bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying Oncology Clinical Trial Candidates Using Artificial Intelligence Predictions of Treatment Change: A Pilot Implementation Study
Authors: Kehl Kenneth L. , Mazor Tali , Trukhanov Pavel , Lindsay James , Galvin Matthew R. , Farhat Karim S. , McClure Emily , Giordano Antonio , Gandhi Leena , Schrag Deborah , Hassett Michael J. , Cerami Ethan 
Published: March 2024

PURPOSE Precision oncology clinical trials often struggle to accrue, partly because it is difficult to find potentially eligible patients at moments when they need new treatment. We piloted deployment of artificial intelligence tools to identify such patients at a large academic cancer center. PATIENTS AND METHODS Neural networks that process radiology reports to identify patients likely to start new systemic therapy were applied prospectively for patients with solid tumors that had undergone next-generation sequencing at our center. Model output was linked to the MatchMiner tool, which matches patients to trials using tumor genomics. Reports listing genomically matched patients, sorted by probability of treatment change, were provided weekly to an oncology nurse navigator (ONN) coordinating recruitment to nine early-phase trials. The ONN contacted treating oncologists when patients likely to change treatment appeared potentially trial-eligible. RESULTS Within weekly reports to the ONN, 60,199 patient-trial matches were generated for 2,150 patients on the basis of genomics alone. Of these, 3,168 patient-trial matches (5%) corresponding to 525 patients were flagged for ONN review by our model, representing a 95% reduction in review compared with manual review of all patient-trial matches weekly. After ONN review for potential eligibility, treating oncologists for 74 patients were contacted. Common reasons for not contacting treating oncologists included cases where patients had already decided to continue current treatment (21%); the trial had no slots (14%); or the patient was ineligible on ONN review (12%). Of 74 patients whose oncologists were contacted, 10 (14%) had a consult regarding a trial and five (7%) enrolled. CONCLUSION This approach facilitated identification of potential patients for clinical trials in real time, but further work to improve accrual must address the many other barriers to trial enrollment in precision oncology research.
Transcranial Magnetic Stimulation–Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas
Authors: Lavrador José Pedro , Mirallave-Pescador Ana , Soumpasis Christos , Díaz Baamonde Alba , Aliaga-Arias Jahard , Baig Mirza Asfand , Patel Sabina , David Siado Mosquera José , Gullan Richard , Ashkan Keyoumars , Bhangoo Ranjeev , Vergani Francesco 
Published: March 2024

BACKGROUND:
Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation.

METHODS:
This was a retrospective cohort study of patients who underwent surgery for motor-eloquent gliomas between 2018 and 2022. Ten healthy subjects were included. Preoperative nTMS-derived variables were collected: resting motor threshold (RMT), interhemispheric RMT ratio (iRMTr)—abnormal if above 10%—and cortical excitability score—number of abnormal iRMTrs. World Health Organization (WHO) grade and molecular profile were collected to characterize each tumor. ML models were fitted to the data after statistical feature selection to predict tumor grade.

RESULTS:
A total of 177 patients were recruited: WHO grade 2—32 patients, WHO grade 3—65 patients, and WHO grade 4—80 patients. For the upper limb, abnormal iRMTr were identified in 22.7% of WHO grade 2, 62.5% of WHO grade 3, and 75.4% of WHO grade 4 patients. For the lower limb, iRMTr was abnormal in 23.1% of WHO grade 2, 67.6% of WHO grade 3%, and 63.6% of WHO grade 4 patients. Cortical excitability score (P = .04) was statistically significantly related with WHO grading. Using these variables as predictors, the ML model had an accuracy of 0.57 to predict WHO grade 4 lesions. In subgroup analysis of high-grade gliomas vs low-grade gliomas, the accuracy for high-grade gliomas prediction increased to 0.83. The inclusion of molecular data into the model—IDH mutation and 1p19q codeletion status—increases the accuracy of the model in predicting tumor grading (0.95 and 0.74, respectively).

CONCLUSION:
ML algorithms based on nTMS-derived interhemispheric excitability assessment provide accurate predictions of HGGs affecting the motor pathway. Their accuracy is further increased when molecular data are fitted onto the model paving the way for a joint preoperative approach with radiogenomics.
Efficacy of Biportal Endoscopic Decompression for Lumbar Spinal Stenosis: A Meta-Analysis With Single-Arm Analysis and Comparative Analysis With Microscopic Decompression and Uniportal Endoscopic Decompression
Authors: Lv Shuangwen , Lv Haiwen , He Yupeng , Xia Xiansheng 
Published: March 2024

BACKGROUND AND OBJECTIVE:
Biportal endoscopic decompression is a minimally invasive surgical technique for lumbar spinal stenosis (LSS). This meta-analysis aimed to evaluate the efficacy and safety of biportal endoscopic decompression through both a single-arm analysis and a comparative analysis.

METHODS:
A comprehensive literature search was conducted to identify eligible studies reporting the outcomes of biportal endoscopic decompression for LSS. Single-arm analysis and comparisons with microscopic and uniportal endoscopic decompression were performed. Evaluated outcomes included visual analog scale (VAS) scores for back pain and leg pain, Oswestry Disability Index (ODI) scores, operation time, estimated blood loss, duration of hospital stay, and adverse events.

RESULTS:
Single-arm analysis demonstrated significant improvements in VAS back pain, VAS leg pain, and ODI scores after biportal endoscopic decompression at postoperative 1-day to 36-month follow-up (all P < .001), compared with preoperative levels. The pooled mean single-level operation time was 71.44 min, and the pooled mean hospital stay was 3.63 days. The overall adverse event rate was 4.0%, with dural tear being the most common complication (3.0%). Compared with microscopic decompression, biportal endoscopic decompression showed significantly lower VAS back pain at 1-month (P < .001) and 6-month (P < .001) follow-up; lower VAS leg pain at 1-month (P = .045) follow-up; lower ODI scores at 3-month (P < .001), 12-month (P = .017), and >12-month (P = .007) follow-up; lower estimated blood loss (P = .003); and shorter hospital stay (P < .001). Adverse event rates did not differ between the techniques. No significant differences were observed between biportal endoscopic and uniportal endoscopic decompression groups for most efficacy and safety outcomes.

CONCLUSION:
Biportal endoscopic decompression emerges as a safe and effective alternative for LSS, presenting potential advantages over the microscopic technique and comparable efficacy with the uniportal endoscopic technique.
Discontinuous, biphasic, ontogenetic shifts in the metabolic allometry of aquatic animals?
Authors: Packard Gary C. 
Published: March 2024

ABSTRACT
Several investigations in recent years have reported patterns of discontinuous, biphasic, loglinear variation in the metabolic allometry of aquatic animals. These putative shifts in pattern of allometry have been attributed to changes in the primary site for gas exchange from cutaneous to branchial as animals undergo ontogenetic changes in size, shape, and surface area. Because of the important implications of the earlier research with regard to both physiology and evolution, I re-examined data that purportedly support claims of discontinuous, biphasic allometry in oxygen consumption versus body size of American eels (Anguilla rostrata) and spiny lobsters (Sagmariasus verreauxi). I used ANCOVA to fit three different statistical models to each set of logarithmic transformations and then assessed the fits by Akaike's Information Criterion. The observations for both species were described better by a single straight line fitted to the full distribution than by a biphasic model. Eels, lobsters, and other aquatic animals undergo changes in shape and surface area as they grow, but such changes are not necessarily accompanied by changes in the pattern of metabolic allometry.
Interactions between U and V sex chromosomes during the life cycle of Ectocarpus
Authors: Vigneau Jeromine , Martinho Claudia , Godfroy Olivier , Zheng Min , Haas Fabian B. , Borg Michael , Coelho Susana M. 
Published: March 2024

ABSTRACT
In many animals and flowering plants, sex determination occurs in the diploid phase of the life cycle with XX/XY or ZW/ZZ sex chromosomes. However, in early diverging plants and most macroalgae, sex is determined by female (U) or male (V) sex chromosomes in a haploid phase called the gametophyte. Once the U and V chromosomes unite at fertilization to produce a diploid sporophyte, sex determination no longer occurs, raising key questions about the fate of the U and V sex chromosomes in the sporophyte phase. Here, we investigate genetic and molecular interactions of the UV sex chromosomes in both the haploid and diploid phases of the brown alga Ectocarpus. We reveal extensive developmental regulation of sex chromosome genes across its life cycle and implicate the TALE-HD transcription factor OUROBOROS in suppressing sex determination in the diploid phase. Small RNAs may also play a role in the repression of a female sex-linked gene, and transition to the diploid sporophyte coincides with major reconfiguration of histone H3K79me2, suggesting a more intricate role for this histone mark in Ectocarpus development than previously appreciated.
Optimal Investment Strategy for α-Robust Utility Maximization Problem
Authors: Yang Zhou , Li Danping , Zeng Yan , Liu Guanting 
Published: March 2024

In reality, investors are uncertain about the dynamics of risky asset returns. Therefore, investors prefer to make robust investment decisions. In this paper, we propose an α-robust utility maximization problem under uncertain parameters. The investor is allowed to invest in a financial market consisting of a risk-free asset and a risky asset. The uncertainty about the expected return rate is parameterized by a nonempty set. Different from most existing literature on robust utility maximization problems where investors are generally assumed to be extremely ambiguity averse because they tend to consider only expected utility in the worst-case scenario, we pay attention to the investors who are not only ambiguity averse but also ambiguity seeking. Under power utility, we provide the implicit function representations for the precommitted strategy, equilibrium strategy of the open-loop type, and equilibrium strategy of the closed-loop type. Some properties about the optimal trading strategies, the best-case and worst-case parameters under three different kinds of strategies, are provided. Funding: This work was supported by National Natural Science Foundation of China [Grants 12071147, 12171169, 12271171, 12371470, 71721001, 71931004, 72371256], the Shanghai Philosophy Social Science Planning Office Project [Grant 2022ZJB005], Fundamental Research Funds for the Central Universities [Grant 2022QKT001], the Excellent Young Team Project Natural Science Foundation of Guangdong Province of China [Grant 2023B1515040001], the Philosophy and Social Science Programming Foundation of Guangdong Province [Grant GD22CYJ17], the Nature Science Foundation of Guangdong Province of China [Grant 2022A1515011472], and the 111 Project [Grant B14019].
Product Service Outsourcing: Impact of Environment Uncertainty and Partial Observability
Authors: Wang Yimin , Li Mei , Ma Ning , Zhang Heng 
Published: March 2024

Problem definition: Product service plays a crucial role for brands to retain customers and spur revenue growth. It is, however, often outsourced to a third-party provider, driven by cost savings and the ability to focus on core businesses. Although there is a large body of literature studying service outsourcing, the impact of service environment uncertainty (i.e., changing customer needs and shifting resource requirements) has received sparse attention in the past but is becoming a major concern because of increased market turbulence. This research explores how environment uncertainty in service provision influences a brand’s intent to outsource, and, if the brand decides to outsource, how it can retain the potential cost advantages offered by a third-party provider. Methodology/results: This research develops a normative model to explore key drivers that impact service outsourcing outcomes under environment uncertainty and partial observability. We find that environment uncertainty can accelerate a brand’s propensity to outsource, and a brand typically benefits from outsourcing initially. Yet, we show that such benefits can dissipate over time because of partial observability. Monitoring efforts help to mitigate the adverse impact of environment uncertainty and partial observability, but cannot attain anticipated outsourcing benefits unless monitoring is costless. In contrast, nudging service providers to self-report the cost of resources is effective even if the monitoring cost is high. Managerial implications: Brands should carefully consider environment uncertainty, partial observability, and monitoring ability when deciding whether to outsource product services to third-party providers. A heuristic monitoring policy can be effective when the monitoring cost is very high or very low but can perform poorly when the monitoring cost is in the intermediate range. Thus, outsourcing is more attractive when environment uncertainty is significant, but the value of outsourcing can only be realized when (a) partial observability is insignificant, (b) monitoring is inexpensive, or (c) provider self-reporting can be nudged. If none of the conditions hold, then the brand can suffer significant losses from the anticipated benefits of product service outsourcing. Funding: This research is partially supported by the first author's 2022 Dean’s Excellence Summer Research Grant from W. P. Carey School of Business, Arizona State University. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0222 .
Design of Patient Visit Itineraries in Tandem Systems
Authors: Liu Nan , Wan Guohua , Wang Shan 
Published: March 2024

Problem definition: Multistage service is common in healthcare. One widely adopted approach to manage patient visits in multistage service is to provide patients with visit itineraries that specify personalized appointment time for each patient at each service stage. We study how to design such visit itineraries. Methodology/results: We develop the first optimization modeling framework to provide each patient with a personalized visit itinerary in a tandem (healthcare) service system. Due to interdependencies among stages, our model loses those elegant properties (e.g., L-convexity and submodularity) often utilized to solve the classic single-stage models. To address these challenges, we develop two original reformulations. One is directly amenable to off-the-shelf optimization software, and the other is a concave minimization problem over a polyhedron shown to have neat structural properties, based on which we develop efficient solution algorithms. In addition to these exact solution approaches, we propose an approximation approach with a provable optimality bound and numerically validated performance to serve as an easy-to-implement heuristic. A case study populated by data from the Dana-Farber Cancer Institute shows that our approach makes a remarkable 28% cost reduction over practice on average. Managerial implications: Common approaches used in practice are based on simple adjustments to schedules generated by single-stage models, often assuming deterministic service times. Whereas such approaches are intuitive and take advantage of existing knowledge of single-stage models, they can lead to significant loss of operational efficiency in managing multistage services. A well-designed patient visit itinerary that carefully addresses the interdependencies among stages can significantly improve patient experience and provider utilization. History: This paper was selected for Fast Track in the M&SOM Journal from the 2022 MSOM Healthcare SIG Conference. Funding: The work of the last two authors was supported in part by the National Natural Science Foundation of China [Grants 71931008 and 72001220]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0134 .
Exercise and physical activity after stoma surgery: EXPASS recommendations
Authors: Russell Sarah , Archer Kerry , Osborne Wendy 
Published: March 2024

Background: No formal published recommendations exist about exercise and physical activity after stoma surgery and there is no consensus on advice among health professionals. Numerous difficulties after stoma surgery cause physical activity and exercise levels to decrease. Health professionals can feel ill equipped to advise, leaving patients confused and unsupported. Aim: Formal recommendations for exercise and physical activity are to be established. Method: An expert panel is working under the auspices of the Association of Stoma Care Nurses (ASCN) UK to review existing literature, explore clinical practice and develop formal Delphi consensus recommendations. The document will be aimed at health professionals but will also be available to individuals undergoing surgery. Conclusion: The formal document will be published by the end of 2024 through ASCN UK. The scope of the EXPASS recommendations will cover adults (aged ≥16 years) with any stoma. It will offer peer-reviewed Delphi guidance on physical activity and exercise before and immediately after surgery as well as for long-term living with a stoma. After peer review, the document will provide clarification, consensus and practical recommendations based on the expert panel's evidence, research and clinical opinion.
E. Gas Production Rates
Authors: Milton Wege J. , Falconer R. M. , Gimblet Ernest , Simmons James , Arrington Louis , Hopkins W. B. , Davis Ralph E. 
Published: March 2024

Abstract
Studies of the rates at which gas can be expected to be produced from a well, a field, or a group of fields are made commonly and for several purposes. Such studies generally are referred to as “availability” or “deliverability” studies.
Availability studies are made to approximate the time period during which a given supply of gas can be expected to meet gas deliveries at various rates. Such studies are made commonly for pipeline companies seeking certificates of public convenience and necessity from the FPC. Availability studies also assist pipeline companies in planning future gas-acquisition programs. They may be used in connection with financing projects. When gas-producing properties are being valued for a sale or purchase, it is desirable that future production rates be predicted because they will have a direct bearing on the rates at which income will be derived from the property. Studies of gathering-system pressures which will be required to maintain various rates of production enable operators to compute gathering-system costs, including compression costs, and to select the optimum rate of production related to the costs thereof.
Barriers and facilitators of severe acute malnutrition management at Felege Hiwot Comprehensive Specialized Hospital, Bahir Dar, North West Ethiopia, descriptive phenomenological study
Authors: Alelign Daniel , Fentahun Netsanet , Yigzaw Zeamanuel Anteneh 
Published: March 2024

BackgroundMalnutrition is a clinical condition that affects all age groups, and it remains a major public health threat in Sub-Saharan Africa. As a result, this research aimed to investigate the barriers and facilitators of treating severe acute malnutrition at Felege Hiwot Comprehensive Specialized Hospital in Bahir Dar City, North West Ethiopia.MethodsA descriptive phenomenological study was conducted from February to April 2021. The final sample size taken was fifteen based on data saturation. In-depth and key informant interviews were conducted with nine caregivers, three healthcare workers, and three healthcare managers supported by observation. A criterion-based, heterogeneous purposive sampling technique was used to select the study participants. Each interview was audio-taped to ensure data quality. Thematic analysis was done to analyze the data using Atlas. ti version 7 software.ResultsTwo major themes and six sub-themes emerged. Barriers related to severe acute malnutrition management include subthemes on socio-economic and socio-cultural conditions, perceived causes of severe acute malnutrition and its management, and the healthcare context. Facilitators of severe acute malnutrition management include severe acute malnutrition identification, service delivery, and being a member of community-based health insurance.ConclusionsEffective management of severe acute malnutrition was affected by a multiplicity of factors. The results reaffirm how socioeconomic and sociocultural conditions, perceived causes of severe acute malnutrition (SAM) and its management and the health care context were the major barriers, while able to identifying severe acute malnutrition, service delivery, and is a member of community-based health insurance were the major facilitators for SAM management. Therefore, special attention shall be given to SAM management.