In conflict-afflicted regions like Ukraine, disrupted health services, displacement, and logistical disturbances have compromised immunization and trust, underscoring the need to understand behavioral, access, and conflict dynamics for resilient strategies. To simulate the interaction between behavioral, structural, and social variables in predicting changes in vaccination beliefs and uptake in war-impacted Ukraine. We conducted a geographically diverse cross-sectional survey across 557 Ukrainian hromadas (local communities) during the ongoing war to assess vaccine confidence and behavioral determinants using an integrated psychological-computational framework. Empirical data were analyzed through k-means clustering and agent-based modeling (ABM) to simulate vaccination dynamics under conflict conditions. This survey-informed ABM examines how social contagion, healthcare access disruption, and conflict exposure may jointly shape vaccination behavior in a conflict-affected setting. To our knowledge, it represents one of the first behavioral simulation frameworks informed by survey data collected during the ongoing war in Ukraine. Our agent-based modeling suggested that vaccination uptake in Ukraine is governed by a dynamic interplay between structural access and peer influence. Belief transitions reached 88%, whereas vaccination uptake increased 3%-15% due to access barriers. Conversely, peer dynamics increased vaccination coverage to 69%-89%, leading to a smoother coverage distribution. Sensitivity analyses indicated that peer conformity was the dominant driver, suggesting a collective mechanism linking social contagion and health behavior adoption. Our findings suggest that structural access and peer influence jointly drive vaccine uptake during conflict, introducing a survey-based agent-based framework that links belief dynamics to behavior. These insights provide actionable pathways for equitable immunization policies in fragile and conflict-affected settings.
Background: The full invasion of Ukraine by Russia in 2022 has created a situation of sustained stress for the Ukrainian population. Initial surveys indicate that Ukrainians have experienced elevated rates of anxiety, depression, and posttraumatic stress disorder (PTSD) since the onset of the war. Most research has focused on adults and there is relatively less study on children and adolescent mental health. Research that has been conducted is limited by (a) predominant reliance on parent reports of children's mental health, (b) biased sampling, (c) lack of integrated child and caregiver reports, and (d) cross-sectional designs.Method: The Ukrainian Families Navigating Insecurity, Trauma, and Yielding Strength (UNITY) initiative is a nationally-representative longitudinal cohort study of mental health in Ukrainian children aged 8-16 years. Children (N = 3,000) will be recruited via schools from 22 oblasts across Ukraine. Sampling will be stratified from regions with high, medium, and low exposure to Russian attacks during the war. Recruitment will be stratified according to 8-12 and 13-16 years of age (on a 1:1 basis), gender of children (1:1), and urban vs. rural region (1:1). One caregiver of the child participant will also be assessed. Children will be assessed for anxiety, depression, PTSD, prolonged grief, externalizing problems, suicidality, positive affect, social and family support, posttraumatic cognitions, somatic symptoms, functioning, and posttraumatic growth. Caregivers will be assessed for family exposure to traumatic events, psychological distress, prolonged grief, psychological wellbeing, parenting practices, hope, and positive affect. The UNITY study will initially be conducted over three waves, with the expectation of ongoing collection following the war. The protocol was pre-registered at https://archive.org/details/osf-registrations-n62gy-v1.Discussion: The UNITY study will provide much-needed evidence regarding the mental health needs of young Ukrainians and their families, and the factors that moderate psychological adjustment during and after the war. The war in Ukraine has placed enormous psychological strain on young Ukrainians.The UNITY study is a longitudinal survey of mental health in children and their caregivers.This study will yield longitudinal evaluations of children’s and caregivers over multiple waves.
This paper explores the management of mass casualty incidents in Eastern Ukraine, focusing on the application of the Eight Domains of Mass Casualty Management by the Ukrainian Medical Service. Following the Russian invasion, Ukraine's military and civilian health services have had to adapt to unprecedented casualty rates to prevent overwhelming the healthcare system. The Eight Domains-distribution, decompress, delay, delegate, deliver faster and deliver better, dynamic levels of care, and de-escalation-serve as compensatory mechanisms to manage this chronic major medical incident. The paper highlights the innovative approaches and adaptive strategies employed by the Armed Forces of Ukraine (AFU) Medical Services to maintain effective medical care despite the high demand and constrained resources. The report underscores the importance of international support and continued research to enhance the resilience and capability of the AFU Medical Services in responding to ongoing and future conflicts and proposes future direction for all military medical services to meet the challenges of large scale conflict operations and warfighting at scale.
The ongoing war in Ukraine have exposed the population to unprecedented stressors the long-term metabolic consequences of which remain insufficiently characterised. This study evaluated changes in glycaemic control and related biomarkers in the Ukrainian population during ongoing war between 2021 and 2024. This large-scale, single centre repeated cross-sectional study analysed routine laboratory data across Ukraine from January 2021 to December 2024. We included a convenience sample of adults aged 18-90 years with complete demographic data who underwent on fasting plasma glucose (FPG) (108,346 individuals), of whom 86,077 also had glycated haemoglobin (HbA1c) results. Additional data was available for 2502 insulin and 9000 cortisol measurements. Biomarker trends were assessed annually and quarterly, stratified by sex, age, and geographic region, and categorised as corresponding to normoglycemia, prediabetes, and diabetes. In 2021, median HbA1c was 5.71% (interquartile range; IQR 5.34-6.34), with 28.7% of individuals in the prediabetic and 22.3% in the diabetic range. By 2024, median HbA1c rose to 5.91%, with prediabetes increasing from 28.7% to 37.7%, and diabetic levels rate growing from 22.3% to 26.4%. As a result, 64% of all individuals tested in 2024 had HbA1c above the normoglycaemic threshold. Women and working-age adults showed the greatest glycaemic deterioration, despite men having higher absolute levels. The Ukrainian population experienced significant metabolic deterioration during the war. Rising HbA1c and the growing prevalence of prediabetes and diabetes, particularly among women and younger adults, indicate escalating cardiometabolic risks. Future prospective longitudinal studies are needed to evaluate the long-term effectiveness of integrated metabolic and psychosocial interventions in conflict-affected populations. National Research Foundation of Ukraine.
Midwifery in Ukraine is currently undergoing a transformative shift from deep-seated traditional roots toward professional autonomy and alignment with international standards. Historically, care transitioned from village midwives, known as babas or spovytukhas, to formalized training in the 18th century, and scientific professionalization led by figures such as Ivan Lazarevich, who championed a physiological approach to childbirth. However, the Soviet period introduced a physician-led, medicalized model that often integrated midwifery with nursing at a sub-degree level. Currently, the profession faces acute modern pressures caused by the 2022 full-scale invasion, which has disrupted services, forced births into shelters, and contributed to a rise in pregnancy complications. Systemic challenges include significant workforce shortages and curriculum gaps; a 2023-2024 United Nations Population Fund (UNFPA) assessment found that Ukrainian curricula cover a good percentage of key sexual and reproductive health and rights (SRHR) competencies, but not all. To address these issues, Ukraine is leveraging the Bologna Process and European Union (EU) accession aspirations to modernize education toward Bachelor of Science (BSc), Master of Science (MSc), and doctoral (PhD) levels. International collaborations, such as the 'Midwifery Bridges' project with Sweden, aim to adopt autonomous care models. Furthermore, simulation-based education has emerged as a critical technological tool for safely developing clinical dexterity and emergency preparedness amid wartime disruptions. Ultimately, these reforms seek to establish midwives as independent, responsible birth attendants providing woman-centered, evidence-based care.
Background: Ukraine has substantial regional differences in climate, landscape, forest cover, and river networks, which may influence leptospirosis transmission. However, recent monthly oblast-level variation in leptospirosis incidence has not been systematically described. We used newly available surveillance data for 2023-2025 to assess seasonal and regional patterns of leptospirosis and their associations with weather, climatic zone, forest cover, and river network density. Methods: We analyzed surveillance data from 23 Ukrainian oblasts. Incidence was assessed by month, oblast, and climatic zone. Weather data were aggregated monthly; forest cover and river network density were included as predictors. Associations were assessed using correlation, cross-correlation, and Random Forest ML models. Results: Incidence showed a clear seasonal increase, reaching its highest levels in late summer and autumn, approximately one to three months after seasonal peaks in temperature and precipitation. The highest incidence was observed in Zakarpattia, Chernihiv, and Ternopil oblasts, while incidence by climatic zone was highest in the Carpathian group and lowest in the Steppe zone. Among weather variables, average temperature showed the clearest delayed association with leptospirosis incidence. River network density was the leading ecological predictor in the adjusted models. The positive unadjusted association between forest cover and incidence became negative after adjustment for river network density, suggesting that these variables captured overlapping ecological characteristics. In the Random Forest analysis, river network density was the top-ranked predictor, and the best-performing model achieved an AUC of 0.795. Conclusions: Leptospirosis incidence in Ukraine varied substantially by season and region. Delayed temperature effects, river network density, and forest cover were associated with regional risk. Monthly oblast-level surveillance with climatic and ecological data may help monitor leptospirosis risk, but war-related disruption to diagnosis and reporting should be considered.
Ukraine has experienced overlapping shocks from the COVID-19 pandemic and a full-scale war, with potential impacts on maternal and perinatal health. We examined national-level changes in these outcomes between 2019 and 2024. In this population-based ecological study, publicly available Ministry of Health data were analysed to examine trends in deliveries, births, and maternal and perinatal outcomes. Changes were assessed using pairwise comparisons, absolute risk differences, and effect sizes. Annual estimates were compared with pre-pandemic, preceding-year, and wartime estimates. Deliveries and births declined by approximately 40%, predominantly during the first wartime year. Between 2019 and 2024 (298,066 and 176,842 deliveries, respectively), the prevalence of diabetes in pregnancy increased from 0.88% (n = 2634) to 2.66% (n = 4707), hypertensive disorders from 3.80% (n = 11,332) to 5.45% (n = 9633), severe postpartum haemorrhage from 0.36% (n = 1070) to 0.53% (n = 941). Among 302,190 and 179,192 births, respectively, preterm births increased from 5.59% (n = 16,907) to 6.25% (n = 11,195), very low birthweights from 1.05% (n = 3184) to 1.29% (n = 2305), and extremely low birthweights from 0.44% (n = 1335) to 0.60% (n = 1068). Pregnancy-related and perinatal mortality, particularly stillbirths, were higher during the second year of the pandemic but not during wartime. Early neonatal mortality did not change throughout. Overlapping crises were associated with fewer births and increased maternal morbidity. Although pregnancy-related and perinatal mortality increased during the pandemic, their relative stability during wartime may suggest preservation of maternal and newborn services, potentially supported by international assistance. Continued support for maternal and neonatal healthcare services remains important in crisis-affected settings. No funding was received.
War reshapes the conditions under which reproductive decisions are made and pregnancy is experienced. Prolonged insecurity, displacement, economic instability, disruption of healthcare, and reduced social support may lead women and families to postpone pregnancy or face pregnancy and childbirth under constrained conditions. These challenges highlight the need for research on how war-related stress and trauma affect women's reproductive behavior and perinatal mental health. This prospective cohort study will recruit at least 328 women through healthcare institutions providing reproductive and perinatal care. Eligible participants will include non-pregnant women, pregnant women, and women within the first year postpartum. Where feasible, partners of enrolled women will also be included to provide complementary dyadic data. Participants will be followed from baseline to 3, 6, and 12 months. Data will be collected through web-based questionnaires and routine clinical records. No experimental intervention will be delivered, and participation in the study will not modify standard clinical care. Repeated measures will capture mental health, reproductive intentions and behavior, war-related and perinatal experiences, and key sociodemographic and obstetric characteristics. Primary analyses will use mixed-effects models to examine mental-health trajectories, with reproductive status modeled both as a baseline cohort characteristic and, where participants change status during follow-up, as a time-varying covariate; reproductive transitions will also be examined as secondary longitudinal outcomes. This protocol addresses an important gap by using a longitudinal design to examine women's experiences in a wartime setting. By situating mental health within disrupted reproductive plans, insecurity, healthcare strain, and family-level experiences, the study may help identify how armed conflicts shape both psychological vulnerability and reproductive decision-making. The findings may inform more responsive care for women affected by war. ClinicalTrials.gov; identifier: NCT07551934.
Mental health in the UK has worsened over the last 15 years, a period marked by major systemic shocks. We investigated annual changes in population-level psychological distress and the impact of five systemic shocks: the referendum on European Union membership (Brexit), two COVID-19 lockdowns, Russia's invasion of Ukraine and the UK Government's 2022 'mini-budget'. We used longitudinal survey data from the UK Household Longitudinal Study, including 87 857 between years 2009 and 2024. We used Bayesian time series models to evaluate annual changes in psychological distress and the association with each shock, including subgroup analyses by age group, sex, ethnicity, deprivation quintile and employment status. We found evidence of increasing psychological distress from 2009 to 2023 (+1.085 point increase in 12-item General Health Questionnaire scores; credible interval (CrI) 0.987 to 1.184). In interrupted time series models, we observed increased psychological distress immediately after the Brexit referendum (+0.117, CrI 0.029 to 0.205) and the first COVID-19 lockdown (+0.649; CrI 0.531 to 0.767), with more insidious monthly increases in psychological distress after the Russian invasion of Ukraine (+0.010, CrI 0.004 to 0.023) and the 2022 mini-budget (+0.015, CrI 0.005 to 0.034). We found considerable sociodemographic variation by age, sex, ethnicity, deprivation and employment status. We found that some systemic shocks had detrimental effects on population mental health in the UK, being most pronounced for the Brexit referendum and first COVID-19 lockdown. Our results demonstrate that population mental health can change in response to systemic shocks. This should inform the design of responsive clinical and public mental health provision.
Chaunocephalus ferox (Rudolphi, 1795) is an intestinal trematode of the family Echinostomatidae that commonly infects waterbirds, including the Asian Openbill (Anastomus oscitans). Despite its wide geographic distribution and ecological relevance in migratory birds, molecular data for this species remain limited. This study aimed to characterize the genetic variation and phylogenetic position of C. ferox recovered from a deceased Asian Openbill in Thailand. Adult flukes were examined using nuclear (28S rDNA and 5.8S-ITS2) and mitochondrial (cytochrome c oxidase subunit 1; CO1) markers. Sequence analyses revealed low intraspecific variation among Thai isolates, with a single variable site detected in each marker. However, comparisons with sequences from Egypt, China, and Ukraine demonstrated measurable genetic divergence, suggesting possible geographic and host-associated structuring among C. ferox populations. Phylogenetic analyses based on nuclear and mitochondrial datasets consistently supported the monophyly of C. ferox within Echinostomatidae and confirmed its distinct genetic lineage among echinostomes. These findings provide baseline molecular data for a trematode parasite of migratory waterbirds, highlighting the potential role of avian hosts in the long-distance dispersal of helminths across wetland ecosystems. Broader geographic sampling is needed to better understand the population structure and evolutionary dynamics of this parasite.
In light of growing concerns about sustainable development and green innovation, the green market has progressively taken center stage in the financial markets. From the nonlinear information transmission angle, we look into the interconnectedness between the global banking sectors and the green markets using transfer entropy causal networks, containing the Dow Jones Green Bond Index (SPGB), Dow Jones Sustainability Index (DJSI), The S&P Global Clean Energy Index (SPCL), and MSCI World ESG Leaders Index (ESGL). We observe significant bidirectional causal relationships between two markets. The banking industries of developed nations and emerging economies like South Korea, Indonesia, and India are the most important, while four green markets are vital. Furthermore, using the CEEMDAN-SE-KM approach, this study also investigates the two markets' heterogeneous performance at various time scales. The causal relationships between two markets exhibit heterogeneity at time scales, and that is most noticeable at the short-term scale. Additionally, after the COVID-19 pandemic and the conflict between Russia and Ukraine, there is an increase in the causal relationships between the two markets and a higher efficiency of information transmission. These results help regulatory bodies and green market players have a more thorough understanding of and dynamic regulation of the green market.
Magnusiomyces clavatus, formerly Saprochaete clavata or Geotrichum clavatum, is an ascomycetous yeast found in the environment as well as the gastrointestinal and respiratory tracts of humans. It has been described as an emerging, albeit rare, cause of invasive fungal disease affecting immunocompromised patients. Intrinsic resistance to fluconazole and echinocandins has been theorized; however, little else is known regarding optimal treatment regimens for this opportunistic pathogen. To our knowledge, only 13 infectious cases have been described in pediatric patients, all of which utilized a combination of antifungals including liposomal amphotericin B (LAmB) and voriconazole with or without flucytosine (5-FC). Here we report a case of a 4-year-old, 12.3 kg, female patient who immigrated from Ukraine and was admitted to our institution for an allogeneic umbilical cord blood transplant in the setting of bone marrow failure secondary to Fanconi anemia. On day +6 after cell transplantation, the patient developed febrile neutropenia found to be because of invasive M. clavatus fungemia on day +7. The patient was empirically treated with LAmB, micafungin, and posaconazole (POS), the latter of which failed to reach therapeutic levels. Ultimately, our patient defervesced and cleared blood cultures after transitioning LAmB to 5-FC, followed by definitive treatment with isavuconazole (ISA) monotherapy. To our knowledge, this is the first case of pediatric M. clavatus ultimately treated with 5-FC plus POS followed by ISA alone.
Military conflicts constitute an increasingly important yet still insufficiently quantified source of environmental contamination in agricultural ecosystems. This study investigated soils affected by missile strikes during the Russian aggression in Ukraine, with particular emphasis on heavy metal accumulation, radionuclide occurrence, and associated phytotoxic effects on wheat (Triticum aestivum L.). Geochemical analyses using X-ray fluorescence spectroscopy revealed pronounced enrichment of Pb, Zn, Cu, Cr, Ni, and Mn in crater soils, frequently exceeding local geochemical background levels and environmental guideline thresholds. Elevated activity concentrations of ^137Cs were additionally detected, indicating contamination associated with explosive materials and projectile components. Despite locally increased radionuclide levels, the calculated radiological indices demonstrated that the investigated soils do not currently pose a significant radiological hazard to human health. The contamination was accompanied by soil acidification, compaction, and degradation of physical structure, suggesting long-term disturbance of soil functioning in affected agricultural areas. Among the detected contaminants, Pb was consistently enriched in crater soils and was therefore selected as a representative model toxicant to investigate the biological mechanisms linking field-observed contamination to crop responses under controlled conditions. Hydroponic experiments demonstrated that Pb exposure induced a clear, dose-dependent inhibition of plant growth, biomass accumulation, and stress tolerance indices, whereas low Pb concentrations produced a slight hormetic response. Anatomical analyses of wheat roots revealed substantial structural reorganisation, including reduced stele and xylem development, enhanced cortical porosity, increased endodermal suberisation and lignification, and reduced vessel diameter, potentially limiting water and nutrient transport. Strong correlations between Pb concentration, anatomical modifications, and morphophysiological responses indicate that root structural disruption represents a major mechanism of toxicity. The results demonstrate that missile-derived contamination may significantly affect soil quality and crop performance even outside active combat zones. Furthermore, the study highlights the usefulness of root anatomical traits as sensitive biomarkers for early detection of military-induced soil stress and provides new insight into the combined, radiological and mechanistic biological approaches for assessing post-conflict agricultural environments.
The escalating challenge of managing vector-borne pathologies necessitates the advancement of vector control strategies that are both highly potent and environmentally benign. This research evaluates the insecticidal efficacy and environmental plasticity of three Bacillus thuringiensis subsp. israelensis (Bti) H14 strains 33, 87/1, and 7-1/3 against laboratory and wild mosquito populations. In controlled laboratory assays, cultures with a spore density of 4.0-4.4 × 109 spores/mL demonstrated significant larvicidal activity against larvae of all instars (L1-L4) of Aedes aegypti. The median lethal concentration (LC50) was established between 1.15 and 1.48 µL/L, resulting in cumulative mortality rates of 95-96% within a 48 h exposure window. Proteomic profiling via SDS-PAGE and Western blotting validated the robust synthesis of the signature δ-endotoxin complex, specifically verifying the presence of Cry4Aa, Cry4Ba, Cry11Aa, and Cyt1Aa. Field applications in specific forest (Polissya) and steppe (Forest-Steppe) aquatic biotopes of Ukraine-characterized by distinct physicochemical profiles (differing significantly in light exposure, water hardness, salinity, and suspended solids)-substantiated the stability of the liquid formulations, achieving larval suppression rates of 95-100% within 48 h against wild Aedes-dominated assemblages at application rates of 0.25-1.0 mL/m2 (equivalent to 2.5-10.0 L/ha). The demonstrated environmental adaptability suggests these novel strains are viable candidates for broad-spectrum ecological engineering applications. Their integration into sustainable vector control strategies offers a mechanism to enhance biosecurity without compromising the ecological balance of local biocenoses.
Human activity recognition (HAR) based on smartphone and wearable sensor data is commonly addressed using statistical learning methods and deep neural networks that often provide strong predictive performance, but at the expense of limited interpretability and substantial computational and energy requirements. Such limitations reduce their suitability for deployment in practical sensing environments where model decisions must be transparent, verifiable and executable on resource-constrained devices. In this work, we investigate the Convolutional Tsetlin Machine (CTM) for multimodal HAR using only the raw inertial signals (9 × 128) of the UCI-HAR dataset, rather than its pre-computed 561-feature representation. The Tsetlin Machine is a novel neuro-symbolic machine learning approach that offers two important advantages over many conventional machine learning methods: (i) it learns logic-based decision rules that support human inspection and provide a transparent basis for analyzing model decisions, and (ii) it operates with comparatively low computational complexity, making it well suited to efficient and low-power on-device learning. The proposed study systematically analyses the contribution of different feature modalities by decomposing the inertial signals space into semantically defined subsets according to: (i) sensor source: accelerometer and gyroscope; (ii) signal group: gyroscope angular velocity, body and total acceleration (including gravity); (iii) coordinate axis: x, y and z. A separate CTM classifier was trained for each modality and its combinations in order to determine the relative discriminative value of each modality group for activity classification. In addition to predictive performance, the study emphasizes the interpretability of the CTM model ensured by expressing each decision in the form of propositional clauses, thereby enabling visualization and direct inspection of the modality-specific patterns supporting each activity class. Owing to its symbolic structure and modest computational demands, the CTM provides a principled framework for the design of explainable, resource-efficient and deployable HAR systems. The proposed work therefore contributes toward trustworthy multimodal sensing by jointly addressing predictive performance, interpretability and suitability for embedded and mobile platforms.
WNTs are a family of signaling proteins involved in numerous biological processes, including morphogenesis, oncogenesis, cell migration and proliferation, cellular specialization, and tissue regeneration. WNT proteins are characterized by a distinctive structure comprising two domains resembling a "thumb" and an "index finger," which enables their interaction with cellular receptors. Despite the identification of 19 WNT proteins in humans, three-dimensional structural data are available for only a subset, highlighting the importance of studying WNT proteins using in silico approaches. This study presents the in silico structural analysis of three human WNT family members - WNT1, WNT3A, and WNT5A - across multiple levels of protein organization. The primary structure of these proteins was analyzed for amino acid composition, and secondary structure predictions for α-helices, β-strands, and loops were correlated with domain structures characteristic of WNT proteins. Tertiary structures were modeled using homology modeling and deep-learning algorithms, and structural properties were investigated through molecular dynamics simulations. The ability of WNT proteins to adopt several closed and open conformational states was demonstrated, as well as the role of the flexibility of the β-hairpin forming the "index finger" in mediating conformational transitions. Thus, by applying a comprehensive bioinformatic approach to WNT proteins, the study highlights the advanced capabilities of in silico methods for analyzing protein structures at multiple levels of organization.
Nitrogen dioxide (NO2) is a hazardous atmospheric pollutant that requires reliable detection technologies with high sensitivity and clear physical interpretability. In this study, the influence of porosity on the impedance response of porous gallium arsenide (GaAs)-based gas sensors was systematically investigated under NO2 exposure. A series of samples with controlled porosity in the range of 10-70% was fabricated by electrochemical etching and analyzed using impedance spectroscopy in the frequency range of 1-100 kHz. The results show that increasing porosity enhances impedance dispersion and gas sensitivity, particularly in the low-frequency region of 5-10 kHz, where the response to NO2 is most pronounced. The concentration dependence of the impedance magnitude exhibits nonlinear sigmoidal behavior, while the maximum relative sensitivity is observed at an intermediate porosity of approximately 52-53%. This indicates a balance between adsorption capacity and electrical conductivity. These findings show that porosity is a key parameter governing the impedance-based sensing behavior of the porous GaAs and support the use of frequency-domain analysis for studying morphology-response relationships in semiconductor gas sensors.