We developed an artificial intelligence (AI) model that evaluates the feasibility of AI-assisted multiparameter flow cytometry (MFC) diagnosis of acute leukemia. Two hundred acute leukemia patients and 94 patients with cytopenia(s) or hematocytosis were selected to study the AI application in MFC diagnosis of acute leukemia. The kappa test analyzed the consistency of the diagnostic results and the immunophenotype of acute leukemia. Bland–Altman and Pearson analyses evaluated the consistency and correlation of the abnormal cell proportion between the AI and manual methods. The AI analysis time for each case (83.72 ± 23.90 s, mean ± SD) was significantly shorter than the average time for manual analysis (15.64 ± 7.16 min, mean ± SD). The total consistency of diagnostic results was 0.976 (kappa (κ) = 0.963). The Bland–Altman evaluation of the abnormal cell proportion between the AI analysis and manual analysis showed that the bias ± SD was 0.752 ± 6.646, and the 95% limit of agreement was from −12.775 to 13.779 (p = 0.1225). The total consistency of the AI immunophenotypic diagnosis and the manual results was 0.889 (kappa, 0.775). The consistency and speedup of the AI-assisted workflow indicate its promising clinical application.

Previous studies have suggested that the trophoblast cells inhibit the proliferation of peripheral natural killer (pNK) cells and the level of pNK cells decrease in middle and late pregnancy stage among healthy women. The change of pNK cells level during early pregnancy and the relationship between the change of pNK level and pregnancy outcomes in women with unexplained recurrent pregnancy loss (URPL) has not been sufficiently explored. This study aims to characterize the level of pre-pregnancy pNK to early pregnancy among women with URPL and whether the change in the level of pNK cells in early pregnancy from pre-pregnancy can predict pregnancy outcomes. In this prospective cohort study, 1758 women with recurrent pregnancy loss were recruited between January 2017 and December 2021, of which 252 URPL women had pre-pregnancy and early pregnancy (4-6 weeks gestation) pNK measurements. These 252 women were divided into two groups: those with a lower gestational pNK levels (Group 1) compared to pre pregnancy, and those without (Group 2). Their respective outcomes on live birth and pregnancy loss were comparatively analyzed using Chi-square and Student's t test. Candidate influence factors for live birth were selected using the Akaike information criterion (AIC). Then the participates were randomly divided into training and testing groups. Multivariable logistic regression model was performed, and nomogram was calculated to assess the possibility of live birth. Predictive accuracy was discriminated by area under the receiver operating characteristic curve (ROC), validated by plotting the predicted probabilities and the observed probabilities. Hosmer-Lemeshow test was used to assess the goodsess of fit. When early gestational pNK cells levels were compared with pre pregnancy pNK cells levels, 61.5% (154) women had a comparatively lower early gestational pNK cells levels versus 38.9% (98) women with increase or no change of their pNK cells levels. The live birth rate in Group 1 was 89.0% (137/154), which was significantly higher than 49.0% (48/98) of Group 2 (p<0.001). Decrease of pNK cells level (odds ratio [OR]=1.36, 95% CI 1.22-1.55, p<0.001) and anti-Muellerian hormone (AMH) (OR=1.41, 95% CI 1.14-1.81, p=0.003) were important predicting factors for higher live birth. Female BMI (OR=0.97, 95% CI 0.82-1.15, p=0.763) and parity (OR=1.61, 95% CI 0.71-4.12, p=0.287) were also predicting factors. Furthermore, the area under the ROC curve of the model to diagnose of live birth was 0.853 with a sensitivity of 81.6% and specificity of 78.0% using the training dataset. And the Hosmer-Lemeshow test showed that the model was a good fit (p = 6.068). We report a comparative decrease in pNK cells levels in over 60% URPL women at 4-6 weeks of gestation, when compared to their pre-pregnancy pNK cells level. Compared to pre pregnancy pNK cells levels, a decrease pNK cells level during early pregnancy might be a useful predictor for LBR in women with URPL.

Background: Multiple myeloma (MM) is an incurable hematologic malignancy, and the majority of patients eventually relapse due to persistent myeloma cells. While minimal residual disease (MRD) reflects tumor burden, the host immune system also plays a crucial role in disease control. Our study aimed to evaluate MRD, complete blood count (CBC), and immune cell profiles in MM patients treated with bortezomib/adriamycin/dexamethasone (PAD) chemotherapy followed by autologous stem cell transplantation (ASCT) to determine their prognostic value and interplay. Objectives: This study aims to identify markers indicative of a favorable prognosis in MM patients. Methods: CBC data were collected from 93 MM patients at diagnosis, prior to ASCT, and 3 months post-ASCT. Immune cell profiles were assessed via flow cytometry using fresh peripheral blood samples from a subset of 33 prior to ASCT and 3 months post-ASCT. We subsequently investigated the associations between MRD status and prognosis, the predictive value of CBC, and the longitudinal changes in immune cell profiles and their correlation with clinical outcomes. Results: An increased frequency of negative immunomodulatory cell subsets and activated T lymphocytes prior to ASCT were associated with a poor prognosis. Conversely, lower levels of exhausted T lymphocytes, alongside higher levels of functional T cells and marginal zone B cells post-ASCT, predicted a favorable prognosis. Conclusions: Our study demonstrates that pre-ASCT immune status, post-ASCT immune reconstitution, and MRD status at 3 months post-ASCT are closely associated with clinical outcomes in MM patients. These findings underscore the critical importance of regular immune monitoring in the comprehensive management of MM.