High Defect Rates Research Articles

Folate fortification for spina bifida: preventing neural tube defects.

Neural tube defects (NTDs), such as spina bifida and anencephaly, are severe congenital anomalies affecting the development of the brain and spine. These conditions are often linked to folic acid deficiency during early pregnancy, a modifiable risk factor. While high-income countries have implemented mandatory folic acid fortification in staple foods, resulting in significant reductions in NTD prevalence, low- and middle-income countries (LMICs) continue to experience disproportionately high rates of these birth defects. Folic acid supplementation and fortification are proven interventions for preventing NTDs, but many LMICs face political, financial, and logistical barriers to implementing these programs. This paper highlights the importance of mandatory folic acid fortification as a cost-effective public health intervention and advocates for its expansion in LMICs. It reviews the successes of fortification programs in high-income countries, explores alternative food vehicles like rice for regions with different dietary staples, and discusses the potential of multi-nutrient fortification strategies. Additionally, this paper emphasizes the need for global collaboration, enhanced monitoring and evaluation, and public health education campaigns to ensure that women of reproductive age, especially in LMICs, receive adequate folic acid. By addressing these challenges, the global health community can significantly reduce the incidence of NTDs, improve maternal and child health, and promote health equity worldwide. The time to act is now, as the benefits of folic acid fortification far outweigh the costs of inaction.

Genomic testing identifies monogenic causes in patients with very early-onset inflammatory bowel disease: a multicenter survey in an Iranian cohort.

Patients with very early-onset inflammatory bowel disease (VEO-IBD) may present because of underlying monogenic inborn errors of immunity (IEI). Strong differences have been observed in the causes of monogenic IBD among ethnic populations. This multicenter study was carried out on 16 Iranian patients with VEO-IBD. We reviewed clinical and basic immunologic evaluation including flow cytometry and immunoglobulin levels. All patients underwent clinical whole exome sequencing (WES). Sixteen patients (8 females and 8 males) with a median age of 43.5 months were enrolled. The median age at the onset of symptoms was 4 months. Most patients (12, 75%) had consanguineous parents. Chronic non-bloody diarrhea (13, 81.3%) and perianal diseases including perianal abscess (6, 37.5%), anal fissure (6, 37.5%), or anal fistula (2, 12.5%) were the most common manifestations. WES identified a spectrum of genetic variants in 13 patients (81.3%): IL10RB (6, 37.5%), MVK (3, 18.8%), and CASP8, SLC35C1, G6PC3, and IKBKB in 1 patient, respectively. In 3 patients (18.7%), no variant was identified. Flow cytometry identified a spectrum of abnormalities that helped to assess the evidence of genetic diagnosis. At the end of the survey, 3 (18.8%) patients were deceased. This high rate of monogenic defects with a broad spectrum of genes reiterates the importance of investigating IEI in patients with infantile-onset IBD.

Solusi Berkelanjutan untuk Perbaikan Kualitas Innerbox di PT. BKI Surabaya

Surabaya is the center of a growing manufacturing industry that always strives to improve the quality of its products. One company that faces serious problems is PT. BKI, which faces a high rate of innerbox defects with potential negative impact on product quality. The study used Six Sigma methodology to identify and address the root cause of innerbox defects within two months. The results of the analysis show that the main causes of innerbox defects include structuring, material, management, environmental problems, as well as improper assembly methods. The proposed solution involves the use of duplex-type cardboard materials, improved assembly techniques, regular machine maintenance, and environmental control. The use of stripping bands instead of duct tape on innerbox packaging is an effective improvement. The implementation of control for two months showed an increase in sigma value from 2.94 to 2.83. The Six Sigma approach is proven to provide a systematic analytical foundation for significant improvement. The results help PT. BKI in improving quality, efficiency, and customer satisfaction

Implementation of DMAIC for Production Quality Control: Case Study of Power Supply Production in Indonesia

The level of competition in the manufacturing industry is getting tougher, making companies must be able to provide the best service to customers. One of the companies in Indonesia engaged in asset monitoring and ship navigation systems, has a production division that produces power supply products. Based on the analysis that has been carried out at the company that there are problems such as a damaged PCB connector that makes the product categorized as a manufacturing defect. This research aims to be able to find alternative improvements to production processes that have a high defect rate. The Define, Measure, Analyze, Improve, and Control (DMAIC) framework is used as a method to shape the mindset of management and employees to be able to solve these problems. Based on this framework, three causes of the problem were found, namely human factors, materials, and inappropriate methods during the production process. Therefore, appropriate corrective actions are taken, and a control process is carried out by comparing control charts, Defects Per Million Opportunities (DPMO) and sigma levels to determine the impact of changes from the improvements made. Quantitatively, there was an increase in the DPMO value of 39.47% and an increase in the sigma level of 8.64%. This shows that the DMAIC framework can provide the right solutions and preventing the same quality problems from happening again.

STRATEGI PENGENDALIAN KUALITAS PRODUK BUMBU TABUR MENGGUNAKAN METODE TAGUCHI

The high defect rate in the powdered seasoning product produced at PT ABC serves as the main reason for this research. The study aims to determine the factors influencing the quality of the seasoning product using the Taguchi method. The analysis conducted identified two levels and three significant factors. These factors include the number of briefing sessions for operators, the intensity of packing machine maintenance, and the determination of sample size in quality control. After experimentation, this research concludes that the optimal conditions for seasoning production involve conducting two briefing sessions for operators, performing machine packing maintenance twice, and taking quality control samples 332 times. The use of 332 samples is based on the minimum sample size required using a statistical approach with a 95% confidence level. The analysis results indicate that machine maintenance has the greatest impact on the quality of the seasoning product, contributing approximately 23.02% at the first level. The number of operator briefings contributes about 7.91% at the second level, while quality control contributes approximately 5.62% at the second level. This research highlights the importance of considering the number of operators briefing sessions, the frequency of packing machine maintenance, and the method used to determine the sample size in quality control when producing seasoning products. By applying the Taguchi method, it is possible to identify the optimal levels for these three factors to produce high-quality seasoning products.

Enhancing Quality Control of Packaging Product: A Six Sigma and Data Mining Approach

This study explores the application of Six Sigma and data mining methodologies to address the high defect rate in the packaging of Wardah Lightening Powder Foundation. Faced with quality control challenges, the research aims to systematically identify the root causes of packaging defects and develop strategic measures to enhance product quality. Employing a comprehensive Six Sigma approach, the study incorporates various analytical tools, including SIPOC diagrams, Critical-to-Quality (CTQ) characteristics, control charts, Pareto diagrams, and Failure Modes and Effects Analysis (FMEA). These tools facilitate a detailed investigation of the packaging process, highlighting significant failure types and inefficiencies. The research methodology involves an extensive data collection and analysis phase, utilizing data mining techniques to delve into historical defect data. This analysis uncovers underlying patterns and correlations that contribute to packaging failures. Based on these findings, the study proposes targeted interventions to mitigate defect levels. These interventions include the implementation of alarm systems and buzzers on production lines to promptly address issues, and the redesign of ink storage labels for clearer communication and error reduction. The outcomes of this study demonstrate a substantial improvement in packaging quality, evidenced by a marked reduction in defect rates. This enhancement not only contributes to operational efficiency but also plays a crucial role in elevating customer satisfaction levels. The research underscores the effectiveness of integrating Six Sigma with data mining in identifying, analyzing, and resolving quality issues in manufacturing processes. It provides valuable insights for organizations in the packaging industry seeking to optimize their quality control mechanisms and achieve higher standards of product excellence.

Reducing Power Dissipation in Memory Repair for High Fault Rates

Reducing Power Dissipation in Memory Repair for High Fault Rates

Study of metabolism and potential toxicity of nine synthetic opioid analogs using the zebrafish larvae model.

The use of novel psychoactive substances (NPSs) has dramatically increased worldwide, and among them, synthetic opioids are one of the fastest growing groups, where cinnamylpiperazines and 2-benzylbenzimidazoles represent two of the most relevant subclasses. However, the data on their toxicity and metabolism are still limited. The aim of the present study was to evaluate the toxicity and metabolic pathways of some compounds belonging to these families, namely, AP-237, 2-methyl AP-237, isotonitazene, flunitazene, etodesnitazene, metonitazene, metodesnitazene, N-pyrrolidino etonitazene, and butonitazene. The study was performed using a zebrafish early life stages model. In fact, zebrafish (Danio rerio) embryos and larvae have recently been recognized as a suitable animal model in alternative to mammals, because they require less time and resources and do not need complex procedures for ethics approval. The cellular toxicity after a single administration was assessed at the fourth day post-fertilization with acridine orange staining. Possible morphological defects were evaluated with a light microscope after 24 h of exposure to 1μmol/L concentration of each drug. Subsequently, the larvae were euthanized and underwent analysis of drug metabolites using UPLC coupled to an Orbitrap high-resolution mass spectrometer. High rates of morphological defects, as well as of cellular death, were detected, but no significant difference in mortality between treatment and control groups was observed. In addition, several metabolites, mainly produced through monohydroxylation, N-dealkylation, and O-dealkylation, were identified in the larvae extracts.

Research on Lean Improvement of a Powder Production Line Based on Contradiction Analysis

The intelligent improvement of production and manufacturing plays an important role in providing automated production for a company. In response to the problems of low production efficiency, high defect rate, and slow mold change in a certain company’s powder production site, this study combines the ideas of quality management and lean improvement, and analyzes the equipment utilization and production capacity through methods such as contradiction analysis, process function analysis, and fishbone diagram, By using Flexsim simulation and analytic hierarchy process, an optimization plan was obtained, which shortened the processing time and mold change time, improved the production capacity of the production line, and provided specific solutions and new ideas for the company’s production and operation. This helps to improve the technical performance of process oriented manufacturing production.

Foot Strike Run Retraining forPatients With Patellofemoral Chondral Defects: A Case Series.

Military service members (SMs) demonstrate high rates of patellofemoral chondral defects (PFCDs) that are difficult to diagnosis and, if untreated, result in a cascade of events eventually leading to osteoarthritis. Running is an essential occupational task for SMs; however, there is little evidence regarding techniques to maintain running ability in individuals with cartilage defects. The purpose of this case series was to assess the clinical application of foot strike run retraining in patients with PFCDs. This case series included two active duty U.S. Marine Corps SMs who presented to outpatient physical therapy with PFCD, diagnosed via MRI. Both patients attended eight foot strike run retraining sessions. Running mechanics and patient-reported outcomes were recorded pre-training, post-training, and at a 1-month follow-up visit. Both patients successfully converted their strike pattern from a rearfoot to a non-rearfoot strike pattern with training and retained this strategy at 1-month follow-up. Post-intervention, both patients demonstrated increased running tolerance, and improvements in Numeric Pain Rating Scale and Lower Extremity Functional Scale scores. Biomechanical analysis showed that both patients demonstrated a 63% to 70% reduction in average and peak vertical ground reaction force loading rates post-treatment. Modification of foot strike pattern from rear to non-rearfoot strike during running for individuals with PFCD can reduce the magnitude of impact loading, which potentially limits disease progression. These findings suggest that foot strike run retraining may be a feasible strategy to reduce pain and improve function in SMs with PFCD who are required to run for occupational responsibilities.

Real-Time Optical Detection of Artificial Coating Defects in PBF-LB/P Using a Low-Cost Camera Solution and Convolutional Neural Networks

Additive manufacturing plays a decisive role in the field of industrial manufacturing in a wide range of application areas today. However, process monitoring, and especially the real-time detection of defects, is still an area where there is a lot of potential for improvement. High defect rates should be avoided in order to save costs and shorten product development times. Most of the time, effective process controls fail because of the given process parameters, such as high process temperatures in a laser-based powder bed fusion, or simply because of the very cost-intensive measuring equipment. This paper proposes a novel approach for the real-time and high-efficiency detection of coating defects on the powder bed surface during the powder bed fusion of polyamide (PBF-LB/P/PA12) by using a low-cost RGB camera system and image recognition via convolutional neural networks (CNN). The use of a CNN enables the automated detection and segmentation of objects by learning the spatial hierarchies of features from low to high-level patterns. Artificial coating defects were successfully induced in a reproducible and sustainable way via an experimental mechanical setup mounted on the coating blade, allowing the in-process simulation of particle drag, part shifting, and powder contamination. The intensity of the defect could be continuously varied using stepper motors. A low-cost camera was used to record several build processes with different part geometries. Installing the camera inside the machine allows the entire powder bed to be captured without distortion at the best possible angle for evaluation using CNN. After several training and tuning iterations of the custom CNN architecture, the accuracy, precision, and recall consistently reached >99%. Even defects that resembled the geometry of components were correctly classified. Subsequent gradient-weighted class activation mapping (Grad-CAM) analysis confirmed the classification results.

Minimizing Defects in Radiator Grille Upper Garnish Parts using Six Sigma (DMAIC) at PT. AAS

To achieve quality improvement, companies must align their production processes with customer needs, control production costs effectively, and maintain product quality. This approach enhances customer satisfaction, increases market share, and boosts profitability. PT. AAS, an automotive company specializing in injection molding and painting, relies on resin as its primary raw material to produce car parts for major clients like Hyundai, Suzuki, and Astra. To dominate the market, PT. AAS must prioritize delivering quality products on time to earn customer trust and secure continuous orders. Initially, the QC data for the injection molding area showed a high defect rate of approximately 17.5% for the Garnish Radiator Grille Upper part, from December 2022 to May 2023. Prior to implementing the Six Sigma method, PT. AAS had a DPMO (Defects Per Million Opportunities) value of 58,177, equivalent to a 3.10 Sigma level. After applying the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) process, the DPMO decreased to 17,991, resulting in a 3.60 Sigma level. This suggests that PT. AAS currently operates at a 4 Sigma level, with a strong potential to reach 5 or even 6 Sigma by addressing the root causes of rejection. The fishbone analysis highlights the need for action across all departments, including Management. Key areas to focus on include Material, ensuring the correct resin delivery to the Injection Molding station; Machine, verifying proper machine settings and utilizing the 5S methodology; Environment, optimizing room temperature and ventilation; and Man, providing training to enhance operators' knowledge and sense of responsibility.

An Intelligent Diagnosis Approach Combining Resampling and CWGAN-GP of Single-to-Mixed Faults of Rolling Bearings Under Unbalanced Small Samples

Rolling bearing is a key component with the high fault rate in the rotary machines, and its fault diagnosis is important for the safe and healthy operation of the entire machine. In recent years, the deep learning has been widely used for the mechanical fault diagnosis. However, in the process of equipment operation, its state data always presents unbalanced. Number of effective data in different states is different and usually the gap is large, which makes it difficult to directly conduct deep learning. This paper proposes a new data enhancement method combining the resampling and Conditional Wasserstein Generative Adversarial Networks-Gradient Penalty (CWGAN-GP), and uses the gray images-based Convolutional Neural Network (CNN) to realize the intelligent fault diagnosis of rolling bearings. First, the resampling is used to expand the small number of samples to a large level. Second, the conditional label in Conditional Generative Adversarial Networks (CGAN) is combined with WGAN-GP to control the generated samples. Meanwhile, the Maximum Mean Discrepancy (MMD) is used to filter the samples to obtain the high-quality expanded data set. Finally, CNN is used to train the obtained dataset and carry out the fault classification. In the experiment, a single, compound and mixed fault cases of rolling bearings are successively simulated. For each case, the different sets considering the imbalance ratio of data are constructed, respectively. The results show that the method proposed significantly improves the fault diagnosis accuracy of rolling bearings, which provides a feasible way for the intelligent diagnosis of mechanical component with the complex fault modes and unbalanced small data.

Fault diagnosis for wind turbines based on LSTM and feature optimization strategies

SummaryHigh penetration of renewable energy is the development trend of the future power system. As one of the clean energy sources, wind power generation has an increasing share in the energy market. However, due to the harsh working environment, the high fault rate and poor accessibility of the wind farms, resulting in the difficult maintenance process and high cost. This article proposes a fault diagnosis (FD) method based on long short‐term memory (LSTM) and feature optimization strategies for wind turbines (WTs), thus reducing the operation and maintenance costs of WTs. First, Pearson correlation coefficient analysis is performed on the collected data features to remove redundant features, and wavelet transform is adopted to remove the redundant data, so as to optimize the fault features and fault data. Then the selected features samples are used to train LSTM‐based FD model. Finally, the actual production data is adopted to verify the proposed method. The proposed method can effectively locate the faults, and provide data support for wind farms, thus improving the reliability, safety, and economic benefits of wind farms.

An ultra-efficient design of fault-tolerant 3-input majority gate (FTMG) with an error probability model based on quantum-dots

Quantum-dot cellular automata (QCA) has recently attracted significant notice thanks to their inherent ability to decrease energy dissipation and decreasing area, which is the primary need of digital circuits. However, the lack of resistance of QCA circuits under defects in previous works is a vital challenge affecting the stability of the circuit and output production. In addition, with the high defect rate in QCA, suggesting resistance and stable structures is critical. Furthermore, the 3-input majority gate is a fundamental component of QCA circuits; therefore, improving this essential gate would enable the development of fault-tolerant circuits. This paper recommends a 3-input majority gate which is 100% fault-tolerant against single-cell omission defects. Moreover, the fundamental gates are introduced based on the proposed gate. In addition, an adder and a 1:2 decoder are also designed. Using QCADesigner 2.0.3 and QCAPro software, simulations of structures and analysis of power consumption are performed.

Low delayed bleeding and high complete closure rate of mucosal defects with the novel through-the-scope dual-action tissue clip after endoscopic resection of large nonpedunculated colorectal lesions (with video)

Background and AimsComplete closure following endoscopic resection (ER) of large non-pedunculated colorectal lesions (LNPCLs) can reduce delayed bleeding but is challenging with conventional through-the-scope (TTS) clips alone. The novel dual action tissue (DAT) has clip arms that open and close independent of each other, facilitating tissue approximation. We aimed to evaluate the rate of complete closure and delayed bleeding with the DAT clip after ER of LNPCLs. MethodsMulticenter prospective cohort study of all patients who underwent defect closure with the DAT clip following endoscopic mucosal resection (EMR) or submucosal dissection (ESD) of LNPCLs ≥ 20 mm from July 2022 to May 2023. Delayed bleeding was defined as bleeding event requiring hospitalization, blood transfusion or any intervention within 30 days after the procedure. Complete closure was defined as apposition of mucosal defect margins without visible submucosal areas < 3 mm along the closure line. ResultsA total of 107 patients (median age 64 years; 42.5% women) underwent EMR (n=63) or ESD (n=44) of LNPCLs (median size 40 mm; 74.8% right colon) followed by defect closure. Complete closure was achieved in 96.3% (n=103) with a mean of 1.4±0.6 DAT and 2.9±1.8 TTS clips. Delayed bleeding occurred in one patient (0.9%) without requiring additional interventions. ConclusionThe use of the DAT clip in conjunction with TTS clips achieved high complete defect closure after ER of large LNPCLs and was associated with a 0.9% delayed bleeding rate. Future comparative trials and formal cost-analyses are needed to validate these findings.

Investigation of the Impact of Defective Ultrasound Transducers on Clinical Image Quality in Grayscale 2-D Still Images

There are several studies that show high defect rates of transducers in clinical use. The purpose of the present study was to investigate whether image quality and the risk for misdiagnosis is affected by using defective transducers. Four defective transducers with varying degrees of defect severity, still in clinical use, were selected. Forty artifact-affected clinical images from each transducer were compared with images acquired from fully functional transducers, of the same model, in an observer study where four experienced radiologists rated each of the 320 images. The rating tasks included if the artifacts were detectable, if the possible artifacts might affect the diagnosis, how well structural details were reproduced and, finally, an assessment of overall image quality. The artifacts in the images were detectable for three of the four transducers (p < 0.05), and in 121 of 640 assessments of the images from the defective transducers the observers were confident that the artifacts could affect the diagnosis. All four faulty transducers were assessed to have decreased ability to resolve structural details (p < 0.05), and three of the four transducers were assessed to have worse overall image quality (p < 0.05). The present study shows that image quality and the risk of misdiagnosis can be affected by using defective transducers. This highlights the importance of frequent quality control of the transducers to avoid decreased image quality and even misdiagnosis.

Condition Monitoring and Fault Detection of Wind Turbine Driveline With the Implementation of Deep Residual Long Short-Term Memory Network

In view of the wide application of wind power, it is critically essential to develop solutions to the high fault rate and the long mean time to repair (MTTR). Multi-sensor fusion methods have been widely applied in condition monitoring and anomaly detection of industrial installation. Aimed at the wind turbine driveline, a new method utilizing the deep residual LSTM network with Attention model (ResLSTM-AM) is proposed in this paper. Firstly, data from multi-sensor fusion systems like supervisory control and data acquisition (SCADA) is preprocessed by quartile data cleaning and corresponding selection using the calculation of maximal information coefficient (MIC) to enhance its reliability. Secondly, we establish the neural network by the deep residual network (ResNet), long short-term memory network (LSTM), and attention mechanism (AM) for time series forecasting of wind turbines. The newly added residual connecting architecture in LSTM layers ensures a higher learning rate in feature extraction and provides a more flexible data flow both in forward and backward signals. Additionally, the attention mechanism after a LSTM layer amplifies the influence of vital data. The model gets validated based on historical SCADA data from actual wind turbines containing healthy conditions and anomaly conditions, showing ResNet contributes more. Based on the root-mean-square error (RMSE), the alarming threshold is calculated by an exponential weighted moving average (EWMA). For two chosen variables, the proposed method is confirmed to be efficient and reliable with the accuracy of 0.9945 and 0.9880 in the results of trials and comparisons with other existing models.

Results of MOLTO, a multicenter, open label, phase II clinical trial evaluating venetoclax, atezolizumab and obinutuzumab combination in Richter syndrome.

7502 Background: Chemoimmunotherapy is the standard first line of patients (pts) with diffuse large B-cell lymphoma (DLBCL) variant of Richter syndrome (RS). Response rate and duration are unsatisfactory. The biology of RS (high rate of DNA damage response pathway defects, high tumor mutation burden coupled with the expression of the PD1/PDL1 axis) prompts investigation of non-chemo combinations leveraging agents that circumvent TP53 abnormalities and trigger anti tumor immune response. MOLTO is a multicenter international ph 2 study (NCT04082897) evaluating activity and safety of atezolizumab (humanized monoclonal antibody blocking PD-L1), venetoclax (BCL2 inhibitor) and obinutuzumab (anti-CD20 MoAb) combination in untreated DLBCL-RS. Methods: Treatment consisted of 35 cycles with obinutuzumab (1000 mg C1-8), atezolizumab (1200 mg C1-18) and venetoclax (400 mg/d C1-35), q21. Primary endpoint was ORR ≥67% at C6. RS diagnosis was centrally revised. RS mutation profile was tested on pre-treatment cell free DNA. Minimal residual disease (MRD) was tested by 12 colors flow cytometry and NGS on peripheral blood mononuclear cells and plasma. Results: 28 planned pts were enrolled from Oct 2019 to Oct 2022 (Table). Three were not evaluable for primary endpoint due to G5 infection (n=1) or early withdrawn (n=2). As per intention-to-treat ORR was 67.9% (19/28) thus meeting primary endpoint. CR rate was 28.6%. No clinical characteristics influenced C6-ORR. After a median follow-up of 11.6 mo, 11/19 pts (57.9%) are in continuous remission (8 on active therapy, 2 received allogenic transplant, 1 discontinued due to MDS) among them, 6 for ≥24 mo. Of the remaining 8 pts, 7 progressed after a median of 14 cycles, 1 died from sepsis at C9 in remission. Median duration of response, PFS and OS were 11.7, 16.2 and 31.6 mo, respectively. Out of the 13 patients who progressed, 4 received a salvage therapy and are alive at a median follow-up of 24.3 mo. Bulky disease and ECOG PS &gt;1 affected PFS. Rate of unmeasurable MRD, impact of mutations and chronic lymphocytic leukemia-RS clonal relation on outcomes will be presented at the meeting. Overall 43 G3-4 adverse events (AE) were recorded in 17 pts (60.7%), mostly hematological (51.2%). Any grade immune-related AEs were reported in 6 pts (G3-4 in 2), none led to discontinuation. No tumor lysis syndrome observed. Infections ≥G3 occurred in 6 pts, including 2 G5. One pt developed MDS. Conclusions: Atezolizumab, obinutuzumab and venetoclax combination is active in pts with untreated DLBCL-RS. This regimen led to durable remissions, longer than 2 yrs in one third of responders. Clinical trial information: NCT04082897 . [Table: see text]

17th International Conference on Malignant Lymphoma, Palazzo dei Congressi, Lugano, Switzerland, 13 - 17 June, 2023.

Introduction: Chemoimmunotherapy is the standard first line treatment of diffuse large B-cell lymphoma (DLBCL) variant of Richter syndrome (RS). However, response rate and duration are unsatisfactory. The biology of RS (high rate of DNA damage response pathway defects, high tumor mutation burden coupled with the expression of the PD1/PDL1 axis) prompts investigation of non-chemo combinations leveraging agents that circumvent TP53 abnormalities and trigger anti-tumor immune response. MOLTO is a multicenter international phase 2 study (NCT04082897) evaluating activity and safety of atezolizumab (humanized monoclonal antibody blocking PD-L1), venetoclax (BCL2 inhibitor) and obinutuzumab (anti-CD20 MoAb) combination in untreated DLBCL-RS. Methods: Treatment consisted of 35 q21 cycles with obinutuzumab (1000 mg C1–8), atezolizumab (1200 mg C1–18) and venetoclax (400 mg/d C1–35). Primary endpoint was ORR ≥67% at C6. RS diagnosis was centrally revised. RS mutation profile was tested on pre-treatment cell free DNA. Minimal residual disease (MRD) was tested by 8 colors flow cytometry and NGS on peripheral blood mononuclear cells and plasma. Results: Overall 28 planned pts were enrolled from October 2019 to October 2022 (Table 1). Three were not evaluable for primary endpoint due to G5 infection (n = 1) or early withdrawn (n = 2). As per intention-to-treatment ORR was 67.9% (19/28) thus meeting primary endpoint. CR rate was 28.6% (8/28). No clinical characteristics influenced ORR at C6. After a median follow-up of 11.6 months, 11/19 pts (57.9%) are in continuous remission (8 on active therapy, 2 received allogenic transplant, 1 discontinued due to MDS), among them 6 for ≥24 months. Of the remaining 8 pts, 7 progressed after a median of 14 cycles, 1 died from sepsis at C9 in remission. Median duration of response was 11.7 months, median PFS was 16.2 months and median OS 31.6 months. Out of the 13 pts who progressed, 4 received a salvage therapy and are alive at a median follow-up of 24.3 months. Bulky disease and ECOG PS >1 affected PFS. Rate of unmeasurable MRD and impact of mutations and chronic lymphocytic leukemia-RS clonal relation on outcomes will be presented at the meeting. A total of 43 G3–4 adverse events (AE) occurred in 17 pts (60.7%), mostly hematological (51.2%). Any grade immune-related AEs was reported in 6 pts (G3–4 in 2), none led to discontinuation. No tumor lysis was observed. Infections ≥G3 occurred in 6 pts, including 2 G5. One pt developed MDS. Conclusions: Atezolizumab, obinutuzumab and venetoclax combination is active in pts with untreated DLBCL-RS. This regimen led to durable remissions, longer than 2 years in one third of responders. Encore Abstract—previously submitted to ASCO 2023 and EHA 2023 The research was funded by: Roche Keywords: combination therapies, immunotherapy, molecular targeted therapies Conflicts of interests pertinent to the abstract A. M. Frustaci Other remuneration: Abbvie, AstraZeneca, Janssen, Beigene; advisory boards, travel grants, speaker invitations