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The bone marrow microenvironment (BMM) has highly specialized anatomical characteristics that provide a sanctuary place for hematopoietic stem cells (HSCs) that allow appropriate proliferation, maintenance, and self-renewal capacity. Several cell types contribute to the constitution and function of the bone marrow niche. Interestingly, uncovering the secrets of BMM and its interaction with HSCs in health paved the road for research aiming at better understanding the concept of leukemic stem cells (LSCs) and their altered niche. In fact, they share many signals that are responsible for interactions between LSCs and the bone marrow niche, due to several biological similarities between LSCs and HSCs. On the other hand, LSCs differ from HSCs in their abnormal activation of important signaling pathways that regulate survival, proliferation, drug resistance, invasion, and spread. Targeting these altered niches can help in better treatment choices for hematological malignancies and bone marrow disorders in general and acute myeloid leukemia (AML) in particular. Moreover, targeting those niches may help in decreasing the emergence of drug resistance and lower the relapse rate. In this article, the authors reviewed the most recent literature on bone marrow niches and their relations with either normal HSCs and AML cells/LSC, by focusing on pathogenetic and therapeutic implications.

Acute Myeloid Leukemia is mainly a disease of the elderly: however, the knowledge on the outcomes of treatment in core binding factor AML (CBFAML) in older population, is limited. We retrospectively collected data on 229 patients with CBF- AML followed long-term in the last two decades. A 5-year overall survival (OS) of 44.2% (95%CI, 39.9-47.5) and a 5-year event – free survival (EFS) of 32.9% (95%CI, 25.5-40.1) was observed. In a subgroup of >70-year patients who completed intensive therapy (induction + >3 courses of consolidation including autologous stem cell transplant: 10 patients) the median EFS was 11.8 months (95%CI, 9.4 – 15.2) and OS was 40.0% (95%CI, 36.4 – 44.1) at 5yr. In univariate analysis, age >70 (hazard ratio (HR) 1.78, [95%CI, 1.15 – 2.54], p=.008), failure to achieve remission following induction (HR, 8.96 [95%CI, 5.5 – 13.8], p=

Abstract We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.93, FLAIR 0.93, CE-T1w 0.99). CE-T1w showed higher signal-to-noise ratio and contrast-to-noise ratio (CE-T1w 23.77 and 18.49, T1w 13.73 and 7.44, FLAIR 13.09 and 10.77, respectively). Manual segmentation of ChP resulted 3.073 ± 0.563 mL (mean ± standard deviation) on T1w, 3.787 ± 0.679 mL on FLAIR, and 2.984 ± 0.506 mL on CE-T1w images, with an error of 28.02 ± 19.02% for FLAIR and 3.52 ± 12.61% for T1w. FLAIR overestimated ChP volume compared to CE-T1w (p < 0.001). The Dice similarity coefficient of CE-T1w versus T1w and FLAIR was 0.67 ± 0.05 and 0.68 ± 0.05, respectively. Spatial error distribution per slice was calculated after nonlinear coregistration to the standard MNI152 space and showed a heterogeneous profile along the ChP especially near the fornix and the hippocampus. Quantitative analyses suggest T1w as a surrogate of CE-T1w to estimate ChP volume. Relevance statement To estimate the ChP volume, CE-T1w can be replaced by non-CE T1w sequences because the error is acceptable, while FLAIR overestimates the ChP volume. This encourages the development of automatic tools for ChP segmentation, also improving the understanding of the role of the ChP volume in multiple sclerosis, promoting longitudinal studies. Key points • CE-T1w sequences are considered the reference standard for ChP manual segmentation. • FLAIR sequences showed a higher CNR than T1w sequences but overestimated the ChP volume. • Non-CE T1w sequences can be a surrogate of CE-T1w sequences for manual segmentation of ChP. Graphical Abstract

Abstract Purpose The present study examines the impact of traumatic childhood experiences in people with obesity seeking bariatric surgery. It considers the presence of eating disorders (ED) in the population with obesity and tests the role of attachment and family relationships as mediators of the relationship between traumatic events and ED. Method 110 participants with severe obesity and 98 participants of a healthy weight (control group) filled out The Childhood Trauma Questionnaire (CTQ-SF), the Attachment Style Questionnaire (ASQ) and the Family Adaptability and Cohesion Evaluation Scale (FACES IV). Results Comparing the two groups on psychological variables, higher scores in the CTQ Emotional neglect and ASQ insecure attachment scales emerged in the control group than the group with obesity. Considering the presence/absence of an ED only in the group with obesity, and comparing these subgroups, higher scores in traumatic experiences emerged in the individuals with obesity and with ED than the individuals with obesity without ED. Moreover, participants with ED scored higher in ASQ insecure attachment and had lower levels of flexibility in family functioning than the group without ED. Finally, Logistic Regression models showed that insecure anxious attachment and dysfunctional familial relationships affected the relationship between traumatic childhood experiences and the presence of ED in the group with obesity. Conclusion These findings suggest the importance focusing on psychosocial factors linked to obesity, specifically on attachment styles and familial relationships as emotion regulation strategies, since the impact of traumatic childhood events on psychopathology could be ameliorated by an individual’s ability to rely on a significant attachment figure. Level of evidence Level II, evidence obtained from well-designed controlled trials without randomization.

Nowadays, engine experimental research represents a very expensive field within the automotive industry, but it remains fundamental for engine and vehicle development. The present work aims to investigate a novel approach for engine control system calibration, by adopting machine learning techniques to model physical parameters of the engine starting from experimental data measured at the test bench. The main goal is to create a methodology which accelerates the calibration process without losing accuracy. A model that estimates air mass flow is created by adopting either a tree ensemble model or an artificial neural network trained on a small dataset, which was previously acquired at the test bench using a random calibration of the volumetric efficiency map. The model’s performance is first validated on a larger, random dataset. Then, the volumetric efficiency calculated from the air mass flow model estimation is used to calibrate the transfer function of the Engine Control Unit. Finally, the sensitivity of the model error correlated with the number of data points acquired is used in order to determine the best practice for a Design Of Experiment, which minimizes data acquisition. The methodology proposed can lead to reduced time and costs of the whole calibration process of the engine, without losing accuracy. The analysis was conducted on the entire vehicle, which is crucial for drivability, especially in motorcycles since they are highly sensitive to air-to-fuel ratio adjustments. This work demonstrates that machine learning models can be adopted for the fine-tuning of the calibration process, which is normally performed manually.

Summary: Background: COVID-19 lung sequelae can impact the course of patient lives. We investigated the evolution of pulmonary abnormalities in post-COVID-19 patients 18–24 months after hospital discharge. Methods: A cohort of COVID-19 patients admitted to the Hospital das Clínicas da Faculdade de Medicina da USP in São Paulo, Brazil, between March and August of 2020, were followed-up 6–12 months after hospital discharge. A subset of patients with pulmonary involvement and chest computed tomography (CT) scans were eligible to participate in this second follow-up (18–24 months). Data was analyzed in an ambidirectional manner, including retrospective data from the hospitalization, and from the first follow-up (6–12 months after discharge), and compared with the prospective data collected in this new follow-up. Findings: From 348 patients eligible, 237 (68%) participated in this follow-up. Among participants, 139 (58%) patients presented ground-glass opacities and reticulations, and 80 (33%) presented fibrotic-like lesions (traction bronchiectasis and architectural distortion). Five (2%) patients improved compared to the 6-12-month assessment, but 20 (25%) of 80 presented worsening of lung abnormalities. For those with relevant assessments on both occasions, comparing the CT findings between this follow-up with the previous assessment, there was an increase in patients with architectural distortion (43 [21%] of 204 vs 57 [28%] of 204, p = 0.0093), as well as in traction bronchiectasis (55 [27%] of 204 vs 69 [34%] of 204, p = 0.0043). Patients presented a persistent functional impairment with demonstrated restrictive pattern in both follow-ups (87 [42%] of 207 vs 91 [44%] of 207, p = 0.76), as well as for the reduced diffusion capacity (88 [42%] of 208 vs 87 [42%] of 208, p = 1.0). Length of hospitalization (OR 1.04 [1.01–1.07], p = 0.0040), invasive mechanical ventilation (OR 3.11 [1.3–7.5] p = 0.011), patient's age (OR 1.03 [1.01–1.06] p = 0.0074 were consistent predictors for development of fibrotic-like lung lesions in post-COVID-19 patients. Interpretation: Post-COVID-19 lung sequelae can persist and progress after hospital discharge, suggesting airways involvement and formation of new fibrotic-like lesions, mainly in patients who were in intensive care unit (ICU). Funding: São Paulo Research Foundation (22/01769-5) and Instituto Todos pela Saúde (C1721).

IntroductionTo investigate cortical network changes using Magnetoencephalography (MEG) signals in Parkinson’s disease (PD) patients undergoing Magnetic Resonance-guided Focused Ultrasound (MRgFUS) thalamotomy.MethodsWe evaluated the MEG signals in 16 PD patients with drug-refractory tremor before and after 12-month from MRgFUS unilateral lesion of the ventralis intermediate nucleus (Vim) of the thalamus contralateral to the most affected body side. We recorded patients 24 h before (T0) and 24 h after MRgFUS (T1). We analyzed signal epochs recorded at rest and during the isometric extension of the hand contralateral to thalamotomy. We evaluated cortico-muscular coherence (CMC), the out-strength index from non-primary motor areas to the pre-central area and connectivity indexes, using generalized partial directed coherence. Statistical analysis was performed using RMANOVA and post hoct-tests.ResultsMost changes found at T1 compared to T0 occurred in the beta band and included: (1) a re-adjustment of CMC distribution; (2) a reduced out-strength from non-primary motor areas toward the precentral area; (3) strongly reduced clustering coefficient values. These differences mainly occurred during motor activation and with few statistically significant changes at rest. Correlation analysis showed significant relationships between changes of out-strength and clustering coefficient in non-primary motor areas and the changes in clinical scores.DiscussionOne day after MRgFUS thalamotomy, PD patients showed a topographically reordered CMC and decreased cortico-cortical flow, together with a reduced local connection between different nodes. These findings suggest that the reordered cortico-muscular and cortical-networks in the beta band may represent an early physiological readjustment related to MRgFUS Vim lesion.

Group-equivariant neural networks have emerged as an efficient approach to model complex data, using generalized convolutions that respect the relevant symmetries of a system. These techniques have made advances in both the supervised learning tasks for classification and regression, and the unsupervised tasks to generate new data. However, little work has been done in leveraging the symmetry-aware expressive representations that could be extracted from these approaches. Here, we present holographic-(variational) autoencoder [H-(V)AE], a fully end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space, suitable for unsupervised learning and generation of data distributed around a specified origin in 3D. H-(V)AE is trained to reconstruct the spherical Fourier encoding of data, learning in the process a low-dimensional representation of the data (i.e., a latent space) with a maximally informative rotationally invariant embedding alongside an equivariant frame describing the orientation of the data. We extensively test the performance of H-(V)AE on diverse datasets. We show that the learned latent space efficiently encodes the categorical features of spherical images. Moreover, the low-dimensional representations learned by H-VAE can be used for downstream data-scarce tasks. Specifically, we show that H-(V)AE's latent space can be used to extract compact embeddings for protein structure microenvironments, and when paired with a random forest regressor, it enables state-of-the-art predictions of protein-ligand binding affinity.

INTRODUCTION: Immunotherapy led to increased survival in advanced non-small cell lung cancer; however, it has also increased treatment costs. In this study, real-world data was used to evaluate the average cost of treatment of patients with lung cancer. MATERIAL AND METHODS: This is a retrospective study that extracted patient-level data from a Brazilian Oncology Group database. The inclusion criteria were patients with non-small cell lung cancer from stage I-IV, and that received at least one line of treatment from 2018 to 2019. The primary endpoint was the average cost of treatment according to the disease stage, and secondary endpoints were the average cost of each line of treatment among patients with advanced disease, and the percentage of this amount that was related to immunotherapy acquisition. The study also assessed overall survival and the cost-effectiveness of immunotherapy at first-line versus immunotherapy at second-line or beyond, that was presented as the incremental cost effectiveness ratio per quality-adjusted life years. RESULTS: Fifty patients were included, being four (8%) at early-stage (I and II), 10 (20%) at locally advanced disease (III) and 36 (72%) at advanced-stage (IV). The average costs of treatment for each disease stage were respectively US$30,040, US$52,162, and US$95,607 =0.071). Among patients with advanced disease that received IO, the average cost of the entire treatment was highest with immunotherapy at first line (US$116,623) compared with immunotherapy at second-line (US$112,967) or third-line (US$37,279). Immunotherapy at first-line resulted in an estimated additional 0.26 quality-adjusted life years compared to immunotherapy at second-line (US$19,240). CONCLUSION: The cost of treating non-small cell lung cancer is higher as more advanced is the neoplasm stage at diagnosis. Regarding immunotherapy, the cost of treatment is higher as earlier the treatment is performed, even tough, the cost-effectiveness ratio for first-line treatment seems to be favorable compared to second-line treatment.

We conducted a registry analysis including adult acute myeloid leukemia (AML) patients in remission who had received thiotepa, busulfan, and fludarabine (TBF) or treosulfan-based (Treo) conditioning for haplo-hematopoietic stem cell transplant (HSCT) with posttransplant cyclophosphamide (PTCy) between 2010 and 2020. A total of 1123 patients met the inclusion criteria (968 received TBF and 155 received Treo). A 1:1 matched-pair analysis was performed on 142 TBF and 142 Treo patients. In the Treo group, 68% of patients received treosulfan at a dose ≥36 g/m2 and 54% of patients received a second alkylator (thiotepa or melphalan). We observed a trend toward increased incidence of grade II–IV acute (a) graft-versus-host disease (GVHD) at 180 days in the TBF group compared with Treo (29% versus 20%; P = 0.08), while incidence of grade III–IV aGVHD was not statistically different. Similarly, the incidence of chronic (c) GVHD was not statistically different in the 2 groups. Incidence of nonrelapse mortality at 2 years was 19% in TBF and 14% in Treo (P = 0.4). Relapse incidence at 2 years was not statistically different in the 2 groups (16% and 18% in TBF and Treo, respectively; P = 0.9). Leukemia-free survival, overall survival, and GVHD-free, relapse-free survival was 65% versus 68% (P = 0.6), 73% versus 76% (P = 0.5), and 54% versus 53% (P = 0.8) in TBF versus Treo, respectively. In conclusion, we did not find a significant difference between the 2 conditioning in the present study; Treo and TBF represent 2 valid alternative regimens for haplo-HSCT with PTCy for AML in remission.

The prognosis of adult acute lymphoblastic leukemia (ALL) is variable but more often dismal. Indeed, its clinical management is challenging, current therapies inducing complete remission in 65–90% of cases, but only 30–40% of patients being cured. The major determinant of treatment failure is relapse; consequently, measurement of residual leukemic blast (minimal residual disease, MRD) has become a powerful independent prognostic indicator in adults. Numerous evidences have also supported the clinical relevance of MRD assessment for risk class assignment and treatment selection. MRD can be virtually evaluated in all ALL patients using different technologies, such as polymerase chain reaction amplification of fusion transcripts and clonal rearrangements of antigen receptor genes, flow cytometric study of leukemic immunophenotypes and, the most recent, high throughput sequencing (HTS). In this review, the authors focused on the latest developments on MRD monitoring with emphasis on the use of HTS, as well as on the clinical impact of MRD monitoring.

Abstract Background context Fast-track is an evidence-based multidisciplinary strategy for pre-, intra-, and postoperative management of patients during major surgery. To date, fast-track has not been recognized or accepted in all surgical areas, particularly in orthopedic spine surgery where it still represents a relatively new paradigm. Purpose The aim of this review was provided an evidenced-based assessment of specific interventions, measurement, and associated outcomes linked to enhanced recovery pathways in spine surgery field. Methods We conducted a systematic review in three databases from February 2012 to August 2022 to assess the pre-, intra-, and postoperative key elements and the clinical evidence of fast-track protocols as well as specific interventions and associated outcomes, in patients undergoing to spine surgery. Results We included 57 full-text articles of which most were retrospective. Most common fast-track elements included patient’s education, multimodal analgesia, thrombo- and antibiotic prophylaxis, tranexamic acid use, urinary catheter and drainage removal within 24 hours after surgery, and early mobilization and nutrition. All studies demonstrated that these interventions were able to reduce patients’ length of stay (LOS) and opioid use. Comparative studies between fast-track and non-fast-track protocols also showed improved pain scores without increasing complication or readmission rates, thus improving patient’s satisfaction and functional recovery. Conclusions According to the review results, fast-track seems to be a successful tool to reduce LOS, accelerate return of function, minimize postoperative pain, and save costs in spine surgery. However, current studies are mainly on degenerative spine diseases and largely restricted to retrospective studies with non-randomized data, thus multicenter randomized trials comparing fast-track outcomes and implementation are mandatory to confirm its benefit in spine surgery.