bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract SY07-03: Cell competition shapes metastatic latency and relapse
Authors: Malladi Srinivas 
Published: April 2024

Abstract
Cell competition, a fitness-sensing process, is essential for tissue homeostasis. Using cancer metastatic latency models, we show that cell competition results in the displacement of latent metastatic (Lat-M) cells from the primary tumor. Lat-M cells resist anoikis and survive as residual metastatic disease. A remodeled extracellular matrix facilitates Lat-M cell displacement and survival in circulation. Disrupting cell competition dynamics by depleting secreted protein and rich in cysteine (SPARC) reduced displacement from orthotopic tumors and attenuated metastases. In contrast, depletion of SPARC after extravasation in lung-resident Lat-M cells increased metastatic outgrowth. Furthermore, multiregional transcriptomic analyses of matched primary tumors and metachronous metastases from patients with kidney cancer identified tumor subclones with Lat-M traits. Kidney cancer enriched for these Lat-M traits had a rapid onset of metachronous metastases and significantly reduced disease-free survival. Thus, an unexpected consequence of cell competition is the displacement of cells with Lat-M potential, thereby shaping metastatic latency and relapse. Overall, we demonstrate that cell competition within the primary tumor results in the displacement of Lat-M cells. We are investigating the impact of altering cell competition dynamics on metastatic incidence that may guide strategies to limit metastatic recurrences.
Citation Format: Srinivas Malladi. Cell competition shapes metastatic latency and relapse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY07-03.
Abstract SY31-03: Cancer takes a nerve: Challenges and opportunities in cancer neuroscience
Authors: Amit Moran 
Published: April 2024

Abstract
Neuronal reprogramming in cancer represents a groundbreaking frontier that intricately links the nervous system's plasticity to tumor progression and response to treatment. This process involves the aberrant activation or suppression of neuronal signals that can significantly influence cancer cell behavior, including proliferation, migration, and resistance to therapies. The concept of repurposing drugs originally designed to target the nervous system for use in clinical oncology offers a promising therapeutic strategy, potentially revolutionizing cancer treatment. By intercepting neuronal pathways that cancer cells exploit for their growth and survival, these drugs could modulate the tumor microenvironment, enhance the efficacy of conventional therapies, and potentially reverse drug resistance mechanisms. Moreover, targeting neuronal signaling in cancer could lead to improvements in patients' functional outcomes, mitigating cancer-related neurological deficits and improving quality of life. Importantly, this approach may also have profound implications for survival outcomes, as modulating the neuro-cancer interface could slow tumor progression and reduce metastatic spread. The repurposing of neuroactive drugs for cancer treatment thus opens a new avenue for personalized medicine, where the intricacies of neuronal reprogramming are leveraged to tailor therapy, improve response rates, and ultimately, enhance patient survival and well-being.
Citation Format: Moran Amit. Cancer takes a nerve: Challenges and opportunities in cancer neuroscience [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY31-03.
Abstract SY35-02: Spatial mapping of mitochondrial networks in lung cancer
Authors: Shackelford David B. 
Published: April 2024

Abstract
Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional profiling of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform comprised of positron emission tomography (PET) imaging, respirometry and 3-dimensional scanning block-face electron microscopy (3D SBEM). Interestingly, the diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumors align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumor cells. In tumors with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. In contrast, we discovered that in tumors with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated i) peri-nuclear localization of mitochondria, ii) structural remodeling of cristae and iii) mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumors. Structure-and-function studies defining the relationship between mitochondrial architecture and metabolic dependencies may hold promise as strategies to profile metabolic liabilities unique to lung cancer subtypes. We anticipate that coupling PET imaging with 3D SBEM will have dynamic applications beyond that of lung cancer and enrich our understanding of how mitochondrial bioenergetics impact human disease.
Citation Format: David B. Shackelford. Spatial mapping of mitochondrial networks in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY35-02.
Abstract SY41-02: Experimental methods for high throughput discovery and validation of tumor antigens
Authors: Heath James R. 
Published: April 2024

Abstract
The discovery and validation of tumor associated T-cell antigens, which can include neoantigens, viral antigens, cancer testis antigens, and others, is fundamental to the design of both cancer vaccines and engineered cell cancer immunotherapies. However, identifying tumor specific antigens that are highly presented within tumors, and identifying and validating T cell receptors (TCRs) that are specific to those antigens, remains a non-trivial exercise. Even identifying and validating a single antigen-specific T cell clonotype for advancement into a clinic trial remains a daunting task. In this talk, I will discuss a number of new experimental and computational tools that are designed to accelerate this process. The experimental toolsets include reagents and strategies that allow for the capture and analysis of T cells specific to hundreds to thousands of tumor-associated Class I and Class II antigens simultaneously, with as many as 100 patient bloods analyzed in a single experiment. Single cell analysis of the resulting data yields a deep characterization of the captured T cells, including T cell receptor α/β genes, antigen-MHC specificity, T cell phenotype, and donor identification. This type of analysis, in turn, provides large data bases that can fuel new computational strategies that can be harnessed (at a still early stage) to predict which TCRα/β genes associate with which putative antigen-MHCs, or to extract the biochemical and biophysical characteristics of TCR-antigen pairings that influence T cell phenotype. Thus, this presentation will span both new experimental and new computational toolsets.
Citation Format: James R. Heath. Experimental methods for high throughput discovery and validation of tumor antigens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY41-02.
A benchmark of health insurance fraud detection using machine learning techniques
Authors: Cherkaoui Ossama , Anoun Houda , Maizate Abderrahim 
Published: April 2024

Health insurance fraud is a complex problem that also has a significant financial impact. Recently, with the availability of large volumes of data and the evolution of computing power, machine learning techniques have become the preferred method for fraud detection. However, the main difficulty facing researchers in this field is the lack of real data sets and the absence of reliable fraud labels. Most published studies use aggregated provider-level or simulated data to test fraud detection algorithms, which may not deliver accurate results. The present study aims to provide a more accurate assessment of fraud detection methods by using real detailed health insurance claims data to compare six of the most common supervised classification algorithms including neural networks and the use of two categorical feature preparation methods. The study was conducted under the guidance of insurance experts, who provided the fraud label inference rules and reviewed the results. A comprehensive description of the benchmarking process and an interpretation of the results are provided in this paper. The results show that supervised classification can be used effectively to detect health insurance fraud, improving detection accuracy by a factor of 4.2 (84% recall for a positive rate of 20%).<p> </p>
Selective Neural Entrainment Reveals Hierarchical Tuning to Linguistic Regularities in Reading
Authors: De Rosa Mara , Vignali Lorenzo , D’Urso Anna , Ktori Maria , Bottini Roberto , Crepaldi Davide 
Published: April 2024

Abstract
Reading is both a visual and a linguistic task, and as such it relies on both general-purpose, visual mechanisms and more abstract, meaning-oriented processes. Disentangling the roles of these resources is of paramount importance in reading research. The present study capitalizes on the coupling of fast periodic visual stimulation and MEG recordings to address this issue and investigate the role of different kinds of visual and linguistic units in the visual word identification system. We compared strings of pseudo-characters; strings of consonants (e.g., sfcl); readable, but unattested strings (e.g., amsi); frequent, but non-meaningful chunks (e.g., idge); suffixes (e.g., ment); and words (e.g., vibe); and looked for discrimination responses with a particular focus on the ventral, occipito-temporal regions. The results revealed sensitivity to alphabetic, readable, familiar, and lexical stimuli. Interestingly, there was no discrimination between suffixes and equally frequent, but meaningless endings, thus highlighting a lack of sensitivity to semantics. Taken together, the data suggest that the visual word identification system, at least in its early processing stages, is particularly tuned to form-based regularities, most likely reflecting its reliance on general-purpose, statistical learning mechanisms that are a core feature of the visual system as implemented in the ventral stream.
Multiagency Ensemble Forecast of Wildfire Air Quality in the United States: Toward Community Consensus of Early Warning
Authors: Li Yunyao , Tong Daniel , Makkaroon Peewara , DelSole Timothy , Tang Youhua , Campbell Patrick , Baker Barry , Cohen Mark , Darmenov Anton , Ahmadov Ravan , James Eric , Hyer Edward , Xian Peng 
Published: April 2024

Abstract
Wildfires pose increasing risks to human health and properties in North America. Due to large uncertainties in fire emission, transport, and chemical transformation, it remains challenging to accurately predict air quality during wildfire events, hindering our collective capability to issue effective early warnings to protect public health and welfare. Here, we present a new real-time Hazardous Air Quality Ensemble System (HAQES) by leveraging various wildfire smoke forecasts from three U.S. federal agencies (NOAA, NASA, and Navy). Compared to individual models, the HAQES ensemble forecast significantly enhances forecast accuracy. To further enhance forecasting performance, a weighted ensemble forecast approach was introduced and tested. Compared to the unweighted ensemble mean, the multilinear regression weighted ensemble reduced fractional bias by 34% in the major fire regions, false alarm rate by 72%, and increased hit rate by 17%. Finally, we improved the weighted ensemble using quantile regression and weighted regression methods to enhance the forecast of extreme air quality events. The advanced weighted ensemble increased the PM2.5 exceedance hit rate by 55% compared to the ensemble mean. Our findings provide insights into the development of advanced ensemble forecast methods for wildfire air quality, offering a practical way to enhance decision-making support to protect public health.
Hemophilia B and gene therapy: a new chapter with etranacogene dezaparvovec
Authors: Anguela Xavier M. , High Katherine A. 
Published: April 2024

Abstract
The US Food and Drug Administration (FDA)’s authorization of etranacogene dezaparvovec (Hemgenix) is a significant milestone, constituting not only the first FDA approval of a gene therapy for hemophilia but also the first approval of a liver-targeted adeno-associated virus vector gene therapy. This review summarizes the nonclinical studies and clinical development that supported regulatory clearance. Similar to other gene therapies for single gene disorders, both the short-term safety and the phenotypic improvement were unequivocal, justifying the modest-sized safety and efficacy database, which included 57 participants across the phase 2b (3 participants) and phase 3 (54 participants) studies. The most common adverse reactions included liver enzyme elevation, headache, flu-like symptoms, infusion-related reactions, creatine kinase elevation, malaise, and fatigue; these were mostly transient. One participant had hepatocellular carcinoma on a study-mandated liver ultrasound conducted 1 year after vector infusion; molecular analysis of the resected tumor showed no evidence of vector-related insertional mutagenesis as the etiology. A remarkable 96% of participants in the phase 3 trial were able to stop factor IX (FIX) prophylaxis, with the study demonstrating noninferiority to FIX prophylaxis in terms of the primary end point, annualized bleeding rate. Key secondary end points such as the annualized infusion rate, which declined by 97%, and the plasma FIX activity level at 18 months after infusion, with least squares mean increase of 34.3 percentage points compared with baseline, were both clinically and statistically significant. The FDA’s landmark approval of Hemgenix as a pioneering treatment for hemophilia stands on the shoulders of &gt;20 years of gene therapy clinical research and heralds a promising future for genomic medicines.
Immunoglobulin replacement vs prophylactic antibiotics for hypogammaglobulinemia secondary to hematological malignancy
Authors: McQuilten Zoe K. , Weinkove Robert , Thao Le Thi Phuong , Crispin Philip , Degelia Amber , Dendle Claire , Gilbertson Michael , Johnston Anna , Keegan Anastazia , Pepperell Dominic , Pullon Humphrey , Reynolds John , van Tonder Tina , Trotman Judith , Waters Neil , Wellard Cameron , Weston Helen , Morrissey C. Orla , Wood Erica M. 
Published: April 2024

Abstract
Immunoglobulin replacement and prophylactic antibiotics are commonly used to prevent infections in patients with secondary hypogammaglobulinemia due to hematological malignancies but have never been directly compared. In this randomized controlled feasibility trial conducted in 7 hospitals in Australia and New Zealand, we enrolled patients with secondary hypogammaglobulinemia with either a history of recurrent/severe infection or an immunoglobulin G level &lt;4 g/L. Participants were randomized in a 1:2 ratio to immunoglobulin (0.4 g/kg per 4 weeks IV) or daily antibiotics (trimethoprim-sulfamethoxazole 160 mg/800 mg or, if contraindicated, 100 mg doxycycline) for 12 months. Participants allocated to antibiotics were allowed to crossover after grade ≥3 infections. The primary outcome was proportion of patients alive on the assigned treatment 12 months after randomization. Between August 2017 and April 2019, 63 patients were randomized: 42 to antibiotics and 21 to immunoglobulin. Proportion of participants alive on allocated treatment at 12 months was 76% in the immunoglobulin and 71% in the antibiotic arm (Fisher exact test P=.77; odds ratio, 0.78; 95% CI, 0.22-2.52). The lower quartile for time to first major infection (median, not reached) was 11.1 months for the immunoglobulin and 9.7 months for the antibiotic arm (log-rank test, P=.65). Three participants in the immunoglobulin and 2 in the antibiotic arm had grade ≥3 treatment-related adverse events. A similar proportion of participants remained on antibiotic prophylaxis at 12 months to those on immunoglobulin, with similar rates of major infections. Our findings support the feasibility of progressing to a phase 3 trial. Trial registration #ACTRN12616001723471.
Analysis of influencing factors and construction of prediction model for postoperative nausea and vomiting in patients undergoing laparoscopic sleeve gastrectomy: a single-center retrospective cohort study
Authors: Liao Bucheng , Liao Wuhao , Wu Xinhai , Liu Shujuan , Li Yanze , Qin Ruixia , Yin Shuang 
Published: April 2024

Abstract
Background
With the increasing number of bariatric surgeries, the high incidence of postoperative nausea and vomiting (PONV) associated with this surgery has also gradually attracted attention. Among the common bariatric surgery methods, patients undergoing sleeve gastrectomy (SG) have the highest incidence of nausea and vomiting. The mechanism of occurrence of PONV is very complex. This study aims to explore the influencing factors of PONV in patients undergoing laparoscopic sleeve gastrectomy (LSG) and construct a nomogram prediction model based on these factors.

Methods
With the approval of the Ethics Committee, the electronic medical records of patients who underwent LSG from July 2022 to May 2023 were collected retrospectively.

Results
A total of 114 patients with complete medical records who underwent LSG from July 2022 to May 2023 were included in this study. Among them, 46 patients developed PONV, resulting in a PONV incidence rate of 40.4%. Multivariate logistic regression analysis revealed that female gender, the use of inhalation anesthesia, and operation time ≥ 120 min were risk factors for PONV in LSG. Additionally, the use of more than two kinds of antiemetic drugs was identified as a protective factor. Based on these factors, a nomogram model was constructed.

Conclusion
PONV in patients undergoing LSG is related to gender, type of anesthesia, duration of surgery, and combination therapy with antiemetic drugs. The nomogram prediction model constructed in this study demonstrates high accuracy and discrimination in predicting the occurrence of PONV in patients undergoing LSG.
A study of hospitalized COVID-19 patients with AKI in a setting of multiracial developing country
Authors: Ooi S. H. , Ng K. P. , Sthaneshwar Pavai , Lim S. K. , Khor P. Y. , Lim J. Y. , Siow W. S. , Lim K. W. , Azlan Muhummad 
Published: April 2024

Abstract
Background
The commonest indication for hospitalization in COVID-19 patients is hypoxemia or severe respiratory symptoms. However, COVID-19 disease may result in extrapulmonary complications including kidney-related pathology. The reported incidence of renal involvement related to COVID infection varies based on geographical location.

Objective
This study aimed to assess the incidence rate of AKI in hospitalized COVID-19 patients and identify risk factors and prognostic predictors.

Method
In this retrospective study, we recruited hospitalized COVID-19 patients from January 2021 until June 2021 at the University Malaya Medical Center. The inclusion criteria were hospitalized for ≥ 48 h with confirmed COVID-19 infection and at least 18 years old. Patient demographic and clinical data were collected from electronic medical records. The staging of AKI was based on criteria as per KDIGO guidelines.

Results
One thousand five hundred twenty-nine COVID patients fulfilled the inclusion criteria with a male-to-female ratio of 759 (49.6%) to 770 (50.3%). The median age was 55 (IQR: 36–66). 500 patients (32.7%) had diabetes, 621 (40.6%) had hypertension, and 5.6% (n = 85) had pre-existing chronic kidney disease (CKD). The incidence rate of AKI was 21.1% (n = 323). The percentage of COVID patients in different AKI stages of 1,2 and 3 were 16.3%, 2.1%, and 2.7%, respectively. Fifteen hospitalized patients (0.98%) required renal replacement therapy. 58.8% (n = 190) of AKI group had complete recovery of kidney function.
Demographic factors included age (p < 0.001), diabetes (p < 0.001), hypertension (p < 0.012), CKD (p < 0.001), and vaccination status (p = 0.042) were associated with an increased risk of developing AKI. We found that the AKI cohort had statistically significant lower platelet counts and higher ferritin levels than the non-AKI cohort. AKI is a risk predictor of prolonged hospitalization (p < 0.001) and higher mortality rates (P < 0.001).

Conclusion
AKI is a common clinical complication among hospitalized COVID-19 patients. The etiology of AKI is multifactorial and may have an adverse impact on patient morbidity and mortality.