Faculty Bibliography

OBJECTIVES/OBJECTIVE:The use of #pathology and #pathologist is increasing on TikTok, a short-form video platform with over 1 billion users. As of July 2024, #pathology had over 21 000 posts and 468 million views, while #pathologist had over 3000 posts. It could be a useful tool for education and recruitment if the content is accurate and engaging. METHODS:To assess the accuracy, engagement, and educational value of this growing content, we conducted a cross-sectional study analyzing 105 English-language TikTok videos identified using these keywords over a 72-hour period. Videos were evaluated using the Patient Education Assessment Tool for audiovisual material (PEMAT-AV) for audiovisual quality, the Global Quality Scale (GQS) for overall content quality, and a modified JAMA benchmark score for information accountability. Additionally, a harm-benefit score categorized educational impact. RESULTS:Statistical analysis revealed that educational content demonstrated significantly higher quality scores on GQS (P = .0001) and PEMAT-AV (P = .0007) than other content types. In contrast, medical profile type was associated with higher PEMAT-AV (P = .0147), JAMA (P = .0332), and harm-benefit (P = .0004) scores. CONCLUSIONS:While the volume of pathology-specific content is currently limited, the high average engagement metrics-298 100 followers, 1.5 million views, and 67 884 likes per video-indicate substantial user interest. The higher-quality scores for educational and medical content suggest that pathology content creators are generally knowledgeable and accurately represent the field on TikTok, highlighting TikTok's potential as a valuable platform for disseminating reliable pathology-related information.

Integrated diagnostics is an emerging multidisciplinary model of care that integrates traditionally siloed domains, including pathology, radiology, genomics, and laboratory medicine, into a coordinated framework designed to improve diagnostic accuracy, treatment selection, and clinical outcomes. In this position statement, the EFLM Integrated Diagnostics Committee proposes a concise and operational definition of integrated diagnostics and outlines the relevance for healthcare systems. Integrated diagnostics has the potential to advance precision medicine through improved data integration, more coordinated interpretation, and enhanced clinical decision-making. Drawing on multidisciplinary expert consensus, we recommend adoption of a standardized conceptual framework to support research, clinical implementation, interoperability, and policy development across healthcare systems with implementation adapted to local needs, scale, and digital maturity.

When a suspected viral hemorrhagic fever (VHF) case presents to a healthcare facility, healthcare personnel must be able to safely provide initial stabilizing care, which may involve performing basic routine laboratory testing. Current gaps exist in the ability of frontline acute care hospitals to safely perform routine laboratory tests on patients with suspected VHFs that generate category A waste. This review outlines a potential solution for frontline acute care hospitals to perform electrolytes, hemoglobin/hematocrit, and malaria testing, in accordance with National Special Pathogens System guidelines, in the patient's isolation room. We discuss guidance on laboratory risk assessment, equipment considerations, space requirements, staffing solutions, waste management, cost estimates, and remaining challenges. Our manuscript provides frontline acute care hospitals with a potential solution to safely provide a minimum set of routine laboratory tests for patients with suspected VHF.

BACKGROUND:Environmental epidemiology studies increasingly integrate "big" geospatial and health data sets to examine associations between environmental factors and health outcomes. Using such data sets ─ and linking between them ─ presents a number of complexities with regard to study design and analytic approaches. These complexities are often magnified with the integration of additional contextual data representing other neighborhood characteristics including socioeconomic factors. Guidance regarding the design of environmental health studies that leverage "big" geospatial and health outcome data is limited and fragmented. OBJECTIVE:Drawing on methodological literature and case studies, this commentary outlines common challenges related to geospatial and health data linkages, posing a series of guiding questions and considerations for investigators conducting environmental health studies, particularly analyses with an etiological focus. DISCUSSION:Recommendations include: 1) using a target trial approach to guide causal analysis, 2) aligning measures with hypothesized causal mechanisms, 3) exploring opportunities to "groundtruth" and validate data, and 4) prioritizing interdisciplinary science. The goal of the commentary is to consolidate insights from multiple disciplines ─ including exposure science, epidemiology, and sociology ─ to provide a foundation for etiologic research focused on advancing environmental health for all populations.

BACKGROUND:Coronary microvascular dysfunction (CMD) is a mechanism of ischemia with nonobstructive coronary arteries (INOCA) diagnosed by invasive coronary function testing (CFT). It is unknown whether CMD reflects a systemic microcirculatory disorder. Sidestream darkfield (SDF) microscopy permits noninvasive imaging of red blood cells (RBCs) in the sublingual microcirculation. OBJECTIVES/OBJECTIVE:We sought to evaluate whether SDF microscopy identifies sublingual microvascular abnormalities in patients with INOCA due to CMD. METHODS:Adults with INOCA underwent CFT for CMD, defined by abnormal coronary flow reserve <2.5 or index of microcirculatory resistance ≥25. Sublingual SDF microscopy was performed to determine the endothelial glycocalyx perfused boundary region (PBR), RBC filling percentage (%RBC), and perfused microvascular density (PMVD). RESULTS:A total of 135 participants with INOCA (mean age 59.3 ± 12.1 years, 80% female) underwent CFT and sublingual SDF microscopy. CMD was present in 63 participants (46.7%). The median PBR was 1.96 (IQR: 0.4), median %RBC was 72.6 (IQR: 8.0), and median PMVD was 406 (IQR: 141). No differences in sublingual PBR, %RBC, and PMVD were observed by CMD status. No correlations between sublingual parameters and continuous measures of coronary flow reserve or index of microcirculatory resistance were observed. CONCLUSIONS:Noninvasive SDF microscopy did not identify sublingual microvascular abnormalities in INOCA patients with CMD.

Pharmaceutical contamination by antibiotics poses a major environmental challenge, particularly as regulators set limits for treated wastewater effluents. This study presents a hitherto unreported application of pulsed high-frequency sonication for degrading trimethoprim (TMP) and associated antimicrobial resistance genes (ARGs) in synthetic and reject wastewater. Optimization with synthetic binary samples revealed that sonication achieved >80% TMP removal at calorimetric-based energy per order (EEO) of 116.54 kW/m³, but mineralization remained low (∼10%). Prolonged treatment (5-6 h) fully eliminated TMP, yielding heavily hydroxylated and probably substituted products with short-chain alcohol groups, which exhibited lower biodegradability than demethylated/demethoxylated metabolites (e.g. m/z 245) dominant at 1-4 h. Notably, 30 min sonication produced hydroxylated TMP (m/z 307) with slight cytotoxicity to HeLa cells. The diaminopyrimidine (DAP) moiety of TMP, which drives its antimicrobial activity, remained largely intact in most metabolites identified in all the treatment times. This indicates that extending the treatment time would not provide additional benefits. Rather, sonication-based degradation should be tuned to promote site-specific attacks on antibiotic molecules, thereby inhibiting antimicrobial activity and minimizing the risk of ARGs development in treated water. Combining high-frequency sonication with low dose ozonation (via Venturi injection) effectively removed TMP (>98%) from low-solids reject wastewater, alongside substantial reductions in solids and COD. However, at higher solids levels, the process may induce cell lysis and release of TMP and ARGs from particulates. These findings position high-frequency ultrasound assisted ozonation as an effective treatment for wastewater streams with low solids, though careful control is needed to mitigate ARG mobilization in turbid matrices.

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease characterized by high levels of cellular heterogeneity and pronounced microenvironmental remodelling. Dynamic changes during its initiation and progression contribute to resistance to conventional therapies. Building upon key molecular catalogues established by bulk and single-cell profiling studies that have advanced our understanding of PDAC biology, recent advances in spatial biology have provided much-needed insights by elucidating regionally compartmentalized transcriptomic and proteomic programmes within the PDAC microenvironment. In parallel, emerging computational frameworks in digital pathology and artificial intelligence have advanced the field into a high-dimensional, quantitative discipline, particularly for classifying molecular and clinical features from histopathology images. Despite these advancements, integration of these two modalities remains a major challenge. Here, we summarize the convergence of molecular features identified through spatially resolved profiling in PDAC and its precursor lesions, as well as current developments in AI-powered pathology in cancer research. We further propose a multi-modal integration framework that maps molecular states onto morphological and architectural phenotypes, offering a roadmap for spatially informed patient stratification beyond descriptive tissue characterization. We posit that the path forward relies on disciplined cross-scale integration of spatial, histological, and clinical data to ensure meaningful translation into clinical practice.

OBJECTIVES/OBJECTIVE:The COVID-19 pandemic highlighted an urgent need to more efficiently identify patients at highest risk for developing respiratory failure. We investigated whether plasma levels of lung injury biomarkers are associated with progression to respiratory failure among adults hospitalized with COVID-19 pneumonia without respiratory failure at admission. DESIGN/METHODS:This was a nested case-control study of COVID-19 patients enrolled in the Accelerating COVID-19 Therapeutic Interventions and Vaccines-3 (ACTIV-3)/Therapeutics for Inpatients with COVID-19 (TICO) platform trial who were on less than 20 L/min supplemental oxygen at enrollment. We compared baseline measurements of lung injury biomarkers between participants who progressed to respiratory failure or died by study day 10 (cases) and matched controls who did not progress to respiratory failure or death. Cases and controls were matched 1:1 on age, baseline oxygen requirement, immunomodulator use, and study arm. SETTING/METHODS:Hospitals enrolling in the ACTIV-3/TICO trials. PATIENTS/METHODS:Four hundred five cases and 405 matched controls. INTERVENTIONS/METHODS:None. MEASUREMENTS AND MAIN RESULTS/RESULTS:Baseline levels of plasma interleukin (IL)-6, IL-8, IL-18, tumor necrosis factor receptor, angiopoietin-2, soluble receptor for advanced glycation end-products (sRAGE), C-reactive protein (CRP), and surfactant protein D (SPD) were compared between cases and controls using matched logistic regression. Forward variable selection was used to identify biomarkers that were independently associated with progression to respiratory failure or death in a multivariate model. All lung injury biomarkers with the exception of SPD were significantly associated with progression to respiratory failure or death, with sRAGE demonstrating the highest odds ratio (OR) for each doubling of biomarker level (OR, 1.85; 95% CI, 1.61-2.12). In multivariate regression analysis, sRAGE, IL-6, and CRP were independently associated with progression, with sRAGE as the biomarker with the strongest association. CONCLUSIONS:Baseline levels of plasma lung injury biomarkers are significantly associated with progression to respiratory failure or death among hospitalized COVID-19 patients without respiratory failure at admission. These findings support the potential utility of measuring lung injury biomarkers in patients hospitalized without respiratory failure and should be tested in more heterogeneous patient groups including non-COVID-19 cohorts.

BACKGROUND:Inflammatory proteins detectable in blood reflect pathoanatomic injury patterns after traumatic brain injury (TBI). Identifying biomarkers of secondary neurologic and systemic injury may improve detection of patients at risk for clinical decline and chronic disability. This study examined the utility of acute and subacute inflammatory biomarkers to differentiate TBI diagnosis and severity, and predict 6-month outcomes. METHODS:-unit increase in biomarker level were reported. RESULTS:Ten biomarkers (c-reactive protein (CRP), serum amyloid A (SAA), interleukin (IL)-1ꞵ, IL-2, IL-4, IL-6, IL-10, IL-15, IL-17A, tumor necrosis factor (TNF)-α) differed significantly between GCS 3-12 vs. 13-15 TBI, CT-positive vs. CT-negative TBI, and GCS 3-12 TBI vs. OC, at both D1 and W2 (p < 0.001). IL-6, CRP, and SAA showed good discrimination of clinical TBI severity (D1/W2 area under-the-curve (AUC): 0.87/0.87, 0.82/0.88, 0.80/0.85, respectively), and moderate-to-good discrimination of radiographic TBI severity (D1/W2 AUC: 0.81/0.82, 0.78/0.83, 0.77/0.79, respectively). Five W2 biomarkers emerged as multivariable predictors of 6-month unfavorable outcomes (IL-15: AOR = 2.26 [1.14-4.49]; SAA: AOR = 1.91 [1.37-2.67]; IL-6: AOR = 1.80 [1.25-2.61]; IL-17A: AOR = 1.72 [1.24-2.39]; CRP: AOR = 1.40 [1.06-1.85]). CONCLUSIONS:Ten circulating inflammatory proteins were associated with TBI diagnosis and severity at D1 and W2. Of these, five biomarkers expressed subacute (W2) levels predictive of 6-month death/severe-disability, underscoring their potential for validation as a novel biomarker class and integration into TBI prognostic models. Distillation of pro- and anti-inflammatory biomarker cascades in TBI could facilitate precision medicine approaches for risk stratification and therapeutic modulation.