bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of immune checkpoint inhibitors combined with chemotherapy in recurrent drug‐resistant gestational trophoblastic neoplasia: Four case reports and literature review
Authors: Liu Weiqing , Zhu Yukai , Wang Ya , Li Rong , Zou Dongling , Chen Rui , Yang Lu , Huang Yu 
Published: March 2024

AbstractBackgroundMultiple studies have confirmed that programmed cell death 1 (PD‐1) and programmed cell death ligand 1 (PD‐L1) is widely expressed in gestational trophoblastic neoplasia (GTN) tissues. Therefore, immune checkpoint inhibitors may be an option for the treatment of recurrent and drug‐resistant GTN.CaseFour patients with recurrent or drug‐resistant GTN who were treated with PD‐1/PD‐L1 checkpoint inhibitor agents combined with chemotherapy were reported. The mean age of recurrence was 45.8 years (35–56 years), including three cases of choriocarcinoma (CC) and one case of invasive mole (IM). International Federation of Gynecology and Obstetrics (FIGO) prognosis score: ≤6 (low risk) in one case, 7–12 (high risk) in one case, ≥13 (very high risk) in two cases. There were two cases of lung metastasis and one case of vulvar and inguinal lymph node metastasis. One of the four patients underwent total hysterectomy and one patient underwent resection of lung metastases. All the four patients received comprehensive treatment of immunotherapy combined with chemotherapy after relapse, among which one patient achieved complete response (CR), two patients achieved partial response (PR), and one patient developed progressive disease (PD). Three patients who achieved PR or CR were maintained by single agent immunotherapy after combination therapy, and there was no disease recurrence during follow‐up. One patient with PD also achieved CR after using salvage chemotherapy after recurrence, and there was no disease recurrence during follow‐up. During the treatment, four patients had different degrees of immune‐related adverse reactions, all of which were grade I‐II, and no severe adverse reactions were found.ConclusionImmune checkpoint inhibitors combined with chemotherapy has an impressive therapeutic effect on recurrent or drug‐resistant GTN with mild adverse reactions, which can be used as a treatment option for such patients. However, due to the lack of large sample data support, the specific time and treatment course of its use, long‐term use of adverse reactions and whether it affects fertility function remain to be solved.
Pharmacokinetic Evaluation of the CYP3A4 and CYP2C9 Drug‐Drug Interaction of Avacopan in 2 Open‐Label Studies in Healthy Participants
Authors: Miao Shichang , Bekker Pirow , Armas Danielle , Lor Mary , Han Yanyan , Webster Kenneth , Trivedi Ashit 
Published: March 2024

AbstractAvacopan, a complement 5a receptor (C5aR) antagonist approved for treating severe active antineutrophil cytoplasmic autoantibody (ANCA)‐associated vasculitis, was evaluated in 2 clinical drug‐drug interaction studies. The studies assessed the impact of avacopan on the pharmacokinetics (PK) of CYP3A4 substrates midazolam and simvastatin and CYP2C9 substrate celecoxib, and the influence of CYP3A4 inhibitor itraconazole and inducer rifampin on the PKs of avacopan. The results indicated that twice‐daily oral administration of 30 mg of avacopan increased the area under the curve (AUC) of midazolam by 1.81‐fold and celecoxib by 1.15‐fold when administered without food, and twice‐daily oral administration of 30 or 60 mg of avacopan increased the AUC of simvastatin by approximately 2.6‐3.5‐fold and the AUC of the active metabolite β‐hydroxy‐simvastatin acid by approximately 1.4‐1.7‐fold when co‐administered with food. Furthermore, the AUC of avacopan increased by approximately 2.19‐fold when co‐administered with itraconazole and decreased by approximately 13.5‐fold when co‐administered with rifampin. These findings provide critical insights into the potential drug‐drug interactions involving avacopan, which could have significant implications for patient care and treatment planning. (NCT06207682)
CCSFLF: Cloud‐edge‐terminal collaborative self‐adaptive federated learning framework
Authors: Zhou Tong , Yu Yaning , Yuan Haonan , Liu Bing , Zhao Hongyang , Wang Ruijin 
Published: March 2024

SummaryThis article addresses the issue of ensuring model accuracy and training efficiency in a constrained federated learning environment. In an actual federated learning environment, each device's software, hardware, and network conditions are heterogeneous. Some terminal devices may not be able to undertake the work assigned by the server, resulting in poor model accuracy and slower convergence speed. However, existing research cannot ensure that each terminal device participating in training can handle the workload allocated by the system without collecting too much equipment information. This article proposes the cloud‐edge‐terminal collaborative self‐adaptive federated learning framework (CCSFLF) to solve this problem. This framework combines the advantages of federated learning and edge computing, reduces the probability that devices cannot handle the workload of system allocation, solves the system heterogeneity, and improves the efficiency of federated learning. CCSFLF can adaptively adjust the number of training tasks for terminal devices and select valuable training participants using a terminal device selection strategy. Multiple edge servers can simultaneously aggregate local models. Cloud servers are responsible for the aggregation and task distribution of global models. The above strategy enables the framework to have a faster convergence rate and higher model accuracy. The experimental results confirm that this framework can reduce the dropout rate of terminal devices by more than 5% in heterogeneous federated learning systems, improve the model accuracy by about 2%, and reduce the training time by 1/3 compared with similar methods, with better performance and applicability.
Soil‐Sampling Grid Size Considerations for Site‐Specific Nutrient Management in the Southeastern U.S.
Authors: Virk Simerjeet , Tucker Matthew , Harris Glendon , Smith Amanda 
Published: March 2024

AbstractOne of the most important aspects of site‐specific nutrient management is precision soil sampling such as grid‐ and zone‐based strategies to determine varying soil nutrient levels within a field. And for grid soil sampling, one of the most important considerations is the size of the grids as it affects both the sampling resolution and costs. Questions and concerns from growers about the effectiveness of different grid sizes in accurately depicting soil nutrient variability have become common recently, warranting an investigation into how grid size affects application accuracy and economics of site‐specific nutrient management in the southeastern U.S. Earn 0.5 CEUs in Nutrient Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.
Blockchain technology adoption and sustainable supply chain finance: The perspective of information processing theory
Authors: Guo Xiaoli , Xia Weili , Feng Taiwen , Tan Jianyu , Xian Fenggang 
Published: March 2024

AbstractAlthough the significance of sustainable supply chain finance (SSCF) has been recognized, our knowledge of its antecedents remains limited. Drawing upon organizational information processing theory (OIPT), our research explores how blockchain technology adoption influences SSCF via supply chain visibility, and the moderating role of supply chain ethical leadership. We examine the proposed relationships employing survey data from 317 manufacturers in China. The findings indicate that blockchain technology adoption positively affects SSCF. Supply visibility and demand visibility partially mediate the influence of blockchain technology adoption on SSCF. Furthermore, supply chain ethical leadership undermines the positive influence of blockchain technology adoption on demand visibility. This research enriches our understanding of the antecedents affecting SSCF by offering insights from the perspective of OIPT.
Prognostic significance of growth differentiation factor‐15 across age in chronic heart failure
Authors: Teramoto Kanako , Nochioka Kotaro , Sakata Yasuhiko , Nishimura Kunihiro , Shimokawa Hiroaki , Yasuda Satoshi ,   the SUPPORT Trial Investigators
Published: March 2024

AbstractAimsGrowth differentiation factor‐15 (GDF15), a cytokine in the transforming growth factor family, is up‐regulated in stress and inflammatory conditions and is elevated in patients with heart failure (HF). However, the age‐specific attributes and prognostic significance of GDF15 across age remain unknown in chronic HF (CHF).Methods and resultsSerum levels of GDF15 were examined in 942 hypertensive patients (median 68 years) with CHF from the SUPPORT trial across the four age groups [under 50 (n = 73), 51–59 (n = 158), 60–69 (n = 296), and 70–79 years (n = 415)] and in the continuous spectrum. Clinical correlates of GDF15 were explored using the classic stepwise and LASSO (least absolute shrinkage and selection operator) regression approaches. Interaction terms with age were tested in the LASSO regression approach. The associations with the composite outcome of HF hospitalization or all‐cause death were investigated across ages. Median GDF15 levels (pg/mL) increased along with aging, from 691 in under 50 years to 855 in 51–59 years, 1114 in 60–69 years, and 1516 in 70–79 years (trend P < 0.001). Age, sex, systolic blood pressure, history of diabetes, ischaemic heart disease, left ventricular (LV) end‐systolic dimension, LV ejection fraction, estimated glomerular filtration rate, haemoglobin, N‐terminal pro‐brain natriuretic peptide (NT‐proBNP), troponin, C‐reactive protein, and the use of angiotensin‐converting enzyme inhibitors, diuretics, and statins were mutually selected as clinical covariates of GDF15. The LASSO regression analysis identified significant interactions between age and the history of diabetes and NT‐proBNP, with particularly robust associations in patients aged between 60 and 70 years. During the mean follow‐up of 8.6 years, 474 composite endpoints of HF hospitalization or death occurred. GDF15 was associated with a higher risk of HF hospitalization or all‐cause death [adjusted hazard ratio 1.84 (95% confidence interval 1.45–2.33)], with a particularly heightened risk in patients aged around 70 years (Pinteraction = 0.0008). The model with GDF15 on top of other established risk factors yielded marginally higher C‐statistics compared with the model without GDF15 (0.803 and 0.796, P = 0.045). The additive value of GDF15 on top of other established risk factors appeared similar across ages. A universal cut‐off value of 1400 pg/mL performed well in discriminating between those with and without HF hospitalization or death.ConclusionsSome clinical correlates of GDF15 have an interaction with age. GDF15 is an important determinant of cardiovascular endpoints, particularly in patients aged around 70 years. The additive value of GDF15 appeared consistent across ages, suggesting the use of a universal cut‐off value.
GMM‐LIME explainable machine learning model for interpreting sensor‐based human gait
Authors: Mulwa Mercy Mawia , Mwangi Ronald Waweru , Mindila Agnes 
Published: March 2024

AbstractMachine learning (ML) has been used in human gait data for appropriate assistive device prediction. However, their uptake in the medical setup still remains low due to their black box nature which restricts clinicians from understanding how they operate. This has led to the exploration of explainable ML. Studies have recommended local interpretable model‐agnostic explanation (LIME) because it builds sparse linear models around an individual prediction in its local vicinity hence fast and also because it could be used on any ML model. LIME is however, is not always stable. The research aimed to enhance LIME to attain stability by avoid the sampling step through combining Gaussian mixture model (GMM) sampling. To test performance of the GMM‐LIME, supervised ML were recommended because study revealed that their accuracy was above 90% when used on human gait. Neural networks were adopted for GaitRec dataset and Random Forest (RF) was adopted and applied on HugaDB datasets. Maximum accuracies attained were multilayer perceptron (95%) and RF (99%). Graphical results on stability and Jaccard similarity scores were presented for both original LIME and GMM‐LIME. Unlike original LIME, GMM‐LIME produced not only more accurate and reliable but also consistently stable explanations.
Surgical tooth extraction in cats and dogs. Part 2: dental extraction techniques
Authors: van Velzen Hannah , Haseler James , Perry Andrew 
Published: March 2024

Background: Considering over 80 per cent of canine and feline patients over the age of three years have dental disease (Kortegaard and others 2008), dental extractions are undoubtedly some of the most commonly performed surgeries in first‐opinion practice. Yet, general knowledge and confidence with regards to these procedures is often lacking, resulting in veterinary dentistry having an undeserved reputation for being difficult and unrewarding. However, with the correct knowledge, a basic set of instruments and proper techniques it can quickly become a much more straightforward and immensely rewarding task.Aim of the article: This two‐part series provides readers with the tools needed to perform extractions successfully. Part one, published in the previous issue of In Practice, reviewed clinical anatomy, dental instrumentation and the basic principles of exodontics, while this article will focus on extraction techniques.
Practical approach to testing the imported dog for parasites
Authors: Wright Ian 
Published: March 2024

Background: Despite the Covid‐19 pandemic and Brexit, the number of dogs being imported into the UK remains high. At the same time there are a variety of factors driving global parasite distributions, increasing the likelihood that imported pets will be infected with exotic parasites. Therefore, early diagnosis of exotic infections is important, both in dogs with clinical signs but also those that are subclinical carriers. Detecting infections allows us to minimise the potential zoonotic exposure, plan for treatment of any pathogens present and maintain UK biosecurity.Aim of the article: This article summarises the clinical signs and testing options for the key parasites that imported dogs may be infected with.
Analysis of the social and physical factors affecting irrigation scheme performance: The case of the Omo Gibe river basin in the Southern Nations, Nationalities and Peoples’ Region, Ethiopia
Authors: Belayneh Moltot Zewdie 
Published: March 2024

AbstractOne hundred years ago, irrigation development began in Ethiopia, but the efficiency and sustainability of the developed scheme have remained very low. As a result, this study aimed to assess the factors that most frequently affect a scheme's performance. The study analysed general physical and social performance indicators. Structural and social factors were used to identify the most common causes of underperformance of the schemes in the Omo Gibe river basin. Frequency analysis was conducted using Statistical Package for the Social Sciences (SPSS). The relative operational scheme performance and relative irrigated area were 32 and 31%, respectively. The beneficiary to target performance was 63%. Structural and social factors such as flooding and subsequent damage to the under sluice and lack of participatory approaches during scheme development were the most common determinants of irrigation scheme performance. Hence, catchment development and community participation in scheme development are crucial for mitigating irrigation scheme underperformance.
高トリグリセリド血症に伴う重症急性膵炎に対してヘパリン・インスリン療法が一助となった1例(Insulin and heparin therapy for hypertriglyceridemia–induced acute pancreatitis: a case report)
Authors: 翔 新田 , 邦博 白井 , 佳奈 長谷川 , 直美 満保 , 博基 村上 , 智行 小林 , 淳一 平田 
Published: March 2024

要旨高トリグリセリド（triglyceride: TG）血症は，急性膵炎を引き起こすことがあり，標準治療とともに血清TG値を低下させることが重要である。今回，高TG血症に伴う急性膵炎を経験したので報告する。38歳の男性が前医を受診し，急性膵炎の診断で当施設へ転院となった。血液生化学検査では，白血球とCRP，アミラーゼの上昇，血清TG値4,432mg/dLと高値であり，CTでは膵頭部を中心とした膵腫大と膵周囲脂肪織濃度の上昇を認めた。予後因子0点，CT grade 1で軽症急性膵炎と診断し，標準治療に加えて，インスリン・ヘパリン療法と脂質異常症治療薬の投与を開始した。第2病日に血清TG値1,179mg/dLまで低下したが，予後因子6点となり重症化した。そのため，high flow nasal cannulaと経腸栄養，持続的血液濾過透析を開始した。その後，血清TG値は低下し，腹痛などの臨床症状や臓器障害は改善，第22病日に退院となった。インスリン・ヘパリン療法は，膵炎を悪化させる要因であるTG値を低下させる治療の一助になると考えられた。
Historical change and variability of spectral wind wave climate in the New York Bight
Authors: Venolia Maria , Marsooli Reza , Portilla‐Yandún Jesus 
Published: March 2024

AbstractThe sea surface is a complex superposition of various wave systems, thus, analysing their characteristics provides more meaningful and accurate information compared to conventional integrated wave parameter approaches. The concept of wave family—a population of wave systems within a specific region in spectral space—provides the foundation for investigating the long‐term climatology of wave systems. This study adopts a wave family approach to investigate the climatology of wave systems and their long‐term climate controllers at the location of a coastal buoy in the western North Atlantic Ocean. The frequency‐direction wave spectrum is constructed for a historical 20‐year period by applying the Maximum Entropy Method on directional buoy measurements acquired from the National Data Buoy Center station 44025, located in the New York Bight. The two‐dimensional wave spectrum is partitioned, using the watershed partitioning algorithm, and the occurrence distribution of spectral partitions is calculated to identify predominant wave families. Each of the four identified wave families carries unique characteristics based on spatial formation and duration of propagation prior to arrival at the study site. The study quantifies long‐term trends and variability in wave height of each wave family on a monthly, seasonal and annual level, and their relative importance to the bulk sea‐state climatology. The nexus between the bulk or wave family seasonal wave heights and the climate indices is quantified to identify the wave climate controllers in the study area.
Survival of northern pintail ducklings in grasslands and croplands: implications for fall‐seeded cereals
Authors: Johns David W. , Devries James H. , Clark Robert G. 
Published: March 2024

AbstractSpecies‐specific management strategies have been implemented to address persistently low continental populations of several duck species, including the northern pintail (Anas acuta). In the Canadian Prairie Pothole Region (PPR), addressing threats from spring‐seeded cereals on pintail productivity may provide sufficient gains to recover populations. Research on pintail duckling ecology has revealed that duckling survival may be greater in grassland‐dominated landscapes than in annual cropland‐dominated landscapes, possibly limiting the benefits of fall‐seeded cropping practices. Winter wheat crops increase nest success and may assist nesting pintail populations through provision of nesting refuges from spring tillage operations, earlier hatch, and greater nest densities compared to traditional spring‐seeded cereal crops. Yet inadequate duckling survival may reduce these benefits. Our principal objective was to examine if pintail reproductive success in winter wheat in cropland‐dominated landscapes was comparable to grassland‐dominated landscapes or, alternatively, if duckling survival rates in cropland‐dominated landscapes offset the gains of greater nesting success in winter wheat. We captured and radio‐marked 104 nesting female pintails in grasslands and croplands of southern Saskatchewan, during 2011–2012. We modeled cumulative survival to 30 days post hatch in relation to landscape composition and land cover type, specifically, the influence of nesting in fall‐seeded crops. Predicted 30‐day survival for ducklings hatched in perennial cover (40.8% [85% CI = 40.0–44.6%]) in grassland‐dominated landscapes and winter wheat (38.2% [32.0–44.4%]) in cropland‐dominated landscapes was more than double survival of ducklings hatched in spring‐seeded cropland (16.9% [12.6–21.6%]) in cropland‐dominated landscapes. Ducklings moving through local environments with more perennial cover and seasonal wetlands, but less wetland edge, had increased survival. The benefit of greater nest survival in winter wheat was not completely superseded by reduced duckling survival for broods raised in intensive agricultural landscapes. The retention of grassland landscapes and expansion and promotion of fall‐seeded crops in cropland‐dominated landscapes can benefit northern pintails across broad regions of the PPR.
Transforming Big Data into AI‐ready data for nutrition and obesity research
Authors: Thomas Diana M. , Knight Rob , Gilbert Jack A. , Cornelis Marilyn C. , Gantz Marie G. , Burdekin Kate , Cummiskey Kevin , Sumner Susan C. J. , Pathmasiri Wimal , Sazonov Edward , Gabriel Kelley Pettee , Dooley Erin E. , Green Mark A. , Pfluger Andrew , Kleinberg Samantha 
Published: March 2024

AbstractObjectiveBig Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)‐ and ML‐ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions.MethodsWe reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI‐ and ML‐ready products were detailed.ResultsOpportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented.ConclusionsBig Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI‐ and ML‐ready data need to be transparent to investigators and clinicians relying on the conclusions.