We report the emergence of macrolide-resistant Bordetella pertussis during a pertussis outbreak in Peru. Among 68 cases, 31% carried the A2047G gene mutation, conferring resistance to macrolides. Whole-genome sequencing revealed 2 genetically distinct groups, indicating multiple introductions into Peru. Our findings support strengthening surveillance for macrolide-resistant pertussis to inform control strategies.

Asthma and chronic obstructive pulmonary disease (COPD) affect more than 650 million people worldwide and remain leading causes of disability, with a rising burden as populations age. Conversational agents (CAs) may offer a more interactive alternative. However, the evidence in obstructive lung disease has not been mapped.

The aim of this study is to map the literature on CA use in asthma and COPD, to describe the roles they have been designed to perform, the outcomes that have been measured, and to map the study designs and methods characterizing the current evidence.

A scoping review was conducted following the Arksey and O'Malley framework. A total of 9 databases (CINAHL, CENTRAL, Embase, IEEE Xplore, PubMed, ProQuest, Scopus, Web of Science, and Google Scholar) were searched from January 1, 2014, to February 22, 2025. Data were synthesized using inductive content analysis and organized via the Patterns, Advances, Gaps, Evidence for Practice, and Research Recommendations (PAGER) framework. Reporting followed PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines.

A total of 6275 records were screened, and 16 reports from 15 studies were included. Studies reported CAs being used for information provision and patient education, health data collection, and emotional or motivational support. Only 4 studies measured direct clinical outcomes (eg, asthma control or medication adherence). Reported usability and satisfaction findings were mixed, with recurring concerns about conversational flow, responsiveness, trust, and personalization.

The evidence base for CAs in asthma and COPD remains in early developmental stages. It consists mainly of small feasibility, developmental, and pilot studies, providing limited evidence on whether CAs improve clinical outcomes. Current evidence can mainly describe the roles CAs have been designed to perform and the user-experience factors that influence engagement. Adequately powered, longitudinal trials using clinically meaningful and standardized endpoints are required before effectiveness can be assessed. Future development should place patients, as the end users, at the center of co-design, with clinicians, including nurses, involved to ensure clinical relevance and safe integration into care.

Nonpharmaceutical interventions (NPIs), including digital contact tracing (DCT), are central to control the spread of airborne pathogens. Nevertheless, the effectiveness of individual interventions and the role of personal behavior remain insufficiently understood.

This study aimed to understand how NPI combination and the individual's behavior contribute to reducing airborne pathogen transmission.

We disentangle the efficacy of individual NPIs, including DCT, with a novel microlevel, behavior-driven agent-based model (ABM) that simulates individual human behavior to analyze the effectiveness of nonpharmaceutical interventions on airborne pathogen propagation. Our model's Zeitgeber architecture delineates contextual characteristics, including daytime, daily routines, locations, and activities. Our method determines each agent's current location and behavior in a realistic environment under NPI restrictions. We model viral load transfer between agents from contact duration, distance, and the infected agent's infectiousness level. We examine the effects of DCT-related behavior parameters, including adoption, adherence, and compliance, with a default intervention, and with further restricting and relaxing NPIs, on key pandemic indicators.

The effect analysis of personal choices regarding DCT indicates that a high DCT adoption rate (activate DCT) should be the first goal of a DCT implementation campaign, followed by adherence (notify others), and compliance (follow recommendations, if notified). There is no monotonic path in the behavior parameter space to improve pandemic characteristics. Assuming realistic behavior with regard to DCT, total infections were reduced by 43% in the default intervention, while DCT combined with other NPIs reduced total infections by up to 52%. Surprisingly, however, some restricting NPI combinations do not improve pandemic characteristics.

DCT implementations will face challenges, as pandemic characteristics do not consistently improve when behavior parameters ( adoption, adherence, and compliance) are increased. When considering realistic behavior, more is not always better; NPI combinations can interfere with each other to the detriment of pandemic control. Our approach offers fine-grained insight on the effectiveness of NPI combinations that cannot be obtained in human studies due to confounding effects. Thus, our approach can guide future pandemic control efforts and prioritization for pandemic preparedness.

Protecting populations against pathogens that induce non-sterilizing immunity remains a major public health challenge. However, conventional mathematical models are often incompatible with within-host data, offering limited insight into how immune responses drive epidemics. To address this gap, we develop a modular, data-driven mathematical framework that links immunological and virological dynamics to population-level transmission. Our approach derives infectiousness from viral load and protection against reinfection from time-varying immune responses, allowing epidemic trajectories to emerge from the summation of individual-level processes. As an example, we use viral load quantified in a SARS-CoV-2 human challenge study and binding antibody levels post-vaccination against SARS-CoV-2. The framework captures individual-level infection dynamics and shows that immune responses fundamentally shape epidemic trajectories. We show that weak correlations between antibody levels and protection lead to frequent reinfections and endemic circulation, whereas strong correlations generate recurrent explosive outbreaks. We fit the model to simulated case data to demonstrate its ability to recover underlying protection and reinfection dynamics. Applied to real-world data, this framework could provide new insights into the drivers of epidemic patterns and inform vaccination strategies for pathogens with non-sterilizing immunity.

Spinal cord stroke (SCS) is an underrecognized cause of severe acute myelopathy in children that can be misdiagnosed as an infectious or inflammatory process. Limited characterization of clinical and neuroimaging features of pediatric SCS impede timely and accurate diagnoses. Our objectives were to (1) identify clinical and radiologic features of SCS to prompt timely evaluation and accurate diagnosis and (2) gain insight into mechanisms of SCS.

We conducted a retrospective case analysis of children (<18 years old) diagnosed with SCS at a specialized referral institution between 2010 and 2025. Clinical records, imaging, and laboratory data were reviewed to identify key features of pediatric SCS.

Among the 56 included patients, 28 were male (50%), and the age distribution was bimodal, with peaks at 1 and 14 years. Pediatric SCS presented with hyperacute onset of motor, sensory, bladder/bowel, and pain symptoms. The lesions were predominantly anterocentral, longitudinally extensive, with the cervical spinal cord being most often affected. Over time from the onset of symptoms, MRI diffusion restriction decreased, while gadolinium enhancement increased. CSF profile was noninflammatory in 95% of cases. Suspected mechanisms were identified in 63% of cases, with vascular compression being the most commonly identified mechanism in 17 participants (30%), while 38% were idiopathic. Chiari I malformations were identified as the main suspected cause of vascular compression, occurring in a subgroup of young patients with cervical SCS (n = 8, 14%). Serum studies identified hypercoagulability in 38% of the 40 participants evaluated.

Recognition of specific clinical and neuroimaging profiles in pediatric patients with SCS may facilitate earlier identification and intervention. We propose a systematic evaluation of clinical history, with particular attention to the temporal course from symptom onset to nadir, early acquisition of spine MRIs with diffusion-weighted imaging sequences, serologic evaluations for hypercoagulability, and CSF studies to exclude inflammatory etiologies. This approach will provide a framework for continued efforts to better understand the mechanisms underlying pediatric SCS and develop prevention and treatment strategies.

Patients with chronic traumatic brain injury (cTBI) experience long-term exacerbated neurological decline, which is even more severe in older patients, yet the underlying mechanisms remain unclear. Cranial bone marrow (CBM) has recently been recognized as an adjacent immune surveillance organ of the brain that rapidly responds to acute brain injury. We investigated whether CBM-derived immune cells contribute to chronic neuroinflammation after cTBI by integrating clinical specimens, cell-tracing strategies, multiomics profiling, transgenic animal assays, adoptive cell transfer, and a proof-of-concept randomized clinical trial. We found that cTBI induced persistent aberrant myelopoiesis in the CBM, characterized by expansion of inflammatory monocytes/macrophages (Mo/Macs), which aggravated with aging. These CBM-derived Mo/Macs actively migrated into brain parenchyma, where they fueled chronic neuroinflammation and drove neurological deficits. Mechanistically, age-related peroxisome proliferator-activated receptor α (PPARα) deficiency caused lipid metabolism dysfunction in these Mo/Macs, enhancing H3K4me3-mediated regulation of inflammatory chromatin states and thereby promoting neuroinflammation. Activation of PPARα via fenofibrate rectified Mo/Mac lipid metabolism and reduced inflammatory Mo/Mac infiltration into the brain. In a proof-of-concept randomized clinical trial enrolling 40 older adult patients with cTBI, fenofibrate treatment reduced plasma neurofilament light chain levels and improved cognitive functions. Together, these findings demonstrate that CBM-originated inflammatory Mo/Macs may serve as key inflammatory drivers of cTBI and further show that fenofibrate represents a potential therapeutic strategy for cTBI treatment in older adults.

Existing clinical assessments for upper-limb motor rehabilitation poststroke pose limitations as end points for efficient clinical trials. This study aimed to develop a digital metric for assessing motor recovery using accelerometer data collected in naturalistic environments. We constructed the digital arm performance scale (DAPS) by analyzing ∼23,000 hours of data from 215 participants, including healthy individuals and subacute and chronic stroke survivors. We decomposed continuous upper-limb accelerometer data into lower-level movement segments, from which key features were extracted and aggregated using a linear mixed-effects model to produce an interpretable digital biomarker. DAPS demonstrated excellent reliability, sensitivity, concurrent validity, known-groups validity, discriminant validity, and responsiveness. Power analysis indicated that DAPS could reduce the required sample size for clinical trials with upper-limb motor recovery end points by more than 60% compared with traditional assessments. These findings highlight the potential of DAPS as a low-burden, scalable assessment tool for upper-limb motor recovery, with potential applications in both clinical trials and practice.

People with HIV (PWH) are at increased risk for cardiovascular diseases and other age-related comorbidities. These risks can be reduced through moderate to vigorous physical activity (MVPA), but MVPA can be difficult to sustain over time. We tested tailored text messages combined with motivational interviewing (MI) to sustain MVPA among PWH. Messages were created using Two Minds Theory and matched to daily survey responses about exercise barriers. 118 PWH ages ≥ 50 were initially randomized to high-intensity interval training or continuous moderate-intensity exercise. After 16 weeks, 92 participants were re-randomized to receive either tailored messages plus MI, or educational control messages, for 12 weeks. Both groups completed daily barrier surveys and wore an ActiGraph monitor for 1 week/month. PWH in the tailored-messaging plus MI group maintained their MVPA, ending at M = 30.5 min per day (SD = 36.7), compared to a decrease among PWH in the educational-control group, ending at M = 26.0 (SD = 25.8), F(1, 255) = 5.76, p = .02, d = 0.51 for the group-by-time interaction using intent-to-treat principles. Findings were similar based on both actigraphy and self-reported MVPA, and were robust to attrition. PWH in the tailored-messaging group also reported higher exercise self-efficacy and better perceived health over time, relative to the educational-control group. Exploratory analyses suggested that the tailored messages' effects were additive to motivational interviewing. In this study, an automated tailored-messaging intervention led to sustained MVPA. Tailored messages were superior to non-tailored educational messages, and may help PWH maintain their long-term health.Trial registry ClinicalTrials.gov study NCT04550676.

To examine the role of non-HDL cholesterol (non-HDL-C) as a predictor of coronary atherosclerosis and atherosclerotic cardiovascular disease (ASCVD) risk in South Asians, and its utility relative to LDL-C and apolipoprotein B for risk stratification and lipid-lowering therapy in this high-risk population.

South Asians experience a disproportionate and premature burden of ASCVD that is not fully explained by conventional risk factors and is underestimated by most established risk calculators. They exhibit a characteristic atherogenic dyslipidemia - elevated triglycerides, low HDL-C, and a predominance of small dense LDL and remnant particles, often with only modestly elevated LDL-C - that is inadequately captured by LDL-C but well reflected in non-HDL-C. Non-HDL-C demonstrates a graded association with ASCVD, correlates with atherosclerotic plaque burden across imaging modalities (coronary artery calcium, coronary CT angiography, and intravascular ultrasound), and has outperformed LDL-C for risk prediction in large meta-analyses. Recent US and Indian guidelines now incorporate non-HDL-C as a coprimary treatment target, with the Lipid Association of India providing South Asian-specific thresholds. Non-HDL-C is an inexpensive, non-fasting lipid measure that better captures the atherogenic lipoprotein burden of South Asians than LDL-C alone and may improve risk stratification and treatment in this group. Data specific to non-HDL-C in South Asians remain limited; future work should define population-specific thresholds, clarify its relationship with apolipoprotein B and lipoprotein(a), and address the under-representation of South Asians in clinical trials and persistent barriers to preventive care.

Although the association of lipoprotein(a) (Lp(a)) with coronary heart disease was reported over 60 years ago, and subsequent studies have identified a causal and independent role for Lp(a) in disease, many fundamental unanswered questions persist surrounding the biology of this enigmatic lipoprotein. There remain critical questions surrounding the structure and metabolism of Lp(a) and the unique biochemical properties of Lp(a) that drive its pathogenic properties in the vasculature. These questions are critical to address as we rapidly approach the availability of drugs that can specifically lower Lp(a).

Lp(a) is more atherogenic than low-density lipoprotein (LDL) on a per-particle basis, and this is largely thought to be due to the presence of the unique glycoprotein apolipoprotein(a) (apo(a)) on Lp(a). Moreover, Lp(a) is enriched in proinflammatory lipids such as oxidized phospholipids (OxPL) and diacylglycerols (DAG). A large body of in vitro data as well as emerging transgenic Lp(a) mouse data and human imaging studies have provided evidence for a multitude of proatherosclerotic mechanisms for Lp(a), exerted on inflammatory/immune cell types such as monocytes and macrophages, and on vascular cells including smooth muscle cells and endothelial cells. These effects would be expected to exacerbate atherosclerosis and promote a rupture-prone plaque phenotype. In addition, Lp(a) may directly contribute to atherothrombosis by potentiating platelet responses and the coagulation cascade and causing the formation of a lysis-resistant clot architecture. While outcomes trials of potent Lp(a)-lowering therapies may soon reveal whether these treatments prevent atherothrombotic events in high-risk patients, further animal model and human studies will be required to understand the nature of these beneficial effects.