British Journal of Haematology

AimsTo evaluate the association between platelet indices and platelet count severity in patients with primary immune thrombocytopenia during routine post-treatment follow-up. MethodsThis retrospective observational study included patients with primary immune thrombocytopenia followed at a single tertiary care center between 2011 and 2025. Demographic and laboratory data were obtained from medical records. Platelet count severity was categorized as less than 30 x 10^9/L, 30 to 100 x 10^9/L, and greater than 100 x 10^9/L. Platelet indices, including mean platelet volume (MPV) and platelet distribution width (PDW), were analyzed using the most recent complete blood count obtained during routine follow-up after treatment initiation. Continuous variables were summarized as median and interquartile range. Comparisons across platelet count categories were performed using the Kruskal-Wallis test with post hoc Mann-Whitney U testing. Correlation analysis and simple linear regression were also conducted. ResultsA total of 243 patients were identified, of whom 232 met the inclusion criteria. Platelet distribution width differed significantly across platelet count severity categories (Kruskal-Wallis p < 0.001) and demonstrated a strong inverse association with platelet count. Mean platelet volume also showed a statistically significant difference across platelet count groups (Kruskal-Wallis p = 0.007), although the association was weaker and less consistent compared with PDW. Regression analysis confirmed a significant association between platelet count and PDW. ConclusionPlatelet distribution width is more closely associated with platelet count severity than mean platelet volume in patients with primary immune thrombocytopenia during routine post-treatment follow-up. PDW may represent a useful adjunctive laboratory parameter when interpreted alongside platelet count in routine clinical practice.

Cancer-induced bone disease is a huge burden on patient lives and costs the NHS millions of pounds every year. Breast, prostate and lung cancer can all lead to poor skeletal outcomes, but patients particularly at risk are those with a diagnosis of multiple myeloma (1). Despite response to tumour targeting treatments, patients experience debilitating bone pain and fractures, affecting quality of life (2, 3). Currently, myeloma patients who are eligible, are offered treatment with induction chemotherapy followed by autologous stem cell transplant (ASCT). Most eligible patients also receive bisphosphonates, to reduce skeletal morbidity, but this treatment is not optimal, or even conducive for bone recovery. Therefore, we wanted to assess whether current induction chemotherapy regimens have the capacity to reset the bone marrow microenvironment (BMME). This prospective observational cohort study will recruit newly diagnosed myeloma patients from Sheffield Teaching Hospitals NHS Foundation Trust. Ethical approval has been granted to undergo two recruitment periods; cohort 1 (20 participants, forming a pilot study) and cohort 2 (up to 100 participants with a streamlined follow-up design). Macro-architectural skeletal bone disease will be assessed by whole-body low-dose CT (WBLDCT) scans, in which osteolytic lesions will be monitored longitudinally. Micro-architecture will be assessed by micro-CT scanning bone marrow trephine samples, and analysing changes in trabecular bone. Bone integrity will be assessed using computational models of both whole body skeletal and micro trephine images. Fasting serum samples will be collected to assess changes in bone turnover markers. This will be supported by histomorphometry and immunohistochemistry analysis of trephine sections. All samples / imaging will be performed at baseline and follow-up. Monitoring of quality of life (validated questionnaires) and occurrence of skeletal related events (SREs) will also take place. The observational period will end one year post ASCT. Data collected from this study, will provide an invaluable opportunity to comprehensively assess myeloma-induced bone disease and broaden our understanding of the disease course. It may also prove a valuable resource to guide the design of interventional clinical studies exploring novel bone-targeted therapies, including bone anabolic therapeutics, moving forward.

Key pointsO_LIWe report findings from a phase 2 study of MY008211A among Chinese men and women aged [&ge;]18 years with paroxysmal nocturnal hemoglobinuria C_LIO_LIIncreases in hemoglobin of [&ge;]20 g/L were maintained for up to 44 weeks of treatment with MY008211A in all 34 patientsiv C_LI Explanation of noveltyParoxysmal nocturnal hemoglobinuria is characterized by red blood cell (RBC) destruction and a prothrombotic state.v Treatments exist such as complement 5 inhibitors but these carry the risk for iatrogenic extravascular hemolysis and anemia.vi As reported here, the novel, oral complement factor B inhibitor MY008211A yielded increases in hemoglobin and RBC levels, while adverse events over 44 weeks were largely mild to moderate in severity, and infections generally consisted of respiratory infections.vii Paroxysmal nocturnal hemoglobinuria (PNH) is a life-threatening disease characterized by red blood cell (RBC) destruction, blood clots, and impaired bone marrow function.viii We evaluated the efficacy and safety of 3 dosages of MY008211A, a novel complement factor B inhibitor,ix for treating PNH.x This was a multicenter, open-label, phase 2, dose-finding study of MY008211A among Chinese men and women with complement inhibitor-naive PNH and signs of active hemolysis.xi Patients with hemoglobin <100 g/L were assigned to oral MY008211A 400 mg twice daily (BID), 600 mg BID, or 800 mg once daily (QD) for 12 weeks and could then continue treatment with 400 mg BID during a 32-week extension.xii The primary endpoint was the proportion of patients achieving an increase in hemoglobin concentration of [&ge;]20 g/L vs baseline on day (D)84, without RBC transfusions after 4 weeks of dosing.xiii Safety assessments included adverse events (AEs).xiv Fifteen, 9, and 10 patients were assigned to MY008211A 400 mg BID, 600 mg BID, and 800 mg QD, respectively.xv All patients completed the study and its 32-week extension.xvi On D84, all 34 patients achieved increases in hemoglobin concentration of [&ge;]20 g/L from baseline;xvii all patients maintained this increase at D308.xviii Through D308, grade [&ge;]3 AEs occurred in 5 (33%), 5 (56%), and 4 (40%) patients in the 400-, 600-, and 800-mg groups, respectively.xix There were no deaths.xx In this multicenter, open-label study of 3 dosages of MY008211A for PNH, all patients achieved and maintained increases in hemoglobin of [&ge;]20 g/L from baseline without RBC transfusions.

ObjectivesThe therapeutic efficacy of rituximab has reduced the discriminatory power of the International Prognostic Index (IPI) in diffuse large B-cell lymphoma (DLBCL), particularly within intermediate-risk categories. To address this "risk dilution," we aimed to develop and internally validate the AB-IPI (Albumin-BCL2 Refined Prognostic Index) using a hypothesis-driven approach that integrates tumor burden, host fitness, and tumor biology. MethodsThis multi-center retrospective study analyzed 289 patients with de novo DLBCL treated uniformly with R-CHOP immunochemotherapy. We combined the standard IPI with serum albumin < 3.6 g/dL (representing host fitness/rituximab pharmacokinetics) and BCL2 protein expression > 50% (representing tumor biology). The model was validated internally using bootstrapping with 1,000 resamples in accordance with TRIPOD Type 1b guidelines. This study adhered to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement for model development and internal validation (Type 1b). ResultsDuring the observation period, 115 death events were recorded. Multivariate Cox regression identified albumin < 3.6 g/dL (Hazard Ratio 2.62), IPI score > 2 (HR 2.13), and BCL2 > 50% (HR 1.72) as independent prognostic factors. The model maintained a robust Events Per Variable (EPV) ratio of 38.3. The AB-IPI stratified patients into four distinct risk groups with 5-year overall survival rates of 88.0% (Low), 76.1% (Intermediate-1), 45.0% (Intermediate-2), and 29.0% (High). The calibration plot demonstrated excellent agreement between predicted and observed probabilities, with a calibration slope of 0.98, indicating minimal optimism and robust risk estimation. Decision Curve Analysis (DCA) demonstrated that the AB-IPI provided a superior Net Benefit across a wide range of clinically relevant threshold probabilities. ConclusionsThe AB-IPI demonstrates superior clinical utility and calibration compared to the standard IPI. By identifying patients with compounded biological risks who are unlikely to be cured by R-CHOP alone, this score offers a practical framework for optimizing therapeutic strategies, such as the allocation of polatuzumab vedotin.

Fanconi anemia (FA) is an inherited disorder classically characterized by childhood-onset bone marrow dysfunction and lifelong cancer predisposition. FA is caused by pathogenic variants in any one of 23 genes identified so far. Of these, FANCA is the most frequently mutated and accounts for disease in two-thirds of all patients with FA. The spectrum of FANCA pathogenic variants (mutations) is broad, and genotype-phenotype correlation is often unclear. Here we describe the natural history of cytopenias associated with FANCA pathogenic variants in 139 individuals diagnosed in 1995 or later. We followed blood cell counts over time and correlated these with the classification of patient mutation subtypes. Most participants experienced age-related declines in hematologic parameters beginning in early childhood. Platelets underwent the earliest decline, reaching platelet count below 50K/l at a median age of 8.2 years. The erythrocyte lineage was the most stable with hemoglobin below 8 g/dl identified at a median age of 10.7 years. Androgen therapy delayed the blood count decline. The presence of at least one predicted hypomorphic pathogenic variant in the FANCA gene significantly slowed the progression of the hematologic abnormalities. This study sheds light on the importance of mutation type in predicting the severity of hematological manifestations in FA. Furthermore, it serves as a historical comparative cohort for emerging therapies aimed at altering hematological disease progression in FANCA-deficient FA patients. Key PointsO_LIThrombocytopenia and neutropenia are the earliest and most reliable indicators of hematologic decline in FANCA-deficient patients C_LIO_LIPresence of two FANCA variants with predicted complete loss of function leads to earlier onset and faster progression of disease C_LI

IntroductionThere is no comparison of iron phenotypes and menses, pregnancies, and live births reports of women with HFE-related hemochromatosis (HFE p.C282Y (rs1800562) homozygosity) and HFE wt/wt (absence of p.C282Y and HFE p.H63D (rs1799945)). Subjects and MethodsWe compared phenotypes and reports of non-Hispanic white women women aged [&ge;]25 y in post-population screening evaluations using univariable methods. ResultsThere were 153 p.C282Y/p.C282Y and 273 wt/wt. Median ages were 50 y (25, 86) and 55 y (25, 92), respectively (p=0.0019). Median transferrin saturation (TS), median serum ferritin (SF), and provisional iron overload prevalence were higher in p.C282Y/p.C282Y (p [&le;]0.0001, each comparison). Prevalences of documented iron overload (3.3% p.C282Y/p.C282Y vs. 0.7% wt/wt), iron overload-related disease (2.0% vs. 0.4%, respectively), and iron deficiency (3.9% vs. 2.6%, respectively) were not significantly different. Median ages at menarche (13 y p.C282Y/p.C282Y vs. 13 y wt/wt) and menopause (50 y vs. 49 y, respectively) were not significantly different. Reports of "in-between bleeding?" (24.2% p.C282Y/p.C282Y vs. 25.2% wt/wt, respectively), "early stopping of periods?" (11.8% vs. 13.9%, respectively), and "had a hysterectomy?" (30.1% vs. 35.9%, respectively) were not significantly different. Respective percentage pairs of women with p.C282Y/p.C282Y and wt/wt who reported 0, 1, 2, 3, or [&ge;]4 pregnancies (or live births) did not differ significantly. Live births/pregnancies were 287/363 (79.1%, p.C282Y/p.C282Y) and 534/673 (79.3%, wt/wt) (p=0.7549). ConclusionsMedian TS, median SF, and provisional iron overload prevalence are greater in women with HFE p.C282Y/p.C282Y than those with wt/wt, although reports of menses, pregnancies, and live births are similar.

IntroductionAnemia is a common and debilitating complication in cancer patients, affecting prognosis, quality of life, and treatment response. The burden of anemia may be higher in resource-limited settings due to nutritional deficiencies and limited healthcare access. However, data on anemia among newly diagnosed cancer patients in Ethiopia remain scarce. This study was aimed to determine the magnitude and predictors of anemia in newly diagnosed adult solid cancer patients in Hawassa, Ethiopia. MethodsA cross-sectional study was conducted among randomly selected 405 newly diagnosed adult solid cancer patients at selected public health facilities in Hawassa City, Ethiopia, from June 2021 to October 2021. Data were collected using structured face-to-face interviews and from medical records. Data were entered into EpiData version 3.1 and exported to SPSS version 26 for analysis. Descriptive statistics were computed for all variables. Binary logistic regression was performed to determine the independent effects of potential explanatory variables on the presence of anemia. Adjusted Odds ratios with 95% confidence intervals were calculated. Statistical significance was set at p-value < 0.05. ResultThe prevalence of anemia was 26.4% (95% CI: 22.1-30.7%), with normocytic anemia (56.1%) being the most common morphological type. Multivariable analysis identified a history of bleeding (AOR = 3.46, 95% CI: 1.94-6.16), advanced cancer stage (AOR = 2.01, 95% CI: 1.20-3.34), and underweight BMI (AOR = 2.14, 95% CI: 1.28-3.55) were significantly associated with anemia. Conversely, higher educational attainment (diploma and above) was protective (AOR = 0.35, 95% CI: 0.13-0.93). ConclusionAnemia affects over one-quarter of newly diagnosed solid cancer patients in Hawassa, with advanced-stage disease, bleeding history, and decreasing body mass index as significant risk factors. These findings highlight the need for routine anemia screening at diagnosis, nutritional interventions, and early bleeding management in oncology settings.

Sickle cell disease (SCD) is associated with chronic systemic morbidity that extends beyond acute crises. However, data describing the clinical and laboratory adolescents and young adults with SCD at steady state in sub-Saharan Africa are limited. We described clinical and laboratory characteristics of adolescents and young adults with SCD at steady state in Uganda. We conducted a hospital-based cross-sectional study of 60 adolescents and young adults with SCD in steady state at Mulago National Referral Hospital. Descriptive statistics were used to summarize participant characteristics and medication use. The mean age was 16.5 {+/-} 3.3 years, and 34 (56.7%) participants were female. Mean hemoglobin was 9.1 {+/-} 2.2 g/dl. Mean systolic and diastolic blood pressures were 107.9 {+/-} 15.5 mmHg and 60.3 {+/-} 12.6 mmHg, respectively; mean heart rate was 89.5 {+/-} 15.5 beats/min. Fifty-two (86.7%) participants reported using hydroxyurea. These observations show that adolescents and young adults with SCD at steady state exhibit hematologic abnormalities and distinctive hemodynamic profiles that underscore substantial chronic subclinical abnormalities that extend beyond acute complications.

Early achievement of deep remission improves patients outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indicators before therapy initiation. This study aimed to develop a tool to predict CML treatment responses to guide optimal therapy selection. Using hierarchical clustering of complete blood count (CBC) data at diagnosis, patients were stratified into two clusters. Patients in Cluster 1 had higher BCR::ABL1IS mRNA levels at 3 and 6 months post-treatment and lower rates of major molecular response compared to cluster 2. Cluster 1 also showed increased granulocyte and immature white blood cell counts and decreased erythroid parameters. Flow cytometric analysis of bone marrow mononuclear cells revealed that cluster 1 had a significant increase in hematopoietic stem cell fractions and a higher ratio of granulocyte-macrophage progenitors to megakaryocyte-erythroid progenitors compared to cluster 2. These findings suggest that differences in bone marrow progenitor cell differentiation affect peripheral blood profiles. Artificial intelligence-driven ghost cytometry (GC) was evaluated for its ability to comprehensively capture these changes and successfully distinguished patients with poorer treatment responses, with GC scores at diagnosis strongly correlating with BCR::ABL1IS mRNA levels at 3 and 6 months post-treatment initiation. The study indicates that multivariate analysis of CBC or GC analysis may enable simple, early prediction of CML treatment efficacy, potentially contributing to effective and individualized CML therapy.

Eculizumab, a humanized monoclonal antibody targeting the complement lytic pathway protein C5, has demonstrated high efficacy in the treatment of paroxysmal nocturnal hemoglobinuria, atypical hemolytic uremic syndrome, generalized myasthenia gravis, and neuromyelitis optica spectrum disorder. However, recent reports have highlighted patients who exhibit a lack of treatment response, necessitating an increase in the recommended dose or a reduction in the dosing interval. In this study, we employed machine-learning predictive models to identify the optimal blood concentration of eculizumab to inhibit the complement lytic pathway. Additionally, we examined the impact of data augmentation through the generation of artificial data on the predictive performance of these models. In conclusion, our machine learning model predicts that the target blood concentration of eculizumab should be increased to a minimum of 152-162 g mL-1 (up from 50-100 g mL-1) to achieve a more complete inhibition of the complement systems lytic pathway.

Relapsed and/or refractory disease remains the leading cause of death in AML, highlighting the need for broadly applicable, high-sensitivity approaches to MRD detection. We developed AML-CAPP-Seq (Cancer Personalized Profiling by Deep Sequencing), a personalized hybrid-capture assay that tracks both canonical AML drivers and patient-specific variants identified by whole-exome sequencing. In 56 patients with longitudinal plasma and matched peripheral blood and bone marrow samples, AML-CAPP-Seq enabled universal MRD assessment and resolution of clonal dynamics using a median of 30.5 variants per patient. Plasma ctDNA outperformed cellular compartments for MRD detection and more strongly predicted relapse-free (HR 17.8, p<0.0001) and overall survival (HR 17.0, p<0.0001) than standard-of-care MRD methods. Among 29 allogeneic transplant recipients, peri-transplant ctDNA-MRD dynamics markedly improved relapse risk stratification (HR 36.0, p=0.0009). Together, these results establish personalized ctDNA profiling as a minimally invasive, highly sensitive, and generalizable platform for enhanced clinical MRD detection and clonal surveillance in AML. Significance StatementWe present a personalized blood test for acute myeloid leukemia that tracks patient-specific circulating tumor DNA, enabling sensitive, universal, noninvasive detection of residual disease. It outperforms standard-of-care marrow and cell-based methods for predicting relapse and survival, including after transplant, reveals clonal dynamics, and supports individualized disease monitoring and risk-adapted treatment.

Allogeneic hematopoietic cell transplantation (allo-HCT) hinges on a delicate trade-off between graft-versus-tumor control and graft-versus-host disease (GvHD), mediated by donor T-cell recognition of antigens presented by recipient human leukocyte antigen (HLA) molecules. We hypothesized that, beyond allele-level matching, sequence divergence at peptide-binding grooves across donor and recipient HLA loci shapes these responses. To this end, we evaluated the effect of HLA evolutionary divergence (HED), a metric quantifying amino acid variability at HLA peptide-binding sites, on selected hematological malignancies in 4,695 patients undergoing allo-HCT from a 9/10 mismatched unrelated donor (MMUD), reported to the EBMT database. We examined (i) locus-specific recipient HED (HED-R) and (ii) "HED-mismatch" (HED-MM), capturing immunopeptidome divergence at the mismatched locus. While dichotomous mismatch status explained differences in survival and acute GvHD risk (with overall greater detriment for class I loci), HED metrics uncovered substantial within-mismatch heterogeneity. In DRB1 mismatched subgroup, HED-MM at this locus, independently predicted inferior relapse-free survival (RFS) with an attenuating time-dependent association, further modulated by cross-locus HED-R. In this subgroup, higher HED-R at HLA-A and HLA-C associated with increased risks of acute GvHD and non-relapse mortality, respectively. Among HLA-B-mismatched pairs, higher DRB1 HED-R associated with worse overall survival (OS) and RFS and higher relapse risk. In the HLA-A-mismatched subgroup, higher HED-R at HLA-A increased chronic GvHD risk. Collectively, HED-derived metrics complement conventional mismatch classification by capturing qualitative differences in donor-recipient immunopeptidome interactions and reveal a complex, non-linear interplay among alleles across mismatch subgroups that modulates the clinical impact of mismatching. KeypointsO_LIIn mismatched unrelated HCT, baseline risk varies across mismatch constellations, with class I mismatches more detrimental than class II. C_LIO_LIHED complements conventional HLA mismatch classification by capturing qualitative donor-recipient immunopeptidome interactions. C_LI

BackgroundSickle Cell Anaemia (SCA), a genetic blood disorder caused by a single mutation in the beta globin gene, displays a highly variable clinical course. Hydroxyurea (HU), an effective treatment, has an unclear mechanism of action. Plasma proteins can act as biomarkers for understanding disease states and response to HU treatment in SCA patients. MethodsPlasma proteome profiling of 31 healthy individuals and 76 SCA patients, including those with and without HU treatment, was performed using a high-performance liquid chromatography system and Orbitrap mass spectrometer. Statistical analysis was performed to identify differentially abundant proteins (DAPs) between SCA patients and healthy controls. Subgroup analyses were performed to look at the impact of HU treatment on plasma proteome. ResultsOur analysis yielded 43 DAPs in the plasma of SCA patients. Global correlation and protein-protein network analysis revealed that these proteins are part of a robust interaction network. Proteins showing higher abundance (LBP, ORM1 and TFRC) were primarily associated with immune response whereas those with reduced abundance (FBLN1 and F13B) were linked to blood coagulation and proteolysis. Differential abundance of several proteins such as CD14, FCN3, LFALS3BP, LAP and TGFBI was observed in either male or female patients indicating influence of gender. Importantly, HU treatment was associated with elevated levels of haptoglobin (HP) and hemopexin (HPX), key proteins involved in free hemoglobin scavenging. Notably, DAPs such as F10, LPA, and FCN3 overlapped with proteins previously reported to be differentially abundant in beta-thalassemia patients. Moreover, multiple proteins, including APOL1, AZGP1, FBLN1, GPLD1, HPX, LGALS3BP, and TFRC correlated with clinical parameters, such as blood transfusion frequency and, vaso-occlusive crisis, and WBC and platelet counts. ConclusionsThis study identifies novel differentially abundant plasma proteins in SCA, expanding the current repertoire of disease-associated biomarkers and proteins modulated by hydroxyurea therapy. The observed overlap with beta-thalassemia associated signatures reinforces shared pathophysiological mechanisms between these hemoglobinopathies. Several of these proteins show significant correlations with key clinical parameters and disease complications, offering insights into disease mechanisms and potential utility in disease management. Collectively, these findings provide a strong foundation for translational validation in larger, independent cohorts.

Iron deficiency (ID) is the most common nutritional deficiency worldwide, often caused by insufficient dietary intakes. Oral supplementation is one of the means to improve iron status. This study evaluated the efficacy and safety of two low-dose iron supplements - >Your< Iron Forte Capsules (YIFC) and Ferrous Sulfate Capsules (FSC) - in individuals with dietary ID. One hundred and one participants (mean age 30.6 years; 98% women) with low iron stores (mean serum ferritin 16.1 {micro}g/L) were randomized to receive either YIFC or FSC once daily for 12 weeks. Changes in blood indices and iron-related parameters were assessed at four and 12 weeks of intervention relative to baseline. The primary outcome was the change in hemoglobin (Hb) after 12 weeks. Eighty-seven participants completed the study. Both supplements significantly increased Hb at 12 weeks (YIFC: mean 6.52 g/L, p<0.001; FSC: mean 5.71 g/L, p<0.001). Product-related adverse events (AEs) were few (17% of all AEs) and of mild to moderate intensity only. One participant receiving FSC withdrew due to a probable product-related AE. The frequencies of product-related AEs were similar between study arms, however, statistically significantly more AEs judged to be definitely related to the product occurred in in the FSC arm. While product-related AEs were confined to the gastrointestinal tract in the YIFC arm, they affected multiple organ systems in the FSC arm. Supplementation with either YIFC or FSC proved as an effective, well-tolerated, and safe strategy for improving iron status in non-anemic dietary iron deficiency. In terms of the AE profile, supplementation with YIFC may offer advantages over supplementation with FSC.

BackgroundErythrocyte indices are essential for the diagnosis and monitoring of hematologic diseases, but their determination depends on automated hematology analyzers, which limits access in regions with limited laboratory infrastructure. Although artificial intelligence approaches have been proposed for hematologic analysis, they usually rely on slide scanners or digitization systems. To date, no validated approaches have been identified in the literature that estimate these indices directly from images obtained through the eyepiece of conventional optical microscopes. ObjectiveTo evaluate the feasibility of automated prediction of erythrocyte indices from blood smear images obtained directly through the eyepiece of conventional microscopes using convolutional neural networks. MethodsTwo hundred blood samples stained using the May-Grunwald-Giemsa method were analyzed and photographed using a standard optical microscope. Four architectures, DenseNet-121, EfficientNet-B0, ResNet-18, and ResNet-34, were evaluated at different resolutions using 10-fold K-Fold cross-validation. ResultsFor RBC, HGB, and HCT, ResNet-34 at a resolution of 1024x1024 pixels achieved superior performance, with R2 between 0.90 and 0.92, Pearson correlation r > 0.95, and mean absolute errors of 0.184 x106/{micro}L, 0.524 g/dL and 1.292%, respectively. For RDW-CV, DenseNet-121 achieved R2 = 0.49 and r = 0.71, reflecting the greater complexity of this parameter. Bland-Altman analysis confirmed adequate agreement, with biases close to zero and more than 94% of observations within the limits of agreement. ConclusionArtificial intelligence demonstrated excellent predictive performance in estimating the erythrocyte indices RBC, HGB, and HCT, with R2 > 0.90, from images obtained using a conventional microscope and accessible hardware. This approach has significant potential to democratize access to hematologic analysis in resource-limited settings, although multicenter validation and regulatory evaluation are required before clinical implementation.

ObjectivePost-thrombotic syndrome (PTS), a common complication of deep vein thrombosis, lacks objective diagnostic biomarkers and its molecular mechanisms remain poorly understood. This study aimed to identify plasma biomarkers and clarify pathways using integrated multi-omics and machine learning. MethodsProteomic and metabolomic profiling of 75 PTS patients and 75 controls was performed. Differential expression analysis, pathway enrichment, and protein-metabolite network analysis were conducted. A multi-algorithm machine learning with 8 feature selection methods prioritized biomarkers. Validations and 14 models were assessed. Results1,104 proteins and 1,891 metabolites were differentially expressed. Citrate cycle and unsaturated fatty acid biosynthesis were enriched. Three proteins, namely DIP2B, KNG1, and SUCLG2, were consistently selected as core biomarkers. All of these proteins were significantly downregulated in PTS and externally validated. A random forest model utilizing these proteins achieved an accuracy of 97.7% in independent testing, with SUCLG2 being the most influential predictor. ConclusionThis study identifies a novel three - protein biomarker panel for the diagnosis of PTS and reveals an immunometabolic axis in the pathogenesis of PTS, which links inflammatory regulation with mitochondrial energy metabolism. These findings provide valuable insights into the development of diagnostic tools and targeted therapeutic approaches.

ObjectiveAutoimmune diseases (ADs) markedly elevate venous thromboembolism (VTE) risk, yet the shared genetic architecture and tissue-specific regulatory mechanisms of this "Autoimmune-Thrombotic Axis" remain poorly defined. We aimed to characterize the genomic landscape of immunothrombosis to identify causal links and therapeutic targets. Approach and ResultsWe integrated large-scale GWAS data for VTE and 16 ADs using a multi-omics framework, including pleiotropy scanning, local genetic correlation, and summary-based Mendelian randomization (SMR). We identified 21 Immunothrombotic Shared Loci (ISLs) and 274 pleiotropic genes enriched in complement and coagulation cascades. Mendelian randomization (MR) analysis revealed a robust causal effect of genetically predicted systemic lupus erythematosus (SLE) on VTE risk (OR = 1.018, 95% CI: 1.008-1.029, P = 0.0003). Mechanistically, IL6R and PLCL1 emerged as central mediators with distinct tissue-specific regulatory partitioning. Colocalization confirmed that shared genetic susceptibility is primarily driven by expression in arterial tissues (aorta and coronary) rather than exclusively in immune cells. Furthermore, the lead SNP rs4129267 was identified as a potential predictor for VTE in rheumatoid arthritis patients, and drug prioritization nominated TNF inhibitors as promising candidates for mitigating thrombotic burden. ConclusionThis study establishes the first genomic atlas of the autoimmune-thrombotic axis, demonstrating that vasculature-specific gene regulation drives immunothrombosis. These findings provide a biological basis for VTE risk stratification and suggest that genotype-guided therapy may optimize vascular outcomes in AD patients.

A role for substance P in promoting neurogenic inflammation and pain has been described in sickle cell disease (SCD). However its origin and contribution to SCD pathophysiology remain unclear. We measured substance P level in plasma from 225 patients with SCD and observed the highest concentrations during acute chest syndrome (ACS). Therefore, we tested the hypothesis that substance P may induce ACS. In transgenic sickle mice, unlike control mice, intravenous injection of substance P caused lethal crises with dose-dependent acute lung injuries. Activation of Fc{varepsilon}R1 with MAR-1 had similar effects, suggesting a role for mast cell or basophil activation and degranulation. Pretreatment of sickle mice with cromolyn, a stabilizer of mast cells and basophils, prevented lethal crisis and lung injuries induced by substance P injection. In SCD patients, blood cellular histamine levels and increased histidine decarboxylase activity were consistent with an involvement of circulating basophils. Flow cytometry analysis revealed higher basophil counts with increased activation and degranulation markers in patients compared with healthy controls. During vaso-occlusive crisis, absolute basophil counts tended to decrease, suggesting their recruitment outside the vascular compartment. The same results were observed in sickle mice after hypoxia-reoxygenation, intravenous hemin injection or substance P injection. Immunohistochemistry revealed the presence of mast cells and basophils in the lungs of sickle mice, but not in control mice, with further basophil recruitment and degranulation after intravenous substance P injection. In SCD patients, we observed extremely high levels of substance P in the sputum collected during ACS, consistently with mast cell and basophil degranulation in the lungs. In vitro, substance P was shown to be a potent chemoattractant for basophils via NK1R. Gene expression analysis on sorted circulating basophils from SCD patients revealed an increased expression of several chemokine receptors, including CCR3 and FPR1, which was confirmed by spectral flow cytometry and could contribute to the recruitment of basophils in the lungs. The two substance P receptors, NK1R and MRGPRX2, were also overexpressed, promoting the vicious cycle of substance P release and pain in SCD patients. Our results reveal a novel mechanism that contributes to the understanding of ACS pathogenesis and highlights the potential role of mast cells and basophils in SCD pathophysiology.

Anemia, particularly iron-deficiency anemia, is a critical global health concern, with a high prevalence among children under six years of age. Early and non-invasive detection can significantly improve health outcomes. This study proposes a computer vision and machine learning framework for anemia screening and hemoglobin (Hb) level prediction using palmar images from pediatric subjects. The region of interest (palm) was segmented using a U-Net model, achieving a Dice coefficient of 0.96. Images were processed across RGB, CIELab, and HSV color spaces to extract key color features, including red fraction, erythema index, and normalized a-component. For anemia classification, multiple machine learning models were evaluated, with Logistic Regression, Gradient Boosting, and a custom Convolutional Neural Network (CNN) achieving the highest test accuracies of approximately 94.5% and 95.53%, respectively. For hemoglobin regression, a Random Forest model in the CIELab color space achieved a coefficient of determination (R2) of 0.95. The Pearson correlation coefficient in the Lab color space was 0.98 for the Random Forest algorithm and 0.94 for the Linear Regression algorithm. The analysis, supported by SHAP values, identified red-related color features as the most significant predictors. The model demonstrated robust performance across different skin tones, with particularly high accuracy (R2 = 0.9926) in darker-skinned individuals, who constituted the majority of the studied Iranian population. The results confirm that pallor analysis of palmar images using artificial intelligence techniques offers a reliable, non-invasive, and effective tool for pediatric anemia screening and hemoglobin estimation, with strong potential for point-of-care applications.

BackgroundPrimary aldosteronism(PA) screening is recommended but disease prevalence exceeds the availability of adrenal vein sampling(AVS). MethodsAn AVS optimal allocation tool for health systems was developed using administrative data and AVS registries from Calgary and Taiwan. Four easily-definable phenotypes of PA based on an elevated aldosterone-renin-ratio (ARR), and the presence/absence of hypokalemia or adrenal mass were identified, representing progressively severe PA and stepwise increasing rates of AVS-defined lateralization. Using supply-and-demand principles, a customizable, web-based tool was developed that considers PA referral volume, PA phenotype prevalence, maximum AVS available/year, AVS success rate, and desired rate of finding unilateral disease. ResultsThe most prevalent phenotype of PA was characterized by an elevated ARR and hypokalemia but no adrenal mass (41.9 [39.9-43.9]%); hypokalemia and adrenal mass accounted for (15.6[14.4-16.9]%) of cases. There was a progressive increase in AVS lateralization rate with increasing severity of phenotype observed in both the Calgary and Taiwan data, ranging from (20-39%) in those with PA without hypokalemia or adrenal mass to (70-90%) in those with hypokalemia and adrenal mass. After accounting for institution-specific lateralization rates and allowing for system-level differences in high- and low-volume PA referrals, and high- and low AVS availability, the customizable AVS allocation tool was able to generate individualized strategies ranging from restrictive (exclusive reservation of AVS for cases with hypokalemia and adrenal mass) to more inclusive strategies (assigning a proportion of AVS allocation to less severe PA cases). ConclusionsAn AVS allocation tool that uses common, simple, and globally available PA case data may assist in health system AVS program case allocation for maximum equity and wait-list control. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/26345289v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1c9be00org.highwire.dtl.DTLVardef@1d91e00org.highwire.dtl.DTLVardef@140aa8aorg.highwire.dtl.DTLVardef@7c76c6_HPS_FORMAT_FIGEXP M_FIG C_FIG