Acute myocardial infarction (AMI) remains difficult to diagnose rapidly outside hospital settings because current evaluation still relies mainly on electrocardiography and blood-based biomarker testing. Here, we developed a coin-sized, Rapid Electrochemical Skin interstitial fluid microneedle device for multiplexed Cardiac-biomarker detection Utilizing deep-learning-based Evaluation (RESCUE). The RESCUE system integrates a mesoporous gold-coated microneedle electrode patch (MNE) with a miniaturized three-channel microelectrochemical workstation (MEW) and Bluetooth data link to enable fully portable operation. Antibodies immobilized on amino-functionalized multiwalled carbon nanotubes enabled simultaneous detection of C-reactive protein (CRP), cardiac troponin I (cTnI), and myoglobin (Myo). Electrochemical measurements showed log-linear responses, with limits of detection of 4.09 ng/mL, 0.078 ng/mL, and 1.642 pg/mL for C-reactive protein, cardiac troponin I, and myoglobin, respectively. In simulated skin and artificial interstitial fluid, the device showed good selectivity and average recoveries above 98%. Biocompatibility studies demonstrated preserved fibroblast viability, rapid closure of microneedle-induced micropores, and no detectable histological or serum biochemical toxicity in mice. In murine model of AMI induced by left anterior descending coronary artery ligation, RESCUE tracks ISF trajectories of all three biomarkers. A seven-feature one-dimensional convolutional neural network (CNN1D) trained on interstitial-fluid and blood biomarker features classified infarct size with 80% accuracy. These results support the feasibility of integrated interstitial-fluid sensing for preclinical AMI stratification.
We present a novel readout method for microchannel plate (MCP) signals using timing anodes made from flexible polyimide laminates. Our approach is fully compatible with ultrahigh vacuum environments, as required for the majority of MCP applications. Multiple anode segments and signal tracks are patterned onto the laminate using standard printed circuit board techniques, enabling precise impedance matching of the anode circuit to a 50 Ω coaxial transmission line. Copper patches on both sides of the laminate form embedded capacitors, which are part of integrated decoupling circuits that reduce latency and noise compared to traditional external signal readout methods. The high breakdown voltage of polyimide permits the application of several kilovolts across the anode for MCP detector operation modes that require biasing of both the MCP and the anode. We demonstrate that the MCP signals captured by these segmented polyimide anodes follow a Gaussian profile in time and have a duration <1.5 ns full-width-at-half-maximum. Using an optical detector characterization method, we demonstrate a timing resolution of 40 ps root-mean-square for our ∅50 mm MCPs in Chevron configuration across eight distinct anode segments.
Most children and adolescents recover rapidly from SARS-CoV-2 infection, yet a subset develops paediatric long COVID (LC). How immune ontogeny shapes LC biology and heterogeneity remains unclear. We deeply phenotype a two-visit cohort with severe LC (n = 74) and controls (n = 27) spanning up to 3.2 years post index infection. Symptom burden remains high and neurofilament light chain (NfL) percentiles inversely associate with functional status (Bell score; r  = -0.3536, P = 0.0060). Cardiopulmonary assessment and serology are unremarkable. Conventional autoantibodies are not enriched, whereas anti-DFS70 supports subgrouping. Immune features are temporally structured; SARS-CoV-2-associated mediators decline within 1 year, while innate-weighted, Th2-skewed cytokines persist. Metabolomics (43 metabolites) recapitulate the identified subgroups and align with EBV serostatus, disease phase (<1 year versus years 1-3.2), and anti-DFS70 positivity. In EBV-naïve LC, higher haemoglobin concentration (MCHC) tracks worse function, whereas higher IL-12p40, thiamine and basophils track milder impairment (all P ≤ 0.0170). These data delineate immune-metabolic and haematological axes of paediatric LC heterogeneity and support biomarker-guided stratification.
Assessment in the microbiology laboratories is traditionally structured around spot diagnosis or Objective Structured Practical Examinations (OSPEs) to assess students' ability to identify the causative agents of infectious diseases. Game-based learning has great potential to engage students and indicate their learning gaps in a non-threatening learning environment. The study introduced 'Bingo Lab' as an innovative gamification intervention in undergraduate microbiology courses. We plan to pilot Bingo Lab in two programs, Dentistry and Nursing. The study tracks students' engagement throughout the activity and examines gender differences and their correlation with microbiology performance. Additionally, it explores how Bingo Lab can create opportunities for meaningful learning and gathers students' feedback on their experience. The intervention was structured in five stages: planning, orientation, Bingo Lab., feedback, and reporting. We shortlisted 25 'unknown' microbiology spots as a mock (revision) exam in a laboratory setup. The spots were randomly mapped on a 5x5 Bingo card. One Bingo is awarded when any student completes five stations, whether horizontally, vertically, or diagonally on the Bingo card. Students' engagement was measured three times: early in the session, in the middle, and towards the end. We also solicited their feedback anonymously using a template of three sections: I like, I wish, and I wonder. Students' engagement scores significantly increased from the early stage to the middle of the activity (p = .005) and from the beginning to the end of the session (p < .001), but there was no significant difference between the beginning and the end of the activity. There were no significant gender differences in engagement at any time point. Bingo Labs were well received by students and helped them address their learning gaps, but they also shared a couple of concerns about having more time for preparation and receiving instructions in advance. Bingo in the microbiology lab was well received by students and enabled them to identify their learning gaps and seek feedback and validation from experts. The study supported the effectiveness of the Bingo Lab as a game-based learning approach in improving students' engagement. In a competitive culture, exam-oriented students need to celebrate their excellence, such as through Bingo, a rewarding experience that boosts their self-esteem. The use of Bingo in microbiology laboratories has been found to be effective in engaging students and guiding them to indicate their learning gaps in a non-threatening environment.
In operating room management, surgical instrument counting is a critical process for ensuring patient safety and preventing intraoperative risks. Traditional manual counting takes 15-30 minutes and is prone to errors under high-pressure environments. With the increasing variety and quantity of instruments, identification difficulty and the risk of omissions during surgery are further heightened. The proposed system is structured around four integrated modules: image acquisition and annotation, YOLOv11-based surgical instrument detection, PaddleOCR-based digital extraction of electronic scale readings, and an intelligent comparison and alert system. This study focuses on the systematic design, integration, and technical validation of a multimodal verification framework tailored to a high-risk orthopedic instrument counting scenario. Designed with patient safety as its core objective, the system operates in near real time to support instrument tracking and discrepancy checking under the experimental setting of this study. The results demonstrate that the system achieved high technical accuracy and processing efficiency under the study setting. Specifically, the YOLOv11 model achieved a precision of 0.91, recall of 0.88, F1-score of 0.89, and a mAP50 of 0.93 in surgical instrument identification. These metrics indicate that the proposed framework has strong technical feasibility for instrument counting verification in the target orthopedic scenario. Furthermore, the PaddleOCR component attained 99.7% accuracy in digit recognition with an average response time of under 0.5 seconds, demonstrating its capability for near-real-time digital extraction. Taken together, these findings suggest that the system has potential clinical relevance for perioperative instrument management and may support safer and more efficient verification processes. Future testing in real or simulated clinical settings will further evaluate its usability, user acceptance, and compatibility with real clinical workflow. This study established an intelligent surgical instrument verification prototype and demonstrated the feasibility of a multimodal safety-checking framework in a specific orthopedic instrument counting scenario. The main contributions of this study are threefold: (1) the development of a workflow prototype that integrates instrument detection, electronic scale reading extraction, and discrepancy alerting; (2) the use of weight-based cross-verification to complement visual recognition and improve checking reliability; and (3) the deployment of a modular system architecture with potential for future extension to perioperative safety management. Future studies incorporating user testing in real or simulated clinical settings will further evaluate system usability and workflow compatibility.
Japanese encephalitis (JE), caused by mosquito-borne Japanese encephalitis virus (JEV), presents significant public health challenges. To facilitate effective prevention and control, this study conducted an epidemiological and genomic characterization of JEV in mosquitoes across China during the period from 2021 to 2022, utilizing the national surveillance system for mosquito-borne pathogens. In total, 832 734 female mosquitoes were collected at 130 surveillance sites spanning 29 provinces. with a minimum infection rate (MIR) of 0.20‰. JEV was detected in 12 provinces and five different mosquito species. The highest MIR was observed in Culex tritaeniorhynchus, reaching 0.73‰. The highest detection rate of JEV was found in the pigsty habitat (MIR: 0.95‰). Notably, peak JEV infections in mosquitoes occurred in July, preceding the peak incidence of human cases observed in August. Eight JEV sequences were obtained from six provinces, seven of which were near full-length. Phylogenetic analysis of the whole genome showed that eight JEV strains obtained from provinces in northern and southern China belonged to the emerging variant of GIb-clade 2. In comparison to vaccine strains, current strains displayed between 12 and 14 amino acid variations within the E protein, and there was an additional glycosylation site at N108 resulting from a G110S mutation. These findings underscore active transmission of JEV across multiple mosquito species within China, highlight critical vector and habitat risks, and advocate for enhanced mosquito surveillance as an early warning system. The nationwide dissemination of GIb-clade 2 strains provides a scientific foundation for targeted control measures against JE.
The extracellular matrix (ECM) is a major component of the tissue microenvironment which may pose a barrier to the distribution of AAV in target organs, preventing delivery of therapeutic cargo. We sought to address this potential barrier to AAV gene therapy by furthering our understanding of AAV-ECM interactions. We hypothesized that both the AAV serotype and ECM composition will impact AAV transport and gene delivery. AAV2, AAV6, and AAV8 viral vectors were fluorescently labeled to allow for visualization of their diffusion through the ECM. Lung, liver, and small intestinal submucosal dECM hydrogels were formulated as models of the ECM with tissue-specific biomolecular content. We then characterized AAV and nanoparticle diffusion within decellularized ECM using fluorescent video microscopy and multiple particle tracking. Additionally, we evaluated AAV transduction in dECM-incorporated 2D and 3D spheroid tissue culture models. All AAV displayed reduced diffusivity through ECM as compared to similarly sized nanoparticles. AAV2 diffusion was least affected by the presence of ECM across tissue types as compared to AAV6 and AAV8. AAV transduction in dECM incorporated in vitro models was significantly reduced in both a 2D and 3D setting. These results suggest binding of AAV to the ECM may decrease their therapeutic effect in target tissues throughout the body. The barrier function of the ECM should be considered in development of AAV for gene therapy applications.
Socio-economic status (SES) is associated with many adverse health outcomes, yet it remains unclear how SES relates to the rate at which people accumulate long-term conditions (LTCs) over time. We investigated this relationship between SES and disease accumulation using longitudinal disease tracking data. We analyzed data from the UK Biobank study (n = 502,368, median age 58 years [range 37-73], 46% male at baseline) with a median follow-up of 15.8 years. We tracked accumulation of 80 specified LTCs (identified from hospital records using ICD-10 codes). Multistate models were used to estimate the transition rates between SES and incremental morbidity states (i.e., 0 to 1 LTC, 1 to 2 LTCs, until 7 to 8 + LTCs), with death as the absorbing state. SES indicators included education level, family income, Townsend Deprivation Index, and Index of Multiple Deprivation. The models were adjusted for age, sex, ethnicity, calendar year, current number of LTCs, and lifestyle factors. Over 7.5 million person-years of follow-up, we observe a clear socioeconomic gradient in disease accumulation rates. All four SES indicators are associated with accelerated morbidity progression and mortality. The socioeconomic gradient is evident across all transition stages but notably stronger for the initial transition from health to the first LTC, where the lowest income group has a 71% higher transition rate (95% CI: 1.67-1.76). Disadvantaged SES is associated with higher rates of progression to subsequent morbidities. These findings show the lasting impact of socioeconomic disadvantages on the widening health gap in later adulthood. Socio-economic status (SES) is associated with many adverse health outcomes in adulthood. However, these associations have generally been studied for a single disease, and it remains unclear how SES is associated with the rate at which people develop and accumulate long-term conditions (LTCs) over time. We studied over 500,000 UK adults for nearly 16 years, tracking disease accumulation from 80 LTCs. We found that people with lower SES developed LTCs more rapidly than those with higher SES. This pattern was consistent for all LTC states, with stronger associations observed with early disease. Even after accounting for lifestyle factors like smoking and exercise, lower SES remained strongly linked to faster disease accumulation. These findings show the lasting impact of socioeconomic disadvantages on the widening health gap in later adulthood, suggesting targeted interventions for those with lower SES may be beneficial.
Avian pathogenic Escherichia coli (APEC) poses a threat to poultry and public health due to its ability to cause avian disease, potentially contribute to foodborne illness, and carry antimicrobial resistance genes (ARGs). Given its ubiquitous nature and capacity to persist in diverse environments, APEC has potential as a marker organism for tracking antimicrobial resistance (AMR) in poultry production systems and surrounding environments. This study investigated the prevalence, genotypic diversity, AMR profile, and potential transmission of APEC across different production stages in commercial, vertically integrated broiler operations. APEC isolates were recovered from environmental samples across the production chain, including pullet, breeder, and broiler farms as well as processing plants. E. coli isolates were classified as APEC if carrying three or more out of five virulence genes. Whole genome sequencing was conducted on 42 APECs. We determined their serotypes, phylogroups, sequence types (ST), and AMR profiles and constructed a single-nucleotide polymorphism (SNP)-based phylogenetic tree. High-risk APEC strains were detected, with ST131 recovered at the post-chill stage, raising food safety concerns. All isolates shared a core resistome, while several ARGs were differently distributed across sample types. SNP analysis revealed genetically closely related APEC strains inside the poultry house and the adjacent outside environment, and critically, between broiler litter and carcass rinses collected at the processing plant that processed the same flock. We demonstrate APEC carrying clinically relevant ARGs spread within farm environment and along the production chain, supporting its utility for AMR surveillance.IMPORTANCEAvian pathogenic Escherichia coli (APEC) is a threat to poultry production and public health due to its ability to cause avian disease, economic losses, potential foodborne implications, and ability to carry antimicrobial resistance genes (ARGs) relevant to human health. In this study, we proposed APEC as a potential marker organism of antimicrobial resistance (AMR) due to its capacity to persist in diverse environments. Our findings show that APEC, across the vertically integrated poultry production chain, harbored clinically important ARGs and exhibited resistance to antimicrobials of human health importance. We also identified evidence of APEC transmission within the farm environment and into the processing plant, with the potential to reach consumers. By examining multiple stages of production and diverse environmental samples, our study provides a more comprehensive understanding of APEC ecology, its resistome, and dissemination. These insights highlight APEC's utility as a marker organism for AMR surveillance in poultry production.
Chromatin dynamics control the timescales of essential biological processes and reflect how chromatin is organized in the nucleus. Previous studies have reported widely varying degrees of chromatin subdiffusion without consensus. For robust subdiffusion measurements, chromatin should be tracked across a sufficiently large dynamic range. Here we track chromatin movement across seven orders of magnitude in time by integrating MINFLUX microscopy with single-molecule and locus tracking in five mouse and human cell types. We discover two fundamentally different dynamics classes that are cell type specific and not described by common chromatin polymer models. In one class, chromatin displays strong subdiffusion across all timescales (α ~0.3), indicating that the local environment is more quickly searched than the distal. In the other class, chromatin shifts from strongly subdiffusive at short timescales to less subdiffusive, making search less local over long timescales. Both classes are only moderately sensitive to perturbations. Search times under these observed dynamics are extremely short for nearby loci (<100 nm) but almost impossibly long over larger distances (>1 µm); this has important implications for processes involving two-locus contacts, such as enhancer-promoter search and DNA double-strand break repair.
Left ventricular (LV) strain rates assessed by two-dimensional speckle-tracking echocardiography have exhibited clinical and prognostic significance but remain sparsely used. We sought to establish age and sex-based normative values of LV strain rates and to assess the prognostic yield of lower limits of normality (LLN). LV strain rate parameters included global systolic strain rate (GSRs), global early diastolic strain rate (GSRe) and global late diastolic strain rate (GSRa). The primary population consisted of healthy participants free of risk factors from the Copenhagen City Heart Study. The prognostic yield of LLN was assessed against a composite endpoint of cardiovascular death, incident heart failure and acute myocardial infarction using Cox regression in a secondary validation population, regardless of health status. The healthy population consisted of 1930 subjects with a median age of 46 years (IQR 33, 58), of whom 1193 (61.8%) were female. Median values were -0.97 s-1 (IQR -1.07, -0.90) for GSRs, 1.43 s-1 (1.17, 1.70) for GSRe and 0.77 s-1 (0.60, 0.93) for GSRa. Normative values were determined according to sex and four age intervals. All three parameters differed across sexes, while GSRs was negatively correlated with heart rate; GSRe and GSRa were negatively and positively correlated with age, respectively. GSRa below the sex- and age-appropriate LLN was independently associated with a higher risk of the composite outcome. This is the largest study to report sex- and age-specific normal values for LV strain rates. The LLNs identified, namely for GSRa, provided independent prognostic information regarding adverse cardiovascular events.
Diabetes self-management education and support (DSME/S) programmes must demonstrate effective engagement of family members to achieve diabetes self-management outcomes and well-being of the whole family. These are complex interventions and their effectiveness is context dependent. We present initial programme theories of DSME/S and aim to answer: In what contexts and through which mechanisms do DSME/S interventions involving family caregivers impact diabetes self-management outcomes? The review will follow the Realist and Meta-narrative Evidence Syntheses: Evolving Standards and Pawson's five steps: define the scope, develop initial programme theories, search for evidence, appraise studies and extract and synthesise data. Literature searching will be combined with feedback from patient and public involvement stakeholders. PubMed, EMBASE, CINAHL, Scopus and PsycINFO will be searched to February 2026, with citation tracking and grey literature included. Data will be synthesised inductively to develop programme theories and context-mechanism-outcome configurations. This study is a realist synthesis protocol and does not require ethics approval. The study will use published evidence and grey literature with contributions from patient and public involvement stakeholders. The study will produce transferrable programme theories that explain the contexts and mechanisms that influence DSME/S intervention impact and the considerations required to maximise family involvement in diabetes care. These programme theories will provide conceptual frameworks for consideration when designing DSME/S interventions for various contexts in order to maximise self-management capabilities of the persons with diabetes while promoting the health of the family as a whole. Findings will be published in peer-reviewed journals and presented at scientific conferences. CRD420251179485.
Resecting pediatric tumors is often surgically challenging caused by insufficient tumor localization, due to limited visibility and palpability. Surgical navigation systems may potentially improve intraoperative tumor localization. This study evaluates the accuracy and precision of an in-house developed navigation setup using tracked ultrasound under standardized conditions. Bone surface-based registrations, using automatic bone segmentation on tracked ultrasound images, were conducted on phantoms to validate the performance of the in-house developed surgical navigation setup. Registration was conducted on different phantoms, consisting of tumors near bones of an extremity (n = 50), the pelvis (n = 5) and the thoracic wall (n = 5). In addition, the same registration framework was evaluated in the case of kidney tumors, where the kidney surface was used instead of the bone surface for registration. Target registration error (TRE) was used as the primary outcome measure. For tumors localized with bone surface-based registration, the setup achieved a median TRE of 1.3 mm with an interquartile range (IQR) of 0.9-2.1 mm. The robustness of the bone surface registration method was demonstrated with consistent results across anatomical regions. For kidney tumor localization with kidney surface-based registration, the setup achieved a median TRE of 3.3 mm with an IQR of 2.7-3.6 mm. Under controlled circumstances, the navigation setup demonstrated reproducible < 2 mm accuracy for tumor localization using the bone surface registration. For kidney tumors, the navigation setup showed < 4 mm accuracy. These findings establish a performance benchmark that can guide interpretation of larger inaccuracies encountered during clinical use and support future development toward clinical implementation.
Load frequency control (LFC) is an essential measure in maintaining stability in power systems in islanded microgrids that include heterogeneous generation sources and energy storage systems. Island microgrid systems (IMGs) that integrate renewable energy sources widely use proportional-integral-derivative (PID) controllers for LFC. However, the overall control performance is highly sensitive to the accurate tuning of PID controller parameters. To address this problem, this paper proposes an adaptive PID tuning approach that studies the individual evaluations of the Deep Deterministic Policy Gradient (DDPG) and Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithms. The proposed reinforcement learning (RL)-based adaptive PID tuning approach is used to adaptively regulate PID gains under the inherent uncertainties of the IMGs environment. The proposed RL-PID controller approach employs an agent that is trained offline through repeated interactions with the IMGs model, where a suitable reward function guides the learning process toward an optimal control policy. Once trained, the agent is implemented online to continuously update the PID gains for coordinated control of the Wind Turbine Generator (WTG), Solar Photovoltaic (SPV), Fuel Cell (FC) units, Electric Vehicle (EV), and Biogas Turbine Generator (BTG), ensuring effective load demand tracking. Simulations of an IMGs demonstrate that both DDPG-based PID controllers and TD3-based PID controllers outperform conventional PID controllers in dynamic response, settling time, and robustness to disturbances. Furthermore, the TD3-PID shows better stability and reduced oscillations compared to the DDPG-PID, which can be explained by the fact that it improves the policy update mechanism, leading to more effective adjustments in response to system changes. Although studied PID tuning approaches incorporate intelligent mechanisms for gain adjustment, the results indicate that the RL-based adaptive PID controller provides improved overall performance.
Addressing methane emissions from the oil and gas supply chain has emerged as a key near-term mitigation target. The past decade of research has improved our understanding of methane emissions, with a primary focus on quantifying emissions without describing their underlying causal mechanisms. Here, we integrate source-specific methane emissions measurements from multiple large-area aerial surveys with source-tracked cause analyses to identify and analyze causal mechanisms that underlie observed emission patterns. Overall, 53% of all observed emissions can be attributed to specific causal categories, with the rest comprising normal operational emissions. While abnormal tank emissions are the most common cause, unloading events exhibit the highest average emission rate. Importantly, we find that large release events are not driven by fundamentally different causal mechanisms than those of small emitters, indicating that escalation due to specific operational conditions, rather than fundamentally distinct causes, drives high-magnitude emissions. In addition, we observe statistically significant temporal and inter-operator variability in the prevalence of different causal categories, reinforcing the need for adaptive, operator-specific mitigation strategies. These findings support a shift in methane mitigation from generalized leak detection with one-size-fits-all solutions toward risk-targeted, process-informed mitigation.
Bastos and Krupenye (2026, Science, 391: 583-586) present an innovative series of studies in which they explore the capacity of a single enculturated bonobo, Kanzi, to represent pretend objects-in other words-"imagination." Their experiments involved pantomimed actions of pouring and emptying juice or placing and dumping out grapes from transparent cups or bowls and asking Kanzi to indicate where the juice or grape would remain, indicating that he was tracking an imagined object, but they failed to account for cuing or alternative explanations. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Programmatic assessment offers a system-level approach to evaluating students' competence by integrating multiple low-stakes assessments, longitudinal evidence and expert judgement. Although widely adopted across several health education disciplines in Australia, radiography education providers have not implemented programmatic assessment at a programme or course level. This paper proposes a radiography-specific programmatic assessment framework. The objective is to translate core programmatic assessment principles into curriculum design strategies that strengthen feedback, improve the defensibility of decisions and enhance national workforce readiness. The paper outlines key purposes of programmatic assessment in undergraduate radiography education including supporting learning, strengthening feedback mechanisms, tracking developmental progress and enabling defensible decisions grounded in longitudinal evidence. Critical design considerations include aligning assessments with a capability framework, generating evidence across diverse clinical contexts, prioritising narrative feedback and using portfolios as central evidence repositories. The analysis highlights the importance of competence committees for high-stakes decisions and the need to support shared assessment practices across varied clinical placement environments. The proposed radiography model integrates six components: capability framework, evidence generation, evidence aggregation, interpretation, decision-making and system learning. This model addresses radiography's multimodality workflow, training variation across sites and accreditation requirements for fairness, transparency and systematic monitoring. Programmatic assessment offers a coherent approach to strengthening radiography education by supporting clearer insight into learner development and ensuring consistent evidence of capability achievement across clinical environments. When adapted to radiography's multimodality practice and evolving workforce demands, programmatic assessment enhances readiness for independent practice and supports continuous curriculum improvement. Programmatic assessment provides a coherent framework for evaluating diagnostic radiography students’ professional capability by integrating longitudinal, narrative-rich evidence across clinical and simulated learning environments.Aligning assessment design with the Medical Radiation Practice Board of Australia (MRPBA) Professional Capabilities enables transparent, defensible progression decisions that evidence accreditation requirements while supporting learner development.Effective implementation of programmatic assessment in radiography depends on deliberate system design, including balanced assessment stakes, structured portfolios, assessor calibration and collective decision-making through competence committees.
Cystic echinococcosis (CE), a neglected zoonotic disease caused by the larval stage of Echinococcus granulosus, requires effective vaccine strategies for sustainable control. This study evaluated the immunogenic profiles of two antigenic targets: EgAgB8/1, a dominant immunogenic component of hydatid cyst fluid, and Eg-01883, a protoscolex-specific antigen identified through bioinformatic screening. E. granulosus strains were isolated from infected dogs for genomic DNA extraction. Recombinant proteins rEgAgB8/1 and rEg-01883 were expressed in E. coli, purified, and validated by SDS-PAGE and western blot. Initial protein microarray screening identified rEgAgB8/1 as exhibiting markedly higher immunoreactivity with cystic echinococcosis (CE) patient sera compared to the minimally reactive Eg-01883. Based on this finding, subsequent investigation focused on rEgAgB8/1 using a BALB/c mouse immunization model. The recombinant protein elicited potent humoral immunity, with antigen-specific IgG titers reaching 1:16,000, and stimulated significant lymphocyte proliferation. Immunized mouse sera specifically recognized native EgAgB8/1 in hydatid crude antigen preparations, confirming natural antigenicity. Flow cytometric analysis demonstrated that rEgAgB8/1 immunization significantly expanded splenic plasmablasts, memory B cells, and T follicular helper cells. Furthermore, it enhanced IFN-γ production in both CD4⁺ and CD8 ⁺ T cells while maintaining baseline IL-10 ⁺ T cell frequencies, and induced robust T cell memory responses. Statistical analyses were performed using Student's t-test for comparative evaluation. These findings establish rEgAgB8/1 as a highly immunogenic antigen capable of eliciting a cellular immune response characterized by dominant IFN-γ production without concomitant IL-10 elevation, alongside durable humoral responses in mice. The comprehensive immunogenicity profile supports further research into its immunological potential against cystic echinococcosis.
Controlling heavy-pnictogen (As, Sb) redox chemistry remains a central challenge in RoHS-compliant III-V colloidal nanocrystal synthesis. The formation of pnictide nanocrystals, where pnictogen must reach its lowest oxidation state, is significantly impeded for heavier pnictogens under typical colloidal synthesis conditions. Consequently, external electron sources are commonly employed, but such empirical one-pot activation offers limited molecular-level insight and control over elementary steps. Here, we decouple pnictogen reduction from nanocrystal synthesis and track the reduction process using ex situ XANES and multinuclear NMR spectroscopy. Distinct from conventional hydride chemistry, in the presence of oleylamine, metal-alkyl reagents act primarily as bases rather than direct reductants, generating metal-amide complexes that mediate thermally regulated pnictogen reduction through amide-to-imine oxidation. Metal cations further tune the reduction depth by competitively accepting hydride equivalents. The resulting partially reduced pnictogen complexes function as practical precursors compatible with nanocrystal syntheses in various synthetic formats, eliminating the need for additional reducing agents during nanocrystal growth. This metal-amide-mediated prereduction establishes a redox design principle for heavy pnictogens, enabling safer and tunable synthesis of pnictide semiconductor nanocrystals.
To meet the demand for efficient and safe underground material transportation in the intelligent construction of coal mines, addressing the unstructured environmental characteristics of mine roadways, this study proposes an improved path planning algorithm based on the A* algorithm. It aims to achieve the dual requirements of driving efficiency and operational safety for robots in complex environments. The algorithm adopts a collaborative architecture combining global and local path planning: at the global level, it enhances search efficiency by introducing a bidirectional adaptive search strategy and incorporates terrain risk weights into the cost function, enabling the planned path to effectively avoid high-risk areas and achieve global path optimization; at the local level, it integrates the DWA algorithm to strengthen the robot's real-time obstacle avoidance capability and ensure operational safety. To validate the algorithm's effectiveness, path planning experiments were conducted in a simulated environment. The results demonstrate that the proposed algorithm effectively avoids various obstacles, significantly shortens path length and search time, providing a viable solution for path planning and navigation of tracked transport robots in complex roadways.