Autoimmune pancreatitis is a distinct type of pancreatitis mediated by autoimmune processes. Imaging studies frequently reveal diffuse or focal pancreatic enlargement, as well as irregular narrowing of the pancreatic duct. The clinical manifestations of this condition often overlap with those of other malignant conditions, such as pancreatic cancer, which can result in a high rate of misdiagnosis. EUS-guided fine-needle aspiration biopsy is a novel approach for the pathological diagnosis of AIP, enabling pancreatic tissue sampling. However, there remains a paucity of research on the efficacy of EUS-guided tissue sampling in the diagnosis of suspected AIP. The objective of this study is to assess the diagnostic value of EUS-guided tissue acquisition (including EUS-FNA and EUS-FNB) in patients with suspected AIP. Patients suspected of AIP who underwent EUS-guided tissue acquisition (EUS-TA) at Changhai Hospital between 2010 and 2025. This study included 148 patients with suspected AIP. Ultimately, 131 were diagnosed with AIP, 9 with pancreatic malignancy, and 8 with other pancreatic diseases. Among the 131 patients diagnosed with AIP, EUS-TA achieved a success rate of 88.66% for obtaining histopathological evidence in type 1 AIP, 76.47% in type 2 AIP, and 85.5% overall for AIP. The ROC curve indicates that EUS-TA demonstrates good diagnostic value for patients suspected of having AIP (AUC = 0.839, 95% CI: 0.729-0.95). Compared with EUS-FNB, EUS-FNA showed significantly lower sensitivity (78.57% vs. 90.67%, P = 0.029), specificity (75% vs. 88.89%, P = 0.017), negative predictive value (33.33% vs. 53.3%, P = 0.007), and accuracy (78.13% vs. 90.48%, P = 0.034). EUS-guided tissue acquisition demonstrates good diagnostic value for patients suspected of AIP, with EUS-FNB showing higher diagnostic value for AIP than EUS-FNA. EUS-FNB is the preferred diagnostic method for patients suspected of AIP.
Instructional interactions in beginner skiing classes may influence both objective skill performance and psychological outcomes. However, longitudinal intervention evidence in high-risk skill-learning contexts remains limited, and objective skill performance and psychological outcomes have often been examined separately. This study aimed to compare the effects of autonomy-supportive teaching and conventional teaching on skill acquisition, self-efficacy, and mental toughness in beginner skiing instruction. A cluster-randomized controlled trial was conducted with 216 novice skiers from eight intact classes. The instructional program lasted 3 weeks and followed an intensive short-term schedule, with three 200-min sessions per week. Skill assessments and questionnaires were administered at three time points: after the standardized teaching phase in Week 1, after the Week 2 instructional sessions, and after the Week 3 instructional sessions. Linear mixed-effects models were used to examine Group × Time interaction effects. Learners receiving autonomy-supportive teaching reported significantly greater increases in perceived teacher autonomy support than those receiving conventional teaching. Skill acquisition, self-efficacy, and mental toughness all showed significant Group × Time interaction effects, with the autonomy-supportive teaching group demonstrating greater incremental improvements over time. Autonomy-supportive teaching can simultaneously improve skill acquisition, self-efficacy, and mental toughness among novice skiers without increasing instructional time or practice volume. This study provides longitudinal empirical evidence for evaluating pedagogical intervention effects in high-risk skill-learning contexts.
Communication competence is a core nursing competency, yet effective pedagogical approaches for systematic skill development remain underexplored in many cultural contexts. Microcounseling, developed by Allen Ivey in the 1960s, offers a structured framework for teaching discrete interviewing skills through modeling, practice, and feedback. It has been applied in Japanese nursing education since the 1980s, yet this nearly four-decade literature has not previously been synthesized. This narrative review synthesized research on microcounseling among Japanese nursing students, examining factor structures, skill acquisition patterns, and educational implications, to identify principles potentially useful for international nursing education. A search of five databases and hand searching identified 33 records; after duplicate removal and screening, 10 studies met inclusion criteria, spanning 1988 to 2024. Findings were combined using narrative synthesis procedures structured by the Synthesis Without Meta-analysis (SWiM) guideline. Factor analyses consistently extracted four skill dimensions mapping onto Ivey's three-tier hierarchy-attending, reflection, and influencing skills-demonstrating structural stability over more than 25 years. Acquisition was differential: questioning techniques improved with brief training, while reflection skills required extended practice; attending behaviors were learned readily but showed developmental fluctuation across the curriculum. A notable "confidence inversion" emerged, with higher self-efficacy reported for influencing than for reflection skills, despite the microskills hierarchy positioning reflection as foundational. Attending behaviors followed a U-shaped trajectory, with second-year students showing decreased confidence after initial clinical exposure, while reflection and influencing-behavior skills increased significantly between second and fourth years. Online learning environments may selectively constrain reflection skill development. Within the limits of a small, single-country evidence base, these findings suggest principles that may inform nursing curricula: graduated skill introduction, explicit emphasis on listening foundations, and targeted support during early clinical experiences. Cross-cultural validation studies remain needed.
Three-dimensional prenatal ultrasound scans of a baby's facial features have become increasingly popular among parents in both private and clinical settings. Ultrasound practitioners often draw on their experience to identify factors that influence image quality when discussing scan outcomes with parents. This study aims to identify the maternal, fetal and technical factors that may affect the quality of three-dimensional souvenir face images during ultrasound scan. A retrospective quality review study was performed with data from a single-centre research study, including ultrasound videos of the fetal growth scans, three-dimensional facial ultrasound acquisitions and post-processing steps. A total of 342 three-dimensional surface-rendered images were attempted from 41 singleton pregnancy subjects, average gestational age 26.69 weeks, range: 21-30. The retrospective image quality for all images was assessed by two observers. Univariable ordinal regression test was used to investigate the associations between demographic/technical factors and the best image quality acheiveable. Of the 41 pregnancies, three-dimensional acquisition time was an average of 03:07 (mm:ss), (range: 01:22-5:31). In total, 49% of women had at least one good or moderate quality image, and 51% women had a poor quality or failed three-dimensional scan as the best quality possible. Image quality was associated with placenta site, explaining 18% of the variation (p < 0.05). We found a maternal-fetal factor which has a high impact on three-dimensional image quality of the prenatal face but nonetheless, sonographer skill, training and other technical factors may be employed to minimise the impact of detrimental factors.
Fast cone beam computed tomography (CBCT) on ring-gantry systems allows for improved image quality and fast 6-second acquisition. However, 6-second acquisition might pose challenges regarding target delineation and capturing the full range of motion of moving lung tumors. Especially, in patients with slow (period > 6 s) or irregular breathing, capturing the entire tumor motion might not be guaranteed. This study evaluated localization and volumetric accuracy of 6- and 60-second CBCT scans in an in-house dynamic anthropomorphic thorax phantom, with synchronized imaging capabilities. The phantom was scanned for a sinusoidal and four patient-derived breathing patterns, including regular, slow or irregular breathing. Target position and volume for 6- and 60-second acquisitions were compared to ground truth delineation on time-averaged 4D computed tomography (4DCT) reconstruction, assessing if 6-second acquisition is sufficient to accurately capture the tumor motion. For sinusoidal and regular patient-derived motion, both 6- and 60-second CBCT acquisition captured target motion, compared to 4DCT (Dice Similarity Coefficient, DSC > 0.9). For large amplitudes, only one out of three 6-second scans fully captured target motion (DSC > 0.85). For slow and irregular patient-derived patterns, localization errors and volume differences up to 10.3 mm and 119% were observed using 6-second acquisition, compared to 4DCT, with superior localization and volumetric accuracy of the 60-second acquisition. The 6-second protocol showed accurate results, capturing full target motion for regular breathing patterns. Adaptive protocols, taking into account patient-specific breathing periods and irregularities may be preferred in patients exhibiting slow or irregular breathing.
Adaptive Four-Dimensional Cone-Beam Computed Tomography (4DCBCT) can reduce scan time and imaging dose in radiotherapy. This is achieved by modulating the projection acquisition rate and gantry rotation speed in response to real-time changes in patient breathing, together with motion-compensated image reconstruction. This study aimed to evaluate the clinical image quality of a fast adaptive 4DCBCT acquisition compared with conventional 4DCBCT in the treatment of lung cancer. Image datasets from the Adaptive 4DCBCT (ADAPT) clinical trial (ACTRN12618001440213), which included 30 patients treated for lung cancer, were analyzed. Two scan types were assessed: fast adaptive 4DCBCT (200 projections acquired over 20 breathing cycles, approximately 60-80s) and conventional 4DCBCT (1320 projections acquired over approximately 80 breathing cycles, 4 min). Two radiation oncologists and four radiation therapists, blinded to the image acquisition technique, independently rated the clinical utility of each scan using a two-question survey. Tumor visibility was rated on a three-point scale, and overall image quality was rated on a ten-point scale. A paired t-test was used to compare scores across acquisition techniques. Fast adaptive 4DCBCT showed a mean tumor visibility score of 2.3 ± 0.8, compared to conventional 4DCBCT (2.4 ± 0.7). For general image quality, fast adaptive 4DCBCT achieved a mean score of 4.1 ± 1.3, compared to conventional 4DCBCT, which had a mean score of 4.3 ± 1.2. There were no statistically significant differences in tumor visibility or image quality scores between fast adaptive 4DCBCT and conventional 4DCBCT scans. Fast adaptive 4DCBCT achieved similar image quality scores to conventional 4DCBCT while requiring only 15% of the imaging dose and 25% of the scan time. This study confirms the clinical feasibility of adaptive scanning protocols for use in radiation therapy for lung cancer.
To evaluate the benefits of combining the Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) acquisition technique and deep learning-based reconstruction (DLR) for fat-suppressed T2-weighted imaging (Fs-T2WI) and diffusion-weighted imaging (DWI) in head and neck MRI. This retrospective study included 34 patients who underwent 3.0-T head and neck MRI. Imaging protocols comprised PROPELLER-based Fs-T2WI and DWI, which were compared against conventional multiplanar fast spin-echo Fs-T2WI and single-shot echo-planar imaging DWI. All sequences were reconstructed using a DLR algorithm. Two radiologists independently performed qualitative assessment, evaluating overall image quality, lesion conspicuity, anatomical delineation, and artifact severity using a 5-point Likert scale. The quantitative assessment involved measurements of the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the lesions, adjacent muscle, parotid glands, and submandibular glands. Interobserver agreement was determined using weighted kappa statistics, and Wilcoxon signed-rank test was used for statistical comparisons. The PROPELLER sequences exhibited significantly higher qualitative scores for all evaluated parameters in both Fs-T2WI and DWI compared to the conventional sequences (p < 0.001). The interobserver agreement for the Fs-T2WI was moderate (0.47-0.53), and that for DWI was good (0.76-0.83). The quantitative analysis further demonstrated significantly higher SNRs and lesion-to-muscle CNRs with the PROPELLER sequences (p < 0.001). The combination of PROPELLER acquisition and DLR significantly improves the image quality and lesion conspicuity in head and neck MRI. This approach effectively suppresses artifacts and improves quantitative image metrics, thereby positioning it as a reliable imaging strategy for routine clinical assessments of head and neck lesions.
To summarize and evaluate the core components, functional modules, and developmental challenges of intelligent oral examination robots, and to clarify their potential clinical relevance as well as the mechanisms by which robotics and artificial intelligence can enhance diagnostic efficiency and standardization in dentistry. This study employed a systematic literature review methodology, retrieving relevant publications from the PubMed and ScienceDirect databases up to September 2025. The search strategy utilized Boolean operators to combine keywords such as 'robot,' 'AI,' 'oral diagnosis,' and 'intraoral scanner,' aiming to comprehensively cover the fields of robotic technology, oral diagnostics, artificial intelligence, and related sensing technologies. The initial search yielded approximately 1,027 articles, of which 134 were ultimately included after screening. Inclusion criteria comprised studies related to oral robotic technologies, applications of artificial intelligence in diagnosis, and robotic navigation, while exclusion criteria included non-peer-reviewed publications and studies with insufficient methodological descriptions. A combined approach of narrative review and critical analysis was adopted, with a focus on key technical domains, including hardware architecture, software integration, multimodal perception systems, and force feedback mechanisms. The analysis identified several key technological components of intelligent oral examination robots, including high-resolution intraoral imaging systems, multimodal data fusion frameworks, force-sensing and adaptive control technologies, automated navigation systems, and AI-driven data-processing algorithms. These systems contribute to improved image acquisition accuracy, standardized diagnostic procedures, enhanced data management, and optimized clinical workflow. However, challenges remain in system integration, safety assurance, real-time responsiveness, and clinical validation. Current technological advances suggest that intelligent oral examination robots have significant potential to reduce clinician workload, improve diagnostic accuracy, and enhance consistency in oral examinations. Continued refinement in hardware-software integration, safety mechanisms, and clinical adaptability will be essential for broader implementation. Intelligent oral examination robots may significantly improve diagnostic quality through automation, standardized data acquisition, and enhanced imaging capabilities. Their application could facilitate early disease detection, improve patient management, and streamline clinical workflows in modern dental practice.
The Supply Chain and Pharmacy breakout session focused on participants' real-world experience with supply chain and pharmaceutical needs for their alternate care facility (ACF). This included details around acquisition and utilization of durable medical equipment, personal protective equipment (PPE), consumables, and pharmacy stock. Participants were encouraged to discuss supply chain management considerations, resource allocation and acquisition, and influencing factors that impacted these topics. Participants explored various approaches to obtain medical supplies and pharmaceuticals, including leveraging existing vendor relationships and establishing climate-controlled storage spaces, while emphasizing the importance of electronic tracking systems and documentation. The overarching goal was to focus on what participants did and how deficiencies were managed. The discussion covered challenges in healthcare coordination during disasters, including supply chain issues, the management of unsolicited donations and volunteers, and the need for innovative solutions like drones and alternative medical applications, concluding with reflections on regulatory oversight and opportunities for process and systems improvements. The group identified several key gaps in emergency response systems, particularly the disconnect between emergency management agencies and healthcare systems, while emphasizing the need for qualified liaisons, just-in-time training, and systematic approaches to ensure effective medical resource management during crises.
Bacterial pathogens commonly become drug resistant via horizontal acquisition of antimicrobial resistance genes (ARGs), which are often encoded on mobile genetic elements (MGEs). Although bacterial defence systems are typically considered barriers to horizontal gene transfer (HGT), previous studies revealed that bacteria with more restriction-modification (RM) systems (the most abundant bacterial defences) frequently carry more MGEs. It was suggested that this counterintuitive relationship might result from stronger selection for RM systems when exposure to costly MGEs increases. Here, we test this hypothesis using a combination of modeling and bioinformatics analysis of >40,000 bacterial genomes to better understand how eco-evolutionary feedbacks between selection for RM and acquisition of MGEs shape bacterial genome evolution. Our model predicts negative associations between HGT and RM, but only if RM diversity is high. By contrast, at low RM diversity, eco-evolutionary feedbacks drive the emergence of positive associations between HGT and RM. Consistent with these predictions, we identified negative relationships between acquired ARG counts and RM counts across species but positive relationships within individual species. Collectively, our work helps to understand how RM systems shape patterns of HGT of ARGs, which may offer opportunities for targeted surveillance of strains at higher risk of horizontally acquiring novel drug resistance alleles.
Ultrasound-guided peripheral venous catheter (PVC) placement is increasingly performed by nurses and requires the acquisition of complex visuomotor and cognitive skills. Technology-enhanced guidance tools have been developed to facilitate learning, yet their educational benefit when added to existing training curricula remains uncertain, particularly in paramedical populations. We conducted a single-center, randomized educational study comparing standard training with technology-assisted training for ultrasound-guided PVC placement among nurses. Twenty nurses were randomized to a control group (standard training; n=11) or an intervention group (standard training plus use of an ultrasound guidance/visualization device; n=9). All participants received identical theoretical instruction and mannequin-based practice. Within 3 months, each nurse performed 10 consecutive ultrasound-guided PVC placements in clinical settings. In the intervention group, the first 5 procedures were performed with device support and the last 5 without to assess skill transfer. The primary outcome was procedural success rate. Secondary outcomes included procedure time, number of attempts among successful procedures, and self-perceived mastery. Analyses were conducted at the attempt level. A total of 200 clinical procedures were analyzed (110 control, 90 intervention). The overall success rate was 78.0%, with no statistically significant difference detected between the control and intervention groups (76.4% vs. 80.0%, P=0.656). Procedures in the intervention group were associated with longer completion times compared with the control group (12.64 vs. 11.25 min, P=0.009). Learning curve analyses showed numerical improvements in procedure time over successive attempts in both groups, but no statistically significant acceleration of learning was detected in the intervention group. Self-perceived mastery did not differ between groups and remained stable over time. In this pragmatic exploratory educational setting, integrating an ultrasound guidance/visualization device into an existing nurse training curriculum was not associated with improved procedural success or faster learning and was associated with longer procedure times. These findings suggest that the educational impact of technology-enhanced training depends less on technology alone than on its curricular integration and support for skill transfer.
Chikungunya fever (CHIKF) has impacted 119 countries and regions globally. In 2025, a local outbreak occurred in Guangdong, China, driven by imported cases from Sri Lanka, resulting in over 25,000 diagnoses. This highlights CHIKF as a significant public health concern. Analyzing imported cases in China and discussing travel medicine and related preventive measures is essential. This study reviewed literature and reports on CHIKF published in international and Chinese databases, as well as government reports, from 2006 to March 1, 2026. Data related to CHIKF, including case numbers, virus types, source countries, and high-risk provinces, were collected, synthesized, and summarized using descriptive statistical methods. Phylogenetic tree analysis, temporal signal assessment, and mutation analysis were conducted on the Chikungunya virus (CHIKV) sequences sourced from China. Between 2006 and 2026, China reported a total of 259 imported CHIKF cases, including those from Hong Kong, Macao, and Taiwan. These imported cases contributed to over 25,000 local transmission cases. Among confirmed cases, the East/Central/South African (ECSA) strain was the most prevalent (61.7%), followed by the Asian strain (37.4%). The primary countries of acquisition were Indonesia and Myanmar, with the Asian strain mostly detected in travelers returning from Indonesia, while the ECSA strain was found in travelers from South and Southeast Asia. The rate of evolution for Chinese cases mirrors that of global trends, and no new branches have emerged. The newly identified mutations in recent years exhibit high-frequency variations in the sequences, along with potential unidentified mutations that have appeared. Returnees from countries with high incidence rates of CHIKF significantly increase the risk of reintroducing the disease to China. An increased number of mutations may enhance the transmission of CHIKV. Therefore, it is crucial to enhance the dissemination of relevant prevention and control measures and expedite vaccine approval to mitigate the incidence of CHIKF among travelers and reduce viral transmission.
A phantom defined by a 3D-printed system of markers representing an anatomical coordinate system is proposed. This phantom is designed for use in magnetic resonance and X-ray imaging devices to validate acquisition parameters and prevent laterality errors during image acquisition and processing. The phantom allows visualization of the coordinate system axes - left-right, posterior-anterior, and inferior-superior - in all orthogonal slices of a volume. A computational method, using the phantom as a reference, is also proposed to automatically detect and correct flips and permutations in RAS coordinate system representations. Testing the phantom across four modalities available in our platforms, followed by conversions of the recordings to the NIfTI format, enables the detection, correction, and adjustment of protocols in 4 out of 5 configurations. The 3D printing models and orientation detection/correction code are shared with the community as open-source and open-access resources to enable quick, cost-effective, and accessible production.
The rapid acceleration of urbanization in developing regions has precipitated a dual crisis for architectural heritage: the physical degradation of structures and the intangible dissipation of cultural memory. Traditional conservation methodologies, which rely predominantly on static documentation, such as photography and manual surveying, are increasingly insufficient for capturing the complex spatial and temporal dimensions of these historic sites. This study introduces a novel, combinatorial methodological framework designed to bridge the gap between rigorous archiving and dynamic public engagement. We detail a workflow that synergizes three distinct technologies: Terrestrial Laser Scanning (TLS) to capture the tangible geometric attributes of the building with millimeter-level accuracy; Conditional Generative Artificial Intelligence (CGAI) to generate historically informed visual representations of lost cultural elements (specifically, traditional temple fair structures) based on archival references; and Augmented Reality (AR) via holographic headsets to superimpose these layers into a unified Mixed Reality (MR) experience. The protocol describes the complete pipeline from data acquisition strategies and point cloud processing to AI-driven model generation and final deployment. This approach yields a dynamic digital simulacrum that successfully overlays high-precision spatial data with interpretive cultural visualizations, offering a technically feasible and scalable workflow for the digital preservation and augmented exhibition of urban heritage landmarks.
Proteinuria is a well-established risk factor for chronic kidney disease progression, and its reduction is associated with improved kidney outcomes. During proteinuric chronic kidney diseases, the abnormal passage of plasma-derived proteins through the damaged glomerular filtration barrier can lead to the activation of various pathophysiological processes in the tubular compartment. These mainly comprise complement activation and excessive proximal tubule reuptake of filtered proteins, such as albumin and associated lipids, which trigger cytotoxic effects through the dysregulation of multiple signaling pathways. Collectively, these signaling events can induce proximal tubular cell apoptosis or the acquisition of injury phenotypes, characterized by the paracrine release of bioactive substances that promote infiltration of immune cells and fibroblast-to-myofibroblast differentiation, eventually contributing to the development of tubulointerstitial fibrosis and progressive loss of kidney function. In this review, we provided an up-to-date overview of the complex mechanisms behind the toxic effects of ultrafiltered proteins on the tubulointerstitium under proteinuric conditions. The mechanistic insights that have been gained recently could be valuable for the future development of new classes of drugs to be used in combination with, or as an alternative to, the currently approved anti-proteinuric treatments in patients who are poorly responsive or unable to tolerate them, respectively.
Phosphorus (P) is essential for plant growth, and its deficiency significantly limits crop productivity. Plant biostimulants offer a sustainable approach to enhance plant tolerance to nutrient stress and reduce fertilizer use. Among these, humic substances (HS) derived from leonardite show promise, though their physiological effects under P deficiency remain unclear. This study evaluated the impact of a leonardite-derived HS on lettuce (Lactuca sativa L.) grown under two P regimes: high P (HP, 1 mM) and low P (LP, 0.2 mM). HS were applied at two concentrations via root (R1: 0.40; R2: 0.60 mL L-¹) or foliar (F1: 7.50; F2: 10.00 mL L-¹) treatments. Phosphorus shortage reduced shoot biomass and chlorophyll content, but stimulated root growth, total phenolic content (TPC), and antioxidant capacity. HS improved shoot growth across both P levels, with R2 being most effective at HP. Under LP, both HS doses produced similar effects. The enhanced tolerance to P deficiency conferred by HS was associated with improved root biometric traits, enhanced P acquisition (PAE), P utilization (PUtE), and overall P use efficiency (PUE), along with elevated acid phosphatase activity, chlorophyll, glycine betaine, TPC, and antioxidant capacity. All HS treatments enhanced root elongation; notably, F2 treatment increased root volume and diameter under LP. Furthermore, HS application modulated the leaf phenolic profile: F2 enhanced the accumulation of specific phenolics, while root-applied HS increased TPC and antioxidant response under LP. In conclusion, this leonardite-derived biostimulant demonstrated potential to enhance plant performance under P-limited conditions, supporting its use for more sustainable nutrient management.
Patient-facing websites operated by medical societies are crucial for disseminating reliable health information; however, their real-world usage and effectiveness are often unquantified. This study investigated the user engagement and demographics of "Scoliosis Town," a patient education website developed by the Japanese Scoliosis Society, to evaluate its performance. We conducted a retrospective analysis of the website's traffic data from June 1, 2018, to March 31, 2023 (58 months), using Google Analytics. Key metrics included the number of users and sessions, user demographics (age and gender), access patterns (device type and acquisition channel), and popular content. The website attracted 2,333,184 users over 3,111,702 sessions. The primary users were female (68.1%), with the 35-44 age group being the largest demographic (29.4%), suggesting the site effectively reached its target audience of patients' mothers. The most frequently viewed pages were those detailing the "causes" and "treatment" of scoliosis. Most users accessed the site via mobile devices (83.3%), primarily through organic search (88.0%), with traffic peaking on weekday evenings. The Japanese Scoliosis Society patient education website successfully reached its intended demographic of caregivers and was actively used to seek fundamental information about scoliosis. This study demonstrates the value of medical society-led digital platforms and validates web analytics as a powerful tool for assessing real-world patient information needs.
Helicobacter pylori colonizes the gastric mucosa of around half of the world's population and is a major cause of chronic gastritis, peptic ulcer disease, and gastric cancer. Current therapies are becoming increasingly ineffective due to the rapid spread of antibiotic resistance, creating an urgent need for new treatment options with distinct mechanisms of action. Drug repurposing offers a practical and cost-effective approach to address this gap. PBT2 is an 8-hydroxyquinoline derivative originally developed for the treatment of neurodegenerative diseases and has more recently been shown to possess antimicrobial activity. In this study, we demonstrate that PBT2 displays potent bactericidal activity against H. pylori, including multidrug-resistant clinical isolates. PBT2 rapidly killed H. pylori in vitro at low concentrations, with faster killing kinetics than commonly used antibiotics, and no resistance was detected after 30 days of continuous exposure. Importantly, PBT2 was effective in clearing an H. pylori infection in a murine model. Quantitative sequential window acquisition of all theoretical-mass spectrometry proteomic analysis revealed that PBT2 triggers broad disruption of essential bacterial processes, including global suppression of translation, impairment of iron-sulfur cluster assembly and respiration, dysregulation of metal homeostasis, and reduced abundance of virulence- and motility-associated proteins. We reported that PBT2 can act as a nickel ionophore, with Ni2+ being the highest-affinity ligand for PBT2 reported to date. Together, these findings suggest that PBT2 acts through a multifaceted, metal-dependent mode of action that limits the potential for emergence of resistance. Our work highlights PBT2 as a promising candidate for repurposing to treat multidrug-resistant H. pylori infections.IMPORTANCEAntibiotic resistance is steadily reducing our ability to treat common bacterial infections, while the development of new antibiotics has slowed. Helicobacter pylori is a clear example of this growing problem, with treatment failures becoming more common worldwide. This study highlights the value of taking a different approach by repurposing existing drugs for new antibacterial uses. Rather than acting on a single bacterial target, the compound examined here disrupts multiple essential processes at once, reducing the probability of resistance developing.
A self-driving metabolomics laboratory has long been envisioned but remains largely unrealized due to the complexity of analytical method design. As an initial step toward this goal, we developed BAGO, a self-optimizing framework for automated liquid chromatography (LC) gradient design in mass spectrometry-based untargeted metabolomics. BAGO aims to enhance global metabolite detection by improving the separation of all compounds, regardless of whether their identities are known or unknown. It operates through a data-driven Bayesian optimization process that iteratively learns from acquired MS data to propose improved gradients. To support this, we propose a global separation index that quantifies coelution among both annotated and unannotated features, enabling robust and structure-agnostic optimization across diverse sample types. Benchmarking across four metabolomics assays involving diverse sample matrices, column chemistries, and gradient durations, BAGO achieved substantial improvements within only 10 optimization iterations by balancing exploration and exploitation. The optimized gradients led to increased numbers of Gaussian-shaped peaks, higher MS/MS acquisition rates, and more annotated metabolites using both identity and analog search approaches. We further applied BAGO to a sex-differentiated metabolomics study of Drosophila abdominal carcasses, completing the workflow in parallel under both initial and optimized gradients. The optimized method resulted in a 41.9% increase in Gaussian-shaped peaks, a 36.8% increase in MS/MS-acquired peaks, and the identification of 18 additional biologically significant metabolites, including sex-associated compounds such as octopamine and pyroglutamic acid. BAGO (https://github.com/HuanLab/bago) is freely available as an open-source tool and represents a generalizable step toward fully automated, self-optimizing experimental workflows in untargeted metabolomics.