Abstract Reliable sub-basin seasonal forecasts of tropical cyclone (TC) activity are fundamental in helping stakeholders make informed decisions and minimize economic and societal losses. While several institutions routinely release TC seasonal forecasts for traditionally studied basins, only a few provide global coverage, limiting confidence for other densely populated regions. Here, we apply a probabilistic clustering approach to identify track patterns across five basins (North Atlantic, Eastern and Western North Pacific, South Indian, and South Pacific) over the period 1993-2016 in retrospective seasonal forecasts produced by the Euro-Mediterranean Center on Climate Change Seasonal Prediction System 3.5. Despite a hemispheric bias in TC frequency - overestimated in the Southern Hemisphere and underestimated in the Northern Hemisphere - the spatial distribution of TC tracks is skillfully represented across all basins. Moreover, predicted and observed year-to-year variability are significantly correlated (p<0.1) for most clusters in the North Atlantic, Eastern Pacific and South Indian, while limited to one third of clusters in the Western and South Pacific. Conversely, skill for subtropical clusters is absent across all basins. An analysis of the North Atlantic reveals that cluster skill is mainly attributable to the representation of the ENSO-TC teleconnection, suggesting it may represent a primary driver of cluster predictability across basins. These findings demonstrate that sub-basin forecast skill can improve basin-wide performance in dynamical models, underscoring the value of regional forecasts for refining seasonal outlooks.

Abstract Continuous physical domains are important for scientific investigations of dynamical processes in the atmosphere. However, missing data—arising from operational constraints and adverse environmental conditions—pose significant challenges to accurate analysis and modeling. To address this limitation, we propose a novel hybrid convolutional neural network–Transformer machine learning model for multivariable atmospheric data imputation, termed CT‐MVP. This framework integrates CNNs for local feature extraction with transformers for capturing long‐range dependencies across time and altitude. The model is trained and evaluated on a testbed using the Specified Dynamics Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (SD‐WACCM‐X) data set spanning 13 yrs, which provides continuous global coverage of atmospheric variables, including temperature and zonal and meridional winds. This setup ensures that the ML approach can be rigorously assessed under diverse data‐gap conditions. The hybrid framework enables effective reconstruction of missing values in high‐dimensional atmospheric data sets, with comparative evaluations against traditional methods and a simple transformer. The results demonstrate that CT‐MVP achieves superior performance compared with traditional approaches, particularly in cases involving extended periods of missing data, and slightly outperforms a simple transformer with the same hyper‐parameters.

Purpose of review Vaccination is a key measure for protecting workers against infectious diseases. Immunization schedules are adapted to age, health status, and occupational risks, yet global vaccination coverage remains suboptimal. Declining interest, hesitancy, and refusal contribute to insufficient uptake. In occupational settings, the feasibility and effectiveness of workplace vaccination programs are increasingly explored. Expanding vaccine offerings and providing free access for all workers could substantially improve coverage. The main aim of the article was to reflect on various aspects of vaccination at work in the current era of growing global problems with acceptance, questioning and refusal of vaccination and possibility of occupational health professionals to contributing to improving employee's vaccination. Recent findings Adult vaccination rates remain low despite recommendations from health authorities. Most studies focus on healthcare workers, but recent research examines delivery systems, attitudes, and barriers influencing vaccination among broader worker populations. Workplace-based vaccination and determinants of hesitancy are key areas of interest. The most frequently studied vaccines are for influenza, COVID-19, and diseases resurging due to declining childhood immunization. New directions include cancer prevention, especially through HPV vaccination. Summary Employers and occupational health services should comply with legal health protection duties while promoting voluntary health initiatives, including routine vaccination of adults. Workplace vaccination programs, particularly those organized or supported by employers, are effective strategies to increase immunization coverage and contribute to improved employee health and well being.

Batai orthobunyavirus (BATV) is a mosquito-borne orthobunyavirus that affects both humans and animals, and currently no licensed vaccine is available. The aim of this study was to design a multi-epitope vaccine candidate against BATV using a computational vaccinology pipeline. Predicted B-cell and T-cell epitopes from the nucleoprotein and envelopment polyprotein were selected and assembled into a single construct using an adjuvant and suitable linkers. The final construct comprised 247 amino acids and was predicted to be antigenic with an antigenicity score of 0.7676, non-allergenic, and non-toxic. Population coverage analysis showed a global coverage of 97.2%. Physicochemical evaluation indicated a theoretical pI of 10, instability index of 23.18, aliphatic index of 78.66, and GRAVY value of -0.252, suggesting a stable and hydrophilic profile. Molecular docking with TLR3 produced a docking score of -1418.9, suggesting a favorable interaction. Molecular dynamics simulations for 100ns further indicated the stability of the vaccine-TLR3 complex. Immune simulation predicted the ability of the construct to stimulate immune responses in silico, and in silico cloning analysis supported its expression feasibility. Overall, these findings suggest that the proposed multi-epitope construct has promising predicted immunological and structural properties; however, experimental validation is required to confirm its immunogenicity and protective efficacy.

In Burkina Faso, access to healthcare has long been a challenge, particularly for the mostvulnerable populations. Since 2008, the country has taken significant steps by launching theUniversal Health Insurance Scheme (RAMU), an initiative aimed at expanding healthcoverage. This article explores the factors that led to the emergence of this program. Drawingon public policy analysis tools and a field survey, this study was based on interviewsconducted with key stakeholders from public administration, civil society, and partnerinstitutions who were directly involved in the process. Primary data were supplemented withsecondary data from documentary analysis. The results indicated that the universal healthinsurance scheme emerged from a widely shared observation : the need to better protectpopulations against health risks within the context of social inequality and economic insecurity. This program also reflects Burkina's commitment to the global movementtoward universal health coverage and strengthening of social protection systems.

Acute management of measles: A systematic review of therapeutic strategies.

Depression characterized by heterogeneous symptom profiles, has increasingly been recognized for its cognitive subtype. Gamma entrainment achieved through rhythmic sensory stimulation, has emerged as a promising method to restore neural synchrony. However, the effects and mechanisms of gamma entrainment to cognitive impairment in depression remain poorly understood. We identified the cognitive impairment subgroup in depression by MATRICS Consensus Cognitive Battery. And then, we randomly classified these cognitively impaired patients into intervention and control group, gamma entrainment training was used. Microstates of neuronal oscillations were conducted through scalp electroencephalogram. Microstate dynamics during eyes-closed conditions in the cognitive biotype of depression revealed distinct alterations across specific neural oscillatory parameters. Significant reductions were observed in Class-B global field power (GFP) and Class-D metrics, including GFP, duration, and coverage. Conversely, Class-C Occurrence frequency (Occ) exhibited increased activation in the cognitive biotype. Transition probabilities between Class B and D were also attenuated. After gamma entrainment， cognitive function improved in cognitive biotype of depression without affecting emotional symptoms. Moreover, significant temporal main effects emerged for Class-B microstate dynamics, including increase in global field power, duration, and coverage, alongside Class-D GFP. Our findings delineate a distinct neurophysiological signature of the cognitive biotype of depression, marked by bidirectional dysregulation of large-scale neural synchrony. These results position gamma-driven neuromodulation as a potential therapeutic strategy for restoring network synchrony in cognitive-biased depression, while highlighting microstate metrics as sensitive biomarkers for biotype stratification. Future studies should validate these dynamics in longitudinal cohorts and assess their predictive value for treatment responsiveness.

"Toward tuberculosis elimination: an update on tuberculosis vaccines in clinical trials".

Worldwide Evaluation of Cervical Cancer Self-Sampling Devices.

The rapid development of low earth orbit (LEO) satellite constellations for navigation augmentation represents significant challenges in optimizing coverage performance while minimizing system complexity. A hybrid optimization algorithm based on pelican optimization algorithm and quantum particle swarm optimization (POA-QPSO) is proposed in this paper for multi-objective optimization design of dual-layer Walker constellations. The algorithm integrates the global search capability of the POA and the local exploitation ability of QPSO, effectively balancing exploration and exploitation through a probability-driven dual-phase search mechanism, a three-tier adaptive parameter adjustment strategy, and a pareto frontier maintenance mechanism. Probability factor and quantum tunneling facilitate low-cost deep search in complex non-convex environments. Experiments demonstrate that the algorithm outperforms MOPOA and MOPSO on ZDT test functions, with an 18.5% improvement in IGD metrics. In LEO constellation optimization, the designed dual-layer configuration (800 km/144 satellites in the first layer and 1426 km/56 satellites in the second layer) achieves a 92.7% global coverage, with an average PDOP of 1.78 and 5.8 visible satellites in polar regions. Furthermore, comparative benchmark tests show that the proposed solution outperforms most mainstream algorithms and performs better than traditional medium Earth orbit satellite systems in mid-to-high latitude regions. This research provides an efficient solution for LEO navigation augmentation system design.

Abstract Infrasound propagation is inherently asymmetric and time‐dependent, making accurate atmospheric specifications essential for predicting when and where signals arrive. The Naval Research Laboratory's Ground‐to‐Space (G2S) model is widely used for this purpose, yet discrepancies between G2S predictions and observations highlight the need for improvement. Here we develop Radiosonde‐to‐Space (R2S) specifications by merging direct radiosonde‐based observations of the lower atmosphere with G2S profiles aloft, producing continuous profiles from the ground surface elevation to 150 km. We compare more than 6,000 G2S–R2S pairs for Albuquerque, New Mexico, and conduct propagation modeling on representative endmembers spanning the range of differences. While G2S typically reproduces most R2S‐predicted arrivals, important exceptions occur that would affect event interpretation in real world scenarios. These results demonstrate that although G2S provides robust global coverage, predictions can change when direct lower‐atmosphere observations are incorporated, motivating broader integration of real‐time radiosonde data into global atmospheric specifications.

This paper examines how international media outlets reported the Pahalgam terrorist attack of April 2025 in Jammu and Kashmir and how these narratives shaped emerging India–Pakistan tensions. The primary objective of the study is to analyze variations in language use, attribution of responsibility, and geopolitical framing across global media coverage, and to assess their implications for international perceptions of terrorism and regional security in South Asia. Methodologically, the study employs qualitative discourse analysis informed by Framing Theory and Critical Discourse Analysis. The analysis focuses on news reports, editorials, and explanatory articles published by six major international media organizations-BBC, Reuters, Al Jazeera, The New York Times, CNN, and Xinhua. These outlets were selected based on their global reach, agenda-setting influence, and geopolitical diversity. The dataset comprises articles published between April and June 2025, capturing both immediate reporting on the attack and subsequent coverage of diplomatic and military developments, including India’s Operation Sindoor. The findings identify five dominant discursive patterns across international media narratives: (i) terrorism framed as a regional security threat, (ii) the recurring India–Pakistan blame game, (iii) Kashmir portrayed as a persistent conflict zone, (iv) the articulation of India’s nationalist security discourse, and (v) Pakistan’s diplomatic positioning and denial narrative. Western media outlets largely adopted neutral terminology such as “militants,” emphasizing diplomatic fallout and de-escalation, while other outlets foregrounded political, humanitarian, and strategic dimensions of the crisis. The study demonstrates that international media do not merely report events but actively shape geopolitical interpretations by legitimizing certain state actions and influencing global diplomatic responses. By situating media narratives within broader power relations and ideological frameworks, the paper contributes to scholarship on media framing, terrorism studies, and international relations, highlighting the role of global media as influential actors in the construction of South Asian security discourse.

Influenza's pandemic threat is driven by antigenic drift, which limits the efficacy of conventional vaccines. To address this challenge, we established a clinical serum-anchored computational design pipeline for a broad-spectrum multi-epitope mRNA vaccine (MEMV), bridging the gap between pure in silico design and clinical applicability. Using 36 longitudinal sera (d0/d28/d365) from 12 well-characterized human cohorts (6 vaccine recipients and 6 influenza patients) and high-density antibody-peptide microarrays, we empirically identified 12 immunodominant B-cell linear epitopes from the nucleoprotein (NP) of influenza A (H1N1/H3N2) and B viruses. These experimentally validated epitopes were combined with in silico-predicted conserved helper T-lymphocyte (HTL)/cytotoxic T-lymphocyte (CTL) epitopes (from NP/HA/NA) to construct MEMVs candidates, ensuring high antigenicity, non-toxicity, and 95.63% global HLA coverage. Molecular docking and 100 ns molecular dynamics (MD) simulations confirmed favorable conformational compatibility between MEMVs and Toll-like receptor 3 (TLR3) in silico immunization via C-ImmSim predicted robust B/T-cell responses and protective cytokine (IFN-γ/IL-10) production. Collectively, this pipeline shortens the preliminary design cycle for influenza vaccines, provides a standard epitope-combination strategy, and offers direct targets for follow-up in vitro/in vivo experiments.

Abstract This paper presents a three-stage in-depth review of multi-topic household surveys to assess whether existing data could be used to estimate a truly global moderate Multidimensional Poverty Index (MPI) that is frequently updated and extensively disaggregated. Drawing on previous studies it first summarises data sources presently used for international or national MPIs, setting out some advantages and drawbacks. The review then sets out criteria used for selection and assessment of reviewed datasets, and schematically presents survey contents and their cross-national comparability. It then assesses potential indicators for comparable multidimensional poverty indices, and identifies data gaps according to reviewed datasets. Additionally, the paper highlights some common shortcomings and comparability issues found in multi-topic household surveys, and proposes feasible adjustments. While this paper covers 152 suitable household surveys and 3 cross-country datasets, it cannot be an exhaustive review. Nor does it claim to assess the suitability of the reviewed surveys for any other purposes. It assesses data availability for a set of concrete structures of internationally comparable, frequently updated, and subnationally disaggregated moderate MPIs, in the hope of closing the gap towards global coverage. It uncovers a large data gap and sets out recommendations to address it.

Oropouche virus is an emerging and neglected arbovirus of growing public health concern in Latin America, with recent epidemiological surveillance reporting 832 confirmed cases in 2023 and 5,913 cases during early 2024 in Brazil, predominantly in the Amazon region. Despite its increasing spread, no licensed vaccines or antiviral therapies are currently available. In this study, we aimed to design and computationally evaluate a multi-epitope vaccine candidate targeting the OROV envelopment polyprotein using integrated immunoinformatics, molecular modeling, and immune simulation approaches. The complete polyprotein sequence was analyzed to identify antigenic, non-allergenic, and non-toxic cytotoxic and helper T-cell epitopes. Selected epitopes were assembled into a chimeric construct incorporating an adjuvant, suitable linkers, and a PADRE sequence to enhance immune recognition. Physicochemical properties, tertiary structure, receptor binding, dynamic stability, and immune response potential were comprehensively evaluated in silico. The final vaccine construct comprised 241 amino acids and demonstrated favorable stability with instability index score of 24.95, hydrophilicity with GRAVY score of - 0.241, and with an estimated global population coverage of 94.07%. Molecular docking revealed favourable binding affinity to TLR4 with a binding energy of - 1067.1, while molecular dynamics simulations showed structural stability, with an average RMSD of 0.40nm and limited fluctuations. Immune simulations predicted rapid antigen clearance, robust Th1-polarized responses characterized by strong IFN-γ and IL-2 production, sustained IgG responses, and expansion of memory B and T cells. Overall, these findings indicate that the proposed multi-epitope vaccine construct is stable, immunogenic, and capable of inducing broad immune responses, providing a strong rationale for experimental validation and future vaccine development against Oropouche virus.

This study investigates global news media representations of cross-Strait relations from 2014 to 2023 using the GDELT database, framed within the mediatization of politics. Combining large-scale event data and computational text analysis, it offers a multi-level analysis of representational patterns, structural inequalities, and framing dynamics. Six indicators track longitudinal trends including four continuous indices and two event type distributions, show attention spikes during major political events and a discursive shift toward negative, conflict-focused coverage, even as low-intensity communicative events dominate. Structurally, a source-domain analysis of 50 high-impact outlets employs a six-dimensional Deviation Index to evaluate differences in visibility and event production preferences. Results reveal a concentrated discourse, with Western and Taiwanese media occupying more central positions in agenda-setting processes, with Mainland Chinese outlets appearing comparatively less visible. Textually, topic modeling uncovers five key frames, reflecting a discursive thematic evolution from event-driven, low-politics coverage to high-politics narratives emphasizing conflicts, ideological divides, and great-power rivalry. Complementary sentiment analysis of news headlines using large language model-based tools indicates the persistent dominance of negative actor-sentiment framing in global coverage. Overall, the study underscores an increasingly securitized and asymmetrical pattern of global media representation of cross-Strait relations. Theoretically, the study extends the applicability of mediatization of politics framework to the analysis of cross-Strait communication. Methodologically, it illustrates integrating large-scale event data with machine-learning techniques to examine international news framing in a highly politicized geopolitical context.

BackgroundThe recent outbreak of the Monkeypox virus (MPXV) across multiple regions has highlighted the need for effective vaccine. This study employed an in-silico immunoinformatics approach to design a multi-epitope vaccine against monkeypox virus.MethodsThe IMV heparin binding surface protein (H3L) of MPV was selected as vaccine target. B and T cell epitopes were predicted and evaluated for their toxicity, allergenicity, antigenicity and global population coverage. A multi-epitope construct was assembled using adjuvant and appropriate linkers. The 3D vaccine structure was modelled, enhanced and then checked for its overall structure and physiochemical properties. The in-silico docking vaccine construct and TLR3 receptor was performed to check affinity and stability of vaccine-TLR3 complex. The vaccine’s ability to express and activate the immune system was demonstrated by its cloning into the E. coli plasmid pET-28b (+).ResultsThe selected H3L protein exhibited 92.22% sequence conservation across Monkeypox virus isolates of different continents, supporting its suitability as broad-spectrum vaccine target. The molecular docking and dynamics analysis confirmed both the stability and strong binding affinity of the vaccine construct with the TLR3. Immune stimulation predicted robust humoral and cellular responses, with evidence of immunological memory formation.ConclusionOverall, we proposed a potential vaccine construct that has the potential to effectively prevents monkeypox. However, in-vivo and in-vitro investigations are needed to validate the biological effectiveness and safety of the suggested vaccine.

The recent outbreak of the Monkeypox virus (MPXV) across multiple regions has highlighted the need for effective vaccine. This study employed an in-silico immunoinformatics approach to design a multi-epitope vaccine against monkeypox virus. The IMV heparin binding surface protein (H3L) of MPV was selected as vaccine target. B and T cell epitopes were predicted and evaluated for their toxicity, allergenicity, antigenicity and global population coverage. A multi-epitope construct was assembled using adjuvant and appropriate linkers. The 3D vaccine structure was modelled, enhanced and then checked for its overall structure and physiochemical properties. The in-silico docking vaccine construct and TLR3 receptor was performed to check affinity and stability of vaccine-TLR3 complex. The vaccine's ability to express and activate the immune system was demonstrated by its cloning into the E. coli plasmid pET-28b (+). The selected H3L protein exhibited 92.22% sequence conservation across Monkeypox virus isolates of different continents, supporting its suitability as broad-spectrum vaccine target. The molecular docking and dynamics analysis confirmed both the stability and strong binding affinity of the vaccine construct with the TLR3. Immune stimulation predicted robust humoral and cellular responses, with evidence of immunological memory formation. Overall, we proposed a potential vaccine construct that has the potential to effectively prevents monkeypox. However, in-vivo and in-vitro investigations are needed to validate the biological effectiveness and safety of the suggested vaccine.

Suboptimal breast milk production during postpartum is a reason for formula feeding, thus preventing exclusive breastfeeding targets. According to the WHO, the global coverage of exclusive breastfeeding should reach 68% by 2023. Non-pharmacological efforts can be implemented by administering moringa leaf tea, which contains flavonoids, phytosterols, alkaloids, saponins, and tannins, which function as lactogogues to stimulate the hormones prolactin and oxytocin. The purpose of this study was to determine the effect of administering moringa leaf tea to breastfeeding mothers at the Fitriatul Laili Rejoagung Banyuwangi TPMB in 2025 on their ability to increase breast milk production. This study involved 30 postpartum mothers: 15 in the intervention group and 15 in the control group. The study used a two-group quasi-experimental pretest-posttest design. Five grams of moringa leaf tea, 200 milliliters daily for seven days, was administered to the intervention group. The control group received normal postpartum care. The sampling method used was sequential sampling. Ten breast milk production indices were used as instruments. A t-test was used for data analysis. This study has been ethically reviewed. According to the findings, the average breast milk production in the intervention group increased from 5.87 to 8.87, while in the control group it increased from 6.00 to 6.60. The intervention group's averages differed from the control group by 3.00 and 0.6, respectively. The p-value was 0.000, indicating that tea made from moringa leaves can increase breast milk production. Therefore, this tea is recommended as a natural substitute for breast milk production.

Based on World Health Organization (WHO) data, the global coverage of exclusive breastfeeding reached 80% in 2024. However, the success of exclusive breastfeeding is influenced by various factors, including family support and postpartum mothers’ knowledge. Exclusive breastfeeding is the primary nutritional requirement for infants during the first six months of life. Despite its importance, the coverage of exclusive breastfeeding in Indonesia remains relatively low, at 66.01% in 2024. Family support and postpartum mothers’ knowledge regarding exclusive breastfeeding are considered crucial determinants of successful exclusive breastfeeding practices. This study aimed to analyze the influence of family support and postpartum mothers’ knowledge about exclusive breastfeeding on the success of exclusive breastfeeding at Alalak Tengah Public Health Center, Banjarmasin City. This research employed a quantitative approach with a cross-sectional design. A total of 38 postpartum mothers were selected using purposive sampling. Data were analyzed using univariate and bivariate analyses with the Chi-Square test. The results showed a significant relationship between family support (p = 0.005) and maternal knowledge (p = 0.000) with the success of exclusive breastfeeding. Most mothers who had good family support and high knowledge successfully practiced exclusive breastfeeding, accounting for 28 out of 38 postpartum mothers. It can be concluded that family support and postpartum mothers’ knowledge significantly influence the success of exclusive breastfeeding.