How I Manage Transplant Ineligible Patients with Myelodysplastic Neoplasms

Myelodysplastic neoplasms, formerly known as myelodysplastic syndromes (MDS), represent a group of clonal disorders characterized by a high degree of clinical and molecular heterogeneity, and an invariable tendency to progress to acute myeloid leukemia. MDS typically present in the elderly with cytopenias of different degrees and bone marrow dysplasia, the hallmarks of the disease. Allogeneic hematopoietic stem cell transplant is the sole curative approach to date. Nonetheless, given the disease's demographics, only a minority of patients can benefit from this procedure. Currently used prognostic schemes such as the Revised International Prognostic Scoring System (R-IPSS), and most recently the molecular IPSS (IPSS-M), guide clinical management by dividing MDS into two big categories: lower- and higher-risk cases, based on a cut-off score of 3.5. The main clinical problem of the lower-risk group is represented by the management of cytopenias, whereas the prevention of secondary leukemia progression is the goal for the latter. Herein, we discuss the non-transplant treatment of MDS, focusing on current practice and available therapeutic options, while also presenting new investigational agents potentially entering the MDS therapeutic arsenal in the near future

Multiple Reaction Monitoring Profiling (MRM-Profiling) of Lipids To Distinguish Strain-Level Differences in Microbial Resistance in Escherichia coli

The worldwide increase in antimicrobial resistance is due to antibiotic overuse in agriculture and overprescription in medicine. For appropriate and timely patient support, faster diagnosis of antimicrobial resistance is required. Current methods for bacterial identification rely on genomics and proteomics and use comparisons with databases of known strains, but the diagnostic value of metabolites and lipids has not been explored significantly. Standard mass spectrometry/chromatography methods involve multiple dilutions during sample preparation and separation. To increase the amount of chemical information acquired and the speed of analysis of lipids, multiple reaction monitoring profiling (MRM-Profiling) has been applied. The MRM-Profiling workflow includes a discovery stage and a screening stage. The discovery stage employs precursor (PREC) ion and neutral loss (NL) scans to screen representative pooled samples for functional groups associated with particular lipid classes. The information from the first stage is organized in precursor/product ion pairs, or MRMs, and the screening stage rapidly interrogates individual samples for these MRMs. In this study, we performed MRM-Profiling of lipid extracts from four different strains of Escherichia coli cultured with amoxicillin or amoxicillin/clavulanate, a β-lactam and β-lactamase inhibitor, respectively. t tests, analysis of variance and receiver operating characteristic (ROC) curves were used to determine the significance of each MRM. Principal component analysis was applied to distinguish different strains cultured under conditions that allowed or disallowed development of bacterial resistance. The results demonstrate that MRM-Profiling distinguishes the lipid profiles of resistant and nonresistant E. coli strains

Assessment of Regional Variability in COVID-19 Outcomes Among Patients With Cancer in the United States.

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography. Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer. Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States. Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time. Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250 000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58). Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients

COVID-19 Severity and Cardiovascular Outcomes in SARS-CoV-2-Infected Patients With Cancer and Cardiovascular Disease

BACKGROUND: Data regarding outcomes among patients with cancer and co-morbid cardiovascular disease (CVD)/cardiovascular risk factors (CVRF) after SARS-CoV-2 infection are limited. OBJECTIVES: To compare Coronavirus disease 2019 (COVID-19) related complications among cancer patients with and without co-morbid CVD/CVRF. METHODS: Retrospective cohort study of patients with cancer and laboratory-confirmed SARS-CoV-2, reported to the COVID-19 and Cancer Consortium (CCC19) registry from 03/17/2020 to 12/31/2021. CVD/CVRF was defined as established CVD RESULTS: Among 10,876 SARS-CoV-2 infected patients with cancer (median age 65 [IQR 54-74] years, 53% female, 52% White), 6253 patients (57%) had co-morbid CVD/CVRF. Co-morbid CVD/CVRF was associated with higher COVID-19 severity (adjusted OR: 1.25 [95% CI 1.11-1.40]). Adverse CV events were significantly higher in patients with CVD/CVRF (all CONCLUSIONS: Co-morbid CVD/CVRF is associated with higher COVID-19 severity among patients with cancer, particularly those not receiving active cancer therapy. While infrequent, COVID-19 related CV complications were higher in patients with comorbid CVD/CVRF. (COVID-19 and Cancer Consortium Registry [CCC19]; NCT04354701)

Accelerating the Throughput of Mass Spectrometry Analysis by Advanced Workflow and Instrumentation

The exploratory profiling and quantitative bioassays of lipids, small metabolites, and peptides have always been challenging tasks. The most popular instrument platform deployed to solve these problems is chromatography coupled with mass spectrometry. However, it requires large amounts of instrument time, intensive labor, and frequent maintenance, and usually produces results with bias. Thus, the pace of exploratory research is one of poor efficacy and low throughput. The work in this dissertation provides two practical tactics to address these problems. The first solution is multiple reaction monitoring profiling (MRM-profiling), a new concept intended to shift the exploratory research from current identification-centered metabolomics and lipidomics to functional group screening by taking advantage of precursor ion scan and product ion scan. It is also demonstrated that MRM-profiling is capable of quantifying the relative amount of lipids within the same subclass. Besides, an application of the whole workflow to investigate the strain-level differences of bacteria is described. The results have zeroed in on several potential lipid biomarkers and corresponding MRM transitions. The second strategy is aimed to increase the throughput of targeted bioassays by conducting induced nanoelectrospray ionization (nESI) in batch mode. A novel prototype instrument named Dip-and-Go system is presented. Characterization of its ability to carry out reaction screening and bioassays exhibits the versatility of the system. The distinct electrophoretic cleaning mechanism contributes to the removal of salt during ionization, which assures the accuracy of measurement

Using Smartwatch and Bluetooth Beacons to Monitor Physical Activity of Older Adults

ObjectiveWe used a novel Sensing At-Risk Population (SARP) system to monitor patients’ physical activity and locations during post-acute rehabilitation; To (1) examine the correlation between SARP measurements and standard physical (PT) and occupational therapists (OT) and nurse (RN) evaluations; (2) examine the effectiveness of SARP to discriminate discharge dispositions.MethodsParticipants were instructed to wear the smartwatch and receive physical and occupational therapy. Spearman correlations were used to determine the associations between SARP measurements and in-person evaluations. Univariate logistic regression was used to identify predictors of discharge dispositions.�ResultsSARP measurements and PT/OT/RN evaluations were correlated significantly. SARP indicated that participants were active for only 5 minutes/hour during post-acute rehabilitation. SARP significantly predicted hospital readmission (AUC>70%).ConclusionsSARP provides physical activity information during post-acute rehabilitation in real-time. Not only is SARP significantly correlated with PT/OT/RN evaluations, but it also helps to discern discharge dispositions

An overview of novel therapies in advanced clinical testing for acute myeloid leukemia

The past decade has seen a sea change in the AML landscape with vastly improved cognizance of molecular pathogenesis, clonal evolution, and importance of measurable residual disease. Since 2017, the therapeutic armamentarium of AML has considerably expanded with the approval of midostaurin, enasidenib, ivosidenib, gilteritinib, and venetoclax in combination with hypomethylating agents and others. Nevertheless, relapse and treatment refractoriness remain the insurmountable challenges in AML therapy. This has galvanized the leukemic research community leading to the discovery and development of agents that specifically target gene mutations, molecularly agnostic therapies that exploit immune environment, apoptotic pathways, leukemic cell surface antigens and so forth. This article provides an overview of the pathophysiology of AML in the context of non-cellular immune and molecularly targeted and agnostic therapies that are in clinical trial development in AML. Ever growing understanding of the molecular pathogenesis and metabolomics in AML has allowed the researchers to identify targets directed at specific genes and metabolic pathways. As a result, AML therapy is constantly evolving and so are the escape mechanisms leading to disease relapse. Therefore, it is of paramount importance to sequentially evaluate the patient during AML treatment and intervene at the right time

Multi-view stereo network with point attention

In recent years, learning-based multi-view stereo (MVS) reconstruction has gained superiority when compared with traditional methods. In this paper, we introduce a novel point-attention network, with an attention mechanism, based on the point cloud structure. During the reconstruction process, our method with an attention mechanism can guide the network to pay more attention to complex areas such as thin structures and low-texture surfaces. We first infer a coarse depth map using a modified classical MVS deep framework and convert it into the corresponding point cloud. Then, we add the high-frequency features and different-resolution features of the raw images to the point cloud. Finally, our network guides the weight distribution of points in different dimensions through the attention mechanism and computes the depth displacement of each point iteratively as the depth residual, which is added to the coarse depth prediction to obtain the final high-resolution depth map. Experimental results show that our proposed point-attention architecture can achieve a significant improvement in some scenes without reasonable geometrical assumptions on the DTU dataset and the Tanks and Temples dataset, suggesting that our method has a strong generalization ability