Artigos de revistas sobre o tema "(Alliance, Ohio)"

In steam-generating systems of all types, producing and testing pure water is of utmost importance for the life of the system. A 1000-MWe (megawatt electric) power plant generates 6 million pounds of steam per hour if fossil fueled and 11 million pounds per hour if nuclear. Should an impurity have a concentration of only 10 ppb, in a year's time, 550 to 1000 pounds of solids can accumulate in the power-generating cycle. These solids may initiate numerous problems, including preboiler-cycle corrosion, boiler-tube failure, and turbine damage.At the Babcock & Wilcox (B&W) Alliance (Ohio) Research Center and throughout the industry, three principal methods are used to monitor water chemistry. On-line continuous analyzers measure parameters such as pH, conductivity, chloride, and sodium. Grab sampling (followed by laboratory analysis) is used for parameters that are measured less frequently; for example, sulfate. For some parameters, such as corrosion products, special sampling techniques are required. This is because no on-line instruments are available, and grab-samples are not chemically stable. Corrosion products are collected near the sample tap using a 0.45-micron filter-disc followed by a stack of resin-impregnated membranes.

Context.— The Department of Anatomic Pathology is a division of the Pathology & Laboratory Medicine Institute at Cleveland Clinic Abu Dhabi. The hospital offers the same model of care as its US-based counterpart the Cleveland Clinic, established in 1921 in Cleveland, Ohio. Pathology services at Cleveland Clinic are internationally acclaimed: the endeavor for Cleveland Clinic Abu Dhabi was to create a parallel facility, with the same standards in a greenfield start-up environment. Objective.— To narrate how we addressed challenges customary in any laboratory start-up and issues distinctive to our setting with the aim to provide a model for others involved in a similar undertaking. Data Sources.— All information in this article is based on published literature obtained by search on internet-based search engines, Clinical and Laboratory Standards Institute, and the authors' firsthand experience. Conclusions.— Key considerations in establishing an anatomic pathology laboratory are careful planning and design, adherence to local and international regulatory standards, selection of equipment and supplies, appropriate staffing, development of a laboratory information system, and sound test validation. In addition to meeting our clinical needs, alliance with the US Cleveland Clinic had an integral role in establishing our laboratory and regional reputation.

Uproleselan (GMI-1271) is a novel antagonist of E-selectin, an adhesion molecule expressed on endothelial cells. E-selectin is expressed transiently in the normal vasculature during an inflammatory response and constitutively in the bone marrow (BM). Binding of E-selectin (E-sel) to sialyl Lex, the E-sel ligand (E-sel-L), on the leukemic cell surface activates cell survival pathways and promotes chemotherapy resistance in AML. In preclinical models, blockade of E-selectin with uproleselan disrupts the activation of cell survival pathways and enhanced the efficacy of chemotherapy across multiple AML tumor models. Furthermore, uproleselan protected against chemotherapy-induced mucositis by regulating macrophage trafficking to the site of injury in the gut lining. A previous phase I/II study of uproleselan added to chemotherapy in patients with untreated AML (older adults ≥60 yrs) and relapsed/refractory AML (≥ 18yrs) showed promising remission rates (CR/CRi) and survival outcomes, and reduced rates of mucositis. In the newly diagnosed older patients, high remission rates were achieved overall (CR/CRi 72%) and for the high risk subgroup with sAML (CR/CRi 69%). In this phase 2/3 study, we will test the addition of uproleselan to a standard daunorubicin/cytarabine regimen in older adults with previously untreated AML. The study will enroll patients age ≥ 60 yrs with untreated acute myeloid leukemia. Patients with acute promyelocytic leukemia, activating mutations in FLT3, or evidence of central nervous system involvement are excluded. Subjects are randomized to 7+3 induction (cytarabine + daunorubicin) +/- uproleselan. Subjects achieving a CR/CRi may receive up to 3 cycles of consolidation with intermediate dose cytarabine 2 gm/m2 IV d1-5 +/- uproleselan. The primary phase II objective is to compare the event-free survival (EFS). A sample size of 262 patients was selected for the phase II to detect an improvement in median EFS from 7 months to 11 months (HR= 0.64) with > 95% power, using a log rank test. The phase III primary objective will compare overall survival (OS). For the phase III, a sample size of 335 evaluable patients per arm (670 total inclusive of patients enrolled in phase II) will provide >90% power to detect an improvement in median OS from 12 months to 16 months (HR= 0.75), using a log-rank test. Correlative studies will measure E-selectin ligand on AML blasts and soluble E-selectin and will also measure minimal residual disease after remission induction by multiparameter flow cytometry. A comprehensive geriatric assessment will identify baseline measures associated with EFS and develop a risk model to predict OS among older adults receiving intensive AML therapy. The study is endorsed by SWOG and ECOG-ACRIN and opened to enrollment on 1/16/2019. Figure Disclosures Uy: Astellas: Consultancy; Pfizer: Consultancy; Curis: Consultancy; GlycoMimetics: Consultancy. Dinner:Agios: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy. Strickland:Jazz: Consultancy; Sunesis Pharmaceuticals: Research Funding; Pfizer: Consultancy; Kite: Consultancy; Astellas Pharma: Consultancy; AbbVie: Consultancy. Liesveld:Onconova: Other: Data safety monitoring board; Abbvie: Membership on an entity's Board of Directors or advisory committees. Byrd:Acerta: Research Funding; Acerta: Research Funding; Genentech: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Ohio State University: Patents & Royalties: OSU-2S; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau. Stone:Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy; Novartis, Agios, Arog: Research Funding. OffLabel Disclosure: Uproleselan in AML

Introduction: AML is a heterogeneous disease with diverse patient outcomes. During the last 4 decades, several cytogenetic and molecular markers have been used for risk stratification of AML pts and to guide therapeutic decisions. In 2017, Gerstung et al. (Nat Genet 2017;49:332) used a knowledge bank (KB; i.e., combination of clinical, outcome, cytogenetic and sequencing data of 111 genes from 1,540 AML pts) to generate an algorithm that is able to predict likelihoods for remission, relapse, and mortality in AML pts. The prognostic value of the established KB algorithm was validated in two independent but smaller pt cohorts (Gerstung et al.: n=186 pts; Huet et al. Blood 2018;132:865: n=155 pts). Aims: The aim of our study was to validate the prognostic relevance of the KB algorithm both in our entire large independent adult pt cohort and in age subgroups (i.e., younger [<60 y] and older [≥60 y] pts). We also compared the performance of the KB algorithm with that of another well-established prognostic classification, the 2017 European LeukemiaNet (ELN) genetic risk classification (Döhner et al. Blood 2017;129:424). Methods: We analyzed 1,617 pts (median age: 53 y; 1,048 aged <60 y and 569 aged ≥60 y; including 167 early death [ED] pts who died within 30 days after diagnosis) with de novo AML appropriate for intensive chemotherapy. The mutational status of 80 cancer- and leukemia-associated genes (Eisfeld et al. Leukemia 2017;31:2211) was determined using a targeted next-generation sequencing panel (variants with variant allele fraction < 5% were defined as not mutated) The status of biallelic CEBPA mutations was determined using Sanger sequencing, and an internal tandem duplication of the FLT3 gene using fragment analysis in pretreatment bone marrow or blood samples. All pts were treated on CALGB/Alliance protocols and none received an allogeneic transplant in first complete remission (CR1). Of the genes whose mutational status is included in the KB algorithm, 26% were not included in our sequencing panel, but all 30 genes that had the biggest impact on the algorithm's ability to predict outcome were contained in our panel. Results: We used the 3-y overall survival (OS) rates to compare the KB algorithm prediction with the actual outcome. In the whole cohort, we found the area under the receiver operating characteristic curve (AUC) to be AUCKB = 0.79 (Figure 1A). Of note, AUC = 1.00 means perfect prediction ability whereas AUC = 0.50 denotes lack of prediction ability equal to that of random chance. Concerning other clinical endpoints, we found that the KB approach had the highest AUC for predicting non-remission death (i.e., pts who died without achieving a CR1, AUCKB = 0.84), followed by relapse death (i.e., pts who died after relapse, AUCKB = 0.69), and non-relapse death (i.e., pts who died in CR1, AUCKB = 0.61). Analysis of the 3-y OS in the subgroup of younger pts yielded similar results with an AUCKB = 0.78. Older pts are known to have poorer prognosis and risk stratification is more difficult for this cohort, but, we still found an AUCKB = 0.79 for the KB approach. Next, we compared the predictive value of the KB approach with the current ELN classification and found that KB outperformed the ELN classification in the whole cohort (AUCKB = 0.79 vs AUCELN = 0.53, P<0.001; Figure 1A) as well as in the younger (AUCKB = 0.78 vs AUCELN = 0.51, P<0.001; Figure 1B) and older pt subgroups (AUCKB = 0.79 vs AUCELN = 0.53, P<0.001; Figure 1C). We also compared KB and ELN after excluding ED pts because the ELN risk group is a poor predictor for ED. We found that KB still outperformed the ELN classification in the whole cohort (AUCKB = 0.78 vs AUCELN = 0.71, P<0.001) and in the younger pts (AUCKB = 0.74 vs AUCELN = 0.69, P=0.005). However, in older pts the difference was of borderline significance (AUCKB = 0.75 vs AUCELN = 0.70, P=0.05). Conclusions: Our analysis of a large cohort of 1,617 pts with de novo AML treated with intensive chemotherapy validated the prognostic value of the recently published KB algorithm for the 3-y OS endpoint. Although we found that the KB approach had a high predictive relevance for non-remission death, the AUCs for relapse death and non-relapse death were lower. We also showed that the KB approach had a better predictive value than the current ELN classification but the differences in the AUCs were smaller when ED pts were excluded. Support: CA233338, U24CA196171, U10CA180821, U10CA180882. https://acknowledgments.alliancefound.org Disclosures Kolitz: Boeringer-Ingelheim: Research Funding; Astellas: Research Funding; Roche: Research Funding. Powell:Jazz Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy, Research Funding; Rafael Pharmaceuticals: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Janssen: Research Funding. Stone:AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy; Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; Novartis, Agios, Arog: Research Funding. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Ohio State University: Patents & Royalties: OSU-2S; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Genentech: Research Funding; Genentech: Research Funding; BeiGene: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau.

Background The phase 3 trial A041202 solidified the Bruton's Tyrosine Kinase (BTK) inhibitor ibrutinib as a standard of care for older patients with previously untreated CLL by showing superior progression-free survival (PFS) as compared with bendamustine plus rituximab. While ibrutinib is highly effective in previously untreated CLL, there do remain disadvantages to this therapy, specifically the low rate of complete response (CR) and therefore the need for continuous administration, which increases cost and toxicity. In older patients especially, toxicities with ibrutinib are common; 17% of patients had atrial fibrillation and 29% had grade 3 or higher hypertension on the A041202 study. Thus, strategies to decrease the exposure time to ibrutinib are of interest. Venetoclax is an inhibitor of BCL2 that has shown efficacy as a single agent and in combination with monoclonal antibodies, specifically the anti-CD20 monoclonal antibody obinutuzumab for patients with previously untreated CLL. One significant advantage to venetoclax is the ability to produce CRs and minimal residual disease negative (MRD-) responses. In this study, we compare ibrutinib plus obinutuzumab (IO) to ibrutinib plus venetoclax plus obinutuzumab (IVO) with a response-dependent discontinuation. While other studies have been designed with the goal of discontinuation of ibrutinib through combinations with venetoclax, no other study has been presented using a response-dependent discontinuation strategy. Study Design and Methods A041702 is a randomized phase 3 study led by the Alliance for Clinical Trials in Oncology that is currently enrolling through the NCI National Clinical Trials Network (NCTN). CLL patients age 70 years or older who are previously untreated and in need of therapy are eligible. Previous treatment of autoimmune complications with steroids or rituximab is allowed. Patients must have intermediate- or high-risk Rai stage, ECOG performance status 0-2, ANC ≥ 1000/mm3 unless due to marrow involvement, and platelets ≥ 30,000/mm3. CrCl must be ≥ 40 mL/min and AST/ALT ≤ 2.5x upper limit of normal. Patients with hepatitis B must have undetectable viral load, and patients must not have an intercurrent illness that is expected to limit survival to < 5 years. Warfarin and strong inhibitors or inducers of CYP3A4/5 are not permitted. Patients are initially preregistered to the study and submit a peripheral blood sample for central FISH analysis of del(17p). Patients who are registered are randomized 1:1 to Arm 1 (IO) or Arm 2 (IVO), and are stratified by Rai stage and presence of del(17p). IO consists of I daily starting cycle 1 day 1, and O dosed as standard starting cycle 1 day 1 and continuing to cycle 6 day 1. IVO consists of IO as in Arm 1, with V starting cycle 3 day 1 with standard 5-week ramp-up and continuing until cycle 14 day 28. At the end of 14 cycles, patients in both arms undergo response evaluation with central peripheral blood and bone marrow MRD testing. Patients on IO then continue I indefinitely. Patients on IVO who are in a bone marrow MRD- CR discontinue all therapy, and those who are not continue I indefinitely. The primary objective of the study is to compare PFS between IO and IVO using the strategy of response-dependent discontinuation. There is 90% power to detect a hazard ratio for PFS of 0.55 (corresponding to 5-year PFS rates of 70% and 82.187% for IO and IVO, respectively), at a one-sided significance level of 0.025 by a log-rank test. This design requires 128 events and 431 total evaluable patients assuming uniform accrual over the course of 3 years and minimum follow-up of 5 years. The study includes two interim analyses for superiority when 50% and 75% of the expected number of events have been observed and three interim analyses for futility when 25%, 50%, and 75% of the expected number of events have been observed. Conclusions A041702 is an ongoing phase 3 clinical trial using a novel response-dependent discontinuation method. Results of this study have the potential to change the standard of care for older patients with previously untreated CLL. The study is expected to accrue for 3 years beginning January 2019, and we welcome participation from sites throughout the NCTN. Support: U10CA180821, U10CA180882, UG1CA189823, U24CA196171; U10CA180820 (ECOG-ACRIN); https://acknowledgments.alliancefound.org; ClinicalTrials.gov Identifier: NCT03737981 Disclosures Woyach: Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Loxo: Research Funding; Morphosys: Research Funding; Verastem: Research Funding. Lozanski:Beckman Coulter: Research Funding; Boehringer Ingelheim: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentec: Research Funding. Ding:Merck: Research Funding; DTRM Biopharma: Research Funding. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Stone:Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; Novartis, Agios, Arog: Research Funding; AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Acerta: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; BeiGene: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; BeiGene: Research Funding; Genentech: Research Funding; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau.

Background: Aberrant expression levels of several miRs have been reported to independently associate with outcome of patients (pts) with CN-AML. In these reports, miR expression was profiled using microarray assays, which interrogate a selected subset of miRs. The advent of next-generation sequencing (NGS) has allowed unbiased measurement of miR expression, but, to our knowledge, NGS has not been used to identify miRs associated with prognosis of AML pts. Here, we analyze small RNA sequencing (smRNA-seq) data from a large cohort of younger adults with CN-AML, for whom outcome data were available, with the goal to identify new prognostic miRs. Methods: We performed smRNA-seq in 281 younger adults (aged 18-59 y) with de novo CN-AML. Cytogenetic analyses were performed in Cancer and Leukemia Group B (CALGB)/Alliance institutional laboratories using standard banding techniques; mutational analyses were done centrally using a targeted DNA sequencing platform. All pts were treated on frontline CALGB/Alliance protocols. Results: We first evaluated which miRs associated with overall survival (OS) in univariable analysis; we detected 9 such miRs. We then used a machine-learning approach, namely random forests, to identify miRs whose concomitant expression could generate an effective outcome predictor in CN-AML. To account for the effect of co-existing prognostic gene mutations, we included the European LeukemiaNet (ELN) risk group status in the random forest analyses. A total of 8 prognostic miRs were identified, 4 of which were also found to be prognostic in univariable analysis (underlined below), thus bringing the total number of unique prognostic miRs to 13: miR-511, miR-1193, miR-155, miR-4517, miR-3681, miR-2355, miR-628, miR-1266, miR-6715a, miR-1180, miR-6715b, miR-132, miR-146b. We used partitioning around medoids to divide our pts into clusters, based on the combined expression levels of the 13 prognostic miRs. Two such clusters were identified: cluster 1 comprised 173 pts and cluster 2 contained 108 pts. Regarding pretreatment and molecular features, pts in cluster 1 had lower percent of bone marrow blasts (P=.04), and had more frequently biallelic CEBPA mutations (P<.001) and less frequently internal tandem duplications of the FLT3 gene (P<.001), RUNX1 (P=.02) and WT1(P=.03) mutations than pts in cluster 2. In outcome analyses, pts in cluster 1 had a higher complete remission rate (CR; 91% vs 73%,P<.001) and a longer disease-free survival (DFS; 5-y rates 52% vs 16%, P<.001) and OS (5-y rates 60% vs 19%,P<.001). In multivariable analysis, cluster 1 status remained significantly associated with higher odds of achieving a CR (P=.001) and longer DFS (P<.001) and OS (P<.001), after adjusting for other covariates. Regarding accuracy of outcome prediction, our composite model had a concordance index of 0.687. When ranked according to importance for prognosis, miR-511 expression was the most significant determinant among the random forest model parameters. To evaluate the reproducibility of our findings, we performed analyses in the publicly available TCGA dataset (Ley et al. NEJM 2013;368:2059). Eighty-eight CN-AML pts with miR expression and survival data were available in the TCGA cohort. As TCGA pts are not classified according to ELN risk groups, we could not directly reproduce the random forest-based cluster analysis. However, a univariable analysis showed that miR-511 and miR-628 expression levels were also prognostic in the TCGA dataset. Next, we evaluated whether the identified prognostic miRs have functional relevance in AML. We focused on miR-511, which was the most important determinant of our outcome predictor and has not been previously studied in AML. Among 6 AML cell lines tested, MV4-11 had the most abundant expression of miR-511. Functional silencing of miR-511 in MV4-11 cells decreased both their viability (as measured by Annexin-PI staining and flow-cytometry, P=.004) and proliferative capacity (as measured by WST1 reagent degradation, P<.001). Conclusion: Unbiased profiling of miRs using smRNA-seq has identified a novel set of 13 miRs with prognostic significance in CN-AML. MiR expression-based cluster status independently associates with clinical outcome of CN-AML pts. Our preliminary in vitro experiments have shown that miR-511, whose association with prognosis was the strongest among the newly identified prognostic miRs, is functionally relevant in AML. Disclosures Uy: Astellas: Consultancy; Pfizer: Consultancy; Curis: Consultancy; GlycoMimetics: Consultancy. Powell:Rafael Pharmaceuticals: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy, Research Funding; Janssen: Research Funding. Kolitz:Astellas: Research Funding; Boeringer-Ingelheim: Research Funding; Roche: Research Funding. Byrd:Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Genentech: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; BeiGene: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Acerta: Research Funding; BeiGene: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau.

Approximately 20% of CN-AML patients (pts) younger than 60 years treated with current standard intensive combination chemotherapy regimens have primary refractory disease, and among pts who achieve a complete remission (CR), over half relapse. Thus, early detection of pts with low likelihood of achieving a CR and those with a high likelihood of relapsing is of crucial importance. To identify molecular profiles associated with achieving and maintaining CR, we performed total transcriptome RNA sequencing and targeted DNA sequencing of 82 cancer- and leukemia-associated genes on pretreatment blood or bone marrow samples from 341 CN-AML pts less than 60 years old, similarly treated with intensive chemotherapy on Cancer and Leukemia Group B / Alliance for Clinical Trials in Oncology therapeutic trials. Pts who died within 30 days of diagnosis were excluded. Pts were classified into 3 mutually exclusive outcome groups: primary refractory (n=55, 16% of pts), pts who achieved a CR but later relapsed (n=165, 48%) and pts who remained in CR for the duration of this study (n=121, 35%). Gene-level differential expression analysis between the 3 groups was performed after removing low-expressed genes, and a set of 385 genes met significance criteria (adjusted P < 0.05 and at least 1.5-fold increase or decrease between 2 groups). Hierarchical clustering pts using these 385 genes revealed 5 distinct pt clusters (Figure A). There were significant differences between the 5 clusters in the proportions of pts in the 3 outcome groups (P<0.001, Figure B). Pts in cluster 1 (n=47 pts) almost all had bi-allelic CEBPA mutations (96%), and comparatively good outcome (all but one pt achieved a CR, and 49% achieved and maintained CR). In contrast, 94% of cluster 3 (n=69) pts harbored FLT3-internal tandem duplications (ITDs), and most pts either failed to achieve a CR (36%), or relapsed (51%). Cluster 2 (n=138) and cluster 4 (n=39) had intermediate outcomes compared to the other clusters (11% and 8% primary refractory pts, respectively; 40% and 51% pts who relapsed after CR, respectively). Notably, within cluster 2, there was a sub-cluster of 24 poor-risk pts who were less like to achieve CR and maintain CR compared to the rest of the cluster 2 pts (P<0.001). Within this sub-cluster 25% of pts were primary refractory, 63% relapsed after CR, and only 13% maintained CR. The sub-cluster was defined by upregulation of 47 genes, only 6 of which were protein coding (BCO2, CXCL3, HILPDA, SDR42E2, SNAI1, and ZAR1L), and 35 were long-non coding RNAs (lncRNAs). To our knowledge none of these lncRNAs have been previously associated with AML relapse. As there were no significant differences in mutations among the 82 sequenced genes between this poor risk sub-cluster and the rest of the pts in cluster 2, expression of these genes might be useful for defining a poor-risk group, independent of mutations. Finally, pts in cluster 5 (n=35) had a less distinct mutation pattern compared to other clusters. Most pts in cluster 5 did poorly. 23% were primary refractory and 67% achieved a CR then relapsed. Because no obvious mutations were detected that would drive this cluster, we performed gene set enrichment analysis (GSEA) for oncogenic signatures using the Broad Institute's GSEA and MSigDB software. Compared to the rest of the pts, those in cluster 5 were significantly enriched in genes shown to be downregulated by oncogenic KRAS expression (false discovery rate q<0.01). However, only one pt in cluster 5 and only 2% of pts in this study had KRAS mutations, and there was no difference in KRAS expression between cluster 5 pts and the rest of the cohort. Thus the observed GSEA differences in KRAS signaling are not due to KRAS mutations or expression changes, but are likely indirect effects of other genetic and epigenetic differences in the cluster 5 patients. Our study shows that expression analysis can identify different outcome groups in younger CN-AML pts. We identified clusters of AML pts with poor CR rates and high incidences of relapse not associated with recurrent gene mutations, who were characterized by upregulation of lncRNAs, or enriched in KRAS signaling gene sets. These may represent new poor-risk subsets of AML pts requiring alternative treatment strategies. Support: UG1CA23333801, U10CA180821, U10CA180882, U10CA180861, U24CA196171 ClinicalTrials.gov identifiers: NCT00048958 (8461), NCT00900224 (20202) https://acknowledgments.alliancefound.org Figure Disclosures Powell: Rafael Pharmaceuticals: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy, Research Funding; Janssen: Research Funding. Uy:Astellas: Consultancy; Pfizer: Consultancy; Curis: Consultancy; GlycoMimetics: Consultancy. Kolitz:Astellas: Research Funding; Boeringer-Ingelheim: Research Funding; Roche: Research Funding. Byrd:TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Acerta: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau.

The landscape of tuberculosis (TB) treatment is evolving rapidly, especially in the face of drug-resistant strains. This review explores the historical and contemporary developments in drug-susceptible TB (DS-TB) and multidrug-resistant TB (MDR-TB) therapies, with a focus on the emerging role of pan-TB strategies. Using a non-systematic literature review method, we analyzed peer-reviewed articles, clinical trial reports, and studies on DS-TB, MDR-TB, and pan-TB approaches published from January 2000 to December 2023. Our findings highlight significant advancements in TB therapies, including the WHO-endorsed four-month regimen for DS-TB and the all-oral BPaL/M regimen for MDR-TB. Pan-TB initiatives, such as the BPMZ regimen by TB Alliance and the Project to Accelerate New Treatments for Tuberculosis (PAN-TB), aim to develop universal regimens for both DS-TB and MDR-TB, showing promise in enhancing treatment efficacy and patient adherence. Continuous innovation and adaptable strategies are crucial in the fight against TB. Pan-TB approaches have the potential to effectively address both DS-TB and MDR-TB, and recent advancements underscore their importance. Future research should focus on extensive clinical trials to validate these strategies and explore innovative methods to improve treatment adherence and efficacy. This review provides valuable insights for clinicians and researchers, emphasizing the importance of developing and implementing effective, universally applicable pan-TB treatments, which are critical for improving patient outcomes and advancing global TB control efforts.

AML is a disease of the elderly. Patients aged ≥60 years (y) account for ~65% of all AML patients. However, while 40% of younger AML patients achieve long term survival, only 5-15% of older patients do. Especially given increasing availability of alternative treatment strategies the identification of patients who benefit from standard induction chemotherapy and those who do not is of crucial importance. The 2017 European LeukemiaNet Genetic Risk Classification (ELN GRC) provides guidance on genetic risk stratification of AML patients and is currently routinely used in clinical practice for both younger and older AML patients. The goal of our study was to test the performance of the 2017 ELN GRC in our cohort of 399 de novo AML patients aged ≥60 y (median: 69 y) which were similarly treated with cytarabine/daunorubicin-based chemotherapy on Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology protocols. Our cohort did not contain any patients with core-binding factor AML [i.e., with inv(16)/t(16;16) or t(8;21)]. We also aimed to identify additional molecular prognosticators in older AML patients. Utilizing the 2017 ELN GRC, 31%, 25% and 44% of patients were classified as Favorable (Fav), Intermediate (Int) and Adverse (Adv) risk, respectively. The median CR rates of 81% for Fav risk, 55% for Int risk and 39% for Adv risk separated patients in accordance with the ELN GRC groups (P<.001). However, there was no difference in disease-free (DFS) and overall survival (OS) rates for Int and Adv risk patients (3-year [3y] DFS, Int risk, 6%, Adv risk, 3%, P=.91; 3y OS; Int risk, 11%, Adv risk, 6%, P=.46). Fav risk patients had superior DFS and OS compared to both Int and Adv risk patients, but with 3y rates for DFS of 25% and OS of 29%, outcomes were still relatively poor. We next tested the prognostic impact of each 2017 ELN GRC marker in our patient cohort. Fav risk group patients with NPM1 mutations (NPM1mut) and either no FLT3-ITD or low FLT3-ITD allelic ratio (FLT3-ITDno/low) had a CR rate of 84%, while patients with biallelic CEBPAmut had a CR rate of only 54% (P=.02, Table 1). While 3y OS of NPM1mut/FLT3-ITDno/low was 31%, it was only 15% for patients with biallelic CEBPAmut (P=.13). Within Int risk patients the outcomes of NPM1mut patients with high FLT3-ITD allelic ratio (FLT3-ITDhigh) and NPM1 wildtype (NPM1wt)/FLT3-ITDno/low patients were equally dismal, and actually resembled those of NPM1wt/FLT3-ITDhigh patients (Table 1). All other patients with gene mutations classified as ELN Adv risk had poor outcomes (Table 1). Thus, the only genetic classification in 2017 ELN GRC that associated with favorable outcome in AML patients ≥60 years was NPM1mut/FLT3-ITDno/low, while biallelic CEBPAmut patients resembled more Int risk patients. NPM1mut/FLT3-ITDhigh, NPM1wt/FLT3-ITDno/low andNPM1wt/FLT3-ITDhighpatients all had CR rates in line with Int risk, but very poor DFS and OS. To potentially refine criteria used to classify patients, we performed outcome analyses of mutations co-occurring with NPM1mut on CR, DFS and OS. In addition to the known adverse impact of FLT3-ITDhigh, presence of DNMT3Amut was also associated with lower CR and OS in NPM1mut (CR, 85 vs 32%, P<.001; 3-yr OS rates, 15 vs 7%, P<.001) vs DNMT3Awt patients, resembling the outcomes of Adv risk patients. In contrast, NPM1mut patients that also harbored mutations in SRSF2 (n=18) had longer DFS and OS compared to NPM1mut/SRSF2wt patients (3-yr DFS rates, 44 vs 16%, P=.01; 3-yr OS rates, 50 vs 21%, P=.03). Thus, with the exception of the small subsets of NPM1mut/FLT3-ITDno/low and patients harboring both NPM1mut/SRSF2mut all evaluated subsets of AML patients had 3-y DFS and OS rates of <20%, indicating the need for early additional interventions in patients that achieve a CR. In summary, our data demonstrate the very poor DFS and OS of older AML patients treated with standard chemotherapy, despite the relatively high probability of achieving a CR. We show that the 2017 ELN GRC performs suboptimally to risk-stratify AML patients aged ≥60 years. NPM1mut/FLT3-ITDno/low status was the only current 2017 ELN GRC prognostic factor associated with improved outcomes in older AML patients. We identified NPM1/DNMT3A (which associated with shorter DFS+OS) and NPM1/SRSF2 (which associated with longer DFS+OS) as additional mutation combinations that might be useful for further group refinement. Disclosures Mims: Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Astellas Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: Membership on an entity's Board of Directors or advisory committees. Stone:Cornerstone Pharmaceuticals: Consultancy; Pfizer: Consultancy; Takeda: Other: Fees for serving on a data and safety monitoring board ; Astellas Pharma: Membership on an entity's Board of Directors or advisory committees; Stemline Therapeutics: Consultancy; Agios: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Fujifilm: Consultancy; Roche: Consultancy; Celator Pharmaceuticals: Consultancy; Ono Pharmaceutical-Theradex Oncology: Consultancy; Orsenix: Consultancy; Actinium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Arog Pharmaceuticals: Consultancy, Honoraria, Research Funding; Otsuka-Astex Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Celgene: Consultancy, Other: Fees for serving on a steering committee, and fees for serving on a data and safety monitoring board; Novartis: Consultancy, Research Funding; Argenx: Other: Fees for serving on a data and safety monitoring board ; AstraZeneca: Consultancy; MacroGenics: Consultancy; Jazz Pharmaceuticals: Consultancy. Powell:Rafael Pharmaceuticals: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Janssen: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy, Research Funding. Wang:Pfizer: Other: Advisory role, Speakers Bureau; Stemline: Other: Advisory role, Speakers Bureau; Jazz: Other: Advisory role; Astellas: Other: Advisory role, Speakers Bureau; celyad: Other: Advisory role; Abbvie: Other: Advisory role; Kite: Other: Advisory role; Daiichi: Other: Advisory role; Amgen: Other: Advisory role; Agios: Other: Advisory role. Kolitz:Boeringer-Ingelheim: Research Funding; Roche: Research Funding; Astellas: Research Funding. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Acerta: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Acerta: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding.

AbstractHappiness is a life’s goal for everyone. It also has an important role in the educational environment, especially for individuals who live in boarding schools. Happiness could escalate student’s motivation especially in learning and indirectly influence student’s activities while staying in boarding schools. The purpose of this study is to determine whether there are influences from religious orientation (intrinsic and extrinsic), hardiness (commitment, control, and challenge), and quality of friendship (stimulating companionship, help, intimacy, reliable alliance, self validation, and emotional security) towards the happiness of santri. This research involved 240 students from boarding schools in Bandung. The sampling technique used in this study is non probability sampling. The questionnaires for measuring happiness using OHI (Oxford Happiness Inventory), religious orientation using ROS (Religious Orientation Scale), hardiness using hardiness scale (how hardy are you?), and quality of friendship using MFQ FF (Mcgrill Friendship Questionnaire - Friend’s Functions). Confirmatory Factor Analysis (CFA) was used to test the validity of each item in the questionnaire from LISREL8.7 software. While statistical testing using multiple regression analysis of SPSS 17 software. Based on the results of the data analysis, there was a significant influence of religious orientation, hardiness, and quality of friendship on students' happiness. AbstrakKebahagiaan merupakan tujuan hidup bagi semua orang. Kebahagiaan juga memiliki peran penting dalam lingkungan pendidikan khususnya bagi individu yang tinggal di pondok pesantren. Dengan adanya kebahagiaan dapat meningkatkan motivasi belajar dan secara tidak langsung dapat mempengaruhi aktivitas yang dilakukan oleh para santri selama berada di pondok pesantren. Tujuan penelitian ini adalah untuk mengetahui apakah ada pengaruh dari orientasi religius (intrinsik dan ekstrinsik), hardiness (commitment, control, dan challenge), dan quality of friendship (stimulating companionship, help, intimacy, reliable alliance, self validation, dan emotional security) terhadap kebahagiaan santri. Penelitian ini dilakukan pada 240 santri pondok pesantren modern di Bandung. Teknik pengambilan sampel yang digunakan dalam penelitian ini adalah non probability sampling. Untuk alat ukur kebahagiaan menggunakan OHI (Oxford Happiness Inventory), orientasi religius menggunakan ROS (Religious Orientation Scale), hardiness menggunakan hardiness scale (how hardy are you?), dan quality of friendship menggunakan MFQ FF (Mcgrill Friendship Questionnaire - Friend’s Functions). Uji validitas alat ukur menggunakan teknik Confirmatory Factor Analysis (CFA) dengan bantuan software LISREL8.7. Sedangkan analisis data menggunakan teknik analisis regresi berganda dengan bantuan software SPSS 17. Berdasarkan hasil analisis data, diperoleh kesimpulan penelitian ada pengaruh yang signifikan orientasi religius, hardiness, dan quality of friendship terhadap kebahagiaan santri.

U.S. Grant was stumped: “The muddle down there is almost beyond my fathoming,” the president told the New York Herald in the summer of 1871. What had him flummoxed was the recently adjourned “Gatling Gun Convention” in New Orleans, a Republican state nominating gathering that reads like a passage from a novel by Gabriel Garcia Marquez. The run-up was punctuated by open combat in the trenches and foxholes of countless ward clubs and party conventions—the so-called “War of the Factions.” When the sitting Republican governor, the colorful and roguish Henry Clay Warmoth, hobbled by a boating accident earlier in the summer, led delegates supporting his candidacy to the designated meeting place inside the U.S. Customhouse on Canal Street, federal soldiers manning the latest in automatic weaponry turned him and his followers away when they tried to barge into a rival group's caucus. Warmoth thereupon guided his followers to another meeting hall. For the next 18 months, warring Republican factions moved in and out of opportunistic alliances with Conservative-Democrats. They divided into rival legislatures, used force to achieve quorums, and arrested and impeached their own senior leaders. If some of the more scurrilous allegations are to be believed, they even poisoned their lieutenant-governor. Were Louisiana politics on the verge of becoming “Mexicanized”—plunged into chronic crisis and political tumult? That was the question beginning to trouble Republican observers north of the Ohio River.

Background : Ibrutinib is the only once-daily Bruton's tyrosine kinase inhibitor with significant progression-free survival (PFS) benefit demonstrated in 5 randomized phase 3 studies in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) compared with standard-of-care chemotherapy and/or immunotherapy (RESONATE, RESONATE-2, iLLUMINATE, Alliance 041202, and ECOG 1912), and significant overall survival (OS) benefit in 3 of these studies. To understand how treatment with single-agent ibrutinib in earlier lines impacts patient outcomes, we evaluated long-term follow-up data from RESONATE and RESONATE-2 to compare efficacy and safety by number of prior lines of therapy. Methods : This integrated analysis included patients treated with single-agent ibrutinib in the first-line (RESONATE-2, NCT01722487) and relapsed/refractory (R/R; RESONATE, NCT01578707) settings. R/R patients were grouped by number of prior lines of therapy (1-2 vs ≥3). Patients with del(17p) were excluded from this analysis given their exclusion from RESONATE-2. Patients with high-risk prognostic features were defined as having TP53 mutation, del(11q), and/or unmutated IGHV. Outcomes included investigator-assessed PFS and objective response rate (ORR), OS, and safety. Results : This analysis of 271 patients included 136 patients in the first-line and 135 patients in the R/R groups (1-2 prior: n=68; ≥3 prior: n=67). Patients in the first-line group were older (median age [range], 73 years [65-89]) than those with 1-2 prior lines (65 years [30-86]) and ≥3 prior lines (67 years [44-83]). The proportion of patients with high-risk prognostic features was lower in the first-line group (first-line: 54%; 1-2 prior: 81%; ≥3 prior: 76%). Median follow-up was 59.8 months for first-line, 66.2 months for 1-2 prior, and 65.1 for ≥3 prior. Median PFS was not reached (NR) for first-line or 1-2 prior lines and was 40.1 months for ≥3 prior lines (Figure 1A). A greater proportion of patients treated with ibrutinib in earlier lines remained progression-free or alive at 60 months (first-line: 70%; 1-2 prior: 60%; ≥3 prior: 33%). First-line treatment resulted in a 34% reduction in risk of disease progression or death compared to 1-2 prior lines (HR: 0.66 [95% CI, 0.40-1.09]). PFS was significantly prolonged for first-line vs ≥3 prior lines (HR: 0.32 [95% CI, 0.21-0.49]) and 1-2 prior vs ≥3 prior lines (HR: 0.48 [95% CI, 0.30-0.77]). For patients with high-risk prognostic features, median PFS was NR for first-line or 1-2 prior lines and was 42.5 months for ≥3 prior lines (Figure 1B); treatment in earlier lines resulted in better PFS for these patients (first-line vs 1-2 prior, HR: 0.64 [95% CI, 0.35-1.18]; first-line vs ≥3 prior, HR: 0.33 [95% CI, 0.19-0.57]; 1-2 prior vs ≥3 prior HR: 0.51 [95% CI, 0.30-0.87]). Median OS for the overall population was NR (range, 0.10+-66.04+) for first-line, NR (5.98-71.56+) for 1-2 prior, and 67.4 months (1.15-69.78+) for ≥3 prior lines. The ORR was 91%, 94%, and 82% for first-line, 1-2 prior, and ≥3 prior lines, respectively. The CR rate (CR+CR with incomplete marrow recovery) was highest for the first-line group (first-line: 30%; 1-2 prior: 12%; ≥3 prior: 10%). At the time of analysis, 58% of patients remain on ibrutinib treatment in the first-line group. Prior to study closure, 38% of patients with 1-2 prior and 18% of patients with ≥3 prior lines remained on ibrutinib treatment. In the overall population, 8 patients (6%) in the first-line group discontinued due to progressive disease while it was the most common reason for discontinuation for patients with 1-2 (n=15, 22%) and ≥3 prior lines (n=25, 37%). Across all three groups, 52 patients (19%) discontinued due to adverse events (AEs) (first-line: n=29, 21%; 1-2 prior: n=13, 19%; ≥3 prior: n=10, 15%). AEs leading to dose reduction occurred in 20% of first-line, 13% of 1-2 prior, and 22% of ≥3 prior lines. Conclusions : Overall, this integrated analysis of data with up to 6 years of long-term follow-up demonstrates that using single-agent ibrutinib in earlier lines of treatment results in better PFS, OS, and ORR with sustained efficacy for patients with CLL, including patients with high-risk prognostic features. During this extended follow-up, only 6% of patients treated in the first-line setting discontinued due to progressive disease. Ibrutinib was well tolerated with only 19% of patients across all lines of therapy discontinuing due to AEs. Disclosures Barr: Gilead: Consultancy; Verastem: Consultancy; Seattle Genetics: Consultancy; AbbVie: Consultancy; Pharmacyclics LLC, an AbbVie company: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Celgene: Consultancy; Merck: Consultancy; Genentech: Consultancy; Janssen: Consultancy; Astra Zeneca: Consultancy, Research Funding. Tedeschi:Janssen spa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Consultancy; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; SUNESIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Honoraria; AstraZeneca: Membership on an entity's Board of Directors or advisory committees. Munir:AbbVie: Honoraria; Alexion: Honoraria; Gilead: Honoraria; Janssen: Honoraria; Novartis: Honoraria; Roche: Honoraria; Morphosys: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sunesis: Consultancy; Pharmacyclics: Other: TBC; Acerta: Membership on an entity's Board of Directors or advisory committees. Hillmen:Acerta: Membership on an entity's Board of Directors or advisory committees; Apellis: Research Funding; Gilead: Research Funding; Roche: Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding. Woyach:Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Loxo: Research Funding; Morphosys: Research Funding; Verastem: Research Funding. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Ohio State University: Patents & Royalties: OSU-2S; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; BeiGene: Research Funding. Ghia:ArQule: Consultancy, Honoraria; BeiGene: Consultancy, Honoraria; Juno/Celgene: Consultancy, Honoraria; Dynamo: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Acerta/AstraZeneca: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Novartis: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy. Mulligan:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Participant, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Participant, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Other: Clinical Trial participant, Research Funding, Speakers Bureau; Commonwealth Serum Laboratories (CSL): Other: Clinical Trial participant; Sanofi-Aventis: Other: Clinical Trial participant; Acerta: Other: Clinical Trial participant. Dai:AbbVie: Equity Ownership; Celgene: Equity Ownership; Exelixis: Equity Ownership; Gilead: Equity Ownership; GSK: Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment. Amaya-Chanaga:AbbVie: Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment. Dean:AbbVie: Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment. o'Brien:Pfizer: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy; Acerta: Research Funding; Alexion: Consultancy; Amgen: Consultancy; Aptose Biosciences, Inc: Consultancy; Astellas: Consultancy; Celgene: Consultancy; Eisai: Consultancy; Gilead: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Kite: Research Funding; Janssen: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Regeneron: Research Funding; Sunesis: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; Verastem: Consultancy.

Introduction: DARA, a human IgGκ monoclonal antibody targeting CD38, is approved as monotherapy and in combination with standard-of-care regimens for relapsed/refractory multiple myeloma and NDMM. In the primary analysis of the phase 2 GRIFFIN study (NCT02874742) in patients with transplant-eligible NDMM, DARA plus RVd (D-RVd) significantly improved rates of stringent complete response (sCR) by the end of post-transplant consolidation therapy versus RVd (Voorhees P, Blood 2020). Here, we present updated efficacy and safety results following 12 months of maintenance therapy with lenalidomide (R) or DARA plus R (D-R). Methods: Patients with NDMM eligible for high-dose therapy (HDT) and autologous stem cell transplant (ASCT) were randomized 1:1 to RVd ± DARA, stratified by ISS stage and creatinine clearance rate. Patients received 4 induction cycles, HDT, ASCT, 2 consolidation cycles, and maintenance with R ± DARA for 24 months. During induction and consolidation, patients received R 25 mg PO on Days 1-14; V 1.3 mg/m2 SC on Days 1, 4, 8, and 11; and d 40 mg QW every 21 days. DARA 16 mg/kg IV was given on Days 1, 8, and 15 of Cycles 1-4 and Day 1 of Cycles 5-6. During maintenance (Cycles 7-32), patients received R 10 mg (15 mg in Cycles 10+ if tolerated) on Days 1-21 every 28 days ± DARA 16 mg/kg IV Q8W (or Q4W per patient decision after Amendment 2). The primary endpoint was rate of sCR at the end of post-ASCT consolidation per IMWG criteria, evaluated by a validated computer algorithm. Key secondary endpoints included progression-free survival (PFS) and rate of minimal residual disease (MRD) negativity (10-5 threshold per IMWG criteria) assessed by next-generation sequencing (clonoSEQ; Adaptive Biotechnologies). The primary hypothesis was tested at a 1-sided alpha of 0.10. All secondary analyses were evaluated using a 2-sided P value (alpha 0.05) and were not adjusted for multiplicity. Results: In total, 207 patients were randomized (D-RVd, n=104; RVd, n=103). Baseline demographics and disease characteristics were well balanced between arms. At the end of post-transplant consolidation (median follow-up, 13.5 months) in the response-evaluable population, the sCR rate favored D-RVd versus RVd (42.4% [42/99] vs 32.0% [31/97]; 1-sided P=0.0680). With additional D-R or R maintenance therapy, responses continued to deepen and remained higher for the D-RVd group versus the RVd group. At the 12-months-of-maintenance therapy data cut (median follow-up, 26.7 months), the sCR rate still favored D-RVd versus RVd (63.6% [63/99] vs 47.4% [46/97], 2-sided P=0.0253; Figure). MRD-negativity (10‒5) rates in the ITT population favored D-RVd versus RVd (62.5% [65/104] vs 27.2% [28/103], P&lt;0.0001; Figure), as well as among patients who achieved complete response (CR) or better at that time (76.5% [62/81] vs 42.4% [25/59], P&lt;0.0001). Similarly, MRD-negativity (10‒6) rates favored D-RVd versus RVd in the ITT population (26.9% [28/104] vs 12.6% [13/103], P=0.0140; Figure), as well as among patients who achieved CR or better at that time (34.6% [28/81] vs 18.6% [11/59], P=0.0555). Estimated 24-month PFS rates were 94.5% and 90.8% for the D-RVd and RVd groups, respectively. In total, 14 deaths occurred (n=7 per group), and 9 were due to progressive disease (D-RVd, n=5; RVd, n=4). With longer follow-up, no new safety concerns were observed. 84.8% (84/99) of patients in the D-RVd group and 79.4% (81/102) in the RVd group had grade 3/4 treatment-emergent adverse events (TEAEs). One grade 5 TEAE occurred in the RVd group, which was unrelated to study therapy (unknown cause). Infusion-related reactions occurred in 43.4% (43/99) of patients, with the majority being grade 1 or 2 and occurring in the first cycle. Conclusions: After 26.7 months of median follow-up, the addition of DARA to RVd induction and consolidation, followed by D-R maintenance in patients with transplant-eligible NDMM continued to demonstrate deep and improved responses, including higher sCR and MRD negativity rates, compared with lenalidomide alone. Maintenance therapy increased sCR and MRD negativity rates, compared to post-consolidation rates. No new safety concerns were observed with longer follow-up. Support: Alliance Foundation Trials; https://acknowledgments.alliancefound.org; Janssen Oncology Disclosures Kaufman: Tecnopharma: Consultancy, Honoraria; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria; Sanofi/Genyzme: Consultancy, Honoraria; AbbVie: Consultancy; Amgen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees. Sborov:University of Utah: Current Employment; Celgene, Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees. Reeves:Incyte: Honoraria; Takeda: Honoraria; Bristol Myers Squibb: Speakers Bureau. Rodriguez:BMS, Takeda, Amgen: Consultancy, Speakers Bureau. Chari:Janssen, Celgene, Novartis, Amgen, Bristol-Myers Squibb, Karyopharm, Sanofi, Genzyme, Seattle Genetics, Oncopeptides, Millennium/Takeda, Antengene, Glaxo Smith Kline, Secura Bio: Consultancy; Janssen, Celgene, Novartis, Amgen, Pharmacyclics, Seattle Genetics, Millennium/Takeda: Research Funding. Silbermann:Karyopharm: Consultancy; Janssen: Consultancy; Sanofi-Aventis: Consultancy, Research Funding. Costa:AbbVie: Consultancy; Sanofi: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Genentech: Consultancy; BMS: Consultancy, Honoraria. Anderson:Amgen: Consultancy, Honoraria, Research Funding; GSK: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding. Shah:GSK, Amgen, Indapta Therapeutics, Sanofi, BMS, CareDx, Kite, Karyopharm: Consultancy; BMS, Janssen, Bluebird Bio, Sutro Biopharma, Teneobio, Poseida, Nektar: Research Funding. Efebera:Pharmacyclics: Research Funding; Ohio State University: Current Employment; Celgene: Research Funding; Takeda: Honoraria, Speakers Bureau. Holstein:Sorrento: Consultancy; Adaptive Biotechnologies: Consultancy; Takeda: Consultancy; GSK: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy, Research Funding. Costello:Takeda, Celgene: Consultancy, Honoraria. Jakubowiak:Adaptive, Juno: Consultancy, Honoraria; AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Wildes:Seattle Genetics: Consultancy; Carevive Systems: Consultancy; Janssen: Research Funding. Orlowski:Founder of Asylia Therapeutics, Inc., with associated patents and an equity interest, though this technology does not bear on the current submission.: Current equity holder in private company, Patents & Royalties; STATinMED Research: Consultancy; Sanofi-Aventis, Servier, Takeda Pharmaceuticals North America, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen, Inc., AstraZeneca, BMS, Celgene, EcoR1 Capital LLC, Forma Therapeutics, Genzyme, GSK Biologicals, Ionis Pharmaceuticals, Inc., Janssen Biotech, Juno Therapeutics, Kite Pharma, Legend Biotech USA, Molecular Partners, Regeneron Pharmaceuticals, Inc.,: Honoraria, Membership on an entity's Board of Directors or advisory committees; Laboratory research funding from BioTheryX, and clinical research funding from CARsgen Therapeutics, Celgene, Exelixis, Janssen Biotech, Sanofi-Aventis, Takeda Pharmaceuticals North America, Inc.: Research Funding. Shain:BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; AbbVie: Research Funding; GlaxoSmithKline: Speakers Bureau; Adaptive: Consultancy, Honoraria; Sanofi/Genzyme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Speakers Bureau; Karyopharm: Research Funding, Speakers Bureau; Amgen: Speakers Bureau. Cowan:Nektar: Research Funding; Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Bristol-Myer Squibb: Research Funding; Celgene: Consultancy, Research Funding; Cellectar: Consultancy; Sanofi-Aventis: Consultancy. Lutska:Janssen: Current Employment. Bobba:Janssen: Current Employment. Pei:Janssen: Current Employment, Current equity holder in publicly-traded company. Ukropec:Janssen: Current Employment, Current equity holder in publicly-traded company. Vermeulen:Janssen: Current Employment, Current equity holder in publicly-traded company. Lin:Janssen Scientific Affairs: Current Employment, Current equity holder in publicly-traded company. Richardson:Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Voorhees:TeneoBio: Other: Advisory Board; Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy; Janssen: Other: Advisory Board; GSK: Honoraria; BMS: Other: Advisory Board; Adaptive Biotechnologies: Other: Advisory Board. OffLabel Disclosure: The specific regimen combination is not yet approved, but individual components are.

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AbstractBackgroundBlack, Indigenous, and other people of color are at greater risk of developing Alzheimer’s disease and related dementias (ADRD). These individuals are less likely than non‐Hispanic whites to have access to ADRD‐ related resources, thus promoting health disparities.MethodIn 2022, the Alliance for Diversity in Brain Health for the Central Ohio Community (ADHOC) was created to fill this gap. Through grass roots efforts from the College of Nursing, the African American Alzheimer’s and Wellness Association teamed up with the Central Ohio Alzheimer’s Association. With leadership support from the National Alzheimer’s Association, we identified strengths, opportunities for collaboration, and long and short‐term goals to meet the needs of the Central Ohio ADRD community. Monthly meetings were held with a core group of four members to establish a community‐driven agenda for education, support, and research.ResultTo date, ADHOC results included a) grant‐funded, inaugural Annual Brain Health Fair with 14 local partnering agencies, b) five ADRD education presentations in five minoritized communities, and c) six research collaborations.ConclusionOur alliance provides a template that can scaled for use in communities globally to build bridges and promote health equity in ADRD communities through education, support and research.

ABSTRACT Jordan Beach received his Bachelor's degree from Mount Union University, Alliance, Ohio, before joining the laboratory of Thomas Egelhoff at Case Western Reserve University and Cleveland Clinic Foundation, Cleveland, Ohio for his PhD. He moved to the National Heart Lung and Blood Institute at the National Institutes of Health in Bethesda, Maryland for his postdoctoral training with John Hammer to use high-resolution imaging to explore myosin II assembly dynamics with the aid of a Lenfant Biomedical Research Fellowship and K22 Career Transition Award. In 2017, Jordan became an Assistant Professor at the Department of Cell and Molecular Physiology at Loyola University Chicago, USA. Patrick Oakes received his Bachelor's degree from Boston College, and his PhD in Physics from Brown University in the laboratory of Jay Tang. He did his postdoctoral work with Margaret Gardel at the Institute for Biophysical Dynamics and the James Franck Institute at the University of Chicago studying how cells sense and generate forces. In 2016 he started his own lab as an Assistant Professor of Physics at the University of Rochester, and in 2019 moved to the Department of Cell and Molecular Physiology at Loyola University Chicago, USA. In 2022 he was promoted to Associate Professor.

The turbomachinery industry continually struggles with the adverse effects of contact rubs between airfoils and casings. The key parameter controlling the severity of a given rub event is the contact load produced when the airfoil tips incur into the casing. These highly nonlinear and transient forces are difficult to calculate and their effects on the static and rotating components are not well understood. To help provide this insight, experimental and analytical capabilities have been established and exercised through an alliance between GE Aviation and The Ohio State University Gas Turbine Laboratory. One of the early findings of the program is the influence of blade flexibility on the physics of rub events. The focus of this paper is to quantify the influence of airfoil flexibility through a novel modeling approach that is based on the relationship between the applied force duration and maximum tip deflection. Results from the model are compared with experimental results, providing sound verification.

The Liberal Democratic Party (LDP) won the Lower House Elections, held on October 31, 2021. The Japanese Party obtained an undisputed victory after a year of harsh criticism addressed to the Suga Cabinet, run by the then LDP party chief, for his ineffective management of the Pandemic crisis. How can the long and almost unchallenged rule of the LDP over Japanese politics, from its foundation in 1955 to the last electoral success, be explained? This paper addresses the topic from an historical perspective, focusing on dr. Akai Ohi’s political campaign in the last General elections. Dr. Ohi (1980) is a Japanese political scientist who ran as a candidate for the Constitutional Democratic Party, the main opposition party, in the second constituency of Hiroshima Region, one of the LDP historical strongholds. The cornerstone of his political campaign was the establishment of the electoral alliance with the Communists in his constituency. The dialogue with dr. Ohi reported in this article explores his experience as a candidate and his analysis as a political scientist.

We describe the new association Lycopo lucidi–Alnetum japonicae Korznikov, Verkholat & Krestov 2021 ass. nov. of the Alnus japonica swampy forests of the coastal plains and river valleys in the south of the Primorye Territory of Russia. The association includes two subassociations: Lycopo lucidi–Alnetum japonicae typicum Korznikov, Verkholat & Krestov 2021 subass. nov. and the preliminary delineated Lycopo lucidi–Alnetum japonicae betuletosum davuricae subass. prov. developing on gently sloping foothills with a lateral inflow of moisture and is transitional to zonal broad-leaved forests of the class Quercetea mongolicae Song ex Krestov et al. 2006. The association is classified to the alliance Fraxino–Alnion japonicae Miyawaki et al. 1977 described from Japan and belonging to the order Alnetalia japonicae Miyawaki et al. 1977 and the class Alnetea japonicae Miyawaki et al. 1977. We also validate the name of the association Stellario longifoliae–Alnetum japonicae Ohno in Miyawaki 1988 nom. inval. (art. 5) from Hokkaido Island, Northern Japan.

Economy vs. ecology. That’s one way to frame the debate that once raged in Youngstown, Ohio, between those who focused on the health of the Mahoning River and those who gave priority to the health of the local economy and the jobs it provided. The latter point of view was often stated in terms of ‘Jobs, not fish!’ and its proponents asked: Compared to jobs in steel mills, which make it possible for workers to have homes and a decent way of life, what does it matter that fish can’t live in the river? Initially, the steel industry benefitted a surprisingly small number of people, mostly owners and investors who treated workers as a resource to be exploited, much like the air and water. But later, thanks to union struggles, workers lived well in the Mahoning Valley, and environmental problems, such as a dirty river, were viewed as a necessary evil. In fact, the foulness of the river assured residents that the mills were going strong and were a source of prosperity. In Youngstown today, deindustrialization has made economic insecurity a fact of life, and the Mahoning, once known as the dirtiest river in the United States, is home to many species of fish. The story of the changes that have taken place in the river landscape centers around the supposed incompatibility of having both jobs along the river’s banks and fish in its waters. Ideas from cultural geography can teach us how to view a landscape where so much conflict has played out. When geographer James S. Duncan presented the idea of a landscape as texts which communicate and transmit information, he also argued that reading the landscape can reveal how power relations have played out in a given region. Sherry Lee Linkon and John Russo built on similar notions in Steeltown USA: Work and Memory in Youngstown as they showed how people's memories, experiences, and struggles are represented in the landscape. Linkon & Russo also noted that conflict and landscape have a reciprocal relationship. ‘Landscapes not only are constructed by economic and social conflict,’ they stated, ‘but also reinforce such divisions of power.’ ( Linkon & Russo, 2002, pp. 15-16). Such a reading of the Mahoning River landscape yields a complex story about the ways people transformed the natural world in order to benefit from it and then lived with the environmental consequences of that transformation. Though this story is very much about how power and class relations have played out there, in the twentieth century such conflict was often overshadowed by tensions between advocates for steel workers and advocates for the river. Recently, however, the growing understanding of the concept of environmental justice, which has been applied to working-class issues by, among others, Christina Robertson & Jennifer Westerman in their call for a working-class ecology (Robertson & Westerman, 2015) and Karen Bell in her agenda for a just transition to sustainability (Bell, 2020), lays the groundwork for alliances between environmentalists and working-class people that were not present when the Mahoning River was an ‘industrial stream.’ Cultural geographers have also shown us that depictions of a landscape contribute to its meaning(s). Building on such ideas, Linkon & Russo examined the landscape of Youngstown through the lens of images and stories, and this essay will view the more specific landscape of the Mahoning River by examining a dozen images created in or near Youngstown since the early twentieth century. Not all of these images depict the river itself, yet all help to clarify the way the conflict between economy and ecology has played out in the Mahoning Valley.

Current economic, social, and environmental trajectories within most world regions are unsustainable. Interaction between bottom-up initiatives and top-down good governance is essential to change them. The One Health movement, made up of many organizations, groups, and individuals from diverse backgrounds and disciplines, seeks to redress the present trajectories but has lacked coordination and cooperation, limiting its effectiveness to date. We take a snapshot of groups/organizations working to promote One Health, explore options to increase cooperation and coordination among global One Health stakeholders, and propose systemic strategies that could positively impact animals, people, the planet, plants, and politics.Methods: Through a review of the compilation of Who’s Who in One Health organizations on the One Health Commission’s (OHC) website and the list of organizations that have pledged support for One Health listed on the One Health Initiative (OHI) website, 289 organizations were identified (as of 29 July 2022: 126 Civil Society Organizations, 133 academic and 30 governmental organizations). A stratified sampling approach and MAXQDA 2022 were used in a mixed-methods analysis to select a sample (N=50) of organizations to evaluate with 10 questions on purpose & focus, structure & transparency, cooperation & implementation, and publications. Results: The words “One Health” appeared in the organizations’ names on 62.0% (N=31) of websites examined, most often those in academic settings (78.2%). As regards transparency of the organizational structures, membership was defined in 70.0% (N=35), again most often by academic organizations (82.6%). Members of the governing structures were named on 34.0% of organizational websites. Projects led in the last two years were described on 32.0%, and cooperation with other organizations was indicated on 64.0% of websites examined. Relevant publications and annual reports were listed on 46.0% and 24.0% of probed websites, respectively. Ranking the number of positive findings for each of the 50 organizations examined revealed that full information for all ten questions was provided by only 4 academic and 1 governmental organization.The OHC website was used as a starting point and thus was not included in the N=50 samples. It was therefore examined as an example of a Non-Profit / CSO working to support bottom-up One Health leadership. Since 2014 the OHC has supported a Global One Health Community listserv of individuals from around the globe. The analysis revealed a dominance of Directors from the US and a high proportion of organizations included on the OHC Who’s Who in One Health organizations webpage were located in North America. The social sciences - sociology and economics in particular – were underrepresented among in its leadership. Conclusion: These 10 questions may not have been fully appropriate for all organizations examined in academic or government settings versus stand-alone non-profit or civil society organizations. However, an examination of the 50 selected websites of organizations working to implement One Health and/or framing their projects and purpose in One Health revealed the global One Health movement to be fragmented and uncoordinated. The authors propose to form a more unified voice for One Health across the international One Health movement, a fully networked, informal global One Health alliance or community of practice that can coordinate sharing of information among the networks and with the general public, and that is able to seek synergies and joining of hands in collective/collaborative actions to effectively and efficiently promote and support bottom-up efforts.