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POEMS syndrome is a rare plasma cell dyscrasia. This study compared the responses to and survival of 347 POEMS syndrome patients given three first-line treatment regimens: autologous stem cell transplantation (ASCT, N  = 165) and melphalan + dexamethasone (MDex, N  = 79), or lenalidomide + dexamethasone (LDex, N  = 103). After a median 45-month follow-up, overall hematologic complete remission (CR H ) was 46.4%, vascular endothelial growth factor complete remission (CR V ) was 55.1%, and neurological remission (R N ) was 93.8%. CR H was better with ASCT (49.7%) than with MDex (37.7%, p  = 0.001). CR V was better with ASCT (66.2%) than with MDex (38.5%, p  = 0.001) or LDex (47.7%, p  = 0.008). Differences in R N achieved by three regimens (91.5% vs. 100% vs. 93.8%, p  = 0.234) were not significant. Overall 3-year progression-free survival (PFS) was 80.5% and overall 3-year overall survival (OS) was 90.8%. PFS was 87.6% with ASCT and 64.9% with LDex ( p  = 0.003). OS in the three regimens did not differ ( p  = 0.079). In medium-high risk patients, ASCT had better CR H and CR V than MDex, and better PFS than LDex. Therefore, although all three treatments had reasonable responses and survivals, patients with higher risk may benefit more from ASCT treatment.

BackgroundElderly patients with acute myeloid leukemia (AML) can be treated with intensive therapy, low-intensity therapy, or best supportive care. Medical decision-making might be affected by physicians’ occupational and non-occupational factors.ObjectiveTo explore the impact of physicians’ personalities and behavioral traits on treatment-related decision-making for elderly AML patients.DesignA nationwide cross-sectional survey.ParticipantsHematologists in mainland China (N = 529; response rate 64.5%).Main MeasuresThe medical decision-making for elderly AML patients was evaluated using 6 clinical vignettes. Hematologists’ attitudes toward risk and uncertainty, Big Five personality traits, and decision-making styles were assessed using binary lottery choices and well-recognized self-report inventories.Key ResultsThe resulting binary regression model in predicting treatment intensity contained professional title group (OR = 0.012, 95% CI 0.001 to 0.136, P < 0.001), conscientiousness (OR = 0.336, 95% CI 0.121 to 0.932, P = 0.036), extraversion (OR = 0.403, 95% CI 0.166 to 0.974, P = 0.044), conscientiousness by title group (OR = 2.009, 95% CI 1.100 to 3.667, P = 0.023), and extraversion by title group (OR = 1.627, 95% CI 0.965 to 2.743, P = 0.068) as predictors of therapy intensity preference. Junior physicians with a higher level of extraversion (mean difference = 0.27; 95% CI 0.07 to 0.45; P = 0.009) or conscientiousness (mean difference = 0.19; 95% CI 0.01 to 0.36; P = 0.028) tended to prescribe more intensive therapy. Meanwhile, no significant correlation was found between physicians’ personalities or behavioral traits and treatment-related decision-making in senior physicians.ConclusionsPhysicians’ personalities contribute to treatment-related decision-making for elderly AML patients, depending on the professional titles. More extravert or conscientious attending physicians tended to prescribe more intensive therapy. Meanwhile, the decisions made by chief and associate chief physicians were not impacted by their personal traits. Junior physicians should be aware of such potential influence when making medical decisions.

ObjectiveTo evaluate the heart response of Erdheim-Chester disease (ECD) through continuous follow-up within our large cohort, for which there is a lack of understanding.MethodsWe conducted a retrospective analysis of clinical data from patients with ECD with cardiac involvement diagnosed at our centre between January 2010 and August 2023. We assessed the heart response by integrating pericardial effusion and metabolic responses.ResultsA total of 40 patients were included, with a median age of 51.5 years (range: 29–66) and a BRAFV600E mutation rate of 56%. The most common imaging manifestations observed were pericardial effusion (73%), right atrium (70%) and right atrioventricular sulcus infiltration (58%). Among 21 evaluable patients, 18 (86%) achieved a heart response including 5 (24%) complete response (CR) and 13 (62%) partial response (PR). The CR rate of pericardial effusion response was 33%, while the PR rate was 56%. Regarding the cardiac mass response, 33% of patients showed PR. For cardiac metabolic response, 32% and 53% of patients achieved complete and partial metabolic response, respectively. There was a correlation between pericardial effusion response and cardiac metabolic response (r=0.73 (95% CI 0.12 to 0.83), p<0.001). The median follow-up was 50.2 months (range: 1.0–102.8 months). The estimated 5-year overall survival was 78.9%. The median progression-free survival was 59.4 months (95% CI 26.2 to 92.7 months). Patients who received BRAF inhibitors achieved better heart response (p=0.037) regardless of treatment lines.ConclusionWe pioneered the evaluation of heart response of ECD considering both pericardial effusion and cardiac metabolic response within our cohort, revealing a correlation between these two indicators. BRAF inhibitors may improve heart response, regardless of the treatment lines.

Continuously monitoring global population spatial dynamics is crucial for implementing effective policies related to sustainable development, including epidemiology, urban planning, and global inequality. However, existing global gridded population data products lack consistent population estimates, making them unsuitable for time-series analysis. To address this issue, this study designed a data fusion framework based on cluster analysis and statistical learning approaches, which led to the generation of a continuous global gridded population dataset (GlobPOP). The GlobPOP dataset was evaluated through two-tier spatial and temporal validation to demonstrate its accuracy and applicability. The spatial validation results show that the GlobPOP dataset is highly accurate. The temporal validation results also reveal that the GlobPOP dataset performs consistently well across eight representative countries and cities despite their unique population dynamics. With the availability of GlobPOP datasets in both population count and population density formats, researchers and policymakers can leverage the new dataset to conduct time-series analysis of the population and explore the spatial patterns of population development at global, national, and city levels.

Rice disease recognition is crucial in automated rice disease diagnosis systems. At present, deep convolutional neural network (CNN) is generally considered the state-of-the-art solution in image recognition. In this paper, we propose a novel rice blast recognition method based on CNN. A dataset of 2906 positive samples and 2902 negative samples is established for training and testing the CNN model. In addition, we conduct comparative experiments for qualitative and quantitatively analysis in our evaluation of the effectiveness of the proposed method. The evaluation results show that the high-level features extracted by CNN are more discriminative and effective than traditional hand-crafted features including local binary patterns histograms (LBPH) and Haar-WT (Wavelet Transform). Moreover, quantitative evaluation results indicate that CNN with Softmax and CNN with support vector machine (SVM) have similar performances, with higher accuracy, larger area under curve (AUC), and better receiver operating characteristic (ROC) curves than both LBPH plus an SVM as the classifier and Haar-WT plus an SVM as the classifier. Therefore, our CNN model is a top performing method for rice blast disease recognition and can be potentially employed in practical applications.

Background Langerhans cell sarcoma (LCS), an exceptionally rare and aggressive neoplasm, remains poorly characterized due to its scarcity. To address this knowledge gap, we conducted a retrospective analysis of 13 LCS patients. This retrospective study included patients ≥ 18 years old with biopsy proven LCS from October 2015 to April 2025. Results The median age at diagnosis was 59 years (range: 33–71). The most commonly affected organs were the subcutaneous soft tissue (61.5%), followed by lymph nodes (53.8%), skin (30.8%), and bone (23.1%). CBL was the most common mutation, detected in four patients (33.3%). Notably, first-line treatment options included surgery and chemotherapy, with an overall response rate of 53.8%. Among all the relapsed or refractory patients, three eventually received targeted therapies (two trametinib and one niraparib), demonstrating promising efficacy with all patients achieved partial remission. With a median follow-up of 18.2 months (range: 2.6–93.1), the estimated 2-year overall survival rate was 92.3%, while the estimated 2-year progression-free survival (PFS) rate stood at 32.9%. Conclusions In our cohort of LCS, we found that the PFS of LCS was poor. Genetic sequencing and the use of targeted therapies may offer a survival advantage for patients with LCS. Clinical trial registration Not applicable.

Langerhans cell histiocytosis (LCH) is an inflammatory myeloid malignancy in the “L-group” histiocytosis. Mitogen-activated protein kinase (MAPK) pathway activating mutations are detectable in nearly all LCH lesions. However, the pathogenic roles of MAPK pathway activation in the development of histiocytosis are still elusive. This review will summarize research concerning the landscape and pathogenic roles of MAPK pathway mutations and related treatment opportunities in Langerhans cell histiocytosis. 12wkDfvt5iVkBt3L9upJpX Video abstract