Pheidole megacephala (Fabricius), the African big-headed ant, is one of the most significant invasive species and has become dominant in disturbed environments worldwide. Its presence poses serious threats to agriculture and biodiversity, highlighting the need for innovative and sustainable pest management strategies. One promising direction is the use of positive-sense single-stranded RNA (+ssRNA) viruses as biocontrol agents. This study investigates a novel control approach by integrating Pheidole megacephala virus 3 (PmV3), a member of Picornavirales, into alginate hydrogel as a viral delivery system for P. megacephala. Alginate hydrogel effectively served as a stable and environmentally friendly carrier, enabling controlled release of +ssRNA viruses over time. Despite replication occurring primarily in worker ants, PmV3 infections were detected in queens and brood by Day 17 after inoculation, indicating successful colony-level viral transmission. Reverse-transcription RT-PCR confirmed viral presence and tagged RT-PCR verified active replication within workers. Kaplan-Meier survival analyses showed significantly reduced worker ant survival in four of 10 treated colonies, demonstrating measurable pathogenic effects of the viral treatment. This study demonstrates the successful incorporation and delivery of +ssRNA viruses using alginate hydrogels and provides clear evidence of viral transmission, replication and colony-level impacts in P. megacephala. These findings highlight the potential of virus-loaded hydrogels as a promising, environmentally friendly tool for developing biologically based control strategies against invasive P. megacephala populations. © 2026 Society of Chemical Industry.

ABSTRACT This study presents the first systematic analysis of neurocranial terminology in Miftah-ı Teşrih (1874), translated from the French Petit Atlas Complet d’Anatomie Descriptive du Corps Humain into Ottoman Turkish by Hristo Stambolski, a prominent anatomy instructor at the Imperial Medical School (Mekteb-i Tıbbiye-i Şahane). The research evaluates the technical accuracy and alignment of the work with modern standards, reflecting the institution’s vision to synchronize medical education with universal scientific norms. A total of 75 unique neurocranial terms were compared with modern Terminologia Anatomica (TA2) standards based on five methodological parameters (P1–P5). Findings reveal a high degree of precise semantic correspondence (P1) of 85.3% (n = 64) between Stambolski’s terminology and TA2. Key observations include the use of sophisticated technical terms such as Mîzâbe-i Kehfiyye (Carotid sulcus) and instances of pedagogical simplification, such as Kavs-ı Hâcibî, which encompasses both the Arcus superciliaris and Margo supraorbitalis. Additionally, historical localization shifts in terms such as Eminentia orbitalis (İrtifâ’-ı Hacâcî) were identified. Stambolski’s work represents a successful transmission of 19th-century French neuroanatomical tradition into Ottoman medical literature. This high terminological fidelity, integrated with a corporate strategy to unify medical language, positions Miftah-ı Teşrih as a critical bridge between historical anatomical tradition and modern neuroscience terminology.

Wireless sensor networks (WSNs) deployed for seismic monitoring must sustain long-term operation under strict energy constraints, where premature node failure degrades spatial coverage and detection reliability. This paper presents a safety-constrained reinforcement learning framework for transmission scheduling in energy-harvesting seismic WSNs. The proposed approach integrates Proximal Policy Optimisation (PPO) with action masking and a runtime guard-layer safety filter that enforces battery-preservation and load-balancing constraints without retraining. The guard layer intercepts policy actions and substitutes safe alternatives when constraint violations are detected, using a scoring function that combines battery headroom with network-wide load equity. Experiments across three network scales (10, 15, and 30 nodes) with solar energy harvesting demonstrate that the guard-enhanced PPO achieves 99.46% transmission success at 30 nodes while maintaining 66.47% node survival—a 58.3% improvement in survival over the highest-reward baseline (Closest) at the cost of only a 6.2% reduction in cumulative reward. Crucially, the guard-enhanced policy outperforms the unconstrained PPO baseline simultaneously on cumulative reward (), transmission success ( pp), and node survival (), demonstrating that hard safety constraints, when properly aligned with the system’s energy model, provide both performance and safety gains rather than a fundamental trade-off. Sensitivity analysis across event rates ( and ) confirms that the guard layer’s advantage persists under both moderate and extreme monitoring conditions. Analysis across scales reveals distinct operational regimes: at 10 nodes, heuristic baselines are near-optimal; at 30 nodes, learned policies dominate, and safety filtering becomes critical for sustained operation.

Heart failure with reduced ejection fraction treatment with quadruple therapy reduces hospitalizations and improves patient survival. Despite evidence-based recommendations to initiate and up-titrate guideline-directed medical therapy to target doses, a gap remains in the achievement of target doses of guideline-directed medical therapies. Evidence-based tools have shown improvement in obtaining target doses of guideline-directed medical therapies using shared decision-making concepts, patient activation videos, and checklists. We conducted a cohort-controlled quality improvement study that aimed to evaluate a digital care platform for the implementation of shared decision-making using a digital patient activation tool, video, and checklist to achieve guideline-directed medical therapies among patients with heart failure with reduced ejection fraction discharged from a large academic medical center. In the implementation phase, 64 patients sent the patient activation video and checklist, which had successful transmission and good engagement, as compared to poor transmission and engagement in the pre-implementation cohort. Though adaptations in digital delivery processes took place throughout the implementation phase, only 26.2% of patients viewed the patient activation video at 2 weeks post-discharge. The trend in improved guideline-directed medical therapy between the pre-implementation and post-implementation cohorts was not statistically significant. Lessons learned for digital dissemination are discussed.

Flea-borne transmission of the plague bacillus, Yersinia pestis, occurs through two regurgitation-based mechanisms. One, called early-phase transmission (EPT), takes place within 24-96 hours post-infection through a poorly understood mechanism. The second requires an intrinsic incubation period and relies on the formation of a biofilm obstructing the flea's proventriculus. Although these mechanisms have been described in different flea species, they have never been characterized in Xenopsylla brasiliensis and Synopsyllus fonquerniei, which are two flea vectors suspected and confirmed to contribute to Y. pestis transmission in Madagascar. Because EPT may facilitate rapid pathogen spread, this study aimed to experimentally assess the ability of both flea species to transmit Y. pestis via EPT. Cohorts of starved X. brasiliensis and S. fonquerniei fleas were artificially infected with Y. pestis. From day 1 (D1) to day 4 (D4) post-infection (p.i.), pools of ten infected fleas were fed on sterile mouse blood. After feeding, bacterial loads in both the blood and the fleas were determined by Colony Forming Unit (CFU) counts on blood agar to assess bacterial transmission. Fleas were also observed under a binocular microscope to determine whether the foregut was blocked, as indicated by the presence of fresh blood in the foregut but not in the midgut. The results showed that X. brasiliensis and S. fonquerniei were able to transmit Y. pestis as early as 24 hours p.i., although transmission events were infrequent. No correlation was found between flea bacterial load (ranging from 4.0 x 101 to 4.4 x 105 CFU) and transmission success. Blockage was observed in 1% of S. fonquerniei (D3 and 4 p.i) and 0.75% of X. brasiliensis (D4 p.i.), without detectable transmission by these blocked fleas during the experimental window. This study provides the first experimental evidence that X. brasiliensis and S. fonquerniei can support early-phase transmission of Y. pestis and are capable of developing proventricular blockage under laboratory conditions. These findings refine our understanding of the potential contribution of these flea species to plague transmission dynamics in Madagascar.

Biological invasions often generate complex ecological paradoxes, particularly when invasive species act as ecosystem engineers that simultaneously compete with and benefit native communities. Understanding these dual dynamics is critical for managing urban biodiversity. Here, we investigated the interactions between invasive monk parakeets (Myiopsitta monachus) and native avifauna to assess the balance between behavioral competition and structural commensalism. We assessed competition through (1) agonistic interactions and (2) correlations between parakeet abundance and that of native species. Commensalism was evaluated by analyzing tenant species in parakeet nests and the drivers of their occurrence. Agonistic interactions manifested through highly species‐specific conflicts: Density‐dependent aggression with rock pigeons (Columba livia) was strictly reciprocal, while parakeets directed targeted intimidation toward Eurasian magpies (Pica pica). Conversely, direct agonistic encounters involving either Eurasian tree sparrows (Passer montanus) or house sparrows (Passer domesticus) were negligible. However, spatially, Passer spp. abundance correlated negatively with the number of parakeet nest chambers (a proxy for parakeet abundance), whereas common blackbirds (Turdus merula) showed a positive correlation. Furthermore, parakeets provided a massive structural subsidy. We recorded 11 native species breeding in 48% of surveyed parakeet nests (N = 252). Tree sparrows and stock doves (Columba oenas) dominated this tenant community, accounting for 86% of native breeding pairs. Native breeding abundance—including tree sparrows, stock doves, and rock pigeons—as well as total species richness scaled positively with nest chamber density. Yet, active parakeet presence limited nest use for stock doves but did not deter tree sparrows or rock pigeons from successful co‐nesting. Our findings reveal a dual ecological dynamic: Parakeets show a negative spatial correlation with declining urban sparrows, yet simultaneously act as ecosystem engineers by providing valuable breeding habitats for local biodiversity. However, without data on tenant reproductive success and pathogen transmission, these novel subsidies risk functioning as ecological traps. Consequently, while indiscriminate nest removal could inadvertently harm native tenants, current evidence does not confirm the long‐term safety of this commensalism. Effective management must transcend simple eradication, adopting a holistic framework that weighs the loss of nesting resources against the competitive and sanitary risks of retaining these invasive populations.

In nations with developing healthcare infrastructures, the dual burden of Type 2 diabetes mellitus (T2DM) and tuberculosis represents a critical health challenge. The aim of this study is to investigate the influence of T2DM on the development of multidrug‐resistance tuberculosis (MDR‐TB) in relation to genetic mutations of Mycobacterium tuberculosis in Ethiopia. A facility‐based cross‐sectional study was carried out between 2023 and 2024. Genetic mutations associated with drug resistance in both diabetic and nondiabetic groups were detected using line probe assays (LPAs). Diagnosis of T2DM was performed using fasting blood glucose and glycated hemoglobin levels. Data were analyzed with SPSS software, and logistic regression models were performed. Our findings revealed that 44 of the 182 participants (24.2%) were TB–T2DM, whereas 138 (75.8%) were TB with nondiabetic groups. Multivariate analysis displayed that the prior TB treatment history (aOR: 2.51, 95%CI: 1.02–6.19, p = 0.046) and a family history of T2DM (aOR: 2.25, 95% CI: 1.10–4.60, p = 0.031) were independently associated with an increased risk of TB–T2DM comorbidity. Genetic analysis identified a total of 50 mutations (22 rpoB, 22 katG, and 6 inhA promoter) associated with resistance to RIF and INH drugs among 31 drug‐resistant M. tuberculosis isolates, which were significantly more common in TB–T2DM comorbid patients (p = 0.009). The rpoB S450L and katG S315T1 were the predominant mutations typically associated with high‐level RIF and INH resistance, respectively, and high biological fitness, allowing for successful transmission within the community. Among the dual mutations identified in MDR‐TB isolates, only the rpoB UN + katG S315T1 mutation was significantly more prevalent in nondiabetics (p = 0.04) compared to the TB–T2DM comorbid group. Multivariate analysis revealed that prior TB treatment history (aOR: 4.00, 95% CI: 1.31–12.50, p = 0.014) and TB–T2DM comorbidity (aOR: 3.12, 95% CI: 1.02–9.10, p = 0.042) were significantly associated with an increased likelihood of MDR‐TB. This increased odd of resistance in comorbid patients highlights the need for bidirectional T2DM screening for all TB patients, particularly those with a history of prior TB treatment or a family history of diabetes. A genome‐wide association study into the mutation patterns responsible for DR is crucial to inform the development of targeted, effective strategies moving forward.

Yersinia pestis, the causative agent of plague, has evolved a dual lifestyle enabling survival in both mammalian hosts and hematophagous flea vectors. While mammalian virulence has been extensively studied, the flea stage represents a highly selective and metabolically constraining environment that plays a decisive role in transmission. Following ingestion during a blood meal, Y. pestis establishes within the flea digestive tract, where it must withstand nutrient limitation, oxidative stress, osmotic pressure, and antimicrobial factors while forming a proventricular biofilm essential for gut blockage and subsequent transmission. This review synthesizes current knowledge of the metabolic strategies deployed by Y. pestis during flea colonization, highlighting a coordinated shift toward amino acid and lipid-derived carbon sources, strict dependence on the pentose phosphate pathway, and a central role for lipoate metabolism. We discuss how these metabolic adaptations are tightly integrated with regulatory networks involving c-di-GMP signaling, two-component systems, and global regulators such as RovM and Hfq, ensuring that biofilm formation occurs only when energetic conditions permit. Finally, we address unresolved questions regarding metabolic flux dynamics, interactions with the flea microbiota, and lineage-specific variation, emphasizing the need for future systems-level analyses. Together, this review positions flea colonization as an active andevolutionarily refined phase that shapes the transmission success of Y.pestis.

High frequency vehicle-to-vehicle (V2V) communication in the Internet of Vehicles (IoV) leads to severe spectrum collisions and limited system capacity. Meanwhile, safety information transmission requires V2V communication with high transmission success rate. This paper proposes a spectrum and power allocation method based on the integration of graph neural networks (GNNs) and dueling double deep-Q network (D3QN) reinforcement learning to address the above problems. Specifically, this method first constructs a graph with V2V communication links as nodes and the interference relationships between different V2V links as edges. Then, it utilizes GNN to extract low-dimensional features of graph nodes for characterizing the interference relationships between links. Finally, by using the learned low-dimensional features combined with local observations of V2V links, the Double Deep Q-Network mitigates Q-value overestimation by separating action selection from value evaluation, and decouples state value and action advantage through a dual-branch network structure. This design optimizes spectrum allocation and power selection, improves the information transmission success rate of V2V links, and reduces interference to vehicle-to-infrastructure (V2I) links. Simulation results demonstrate that the proposed resource allocation method improves both the successful transmission rate of safety-critical messages over V2V links and the sum capacity of V2I links.

Rustrela virus (RusV) is a newly discovered member of the genus Rubivirus. RusV causes a fatal, non-suppurative meningoencephalomyelitis in a variety of mammals. Various aspects of RusV biology remain poorly understood, e.g. the excretion of infectious virus and its transmission. To address these questions, we performed in vivo experiments including putative reservoir (wood mice) as well as potential dead-end hosts (Lewis rats). To investigate the natural route of RusV infection and transmission, subgroups of wood mice and Lewis rats were either inoculated intranasally or orally. Successful infection was only observed in animals inoculated via the intranasal route, leading to the assumption that the virus could enter via olfactory neurons and subsequently spread throughout the central nervous system. To gain an initial understanding of the mechanisms of viral transmission, we co-housed RusV-inoculated wood mice with non-infected sentinels. In addition, wood mice or Lewis rats were placed in cages previously occupied by infected wood mice as donor animals for indirect transmission via the environment. Successful RusV transmission was observed solely in co-housed sentinels. These findings suggest that RusV transmission requires direct contact with bodily fluids, such as saliva or nasal secretions or at least a higher infective dose. In contrast, indirect exposure to a presumably contaminated cage does not seem to be sufficient for transmission between reservoir animals or reservoir and dead-end hosts.

This paper first introduces the object-oriented DLMS/COSEM protocol and its characteristics, and then introduces the power information collection and management system-object-oriented interoperability data exchange protocol (DL/T698.45), which specifies the content of the master station, terminals and information transmission of the power information collection and management system. Aiming at the problem that the existing object-oriented protocol is time-consuming for terminal data collection, this paper designs a multi-source heterogeneous communication protocol that integrates the DLMS/COSEM protocol and the DL/T698.45 communication, and adds the corresponding attributes and methods in each functional module to realize the support for multi-source heterogeneous data communication in different functional modules. After that, the performance of the fused service protocols is tested using Peach fuzzy test method and adaptive genetic algorithm, combined with use case analysis. The results show that the Peach fuzzy tester proposed in this paper can shorten the test duration by 25.35% and reduce the number of test cases by 13.74%, which can effectively reduce the failure rate of test cases and make the model in this paper have a high test coverage and very good relevance. The average response time of the DLMS/COSEM-DL/T698.45 protocol is less than that of the DLMS protocol. The transmission success rate is significantly higher than that of the DLMS protocol, which shows that the design of the protocol that integrates the DLMS/COSEM protocol and the DL/T698.45 communication is more reasonable.

Unmanned aerial vehicle (UAV) swarms face significant performance degradation when operating on a single-frequency channel, as the Statistical Priority-based Multiple Access (SPMA) protocol suffers from intensified contention conflicts due to scarce frequency resources. To address this issue, this paper proposes a joint clustering and power optimization method for the SPMA protocol in frequency-constrained scenarios. First, a utility function centered on the end-to-end transmission success rate is constructed, and the optimal clustering scheme selection is formulated as a constrained combinatorial optimization problem. Second, a three-stage heuristic algorithm is designed; all iterations are executed virtually at network initialization. K-means is used to perform initial clustering and determine the minimum power required for intra-cluster services, GPSR is used to establish multi-hop routes for inter-cluster services, and the ant colony algorithm refines the transmission power of forwarding nodes, achieving joint optimization of cluster structure and power configuration. Simulation results show that, compared with the standalone SPMA protocol and the typical clustering algorithm ICW, the proposed algorithm reduces transmission power by 90.4% relative to SPMA (with slightly higher power than ICW) and achieves a comprehensive improvement over both benchmarks. Specifically, the success rate is improved by 63.5% compared with SPMA and 162.3% compared with ICW under high traffic loads, thus achieving a well-balanced compromise between power consumption and transmission reliability. This verifies the feasibility and effectiveness of the proposed optimization method in frequency-constrained scenarios.

Viral transmission from infected donors to uninfected recipients is the key event underlying the spread of viral pathogens at the level of a host population. Successful viral transmission from a donor to a recipient depends on several factors including the infectiousness of the donor. Donor infectiousness in turn can depend on the viral kinetics and viral load of the donor, donor behavior and symptoms, and donor immunity. Here, we use a mouse model of murine respirovirus (otherwise known as Sendai virus SeV) infection to quantitatively explore donor determinants of respiratory virus transmission. The experimental transmission studies we analyze are specifically designed to address the effect that pre-existing donor immunity may have on transmission potential by studying SeV transmission from both immunized and control (placebo-immunized) donors to naïve recipients. We specifically focus on the impact of tissue resident memory (TRM) CD8 T cells on donor transmission potential by considering immunization strategies that primarily generate CD8 T cell immunity. Through quantitative analyses of these experiments, we find that pre-existing CD8 TRMs act to reduce donor transmission potential. This finding is in agreement with previous findings and can be in part explained by a reduction in total infection load in immunized donors. However, even once differences in infection load between immunized and control donors are accounted for, immunized donors still have reduced infectiousness relative to control donors. We explore possible reasons for this unexpected pattern using a mathematical model that integrates within-host viral dynamics and between-host transmission occurrences. Analysis of model simulations, along with observations from knock-out experiments, suggests that interferon gamma (IFN-[Formula: see text]) may be partly responsible for the observed differences in infectiousness between control and immune donors. Future experimental transmission studies should consider measuring IFN-[Formula: see text] levels and its effects when interpreting transmission outcomes in the context of host immunity.

Background: Wireless Sensor Networks (WSNs) face serious challenge to optimize the trade-off between energy, delay and QoS due to the limited capabilities of sensor. This kind of routing protocols like AODV, DSR, LEACH are the protocols in which the single metric is optimized; the overall network efficiency is degraded. This paper presents a new Chaotic Particle Swarm Optimization (CPSO)-Based Multi-Metric Routing Protocol that unites. The suggested approach optimizes energy usage, decreases total transmission latency, and significantly improves the successful packet transmission rate. Methodology: The disordering increases the exploration ability of PSO, resulting in anti-premature and global search is more superior. Extensive network simulations in NS-3 show that the proposed protocol decreases total energy consumption by 38% and enhances packet delivery ratio by about 20–25% in comparison with AODV, DSR, and LEACH. Furthermore, on average CPSO experiences about 45% less latency. Conclusion: This work is an important step towards intelligent, adaptive and resource-aware routing in next-generation wireless sensor and IoT networks.

The rapid development of digital technology has profoundly transformed the landscape for the safeguarding and dissemination of Intangible Cultural Heritage (ICH), especially in the Chinese context. This exploratory study seeks to systematically identify the key factors driving the digital dissemination of Chinese ICH. Using a mixed-methods approach, the research integrates a quantitative survey of 403 university students (as digital-native audiences) with in-depth interviews of six ICH experts and administrators. Eight dimensions are identified as having significant effects on dissemination effectiveness, including digital platform interface design, user participation, content presentation, user interaction, technological empowerment, ICH-genre suitability, evaluation system completeness, and sustainable support mechanisms. The findings lead to targeted recommendations for platform design, content and technology strategies, and support systems, offering both theoretical grounding and practical pathways for the successful transmission and broader dissemination of ICH in the digital era.

Aquaponic systems require stable environmental control to maintain the balance between fish and plant growth. This study proposes a novel Internet of Things (IoT)-based smart aquaponic system that integrates real-time monitoring, adaptive automatic control, and cloud-based data management within a unified sensor–edge–cloud architecture. The key innovation of this work lies in the seamless integration of the Firebase Realtime Database for low-latency synchronization, an interactive web-based dashboard for real-time visualization, and a hysteresis-based adaptive control mechanism that overcomes the limitations of conventional threshold-based systems, particularly rapid actuator switching (chattering). The system employs an ESP32 as the main processing unit, a DHT11 sensor for temperature and humidity measurement, and a TDS sensor for dissolved nutrient monitoring. Data are transmitted every 10 seconds to the cloud and complemented by event-driven Telegram notifications to enable timely user intervention. Experimental results demonstrate stable system performance, achieving a data transmission success rate of 98.47% over 24 hours. The temperature measurement shows a Mean Absolute Error (MAE) of 0.48°C (≈1.6% relative error), while an average latency of 1.4 seconds indicates responsive real-time synchronization. Furthermore, the implementation of hysteresis-based control effectively reduces actuator instability and enhances system reliability. These findings indicate that the proposed integrated architecture not only improves monitoring accuracy and control stability compared to existing IoT-based aquaponic systems, but also enables practical, remotely accessible, and scalable solutions. The system is particularly suitable for small- to medium-scale aquaponic applications, supporting data-driven decision-making and contributing to sustainable agriculture practices.

This paper proposes a joint optimization algorithm based on reinforcement learning to address the time slot and power allocation problem in underwater acoustic communication networks (UACNs). By maximizing the total capacity of successful transmissions as the optimization objective, two sub-objectives are formulated corresponding to time-slot scheduling and power allocation. The sub-objective corresponding to time-slot scheduling is addressed by constructing a Markov Decision Process (MDP) model based on Deep Q-Network (DQN) learning. In this model, the agent learns the time slot allocation policy with the goal of increasing the number of successfully transmitted links while reducing the collision. For the sub-objective corresponding to power allocation, another MDP model is developed, solved by the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, in which each underwater transmission node acts as an independent agent. The MADDPG approach enables the system to improve channel capacity under energy limitation, which maximizes the total capacity of successfully transmitted links. In terms of model execution, the DQN adopts a centralized training and time slot allocation, while MADDPG uses a centralized training and distributed execution to select the transmission power by each node. Simulation results show that the proposed joint optimization algorithm demonstrates better performance in the number of successfully transmitted links and channel capacity compared to TDMA, Slotted ALOHA, and other algorithms.

Numerous factors interfere with the successful transmission of messages during verbal conversations leading speakers to use different speech modes, i.e., specific prototypes of speech with unique phonatory and articulatory characteristics. Despite their omnipresence in verbal exchanges, no theoretical model in the speech production literature has provided a mechanistical account of the encoding processes underpinning speech in different modes. The present study thus aims to investigate how speech modes are planned/programmed relative to standard speech using the high temporal resolution provided by electroencephalography (EEG). 20 Participants uttered pseudowords in three different conditions-standard speech, speaking louder than usual and faking an English accent in French-during a delayed production task. Event-related potential (ERP) of standard speech was contrasted separately with the two others speech modes. Results indicate that speaking by adopting speech modes varying in articulatory and phonatory properties entails increased neural activity of the brain networks that are already involved in standard speech production. Especially, electrophysiological signatures of loud speech and faking an accent were both associated to differences in ERP responses relative to standard speech in a time period covering the last 200 msec preceding the vocal onset. This observation was coherent across waveform analysis (more extended differences in time and space for faking an accent), topographical dissimilarity analysis and microstates analysis (more extended for loud speech). The present findings highlight that different speech modes are encoded in the last 200 msec preceding their vocal production, possibly in a mode-specific way which will need further investigation.

Cardiovascular diseases (CVDs) are one of the leading causes of mortality worldwide, highlighting the need for continuous and real-time cardiac monitoring systems. This paper presents the design and development of a low-cost, wearable IoT-based wrist electrocardiogram (ECG) monitoring system for continuous cardiac health assessment. The proposed system integrates an AD8232 ECG sensor for signal acquisition and an ESP32 microcontroller for signal processing and wireless communication. The acquired ECG signals are processed and transmitted to a cloud-based platform using Wi-Fi, enabling real-time remote monitoring and analysis. The system was experimentally evaluated on 40 participants, including both healthy individuals and cardiac patients, under resting and stress conditions. The results demonstrate that the system successfully captures ECG waveforms with identifiable P-wave, QRS complex, and T-wave components. The proposed system achieved an accuracy of 92% for healthy subjects and 88% for cardiac patients, along with a data transmission success rate of 95%, indicating reliable performance. The wrist-based design enhances user comfort and portability compared to conventional chest-based ECG systems, making it suitable for long-term wearable applications. Although challenges such as motion artifacts and signal variability exist, the proposed system demonstrates significant potential for telemedicine and remote healthcare applications.

Infections with soil transmitted helminths (STHs) are highly prevalent in humans living in the intertropical region. While, in most cases, STHs can establish chronic infections, the dynamics of the infection can be altered when other parasites exploit the same host. These changes can have consequences in terms of the health of the host, the epidemiology of the disease (e.g., the duration of the infection and the inter-host transmission success) and the fitness of the parasite. Here, we investigated if the coinfection with Plasmodium yoelii alters the dynamics (fecundity and with-host persistence) of the murine nematode Heligmosomoides polygyrus. We found that, compared to single infected mice, coinfected hosts excreted more worm eggs, while the worm biomass in the intestine did not differ between single infected and coinfected mice. Moreover, the increase in egg excretion was also observed when Plasmodium infected hosts that had been harboring the nematode during the past four weeks (i.e., when the population size of adult worms can only decrease due to mortality). Therefore, the enhanced shedding of eggs reflects a plastic adjustment of worm fecundity to the environment provided by a coinfected host. This plastic response was modulated by the host Th2 immunity, as coinfection inhibited IL-4 and IL-13 gene expression, plasma levels of IL-5 and IL-13, and the expansion of GATA-3+ CD4+ T cells in the spleen. In agreement with this, experimentally neutralizing IL-13 with monoclonal antibodies reproduced the results observed in coinfected mice (an increase in egg excretion), while the administration of recombinant IL-13 reduced egg shedding. Interestingly, coinfection extended the patent period of Heligmosomoides polygyrus (longer within-host persistence); moreover, a higher cumulative number of eggs was excreted, up to 99 days post-infection, in coinfected hosts. Although the gene expression of Th2 cytokines was lower at day 99 p.i., coinfected mice still had a downregulated expression compared to single infected hosts. These results offer a proof of concept that coinfection with Plasmodium has the potential to affect the epidemiology of STHs by increasing the number of eggs excreted over the whole infectious period and maintaining a larger environmental reservoir of transmissible stages.