss and real sequences loss as decreasing abruptly, while generator loss and real sequences loss decrease for a while. FID score along with pre-trained model BERT, scores from 91.8821079 to 0.4509833. Our findings demonstrate the tractability and improve the dataset for protein sequence design. Graphical Abstract:

SCOPE Necrotizing enterocolitis is a serious and life-threatening condition affecting very low birth weight neonates. The composition of human milk oligosaccharides in breast milk varies significantly. This nested case-control study aimed to evaluate the association between levels of the HMO 2-fucosyllactose in breast milk and the occurrence and severity of NEC. METHODS AND RESULTS A total of 247 mother-infant dyads, between 26 and 32 weeks of gestation, were enrolled over a one-year period in a nested case-control study. Breast milk samples were collected between the 9th and 15th day of life. Clinical data for enrolled infants were reviewed at discharge or at six weeks of life. Each case was matched with five controls (1:5). Only matched samples were analyzed for 2’-fucosyllactose (2-FL) levels using LC-MS/MS. The median 2-FL levels in cases were significantly lower compared to controls (p < 0.03). However, univariate analysis did not show a significant association. An inverse correlation was observed between NEC severity and 2’-FL levels. Notably, 2’-FL levels below 311 µg/mL demonstrated a sensitivity of 80% in predicting NEC occurrence. 2. CONCLUSION Studies are needed to explore the role of 2’-FL in NEC prevention and its potential as a supplement.

Pollen from 20 populations representing 13 Iranian species of the genus Crocus was analyzed using light microscopy (LM) and scanning electron microscopy (SEM) to investigate the palyno-morphological features and their taxonomic significance. Polliniferous materials were sourced from either fresh plants or herbarium samples. For LM analysis, pollen grains were acetolyzed, while intact pollen grains were used for SEM micrographs. The study examined various pollen traits, including polar and equatorial diameters, aperture and meso-aperture width, exine thickness, and P/E ratios in LM analyses. Additionally, SEM observations focused on spinule width and length and the density of spinules and perforations on the exine. The investigation revealed that the pollen grains of Crocus are monads, oblate-spheroidal in shape, and measure approximately 61 to 106.48 micrometers along their equatorial axis. The smallest pollen grains were observed in C. reinhardii, while the largest were found in C. archibaldiorum. The pollen grains were intectate, with the exine irregularly perforated and covered with microechinate ornamentation. Two distinct types of pollen apertures were identified in the studied species: polyaperturoidate apertures in the two populations of Crocus haussknechtii from section Crocus and spiraaperturate pollen in the remaining taxa belonging to section Nudiscapus. Our data suggest that pollen characteristics offer valuable synapomorphies for delimiting sections within the genus Crocus, and also provide significant support for understanding and clarifying relationships within taxonomic aggregates and complexes.

Pigs have been improved throughout decades by increasing meat content in the carcasses. However, this has led to a reduction in fat levels, particularly intramuscular fat (IMF), which is crucial for flavor. The current study, utilized combined RNA-ATAC sequencing analyses to identify possible key transcription factors (TFs) that regulate important molecular mechanisms in the liver associated with fat deposition in pig bodies. In the study were used native pigs Złotnicka White, which is not under selection pressure. RNA-seq identified 272 genes as differentially expressed (DEGs, showing >1.2 FC). ATAC-seq identified 6,333 significant peaks (DAR – differentially accessible regions) in TSS flanking region. 98 genes were overlapped between RNA and ATAC seq data and these significant DEGs-DARs were further included into motif analysis. TRRUST and MEME tools were used to identify crucial TFs, which predicted possible binding TF motifs based on transcription start site ATAC signals. The candidate TFs for fat deposition in pigs suggested in the present study are SREBP1, ATF4, KLF11, RORA and MYC, which were enriched due to TSS ATAC signals. Moreover, for TFs MYC, ATF4 and, KLF11, ATAC signals within transcription start site flanking regions were identified.

Background: This study explores the impact of omalizumab and mepolizumab on the dynamic changes in type 2 (T2) markers (blood eosinophils, serum total IgE) and their correlation with clinical outcomes in T2-high severe asthma. Methods: Ninety patients with T2-high severe asthma treated with omalizumab (n=50) or mepolizumab (n=40) were followed prospectively, with asthma control test (ACT) scores, forced expiratory volume in 1 second (FEV1), acute exacerbations (AE), and steroid use assessed at baseline, 6, and 12 months. Changes in T2 markers were analyzed for their correlations with improvements in clinical outcomes. Results: Both treatments significantly improved ACT scores and FEV1 at 6 and 12 months. AE and steroid use also significantly decreased. Blood eosinophil counts significantly reduced in both treatment groups, while total IgE levels increased with omalizumab but showed a non-significant decrease with mepolizumab at 6 and 12 months. Baseline blood eosinophils and total IgE levels demonstrated a significant moderate correlation in both treatment groups (omalizumab: r = 0.31, p = 0.0403; mepolizumab: r = 0.44, p = 0.0182). In the omalizumab group, higher baseline blood eosinophils were associated with greater FEV1 improvement ( r = 0.65, p = 0.001; r = 0.53, p = 0.012), while in the mepolizumab group, total IgE level reductions correlated with improved FEV1( r = -0.77, p = 0.042; r = -0.66, p = 0.02) at 6 and 12 months. Conclusion: Omalizumab and mepolizumab improved clinical outcomes and uniquely influenced T2 marker dynamics in T2-high severe asthma, with baseline blood eosinophils and total IgE level reductions predicting FEV1 improvements, respectively.

This article develops a duality principle through an exactly penalized D.C. approach applicable to some originally non-convex primal variational formulations. More specifically, in a first step, we develop applications to a Ginzburg-Landau type equation. The results are obtained through basic tools of functional analysis, calculus of variations, duality and optimization theory in infinite dimensional spaces. It is worth emphasizing we have obtained a concave dual variational formulation which may be applied to a large class of similar models in the calculus of variations. Finally, we also highlight the article establishes sufficient global optimality conditions for the model in question.

In today’s digitized world, people rely heavily on numerous smart machines to perform everyday tasks. The number of smart devices has surged recently, leading to an increase in security vulnerabilities. Among these, the “Low-rate denial of service (LDoS)” attack stands out as particularly dangerous due to its stealthy and varied nature, posing significant challenges for current intrusion detection systems. This research introduces a hybrid approach to investigate LDoS attack features, combining hyperparameter optimization (HPO) with principal component analysis (PCA). To address dataset imbalance, the SMOTE technique is applied. PCA is used for dimensionality reduction, with the key hyperparameter ’n_components’ optimized through HPO. The study utilizes the ‘CICIDS2017’ and ‘CSECISDOS2018’ datasets, highlighting the importance of dimension reduction for improved performance. The hybrid method, termed HPO-S-PCA, is employed to analyze LDoS traffic features and extract relevant features. The research observed a trade-off between True Positive Rate (TPR) and accuracy in existing studies and focused on enhancing both performance metrics through the novel hybrid approach. Machine learning classifiers such as ‘Logistic Regression (LR)’, ‘Support Vector Machine (SVM)’, ‘Decision Tree (DT)’, ‘Random Forest (RF)’, ‘K-Nearest Neighbors (KNN)’, ‘Kernel SVM’, and ‘Naive Bayes (NB)’ were trained to detect LDoS attacks using the extracted features. Among these, RF and KNN classifiers achieved 99.9% detection rate for positive anomalies. PCA with best n_components perform well and provide expected results for MRE and EVR. K-Nearest Neighbors outperforms all based on accuracy, TPR, MRE and EVR.

RNA-binding E3 ubiquitin ligases (RBULs) provide a link between RNA metabolic processes and the ubiquitin proteasome system (UPS). In humans, RBULs are involved in various biological processes, such as cell proliferation and differentiation, or sexual development. To date, little is known about their role in the protozoan parasite Plasmodium falciparum, the causative agent of malaria tropica. We previously identified a first P. falciparum RBUL, the RING finger E3 ligase PfRNF1, which is highly expressed during gametocyte development. Here, we conducted BioID-based proximity interaction studies to unveil the PfRNF1 interactome. We show that in immature gametocytes PfRNF1 forms an interaction network that is mainly composed of RNA-binding proteins including the translational repressors DOZI and CITH and members of the CCR4-NOT complex, as well as UPS-related proteins. In particular, PfRNF1 interacts with recently identified regulators of sexual development like the zinc finger protein PfMD3, with which it shares the majority of interactors. The common interactome of PfRNF1 and PfMD3 comprises several yet unknown proteins specifically expressed in male or female gametocytes. Our results demonstrate that PfRNF1 engages with RNA-binding proteins crucial for sex determination of gametocytes, thereby linking posttranscriptional regulation with the ubiquitin system.

Implementing proteomics-based solutions has emerged as a potentially highly powerful and transformative approach in enhancing patient management by streamlining clinical decision-making and accelerating drug development. Specific changes in proteins are generally responsible for onset and progression of disease. This understanding serves as a foundation for identifying biomarkers, discovering drug targets, and developing novel therapeutics. Despite substantial progress, several challenges and gaps persist. These include among others technical limitations, regulatory hurdles, legal, ethics and data protection issues. Addressing these obstacles necessitates a multifaceted approach involving critical evaluation, cross-disciplinary collaboration, and the inclusion of diverse stakeholder perspectives. Such a comprehensive strategy appears essential for advancing proteomics from research to implementation, ultimately benefiting patients. To this end, the PROTEOMICS journal is launching a special section dedicated to clinical proteomics. This initiative aims to highlight the critical aspects of (prote)omics-guided biomarker and drug development, address existing challenges, and propose potential solutions for implementation. By fostering collaboration among scientists, clinicians, patients, regulators, insurance companies, pharmaceutical companies, and funding agencies, we hope to spark discussions that pave the way for adopting proteomics-based approaches to improve patient outcomes.

RED MAN SYNDROME DIAGNOSED IN AN ORTHOPAEDIC PATIENT: A CASE REPORT.