bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension
Authors: Raman Raghu , Mandal Santanu , Das Payel , Kaur Tavleen , Sanjanasri J. P. , Nedungadi Prema
Published: June 2024

This study explores the adoption and societal implications of an emerging technology such as Chat Generative Pre‐Trained Transformer (ChatGPT) in higher education students. By utilizing a mixed‐method framework, this research combines Rogers’ diffusion of innovation theory with sentiment analysis, offering an innovative methodological approach for examining technology adoption in higher educational settings. It explores five attributes—relative advantage, compatibility, ease of use, observability, and trialability—shaping students’ behavioral intentions toward ChatGPT. Sentiment analysis offers qualitative depth, revealing emotional and perceptual aspects, and introduces a gender‐based perspective. The results suggest that five innovation attributes significantly impact the adoption rates and perceptions of ChatGPT, indicating its potential for transformative social change within the educational sector. Gen Zs viewed ChatGPT as innovative, compatible, and user‐friendly, enabling the independent pursuit of educational goals. Consequently, the benefits provided by ChatGPT in education motivate students to use the tool. Gender differences were observed in the prioritization of innovation attributes, with male students favoring compatibility, ease of use, and observability, while female students emphasized ease of use, compatibility, relative advantage, and trialability. The findings have implications for understanding how technological innovations such as ChatGPT could be strategically diffused across different societal segments, especially in the academic context where ethical considerations such as academic integrity are paramount. This study underscores the need for a demographic‐sensitive, user‐centric design in generative artificial intelligence (AI) technologies.
Experimental Study on the Evolution of Fracture Aperture of Single‐Fracture Granite during Liquid Nitrogen Cold Shock Cycling
Authors: Niu Haiping , Yu Weidong
Published: June 2024

Fractures in hot dry rock (HDR) reservoirs are the locations where heating fluid flows exchange heat with the HDR matrix. Cold shock with liquid nitrogen is one method for stimulating cracks. This study investigates the evolution law of fracture aperture under cold shock with liquid nitrogen. The real‐time high‐temperature triaxial servo control rock testing machine was used to conduct permeability experiments to examine the fracture aperture of single‐fracture granite during liquid nitrogen shock cycles at various temperatures. The effects of pore pressure, temperature, and shocking cycles on the fracture aperture are analyzed, and the difference in fracture aperture variation under liquid nitrogen cooling and natural cooling modes is compared. The results showed that (1) during liquid nitrogen cooling, the fracture aperture expands as pore pressure rises; the effect of pore pressure on the fracture aperture becomes more robust as the number of liquid nitrogen shocking cycles and initial temperature increases; (2) under 1‐2 soaking cycles, fracture aperture decreases as the temperature rises. Under two or more soaking cycles, the fracture aperture first increases and then decreases with increasing temperature; (3) when the initial temperature of fractured granite is 100°C, the fracture aperture is not significantly changed by repeated cold soaking cycles. However, with a higher initial temperature, the fracture aperture develops with more liquid nitrogen cold soaking cycles. The liquid nitrogen cooling method is more conducive to increasing the fracture aperture than natural cooling. The experimental results can provide primary experimental data for future research into controlling the evolution of granite cracks.
The Management of Hyperplastic Pulpitis in Immature Permanent Molar Using Vital Pulp Therapy: A Case Report with 12 Months Follow‐Up
Authors: Mando Anas , Laflouf Mohannad , Tolibah Yasser Alsayed
Published: June 2024

Hyperplastic pulpitis is an irreversible type of pulpitis that primarily affects young patients. It occurs when an inflamed pulp becomes exposed due to factors such as dental caries, dental trauma, or other causes. Root canal treatment is commonly employed to manage hyperplastic pulpitis. However, vital pulp therapy can be considered as a less invasive option. The main objective of this treatment is to preserve the vitality and functionality of the remaining pulp tissue. This case report discusses the potential management of hyperplastic pulpitis in an immature molar using vital pulp therapy instead of a full root canal treatment. The report includes clinical and radiographic follow‐up at six and twelve months.
Comparative Analysis of Deep Learning Techniques for Load Forecasting in Power Systems Using Single‐Layer and Hybrid Models
Authors: Jang Jiyeon , Kim Beopsoo , Kim Insu
Published: June 2024

Accurate power load forecasting is critical to maintaining the stability and efficiency of power systems. However, due to the complex and fluctuating nature of power load patterns, physical calculations are often inefficient and time‐consuming. In addition, traditional methods, known as statistical learning methods, require not only mathematical background and understanding but also statistical background and understanding. To overcome these difficulties, the authors proposed a simpler way to predict load by using artificial intelligence. This study investigated the performance of forecasting techniques, including three single‐layer and seven hybrid multilayer deep learning models that combine them. This study also analyzed the effect of hyperparameters on the learning results by varying the epoch and activation functions. To evaluate and analyze the performance of the deep learning model, this study used load data from the power system in Jeju Island, Korea. In addition, this study included weather factors that may affect the load to improve the prediction performance. The prediction process is performed on the Python platform, and the model that showed the highest accuracy was LSTM‐CNN, a hybrid combination of LSTM and CNN models. Considering both the maximum and minimum error, the error value was low at 0.231%. By providing detailed insights into the entire research process, including data collection, preprocessing, scaling, prediction, and analysis, this study provided valuable guidance for future research in this area.
Impact of Self‐Monitoring Blood Glucose on Glycaemic Control Among Insulin‐Treated Patients With Diabetes Mellitus in Northeastern Tanzania: A Randomised Controlled Trial
Authors: Muhali Sophia S. , Muhali Fatma S. , Mfinanga Sayoki G. , Sadiq Abid M. , Marandu Annette A. , Kyala Norman J. , Said Fuad H. , Nziku Eliada B. , Mirai Tumaini E. , Ngocho James S. , Mlay Henry L. , Waria Gilbert G. , Chambega Angelina , Kessy Stella N. , Kilonzo Kajiru G. , Lyamuya Furaha S. , Mkwizu Elifuraha W. , Shao Elichilia R. , Chamba Nyasatu G.
Published: June 2024

Introduction: Tracking of blood glucose levels by patients and care providers remains an integral component in the management of diabetes mellitus (DM). Evidence, primarily from high‐income countries, has illustrated the effectiveness of self‐monitoring of blood glucose (SMBG) in controlling DM. However, there is limited data on the feasibility and impact of SMBG among patients in the rural regions of sub‐Saharan Africa. This study is aimed at assessing SMBG, its adherence, and associated factors on the effect of glycaemic control among insulin‐treated patients with DM in northeastern Tanzania.

Materials and Methods: This was a single‐blinded, randomised clinical trial conducted from December 2022 to May 2023. The study included patients with DM who had already been on insulin treatment for at least 3 months. A total of 85 participants were recruited into the study and categorised into the intervention and control groups by a simple randomization method using numbered envelopes. The intervention group received glucose metres, test strips, logbooks, and extensive SMBG training. The control group received the usual care at the outpatient clinic. Each participant was followed for a period of 12 weeks, with glycated haemoglobin (HbA1c) and fasting blood glucose (FBG) being checked both at the beginning and at the end of the study follow‐up. The primary and secondary outcomes were adherence to the SMBG schedule, barriers associated with the use of SMBG, and the ability to self‐manage DM, logbook data recording, and change in HbA1c. The analysis included descriptive statistics, paired t‐tests, and logistic regression.

Results: Eighty participants were analysed: 39 in the intervention group and 41 in the control group. In the intervention group, 24 (61.5%) of patients displayed favourable adherence to SMBG, as evidenced by tests documented in the logbooks and glucometer readings. Education on SMBG was significantly associated with adherence. Structured SMBG improved glycaemic control with a HbA1c reduction of −1.01 (95% confidence interval (CI) −1.39, −0.63) in the intervention group within 3 months from baseline compared to controls of 0.18 (95% CI −0.07, 0.44) (p < 0.001).

Conclusion: Structured SMBG positively impacted glycaemic control among insulin‐treated patients with DM in the outpatient clinic. The results suggest that implementing a structured testing programme can lead to significant reductions in HbA1c and FBG levels.

Trial Registration: Pan African Clinical Trials Registry identifier: PACTR202402642155729.
Increased Cerebrospinal Fluid Adenosine 5′‐Triphosphate Levels in Patients with Guillain–Barré Syndrome and Chronic Inflammatory Demyelinating Polyneuropathy
Authors: Nukui Takamasa , Niimi Hideki , Hayashi Tomohiro , Dougu Nobuhiro , Yamamoto Mamoru , Shibuya Ryoko , Matsuda Noriyuki , Tanaka Ryo , Hirosawa Hiroaki , Furuta Risako , Mitsui Taichi , Maesaka Hiroki , Takasawa Syuhei , Kitajima Isao , Nakatsuji Yuji
Published: June 2024

Background. Extracellular adenosine 5′‐triphosphate (ATP) acts as a signaling molecule in the peripheral nerves, regulating myelination after nerve injury. The present study examined whether the cerebrospinal fluid (CSF) ATP levels in patients with Guillain–Barré syndrome (GBS) and chronic inflammatory demyelinating polyneuropathy (CIDP) are related to disease severity. Methods. CSF ATP levels in 13 patients with GBS and 18 patients with CIDP were compared with those in a control group of 16 patients with other neurological diseases (ONDs). In patients with CIDP, CSF ATP levels were compared before and after treatment. The correlations between CSF ATP levels and other factors, including clinical data and CSF protein levels, were also evaluated. Results. Median CSF ATP levels were significantly higher in patients with GBS and CIDP than in those with ONDs. When patients with CIDP were classified into two groups depending on their responsiveness to immunotherapy, median CSF ATP levels were significantly higher in good responders than in ONDs. CSF ATP levels tended to decrease after treatment in patients with CIDP. In patients with CIDP, there is a negative correlation between CSF ATP and CSF protein levels. Conclusions. CSF ATP levels were increased in patients with GBS and CIDP. In particular, CSF ATP levels tended to decrease following treatment in patients with CIDP. CSF ATP levels may be useful biomarkers for the diagnosis or monitoring of therapeutic effects in patients with GBS and CIDP.
Implementation of the Fuzzy Logic Controlled 31‐Level Diode Switched Multilevel Inverter with Optimal Components for Solar PV‐Fed System
Authors: Vara Prasad Paneti Anjaneya , Dhanamjayulu C.
Published: June 2024

This work presents a novel architecture for the 31‐level asymmetrical DC voltage source configured diode switched multilevel inverter, which has a single phase and fewer components. Using asymmetric DC sources and an H‐bridge, the proposed topology generates a maximum output voltage of 31 levels. This 31‐level topology is suitable for both renewable energy source conversion (RES) and electric vehicle (EV) applications. This topology requires fewer total components, lower cost, and smaller size. Along with the numerous benefits of MLIs, reliability issues are critical due to the larger number of devices required to minimize THD. Several characteristics, such as total standing voltage (TSV), reliability, cost function (CF), efficiency, and overall power losses, are investigated for the developed 31‐level MLIs. The TSV and CF of the proposed MLI are critical factors in demonstrating that the proposed topology is cost‐effective when compared to other recent topologies. Many parameters are thoroughly compared and tabulated, as well as represented graphically. The suggested MLI has lower TSV and component demand. Total harmonic distortion complies with IEEE specifications. The reliability aspects were also calculated and validated. The proposed MLI is controlled by a fuzzy logis controller (FLC) to achieve efficient results. The topology is simulated in MATLAB/Simulink software under a variety of conditions and dynamic load changes, and a prototype with a dSPACE controller is also implemented.
Review and Evaluation of European National Clinical Practice Guidelines for the Treatment and Management of Active Charcot Neuro‐Osteoarthropathy in Diabetes Using the AGREE‐II Tool Identifies an Absence of Evidence‐Based Recommendations
Authors: Renwick Nichola , Pallin Jennifer , Bo Jansen Rasmus , Gooday Catherine , Tardáguila-Garcia Aroa , Sanz-Corbalán Irene , Tentolouris Anastasios , Jirkovská Alexandra , Koller Armin , Korzon-Burakowska Anna , Petrova Nina , Game Frances
Published: June 2024

Background: Charcot neuro‐osteoarthropathy (CNO) is a rare but devastating complication of diabetes associated with high rates of morbidity; yet, many nonfoot specialists are unaware of it, resulting in missed and delayed diagnosis. Clinical practice guidelines (CPGs) have proven useful in improving quality of care and standardizing practice in diabetes and diabetic foot care. However, little is known about the consistency in recommendations for identification and management of active CNO.

Aim: The aim of this study is to review European national diabetes CPGs for the diagnosis and management of active CNO and to assess their methodological rigor and transparency.

Methods: A systematic search was performed to identify diabetes national CPGs across Europe. Guidelines in any language were reviewed to explore whether they provided a definition for active CNO and recommendations for diagnosis, monitoring, and management. Methodological rigor and transparency were assessed using the Appraisal of Guidelines for Research and Evaluation (AGREE‐II) tool, which comprises 23 key items organized within six domains with an overall guideline assessment score of ≥ 60% considered to be of adequate quality to recommend use. Each guideline was assessed by two reviewers, and inter‐rater agreement (Kendall’s W) was calculated for AGREE‐II scores.

Results: Seventeen CPGs met the inclusion criteria. Breadth of CNO content varied across guidelines (median (IQR) word count: 327; Q1 = 151; Q3 = 790), and 53% provided a definition for active CNO. Recommendations for diagnosis and monitoring were provided by 82% and 53%, respectively, with offloading being the most common management recommendation (88%). Four guidelines (24%) reached threshold for recommendation for use in clinical practice (≥ 60%) with the scope and purpose domain scoring highest (mean (SD): 67%, ± 23%). The remaining domains had average scores ranging between 19% and 53%. Inter‐rater agreement was strong (W = 0.882; p < 0.001).

Conclusions: European national CPGs for diabetes provide limited recommendations on active CNO. All guidelines showcased deficits in their methodology, suggesting that more rigorous methods should be employed for diabetes CPG development across Europe.
Automatic Fingerprint Data Labeling Using WiFi Signal and Smartphone Camera for Indoor Positioning
Authors: Kim Dongdeok , Suh Young-Joo
Published: June 2024

WiFi fingerprinting has been one of the most practical approaches for implementing an indoor positioning system. However, the need to measure location labels for fingerprint data has hindered the deployment of WiFi fingerprint‐based positioning systems. To reduce the cost of location labeling, several methods for automatically labeling locations or bypassing location labeling have been proposed. However, these methods still need to measure location labels for partial fingerprint data, or the estimated location labels are inaccurate. In this paper, we propose Heimdall, an automatic fingerprint data labeling method using a smartphone camera and WiFi signal for an indoor positioning system. Since Heimdall utilizes camera geometry for accurate automatic labeling, it aims to find the location labels of unlabeled fingerprint data composed of WiFi received signal strengths (RSSs) and photos collected using smartphones in multiple reference points (RPs). Using structure from motion (SfM) with all photos in the unlabeled fingerprint dataset, the location and orientation of the cameras can be recovered on an arbitrary world coordinate system. However, the world coordinate system derived by SfM is warped. In other words, it is different from the real‐world coordinate system where we express the location labels since SfM has similarity ambiguity, including scale, rotation, and translation ambiguity. Heimdall finds the location labels by estimating and applying an unwarping transformation that removes those ambiguities. We use two types of geometric constraints for estimating the unwarping transformation. First, several geometric entities in the warped‐world coordinates and real‐world coordinates are extracted from the photos and prior information about the indoor layout. The unwarping transformation transforms the geometric entities in warped coordinates to those in real‐world coordinates. Second, we utilize the log‐distance pathloss model with RSSs to derive the constraint about distances from the location label to the access points. We construct the optimization problem subject to those constraints to estimate the unwarping transformation. To evaluate the performance of Heimdall, we performed several experiments. Heimdall yields a mean location labeling error of 0.12 m and a standard deviation of location labeling error of 0.06 m for the best case in the experiment. These results demonstrate that a fingerprint‐based indoor positioning system can use the location labels estimated by Heimdall without performance degradation.
Target Damage Assessment Method Based on Interval‐Valued Intuitionistic Fuzzy Aggregation Operator under Dynamic Multi‐Expert
Authors: Li Lin , Sun Shiyan , Shi Zhangsong , Zeng Yaqin , Wang Xuan
Published: June 2024

This study aims to solve the problem that the current target damage assessment method does not fully take into account the time series characteristics of the target and the dynamic changes in the battlefield situation, thus leading to insufficient accuracy of the assessment results. Target damage assessment method based on interval‐valued intuitionistic fuzzy aggregation operator (IVIFAO) under dynamic multi‐experts is a combination of interval‐valued intuitionistic fuzzy set (IVIFS) theory and dynamic multi‐attribute swarm decision‐making theory. Firstly, we extracted the effective factors that cause damage to the target and established the damage assessment index system. Secondly, in order to take into account the subjective weights and objective weights, we proposed a comprehensive weight model of damage factors based on interval‐valued intuitionistic fuzzy entropy (IVIFE) based on a cosine function (IVIFECF). The spatio‐temporal weights for each moment are determined using the Poisson distribution method. Then, given the inherent ambiguity and complexity of the decision‐making process, the decision‐making information is represented by interval‐valued intuitionistic fuzzy numbers (IVIFNs). We constructed a weighted interval‐valued intuitionistic fuzzy (WIVIF) decision matrix. Here, the interval‐valued intuitionistic fuzzy weighted geometric average (IVIFPWGA) operator is used to synthesize decision‐making information related to damage factors. We further introduce the dynamic interval‐valued intuitionistic fuzzy power‐weighted geometric average (DIVIFPWGA) operator, which combines instantaneous decision information with time series weights to generate a dynamic multi‐expert fusion WIVIF decision matrix. Finally, the improved TOPSIS method is used to rank the IVIFNs, resulting in a comprehensive damage assessment of the targets, which is analysed for superiority with the novel method, comparing both real‐time and scalability. The stability and validity of the method were verified.
Comparative Determination of Glomerular Filtration Rate Estimation Formulae in Type 2 Diabetic Patients: An Observational Study
Authors: Ofori Emmanuel Kwaku , Nketiah-Dwomo Irene , Tagoe Emmanuel Aryee , Amponsah Seth Kwabena , Adams Ismaila , Nyarko Eric Nana Yaw , Amanquah Seth Dortey
Published: June 2024

Assessing glomerular filtration rate (GFR) involves collecting timed urine samples for 24 hours, requiring significant time and resources in the clinical setting. Using predictive GFR formulae to assess renal function may be a better alternative. Our goal was to determine which predictive GFR formula had the highest level of concordance with the GFR that has been measured in a resource‐poor setting. This is an observational study. We selected fifty (50) individuals diagnosed with type 2 diabetes (T2DM) in Kumasi, Ghana. The sociodemographic and clinical characteristics were obtained using a structured questionnaire. Urine was obtained from each subject over 24 hours. The levels of glucose (FBG) and creatinine in patients’ blood, as well as the levels of creatinine in their urine, were measured after the patients had fasted overnight. Participants had a mean age of 57.4 ± 10.7 (years), BMI of 27.8 ± 4.1 (kg/m2), FBG of 9.0 ± 3.1 (mmol/L), and creatinine concentrations of 95.6 ± 29.1 (μmol/L). A Krouwer plot was used to compare the measured GFR with three formulae: Chronic Kidney Disease Epidemiology (CKD‐EPI), Modification of Diet in Renal Disease (MDRD), and Cockroft‐Gault (CG) for GFR prediction. Among the 3 estimates, CG showed nonsignificance (p > 0.05) with the measured GFR. The primary finding was that the GFR calculated using the CG formula was not different from the GFR measured, suggesting that CG is the most appropriate alternative GFR estimate among a cross‐section of T2DM patients in Ghana.
Mental Fatigue in Parkinson’s Disease: Systematic Review and Evaluation of Self‐Reported Fatigue Scales
Authors: Chen Junle , Zhou Yanjun , Rao Hengyi , Liu Jianghong
Published: June 2024

Fatigue is a common and debilitating symptom affecting a significant proportion of individuals with Parkinson’s disease (PD), often overshadowing even motor symptoms in its impact on quality of life. The accurate definition and assessment of mental fatigue in PD is crucial for both clinical management and research, yet it remains a challenge due to the subjective nature of the symptom and the heterogeneity of assessment scales. This systematic review examined the existing measures of self‐reported mental fatigue in PD by searching through PubMed, Embase, and Scopus databases using specific keywords from 2001 to 2024. Out of the 4182 articles found, 40 met the inclusion criteria, and 14 different scales were identified to measure self‐reported fatigue in PD patients. However, most of these scales lack a consistent definition of fatigue, indicating a need for validated combinations of unidimensional and multidimensional scales to accurately assess mental fatigue in PD. The review found that it is best to use Fatigue Severity Inventory (FSI) and Multidimensional Fatigue Inventory (MdFI) to screen for severity of PD mental fatigue and Neuro‐QoL Item Bank v1.0 (Neuro‐QoL) to evaluate its impact on patients’ lives. Furthermore, multidimensional scales Parkinson’s Disease Questionnaire (PDQ) and Functional Assessment of Chronic Illness Therapy‐Fatigue Scale (FACIT‐F) are frequently coupled with Fatigue Severity Scale (FSS), Parkinson’s Fatigue Scale (PFS), and/or Modified Fatigue Impact Scale (MFIS) due to their short length and holistic coverage of variables in patients’ quality of life. Combining fatigue scales can be used for screening and scoring methods. The review also recommends validating fatigue scales translation and combining them with biomarkers to improve the accuracy and effectiveness of fatigue assessment in clinical practice. Future research should analyze correlations between fatigue scales, expand language types, and explore the link between fatigue scales and the pathophysiological basis of PD. Our findings underscore the need for a standardized approach to the measurement of fatigue in PD and set the stage for future research to consolidate assessment tools that can reliably guide treatment strategies and improve patient outcomes.
Abstract A007: Assessment of metabolic vulnerabilities of breast cancer brain metastasis
Authors: Abbott Keene L. , Subudhi Sonu , Ferreira Raphael , Gültekin Yetiş , Steinbuch Sophie C. , Honeder Sophie E. , Kumar Ashwin S , Wu Michelle , Ramesh Diya , Hansen Jacob , Riedmayr Lisa M. , Duquette Mark , Ali Ahmed , Henning Nicole , Sivanand Sharanya , Kunchok Tenzin , Waite Millenia , Do Brian T. , Spanoudaki Virginia , Sánchez-Rivera Francisco J. , Church George M. , Jain Rakesh K , Vander Heiden Matthew G.
Published: June 2024

The metastasis of cancer to the brain is a major contributor to patient morbidity and mortality. Prior work suggests that there is therapeutic potential in targeting metabolic processes within brain metastatic cancer, however how best to identify novel targets and select patient populations remains unclear. In this study, we determine what nutrients are available to breast cancer cells in the brain and how those nutrients are used. We also engineer breast cancer cells that are auxotrophic for specific nutrients and assess how this impacts tumor growth in the brain using various approaches. These methodologies include direct implantation into the brain and introduction into the circulation to evaluate tumor formation as brain metastases. Unexpectedly, we find that no single approach, including assessment of brain nutrient availability, tumor biosynthetic activity, and evaluation of genetic dependencies using in vivo CRISPR screens reliably predicts metabolic dependencies that broadly extend across models of breast cancer brain metastasis. Our findings underscore the necessity of a holistic approach in considering how best to identify and prioritize new targets for treating metastatic cancer.

Citation Format: Keene L. Abbott, Sonu Subudhi, Raphael Ferreira, Yetiş Gültekin, Sophie C. Steinbuch, Sophie E. Honeder, Ashwin S Kumar, Michelle Wu, Diya Ramesh, Jacob Hansen, Lisa M. Riedmayr, Mark Duquette, Ahmed Ali, Nicole Henning, Sharanya Sivanand, Tenzin Kunchok, Millenia Waite, Brian T. Do, Virginia Spanoudaki, Francisco J. Sánchez-Rivera, George M. Church, Rakesh K Jain, Matthew G. Vander Heiden. Assessment of metabolic vulnerabilities of breast cancer brain metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A007.
Abstract A010: Proteasome inhibitors induce a BAX and BAK independent, non-canonical apoptosis
Authors: Mukiza Tresor O , Enrique-Rodriguez Ricardo , Budhraja Amit , Brakefield Lauren , Moldoveanu Tudor , Opferman Joseph T
Published: June 2024

In the intrinsic pathway of apoptosis, death stimuli (including drugs, cellular stress, viral infections, etc.) trigger the oligomerization of BAX and BAK resulting in pore formation in the outer mitochondrial membrane to release cytochrome c from the intermembrane space. The released cytochrome c then activates APAF-1 and CASPASE9 to form a 1.4 MDa complex known as apoptosome, which recruits and activates downstream caspases that dismantle the cell. However, we have found that proteasome inhibition leads to a BAX and BAK independent apoptotic cell death. We show using immunofluorescence, fluorogenic assays, and flow cytometry that the proteasome inhibitors, bortezomib and MG-132, trigger a caspase dependent cell death that requires the apoptosome components APAF-1 and CASPASE9, but not cytochrome c. Furthermore, size exclusion chromatography revealed that unlike classical death stimuli, which induce the mega-dalton canonical apoptosome fomation, proteasome inhibitors induce a minor shift in APAF-1, forming a smaller, non-canonical apoptosome. Current efforts are focused on the identification of the APAF-1 activator. Our results indicate the existence of a non-canonical caspase-dependent cell death pathway, which could be a novel therapeutic target in malignancies by bypassing the BCL-2 family of apoptotic regulators.

Citation Format: Tresor O Mukiza, Ricardo Enrique-Rodriguez, Amit Budhraja, Lauren Brakefield, Tudor Moldoveanu, Joseph T Opferman. Proteasome inhibitors induce a BAX and BAK independent, non-canonical apoptosis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A010.
Abstract B002: POLB knockout is synthetic lethal with PARP inhibition leading to complete and durable responses in BRCA-mutant tumor xenografts
Authors: Bandi Madhavi
Published: June 2024

Despite the clinical benefit of PARP1/2 inhibitors (PARPi), which are FDA-approved for the treatment of certain BRCA-mutant cancers, many patients achieve incomplete disease control and develop progressive disease. Motivated by this clinical need, we utilized our CRISPR target discovery screening platform to identify novel targets that synergize with PARP inhibitor treatment. By conducting parallel screens in both BRCA-mutant and wildtype cells, we identified DNA polymerase beta (POLB) as a novel target that - when combined with PARPi - selectively kills BRCA-mutant lines while sparing normal cells. POLB knockout and cDNA rescue experiments using both BRCA1 and BRCA2-mutant isogenic cell lines further demonstrated that the catalytic activity of POLB is required for synthetic lethality with PARPi. Most strikingly, POLB knockout combined with sub-therapeutic doses of PARPi, led to profound tumor regression and prevented in vivo tumor regrowth, even after cessation of drug treatment. Mechanistically, POLB knockout is associated with increased single and double strand DNA breaks, accumulation of poly-ADP-ribose polymers, cell cycle arrest and apoptosis. Together, these results suggest that POLB inhibitors in combination with PARPi have the potential to drive deep and durable responses providing a novel therapeutic option for cancer patients with BRCA1/2-mutations.

Citation Format: Madhavi Bandi. POLB knockout is synthetic lethal with PARP inhibition leading to complete and durable responses in BRCA-mutant tumor xenografts [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B002.
Abstract B006: Data-driven discoveries of molecular mechanism and therapeutic vulnerabilities of CDK12 mutant tumors
Authors: Yang Lixing
Published: June 2024

Somatic structural variations (SVs) are common in cancer. Although a small fraction of SVs in breast and ovarian cancers can be attributed to homologous recombination deficiency, the underlying molecular mechanisms for the vast majority of somatic SVs remain unclear. Here, we focus on the roles of transcription and DNA replication collisions in genomic instability in cancer. Such collisions are unavoidable in cells since both transcription and replication use the same DNA as template. We hypothesized that transcription replication collisions (TRCs), if not properly repaired, would lead to collapsed replication forks and result in SVs. To this end, we studied somatic SVs in 6193 high-coverage whole-genome sequenced primary and metastatic tumors from three independent pan-cancer cohorts. A total of 13 conserved SV signatures, representing independent molecular mechanisms, were deconvoluted from these cohorts using non-negative matrix factorization approach. We detected replicated-strand bias, the expected footprint of transcription-replication collision, in large tandem duplications (TDs) across multiple cohorts. This bias was only observed in expressed genes, consistent with TRCs depending on transcription activity. Large TDs were abundant in female-specific (breast, ovarian and uterus), upper gastric-intestinal tract, and prostate cancers. They were associated with CDK12 mutations and worse patient survival. CDK12 is a cyclin-dependent kinase, a key regulator of transcription elongation and termination. Deleting or suppressing CDK12 using CRISPR-Cas9 in prostate cell lines increased RNA:DNA hybrids (R-loops), promoted TRCs, and ultimately led to large TDs. Finally, we found that cells lacking CDK12 were sensitive to WEE1, CHK1 and ATR inhibitors. In summary, our data suggest that large TDs in cancer form due to impaired TRC repair and can be used as a biomarker for prognosis and treatment.

Citation Format: Lixing Yang. Data-driven discoveries of molecular mechanism and therapeutic vulnerabilities of CDK12 mutant tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B006.
Abstract B010: Drug tolerant persister cancer cells escape therapy-induced senescence
Authors: Fortier Anne-Marie , Topolski Jason , Alzial Gabriel , Monast Anie , Kuasne Hellen , Zuo Dongmei , Pacis Alain , Deblois Genevieve , Park Morag
Published: June 2024

Triple-negative breast cancer (TNBC) accounts for 15% of breast cancers and is the most aggressive subtype lacking precision oncology therapeutic strategies. Standard-of-care is predominantly chemotherapy in the neoadjuvant setting (NACT). Despite good responses, ∼40% of TNBC patients develop resistance and present residual disease at surgery. Overcoming resistance and implementing better therapeutic options is critical. Our objectives are to develop targeting opportunities for drug tolerant persister (DTP) cells which underlie residual disease. Using our unique biobank of patient derived xenografts from treatment naive as well as NACT resistant TNBC, we developed longitudinal in vivo models of residual and relapse tumors to standard-of-care therapy. Transcriptomic analysis revealed transient metabolic changes such as oxidative phosphorylation, starvation and autophagy, associated with hallmarks of senescence at residual disease. We demonstrated that therapy-induced senescent cells in vitro can escape cell cycle arrest and resume proliferation through autophagy. Interfering with autophagy impairs redox balance, promotes ferroptosis and delays tumor relapse. These results support that autophagy is a promising targetable vulnerability in TNBC residual disease.

Citation Format: Anne-Marie Fortier, Jason Topolski, Gabriel Alzial, Anie Monast, Hellen Kuasne, Dongmei Zuo, Alain Pacis, Genevieve Deblois, Morag Park. Drug tolerant persister cancer cells escape therapy-induced senescence [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B010.
Abstract B016: Discovering novel synthetic lethal relationships with large-scale cellular simulations
Authors: Purcell Oliver , Lang Paul , Komianos James , Vashi Nimi
Published: June 2024

Synthetic Lethality (SL) is a compelling example of a large combinatorial space, with the number of (order-independent) pairwise combinations of human genes totaling approximately 400 million. When further considering higher-order combinations beyond pairs i.e. additional biomarkers that modulate the the efficacy of an SL pair, this space grows exponentially larger still. Understanding these higher-order combinations is crucial for the discovery of synthetic lethal pairs with better defined therapeutic windows and improved segmentation in clinical trials. As the size of this combinatorial space is far greater than can be searched by existing screening technologies, novel approaches are required to efficiently search this space and prioritize higher-order candidate SL combinations for screening. DeepOrigin is developing large-scale dynamical models of cellular systems to drive the in silico discovery of novel therapeutics across a range of diseases. These models can be simulated efficiently and in parallel, and are therefore ideally suited for searching large combinatorial spaces. We have applied our proprietary Cellular Simulation Pipeline to the problem of identifying higher-order combinations in Synthetic Lethality, so far predicting hundreds of novel synthetic lethal pairs. These pairs are currently being validated in vitro, and we present a selection of these results that demonstrate the utility of this approach. This approach could provide both novel therapeutic targets while providing additional stratification criteria for increased clinical study success.

Citation Format: Oliver Purcell, Paul Lang, James Komianos, Nimi Vashi. Discovering novel synthetic lethal relationships with large-scale cellular simulations [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B016.
Abstract B021: CFLAR targeting selectively exploits extrinsic apoptosis signaling in triple-negative breast cancer
Authors: Quereda Victor , O'Brien Shane W. , Della Pietra Tony C. , Foley James J. , Fedoriw Andy
Published: June 2024

The extrinsic apoptotic pathway activates programmed cell death through the binding of extracellular death ligands, such as TNFα, to their cognate receptors. Although some death ligands are often upregulated in the tumor microenvironment, this pathway is subverted in cancer cells to instead favor growth and survival rather than the induction of apoptosis. Reflecting the strict control cancer cells exert over this pathway, functional genomics screens, such as DepMap, have identified several of the extrinsic apoptotic components as essential targets, with selective dependency in a subset of cancer cell lines. We have genetically validated that downregulation of CFLAR, a negative regulator of the extrinsic apoptosis pathway, causes apoptosis and cell growth inhibition alone, but specially in combination with TNFα signaling, across multiple cancer types, with increase prevalence in Triple-negative breast cancer. Furthermore, we have shown that in order to have maximal activity most cell lines require targeting of CFLAR short isoform splicing variant. Importantly, CFLAR downregulation in non-tumoral models presented much less activity than the observed in the sensitive cancer models supporting the selective activity of CFLAR in a subset of cancer cells.

Citation Format: Victor Quereda, Shane W. O'Brien, Tony C. Della Pietra, James J. Foley, Andy Fedoriw. CFLAR targeting selectively exploits extrinsic apoptosis signaling in triple-negative breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B021.
Abstract B024: Leveraging synthetic lethality across EP300-mutant solid cancers through selective CBP degradation
Authors: Sappal Darshan , Adam Ammar , Ahmad Hafiz , Adams Benjamin , Adhikari Ketaki , Austin Wesley , Bullock Breanna , Di Bernardo Julie , Dixon Thomas , Daniels Danette , Dominici Claudi , Elliott GiNell , Ethell Brian , Gervais Anais , Hossain Md Imran , Huang David , Lahr David , La Bonte Laura , Lin Mei Yun , Mayhew David , Mizeracka Karolina , Negretti Solymar , Nguyen Tyler , Prifti Olga , Schiller Shawn , Sherbanee Brenna , Terry David , Ucisik Nihan , Wittenborn Elizabeth , Wilson Molly M , Zhou Qianhe , Zimmerman Mark
Published: June 2024

CREB binding protein (CBP) and E1A binding protein P300 (EP300) are paralog histone acetyltransferases that can function as transcriptional coactivators to regulate diverse cellular processes. Mutations in CBP and EP300 have been implicated in the biology of various cancer types. Functional genomic screens have revealed a bidirectional synthetic lethal relationship between these paralogs in tumor cells, highlighting a therapeutic opportunity in targeting CBP selectively in EP300-mutant cancers while sparing other tissues in which EP300 is intact. This strategy would enable an improved therapeutic window beyond those observed with dual CBP/EP300 inhibitors, which exhibit hematological toxicities. However, due to the high degree of homology between the CBP and EP300 proteins, identifying chemical matter that selectively disrupts CBP activity has proven challenging. Here, we demonstrate selective and potent CBP degrader compounds that disrupt proliferation in EP300-mutant cancer cell line models. Notably, these degraders have little impact on cell lines with intact EP300. Moreover, in cell line-derived xenograft (CDX) tumor models, we achieve potent and sustained CBP degradation and associated tumor growth inhibition. Our CBP-selective protein degraders have the potential to be a first-in-class therapeutic option for patients with tumors harboring EP300 mutations.

Citation Format: Darshan Sappal, Ammar Adam, Hafiz Ahmad, Benjamin Adams, Ketaki Adhikari, Wesley Austin, Breanna Bullock, Julie Di Bernardo, Thomas Dixon, Danette Daniels, Claudi Dominici, GiNell Elliott, Brian Ethell, Anais Gervais, Md Imran Hossain, David Huang, David Lahr, Laura La Bonte, Mei Yun Lin, David Mayhew, Karolina Mizeracka, Solymar Negretti, Tyler Nguyen, Olga Prifti, Shawn Schiller, Brenna Sherbanee, David Terry, Nihan Ucisik, Elizabeth Wittenborn, Molly M Wilson, Qianhe Zhou, Mark Zimmerman. Leveraging synthetic lethality across EP300-mutant solid cancers through selective CBP degradation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B024.
Abstract B025: A genome-wide CRISPR screen identifies synthetic lethality of double-stranded RNA with BRCA1 loss
Authors: Mazzarella Luca , Trastulli Deborah , Galavotti Sara , Vozza Gianluca , Pinamonti Veronica , Zagaria Nunzia
Published: June 2024

Double-stranded RNAs (dsRNAs) are potent immunostimulatory nucleic acids of viral origin but also physiologically produced by mammalian cells. Recent studies demonstrated that elevating dsRNA levels, either exogenously through dsRNA mimetics like Polyinosinic-polycytidylic acid (pI:C) or endogenously through epigenetic modulation of retroviral elements, can elicit anticancer effects. In response to dsRNA, cells elicit a dual response consisting in Interferon (IFN) production and translational shutdown associated, in some cells, with cell death. These two responses are linked in a feed-forward loop in which induced cytokines themselves enhance dsRNA sensing by the death-inducing pathway, complicating our understanding of the cell-intrinsic mechanisms at play. The 2',5'-oligoadenylate synthetase (OAS)-RNASEL system is widely thought to be the main responsible for dsRNA-induced cell death, but it remains unclear how its activity leads to cell death. To elucidate these mechanisms, we decided to minimize the impact of interferon modulation by studying dsRNA-induced death in interferon-saturated conditions. We performed a genome-wide CRISPR screen for factors involved in dsRNA-induced death in our interferon-saturated conditions in HT29 cells. Pathway enrichment analysis of screen hits revealed that RNA surveillance, RNA Polymerase II Transcription Initiation, Mitochondrial translation and respiratory chain and DNA Repair genes have a protective role against dsRNA increase. In particular, we identifiedBRCA1 but not BRCA2 as a candidate hit. The differential sensitivity of BRCA1-KO cells was subsequently validated in cloncal populations. Ongoing research is aimed at validating this interaction in vivo models. Our work shed light on potential new mechanisms involved in dsRNA dependent cell death, revealing a connection with DNA damage and BRCA1. If confirmed, these findings may pave the way for the use of dsRNA mimetics, possibly in conjunction with immune checkpoint inhibitors, in the treatment of BRCA1-mutated tumors.

Citation Format: Luca Mazzarella, Deborah Trastulli, Sara Galavotti, Gianluca Vozza, Veronica Pinamonti, Nunzia Zagaria. A genome-wide CRISPR screen identifies synthetic lethality of double-stranded RNA with BRCA1 loss [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B025.
Abstract IA006: Synthetic lethalities for SWI/SNF mutant cancers
Authors: Roberts Charles W.M.
Published: June 2024

Genes that encode subunits of SWI/SNF (BAF) chromatin remodeling complexes are mutated in over 20% of cancers. These include recurrent mutations of ARID1A (BAF250a) in ovarian, endometrioid, bladder, stomach, colorectal and pancreatic cancers and neuroblastoma; of the SMARCA4 (BRG1) subunit in medulloblastomas and non-small cell lung cancers; of the PBRM1 subunit in renal carcinomas; of the ARID2 subunit in hepatocellular, lung, and pancreas carcinomas as well as melanomas; of the BRD7 subunit in breast cancers. The SWI/SNF complex includes both core and lineage-specific subunits and utilizes the energy of ATP to modulate chromatin structure and regulate transcription. My laboratory began studying the SWI/SNF complex when SMARCB1 (INI1/SNF5/BAF47) became the first SWI/SNF subunit linked to tumor suppression when it was found to be biallelically inactivated in nearly all cases of a highly aggressive type of pediatric cancer called malignant rhabdoid tumor (MRT). Despite the extremely aggressive and lethal nature of MRT we have shown that these cancers are diploid and have remarkably simple genomes. We leverage this model tumor to identify how SWI/SNF complexes function, to determine how mutation of SWI/SNF subunits drive cancer and other diseases, and to identify therapeutic vulnerabilities that result from SWI/SNF mutations. We have leverage the Cancer Dependency Map, and the Pediatric Cancer Dependencies Accelerator, to systematically identify robust and impactful synthethic lethalities resulting from SWI/SNF mutations. These mechanisms and insights will be presented.

Citation Format: Charles W.M. Roberts. Synthetic lethalities for SWI/SNF mutant cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA006.