Journal of Clinical Pathology

BackgroundUnited Kingdom Standards for Microbiology Investigations limits the pre-analytical delay of blood cultures to a maximum of four-hours between collection and incubation. Compliance with this delay standard is a measure of the ability of a microbiology service to support the management of sepsis which is a life-threatening complication of infection. A positive blood culture confirms the infection and an early result is critical to the effective management of the condition. Delayed results lead to the prolongation of empiric broad spectrum antimicrobial therapy which is considered a causal factor in the emergence of antimicrobial resistance. This retrospective observational study documents compliance with the standard by microbiology services in England in 2022/23. The impact of laboratory centralisation on the ability of microbiology services to comply with this standard is examined. MethodsFreedom of Information requests were submitted to 116 National Health Service Trusts/administrative units in England requesting retrospective audit data showing compliance with the recommended pre-analytical delay standard. Data relating to service configuration and cost were also requested. ResultsResponses were received from 89 Trusts (76.7%) managing 146 hospitals. Overall, the rate of compliance was low, with only four hospitals (2.7%) showing full compliance and 31.5% showing >80% compliance. ConclusionsPoor rates of compliance with the PAD standard are a concern as prompt attention to blood cultures improves patient outcomes from sepsis and supports antimicrobial stewardship. Laboratory centralisation has resulted in withdrawal of staff and facilities from some hospitals with insufficient investment in others, leading to a demonstrable inability of many hospitals to comply with this standard. Compliance will require investment in microbiology services. The financial implications of the improvements proposed should be evaluated in the context of overall health care and community benefits.

BackgroundNeonatal sepsis is a major cause of morbidity and mortality, particularly in low- and middle-income countries such as Senegal, where incidence is 78-104 per 1,000 live births and mortality exceeds 20 per 1,000, with case fatality rates around 36%. Diagnosis is difficult due to non-specific clinical signs and lack of molecular biomarkers, highlighting the need for improved early diagnostic molecular markers that could be applied even outside of hospital settings. ObjectivesCompare neonatal and adult serum proteomes to establish a reference and identify serum protein biomarkers of neonatal sepsis. MethodsSerum samples from Senegalese neonates and adults were analyzed using data-independent acquisition (DIA) proteomics on neat serum (Evosep-timsTOF HT platform). The cohort comprised 6 neonates with non-confirmed sepsis (NCS), 22 with confirmed sepsis (CS), 17 healthy newborn controls (HC), 6 unclassified and 20 healthy adults. Downstream analyses included differential protein abundance testing, unsupervised clustering, weighted gene co-expression network analysis (WGCNA), and correlation analyses with clinical parameters. ResultsWe identified 979{+/-}20 proteins in newborns versus 718{+/-}40 in adults. Newborns showed reduced immune-response proteins, a narrower dynamic range, and increased structural proteins such as collagens, consistent with immune immaturity and tissue development. Unsupervised WGCNA analysis led to a 53-protein cluster discriminated CS from NCS/HC. Some of these dysregulated proteins identified have already been reported in independent studies using different approaches in neonatal and/or adult sepsis. Our larger panel however of identified markers maps to three major biological processes involved in sepsis: (i) pathogen sensing (LBP, CD14), and acute-phase inflammation (e.g. CRP, SAA1/2, ORM1/2); (ii) innate immune activation and leukocyte recruitment (e.g., FCGR3A, CSF1R, CD163, CD206) and final platelet exhaustion and metabolic dysregulation, (e.g., PF4, PPBP, THBS1, GP5); (iii) endothelial injury and microvascular dysfunction with tissue remodeling (e.g., ICAM1, VCAM1, VWF, SPARC) and loss of protective lipoproteins and serpins (e.g., APOA1, APOA2, APOM, SERPINA4, SERPINA5) ConclusionThis study provides a very comprehensive neonatal serum proteome characterization and identifies, for the first time, a protein panel of proteins mapped to three major processes in sepsis.

Background: External Quality Assurance (EQA) is an essential component of modern laboratory medicine. Current scientific evidence on EQA focuses primarily on the analyses carried out by EQA providers while relatively little research has been conducted in individual clinical laboratories. Methods: In this retrospective single-center observational study in a clinical laboratory, EQA results were analyzed over a period of four years (2021-2024). The evaluation was based on EQA action reports documented in the institutes internal quality management system. Deviations were classified according to department, type of discrepancy, root cause category (analytical, preanalytical, systemic, unidentifiable), and measures taken. Results: A total of 7226 EQA participations were evaluated during the observation period. The overall error rate remained consistently low, ranging between 0.8% and 1.6%, with no significant change over time (p = 0.87). Most deviations occurred in the departments of clinical chemistry and immuno/autoimmune diagnostics (p < 0.001). These were predominantly quantitative discrepancies (false low/false negative or false high/false positive). Root cause analysis showed a clear dominance of analytical causes (p < 0.001), while preanalytical and systemic causes were identified less frequently. In most cases, corrective measures, such as re-analyses, recalibrations, process adjustments, or staff training, were implemented promptly. Hard structural measures, such as changing methods or discontinuing tests, were rarely necessary. Conclusion: In a clinical laboratory, EQA is an important tool for structured error analysis and continuous quality improvement. Consistent processing of deviating EQA results goes hand in hand with stable analytical performance and a low error rate.

Background: Wide-spread mast cell (MC)-associated symptoms and MC activation syndrome (MCAS) are often reported in patients with hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD). The goal of this study was to develop a novel MC score based on 11 self-reported MC-related conditions with clinical and research utility to better understand MC symptoms in hEDS and HSD patients. Methods: From November 1, 2019, to June 13, 2025, patients (n=2,141) filled out an Intake Questionnaire at the Mayo Clinic Florida EDS Clinic that included 11 self-reported questions related to categories of MC-related conditions for a MC score ranging from 0/11 to 11/11. Based on the MC score distribution in hEDS and HSD patients, a MC score of 0-1 was considered a low MC score and [&ge;]5 was considered a high MC score. Symptoms/comorbidities were compared between patients with high vs. low MC scores. Results: From the 2,141 hEDS/HSD patients, 535 (25.0%) had a MC score [&ge;]5 (Hi MC). MCAS-specific symptoms such as nausea and vomiting were reported more often in hEDS/HSD patients with a high vs. low MC score (p<0.0001). Random clinical blood tryptase and urinary MC markers were not elevated in patients with high MC scores (n=50/group), although high MC scores were found to significantly reduce urinary creatinine levels indicating that the protein used to normalize data was affected by MC activity. In contrast, random blood IgE, tryptase and major basic protein (MBP) by ELISA were increased in patients with high MC scores (e.g., IgE hEDS p=0.0004, HSD p=0.003). Of note, the percentage of patients reporting abuse or post-traumatic stress disorder was nearly doubled in patients with high vs. low MC scores (Abuse and PTSD: hEDS p < 0.0001; HSD p < 0.0001). Overall, 109/135 (80.7%) in hEDS and 129/135 (95.6%) in HSD reported more symptoms/comorbidities if they had a high MC score. Conclusions: We found that hEDS/HSD patients with high MC scores self-reported more widespread symptoms/comorbidities and higher MC-related blood markers than patients with low MC scores indicating the utility of this tool to evaluate the level of widespread MC activity in hEDS, HSD and other patients.

PurposeOvarian clear cell carcinoma (OCCC) is strongly associated with endometriosis and shows geographic variation in incidence. We investigated whether OCCC and adjacent endometriosis exhibit distinct transcriptional states and whether these patterns differ between United Kingdom (UK) and Japanese cohorts. Experimental DesignWe performed whole-transcriptome spatial profiling on specimens from 16 OCCC cases (8 UK, 8 Japan) in which tumor and endometriosis were both present. Gene expression was analyzed in tumor, endometriosis and stroma. ARID1A status was assessed by immunohistochemistry. ResultsMedian age was 59 years (range 26-82). 13/16 cases (81.3%) had early-stage disease. Tissue compartment rather than cohort of origin was the dominant source of variation across endometriosis and tumor regions. Endometriosis was enriched for inflammatory and immune-related pathways compared to tumor, whilst there was greater representation of chromatin and protein-DNA complex assembly pathways in tumor regions. These patterns were conserved across both cohorts and after stratification by ARID1A status. Mesenchymal-associated gene expression scores also significantly differed across stroma, endometriosis and tumor with clear compartmental separation. Cell type deconvolution analyses showed clear compositional differences between stromal and epithelial disease compartments. ConclusionsOCCC and coexisting endometriosis are transcriptionally distinct, with the dominant contrast being compartmental rather than geographic. ARID1A alone is unlikely to account for the principal spatial transcriptional states identified here. Further analyses will be required to ascertain whether these differences reflect genuine biological differences between OCCC and coexisting endometriosis or represent different stages of endometriosis-associated tumorigenesis. Translational RelevanceOvarian clear cell carcinoma often arises in association with endometriosis, yet the biological transition between these lesions remains poorly understood. Using spatial transcriptomics in matched tumor and adjacent endometriosis from Japanese and UK cohorts, we showed that endometriosis is characterized by inflammatory and antigen-presentation features, whereas tumor regions showed chromatin-organization and oncogenic transcriptional states. These patterns were largely maintained irrespective of ARID1A status and geographic background. In addition, spatial deconvolution suggested differences in local immune composition, with tumor regions showing relatively greater neutrophil- and T cell-associated signals. Together, our data suggest that OCCC and coexisting endometriosis share a spatially linked tissue context, but that tumor regions have distinct transcriptional profile and microenvironment that may be involved in the malignant transformation and inform interpretation of molecular classification in endometriosis-associated OCCC.

Background Coeliac disease (CD) diagnosis on duodenal biopsies is limited by interobserver variability. We have previously demonstrated pathologist-level performance with our artificial intelligence (AI) model for the histopathological diagnosis of adult CD, but not in paediatric practice. As paediatric CD screening programmes expand internationally, accurate and scalable diagnostic tools are needed. We investigated whether an AI model trained exclusively on adult whole-slide images (WSIs) can generalise to paediatric CD diagnosis across independent centres. Methods A training and validation dataset of 9,958 WSIs from 8,421 adult patients (961 CD) from five centres was used to develop an ensemble of multiple-instance learning models using features from a foundation model. Testing was performed on 708 consecutive paediatric patients (86 CD) from two centres (Edinburgh and Southampton) not included in training. Model calibration was assessed, and probability outputs were grouped into clinically interpretable categories. Findings In adult cross-validation, the AI model achieved an area under the receiver operating characteristic curve (AUC) of 98.7%, sensitivity of 84.9%, specificity of 99.0%, and negative predictive value (NPV) of 98.1%. On testing (paediatric) datasets, performance remained high (AUC 98.8%, sensitivity 80.2%, specificity 98.4%, NPV 97.3%). Restricting analysis to predictions outside the intermediate-probability range (predicted CD probability <10% or [&ge;]65%; 85.3% of cases) improved sensitivity to 100% and specificity to 98.7%. No misclassifications were observed among high-confidence predictions (<2% or [&ge;]85%; 66.0% of cases). The expected calibration error was 0.03. Performance improved significantly when biopsies from both duodenal sites (bulb [D1] and descending [D2/3]) were considered. Interpretation Our AI model, trained on adult biopsies, generalises to paediatric CD diagnosis across centres and scanner platforms. Well-calibrated probability outputs provide clinically interpretable measures of diagnostic confidence and could support safe identification of CD-negative biopsies within defined thresholds. These findings demonstrate the feasibility of applying adult-derived AI models in paediatric populations and reinforce the importance of multi-site (D1 & D2) biopsy sampling.

BackgroundClassification of central nervous system (CNS) tumors has become increasingly complex over the past decade, raising concerns about the availability, feasibility and sustainability of comprehensive molecular diagnostics. We have evaluated nanopore whole genome sequencing (nWGS) as a single workflow to replace multiple diagnostic assays. MethodsWe performed nWGS on DNA extracted from 90 adult CNS tumor samples (58 retrospective, 32 prospective) and compared the results to findings from standard of care (SoC) diagnostic work-up. Analysis was done through an automated workflow that consolidated diagnostically and therapeutically relevant genomic alterations, including copy-number variation, structural, and single-nucleotide variants, chromosomal aberrations, gene fusions and methylation-based classification. ResultsNanopore WGS enabled final diagnostic classification in all samples with >15% tumor cell content, requiring [~]3 hours of hands-on library preparation, parallel sample processing, and sequencing times within 72 hours. Methylation-based classification was available within 1 hour and was concordant with the integrated final diagnosis in 89% of cases (80/90). All diagnostically relevant copy-number variations, single-nucleotide variants, and gene fusions were concordant with standard-of-care testing, and MGMT promoter methylation status matched in 94% of cases. In addition, nWGS identified prognostic and potentially actionable variants that were not reported or covered by SoC. ConclusionsNanopore WGS delivers comprehensive genetic and epigenetic results with a fast turn-around compared to standard methods. This enables efficient, accurate, and scalable molecular diagnostics of CNS tumors using a single platform. Its broad applicability supports its implementation in routine clinical practice and may be extended to other cancer types requiring complex genomic profiling.

Digital pathology, coupled with advanced image recognition algorithms, represents a transformative frontier in histopathological diagnosis. This sub-Saharan African laboratorys exploratory study investigates the application of a Convolutional Neural Network (CNN) model, specifically leveraging the VGG16 architecture with transfer learning, for automated analysis and classification of selected gastrointestinal (GIT) and liver tissue samples, incorporating both routine and specialized staining protocols. The study utilized a dataset comprising 114 samples (18 liver, 96 GIT images) derived from archival formalin-fixed paraffin-embedded tissue blocks at University College Hospital, Ibadan, Nigeria. Specialized staining techniques included Alcian Yellow for GIT mucin visualization and Massons Trichrome for liver fibrosis assessment, alongside conventional H&E staining. Model performance was evaluated using statistical methodologies including Wilson Score confidence intervals (CI), Bayesian probability assessment, and effect size analysis. Results reveal a striking dichotomy in model performance. The GIT tissue model achieved perfect classification accuracy (100% test accuracy) with exceptional statistical significance (Z=10.0, p<0.0001), Wilson CI [96.29%, 99.99%], Cohens h=1.571, and Bayesian probability >99.99%. Conversely, the liver tissue model demonstrated diagnostic failure (42.86% test accuracy), with Z=-1.428, p=0.9236, Wilson CI [33.59%, 52.65%], Cohens h=-0.144, and Bayesian probability of 7.64%. This performance divergence correlates with training data availability, as the liver dataset fell far below empirically established thresholds (>100-200 samples) for reliable classification. The liver models failure reveals limitations in transfer learning with insufficient data. These findings underscore critical implications for AI-enhanced digital pathology, demonstrating potential deployment of the GIT model as a promising one that supports tissue-specific model development.

BackgroundWilms tumour (WT) relapse occurs more frequently in patients with blastemal-type WTs. The presence of cancer stem cells (CSCs) is linked to tumour survival and relapse, and CSCs may be found in greater numbers in blastemal cell foci. CSC-associated phenotypes have been described in untreated WT, but their persistence, organisation and relevance after neoadjuvant chemotherapy is unknown. MethodsWe analysed 23 formalin-fixed paraffin-embedded blocks from 18 chemotherapy-treated patients where WTs were enriched for viable blastema, using human fetal kidney as developmental control. Immunohistochemistry and -fluorescence analysis determined progenitor (PAX2, SIX2, CITED1) and CSC-associated (NCAM, ALDH1, CD133) marker expression. We qualitatively and semi-quantitatively evaluated spatial expression patterns and co-localisation across tumour compartments. ResultsPAX2 and SIX2 were co-expressed in blastema in most cases (15/18), with PAX2 expression higher at the periphery of blastemal foci and SIX2 expression found uniformly in central aspects. CITED1 expression was also associated with SIX2 in blastema tissues (14/18). NCAM was blastema-enriched (15/18) with higher central intensity, frequently adjacent to PAX2-expressing peripheral zones. ALDH1 expression was present across blastema and epithelium while NCAM-, ALDH1-double-positive cells were rarely observed (4/18). CD133 expression was less commonly seen (2/18), localising near epithelial/nephrogenic structures. ConclusionsAfter neoadjuvant chemotherapy, WT blastema retained overlapping but non-identical progenitor/CSC-associated marker landscapes with reproducible peripheral-centre gradients. These spatial arrangements suggest a blastemal niche for CSCs that may sustain a therapy-resistant state. Our analysis provides the foundation for future functional validation and molecular profiling to define key lineage relationships and therapeutic vulnerabilities in post-chemotherapy WT. [250/250 words]

IntroductionTotal and social cognition deficits independently predict functioning in psychosis, but targeting these in clinical trials are unsuccessful in improving function. The admixture of schizophrenia and affective psychoses (aff-P) cases could be a roadblock if these differ in cellular pathology. MethodsWe examined cognitive functioning (MATRICS) and hippocampal cellular pathologies based on metabolite biomarker concentrations (1H-MRSI), using categorical and transdiagnostic classifications in 80 participants: 22 non-psychotic affective disorder (NP-aff), 25 healthy controls (HC), and 33 with psychosis, including 20 schizophrenia and 13 aff-P cases. ResultsNP-aff and HC had similar total cognition (46.64{+/-}12.01 vs 41.10{+/-}17.88), both superior psychosis (28.34{+/-}12.34; ps<0.01). Metabolite concentrations were similar across all groups but showed significant within-group associations to cognitive tests. For HC, total cognition, working memory and reasoning deficits were associated with reduced neuronal integrity (-.414, -.422, -.433, ps<.05), although no biomarker predicted total cognition in the clinical groups. For NP-aff, elevated myelin/membrane concentrations accompanied cognitive deficits; significantly so for visual learning deficits (.446, p<.05), which were also associated with decreased glia (-.503, p<.05). In all psychotic cases only reduced myelin/membrane concentrations predicted deficits (-.514, p<.05); but separating schizophrenia from aff-P, respectively showed reduced glutamate/excitation in schizophrenia (-.673, p<.05) but higher myelin/membrane and neuronal integrity concentrations (.575, .581, ps<.05) in aff-P. ConclusionsSchizophrenia and aff-P significantly differed for biomarkers of cellular pathology related to social cognition. Distinctly different underpinnings for cognition were also identified for other groups, aligning with DSM-5 and ICD disorder based categories. These findings include support for heterogeneous, but not transdiagnostic, conceptualizations of cognition and psychosis.

Background Coeliac disease affects approximately 1% of the global population and remains substantially underdiagnosed. Histopathological assessment of duodenal biopsies is the diagnostic gold standard but is subject to approximately 20% inter-observer disagreement. While machine learning approaches show promise, most prior work relies on black-box models with limited interpretability, restricting clinical adoption. Methods We present an interpretable pipeline that follows established histopathological criteria by extracting clinically meaningful morphological features from H&E-stained whole-slide images. Five sequential stages perform pre-processing, semantic segmentation of villi, crypts, intraepithelial lymphocytes (IELs) and enterocytes, crypt morphometry, villus length estimation via a novel polyline-based keypoint model, and coeliac disease classification using three quantitative features: IEL-to-enterocyte ratio, villus-to-crypt area ratio, and villus-length-to-crypt-depth ratio. Training and validation used data from four institutions; independent testing used 1,357 WSIs from two further institutions including one with a previously unseen scanner manufacturer, spanning five diagnostic categories: coeliac disease, normal mucosa, chronic inflammation, gastric metaplasia, and gastric heterotopia. Results Semantic segmentation achieved villus and crypt precision and recall of 87-90%. Villus length estimation correlated strongly with expert annotations (Pearson's r=0.85, mean relative error 13.5% post-calibration). All three morphological features significantly separated coeliac disease from all non-coeliac diagnostic groups across internal and external datasets (p<0.01 in all comparisons). On the test set the diagnostic classifier achieved accuracy 94.5%, PPV 92.9%, NPV 94.7%, and AUC 0.982. Conclusions This interpretable framework achieves strong multi-centre diagnostic performance while producing quantitative morphological outputs, villus length, crypt depth, and IEL-to-enterocyte ratios, that directly reflect established histopathological criteria, representing a meaningful step towards standardised AI-assisted coeliac disease diagnosis.

Background. Definitive diagnosis of Hirschsprung's disease (HD) requires pathological identification of enteric ganglion cells. This process is time-consuming and subject to inter-observer variability. Artificial intelligence (AI) tools have the potential to standardize and accelerate this workflow, but no study has determined which AI approach best serves intraoperative HD pathology diagnostics. Method. This study compared the U-Net and You Only Look Once version 26 (YOLO26) frameworks for ganglion cell detection using a single-centre retrospective dataset of 54 whole-slide images (WSIs) from rectal biopsies. WSIs were tiled into 397,731 image patches (128x128 pixels), further partitioned into training (70%), validation (15%), and testing (15%) sets. Models were evaluated on tile- and patient-level diagnostic metrics and processing latency. Results. The U-Net achieved a tile-level sensitivity of 82.9%, showing no statistically significant difference compared to YOLO26 (79.1%; p = 0.097). However, YOLO26 demonstrated a statistically significant advantage in tile-level specificity (96.1% vs. 93.9%; p < 0.001) and reduced mean inference latency (7.64 ms vs. 11.57 ms/tile). At the patient level, both models achieved 100% diagnostic sensitivity. Despite low patient-level specificity (0.0% U-Net; 11.8% YOLO26), the tissue-level diagnostic burden of false positives was 6.00% for U-Net and 3.50% for YOLO26. Conclusion. The U-Net is preferred when nominal gains in sensitivity are prioritized, while the YOLO26 is an alternative that optimizes efficiency and false positive suppression. Both models serve as robust screening filters to augment the pathologist's workflow and should be selected based on workflow requirements. Prospective validation on larger, multi-centre datasets is required before clinical implementation.

ObjectivesBenign Prostatic Hyperplasia (BPH) is the non-cancerous enlargement of the prostate accompanied by lower urinary tract symptoms, affecting 50% of men by the age of 501,2. Advanced highly symptomatic BPH exhibits large epithelial glandular nodules with microglandular/atypical adenomatous hyperplasia, but how these features form is unknown3. Our lab has reported that the common parasite Toxoplasma gondii can infect the prostate and induce glandular nodule formation in mice3. The objective of this study is to determine if T. gondii exposure in humans correlates to BPH and nodule formation and if it induces urinary dysfunction concurrent in the mouse model. MethodsWe assessed Toxoplasma exposure by serum ELISA in patients with BPH and non-BPH donor controls, and compared seropositivity rates between the groups. We further assessed the histopathology of these patients for the presence of inflammation and epithelial glandular nodule formation and compared Toxoplasma positive and negative samples. We determined voiding function in Toxoplasma-infected mice between 14 and 60 days of infection with void spot with Void Whizzard software. ResultsMen diagnosed with BPH are more likely to be seropositive for Toxoplasma than age-matched undiagnosed donor controls. In addition, BPH patients that are seropositive for Toxoplasma are more likely to exhibit glandular nodule formation with microglandular / adenomous hyperplasia than seronegative BPH patients. In animal studies, Toxoplasma infection results in abnormal void patterns concurrent with microglandular hyperplasia and nodule formation. ConclusionsThese results suggest that Toxoplasma may be contributing to BPH pathology and lower urinary tract dysfunction in both humans and mice, opening new insights into the development of this important disease. The results also serve to further characterize this model of prostatic hyperplasia and define it as a potential urinary dysfunction model.

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d695aborg.highwire.dtl.DTLVardef@fc250forg.highwire.dtl.DTLVardef@1e52e8eorg.highwire.dtl.DTLVardef@15378e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Introduction: Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality, and low-dose aspirin (LDA) prophylaxis is the cornerstone of evidence-based prevention. Despite guideline recommendations, LDA adherence remains poor, with 10-25% of moderate-risk patients taking aspirin. Objective personalized risk stratification using biomarkers has been shown to motivate behavior change in other disease contexts. Survey data suggest that patients are more motivated to take aspirin if informed by an objective predictive test. Here, we report real-world LDA adherence among patients who received a high-risk result from a cell-free RNA (cfRNA) PE risk prediction test. Methods: This retrospective, observational survey study included asymptomatic patients of advanced maternal age (AMA; [&ge;] 35 years at delivery) with singleton pregnancies without USPSTF-defined preexisting high-risk conditions for PE who received the cfRNA PE risk prediction test. Patients who opted in to receive text message surveys were asked about LDA use following receipt of test results. High adherence was defined as reporting LDA use on at least 6 of 7 days per week at least 85% of the time surveyed. The primary analysis included patients with a high-risk test result and at least one LDA frequency survey response following receipt of test result. The observed proportion of adherent patients was compared to a baseline estimate of 25% using an exact binomial test. Results: Of 166 patients who received a cfRNA PE risk prediction test result, 48 (28.9%) received a high-risk result. Of these, 29 (60%) opted in and responded to at least one survey, constituting the primary analysis population. Twenty-seven of the 29 (93.1%; 95% CI: 78.0-98.1%) were classified as highly adherent, significantly higher than the 25% baseline adherence estimate for moderate-risk patients (p < 0.0001). Conclusion: Among surveyed patients who received a high-risk cfRNA PE test result, the proportion classified as highly adherent to LDA (93%) substantially exceeded published estimates of adherence in a similar patient population and met the clinically meaningful threshold of [&ge;] 80% associated with reduced risk of preterm preeclampsia. These findings indicate that objective and personalized biomarker risk testing may be a powerful driver of behavior change that current guidelines have failed to produce.

Objectives: To evaluate if direct access to a Pregnancy Early Access Center (PEACE) improves the timeliness and efficiency of pregnancy loss care. Methods: We conducted a retrospective cohort study of patients diagnosed with EPL from January 2017 to December 2022 within a single healthcare system. We included EPL patients treated with procedural or medication management who had been assessed for a related early pregnancy complaint in the thirty days prior. The exposure was direct utilization of PEACE (yes/no) between first EPL symptom visit and EPL management. The primary outcome was "care latency" defined as days from initial presentation for concerning early pregnancy symptoms to initiation of active management. Secondary outcomes included "care continuity," the number of care teams encountered, "care efficiency," the number of patient encounters, and the type of EPL management received. Results: The evaluable cohort included 2151 individuals, with 36.5% patients of Black race and 30.3% publicly insured. A total of 885 (41.1%) received any EPL care at PEACE and 246 (11.4%) initiated their care at PEACE. Patients initiating care through PEACE experienced a 5-day reduction in care latency compared to patients who did not access PEACE. Adjusting for age, race, and insurance type, patients whose index EPL visit was with PEACE initiated their treatment twice as quickly as those who never saw PEACE (aHR 2.36 [95% CI, 2.05-2.71]). Care efficiency (median 2 [1-3] encounters) and care continuity (median 4.5 [4-7] care teams) were also improved by an index visit with PEACE when compared with controls (3 [2-4] and 6 [4-8] p<0.01), respectively). Conclusions: The Pregnancy Early Access Center (PEACE) model is associated with reduced care latency and improved efficiency and continuity when compared with routine care. PEACE reduces barriers to timely, patient-centered early pregnancy care.

Background: Hypertensive disorders of pregnancy (HDP) may first be diagnosed antepartum, during labor, or postpartum. We utilized untargeted large-scale proteomics to identify pathways associated with HDP based on timing of onset. Methods: We performed a nested case-control study comparing differential protein expression, from the SomaScan 7K platform, based on timing of onset of HDP versus controls (referent) using first-trimester samples from the NuMoM2b-Heart Health Study, a multi-site cohort that followed nulliparous individuals from the first trimester. Associations of proteins with timing of onset of HDP, adjusted for co-variates, were assessed using logistic regression q value-based false discovery rates and pathway enrichment and differential expression analysis were conducted. Results: Of 1628 individuals included, 678 had HDP, of which 67% manifested antepartum (AP), 29% intrapartum (IP), and 3% postpartum (PP). After adjusting for co-variates, compared to controls, 698 proteins, 39 proteins, and 144 proteins were differentially expressed in those with HDP according to AP, IP, PP onset, respectively. There was little overlap in individual protein expression based on timing of HDP. Pathway enrichment and graphical summary analyses suggested distinct processes. Specifically, there was downregulation of angiogenic proteins in AP HDP, downregulation of immune-related proteins in IP HDP, and upregulation of complement activation promoting fibrotic changes leading to cardiac dysfunction in PP HDP. Conclusion: There are differences in first-trimester protein expression based on whether HDP first manifests AP, IP or PP. This raises the possibility that there may be distinct mechanistic phenotypes that could uniquely inform diagnostic and therapeutic targets for HDP.

Background: Mucopolysaccharidosis type IIIA (MPS IIIA; Sanfilippo syndrome) is a fatal neurodegenerative lysosomal storage disorder caused by impaired degradation of heparan sulfate (HS). Despite rapid advances in gene and enzyme therapies, there remains a critical need for an analytically validated, quantitative biomarker that accurately reflects central nervous system (CNS) substrate burden. Such biomarker would be a valuable tool in assessing disease progression and monitoring therapeutic efficacy. Objective: This study describes the method development, fit for purpose validation, and preliminary clinical application of a quantitative liquid chromatography-mass spectrometry (LC-MS/MS) assay for the HS-derived disaccharide N-sulfoglucosamine-glucuronic acid (GlcNS-GlcUA) in human cerebrospinal fluid (CSF), a critical biomarker for diagnosis, disease monitoring, and regulatory evaluation of emerging MPS IIIA therapies. Methods: A structurally defined GlcNS-GlcUA reference standard and its [13C6]-labeled internal standard were used in a derivatization and detection workflow employing 1-phenyl-3-methyl-5-pyrazolone labeling, and LC-MS/MS. Results: The method exhibited acceptable linearity across 0.005-0.500 nmol/mL (r[&ge;]0.9976), with intra- and inter-assay imprecision [&le;]3.5%CV and accuracy within 95%-110% of nominal concentrations. No matrix or hemolysis interference or carryover was observed, and the analyte remained stable during freeze-thaw storage conditions. Application of the method to 12 CSF samples from patients with MPS IIIA demonstrated quantifiable GlcNS-GlcUA levels ranging from 0.0054 to 0.106 nmol/mL, confirming suitability for clinical and regulatory use. Comparison of the MPS IIIA sample results between the development laboratory and the contract research organization laboratory support robust inter-lab assay transfer. Conclusions: This validated LC-MS/MS method establishes a regulatory-grade quantitative assay for measurement of CSF HS in MPS IIIA. Its high analytical sensitivity and reproducibility enable reliable assessment of CNS substrate reduction and pharmacodynamic response, supporting biomarker-driven therapeutic development and accelerated approval pathways for neuronopathic mucopolysaccharidoses.

Background: Complicated acute appendicitis carries a higher risk of postoperative morbidity relative to uncomplicated cases. It remains unclear whether surgical timing (night vs. day; weekend vs. weekday) or surgeon seniority influence short-term outcomes in this high-risk population. Methods: This was a retrospective analysis of the RIFT Turkey dataset restricted to histologically confirmed cases of complicated appendicitis who had undergone laparoscopic appendectomy. Primary exposures were surgical timing (day [n=92] vs. night [n=123]; weekday [n=172] vs. weekend [n=43]) and surgeon seniority (trainee [n=89] vs. consultant [n=126]). The primary outcome was unplanned readmission and/or reintervention within 60 days. Secondary outcomes were conversion to open surgery and length of stay (LOS) >3 days. Propensity score matching (PSM) using RIPASA score (caliper 0.05, SMD <0.1) was performed as a pre-specified sensitivity analysis for each comparison. Results: Night-time surgery was associated with higher frequencies of unplanned readmission / reintervention (12.2% vs. 6.5%; OR 1.99 [95% CI 0.74-5.35], p=0.166) and surgical conversion (9.8% vs. 3.3%; OR 3.21 [0.88-11.72], p=0.064) compared with daytime surgery, neither reaching significance. Trainee surgeons had significantly higher readmission/reintervention rates than consultants (15.7% vs. 5.6%; OR 0.32 [0.12-0.82], p=0.013). PSM-adjusted results also showed similar relationships: night vs. day (readmission OR 2.45 [0.85-7.03], p=0.09; conversion OR 2.84 [0.73-11.1], p=0.13), weekend vs. weekday (readmission OR 1.53 [0.24-9.72], p=0.65), and trainee vs. consultant (readmission OR 0.25 [0.08-0.79], p=0.013). Conclusion: Surgical timing was not significantly associated with short-term outcomes in complicated appendicitis, though night-time surgery showed a consistent trend towards higher complication rates. Surgeon seniority was the only factor independently and significantly associated with unplanned readmission and reintervention in both primary and PSM analyses, indicating the need for senior supervision during out-of-hours procedures. Keywords: complicated appendicitis; surgical timing; night surgery; weekend effect; surgeon seniority; propensity score matching; RIFT Turkey

IntroductionThe NIMH Research Domain Criteria (RDoC) posits similar cellular pathologies for particular symptom domains across diagnostic categories. Conversely, knowledge that these differ could advance treatment discovery, especially for affective and non-affective psychoses, as studies usually intermix them. MethodsWe tested this by comparing metabolite biomarker concentrations for cellular pathologies from whole hippocampal proton magnetic spectroscopic imaging ( 1H MRSI) with symptoms from the original and five factor PANSS, and the Hamilton Depression and Young Mania Scales. Participants were 26 healthy controls; 22 non-psychotic affective cases (NP-aff); and 33 with psychosis (including 20 schizophrenia (Scz) and 13 affective psychosis (aff-P) cases). ResultsPANSS activation factor was related to reductions in all cellular component biomarkers in Scz, including glia, membrane turnover, neural integrity, glutaminergic neurotransmission, and energy metabolism (ps<.05), but only to energy metabolism in NP-aff (p=.03). Biomarkers for mood symptoms also varied across categories, suggesting gliosis for mania and depression in HC (ps[&le;].025), but increased membrane turnover for mania in aff-P (p=.015), and decreased neural integrity and energy metabolism for depression in Scz (ps<.05). In contrast, negative symptoms and autistic preoccupation were related to reduced glia in both NP-aff and aff-P (ps<.05). Autistic preoccupation in Scz was related to both reduced glia and membrane turnover (ps<.05). Only Scz showed a significant finding for positive symptoms, specifically reduced membrane turnover (p=.018). DiscussionThese results suggest both distinct and similar cellular pathologies for symptoms across diagnoses, including affective and non-affective psychoses. The differences support categorizing disorders and stratifying different psychoses in research rather than transdiagnostic approaches.