bluuebunny/crossref_metadata_2025_split huggingface dataset:
A randomized phase III double-blind placebo-controlled trial of first line chemotherapy and trastuzumab with or without bevacizumab for patients with HER2/neu-positive metastatic breast cancer: a trial of the ECOG-ACRIN Cancer Research Group (E1105)
Authors: Mezzanotte-Sharpe Jessica , ONeill Anne , Mayer Ingrid A. , Arteaga Carlos L. , Yang Ximing J , Wagner Lynne I. , Cella David , Meropol Neal J. , Alpaugh R. Katherine , Saphner Thomas J. , Swaney Robert E. , Hoelzer Karen L , Gradishar William J. , Abramson Vandana G. , Sundaram P. Kothai , Jilani Shamim Z. , Perez Edith A. , Lin Nancy U. , Jahanzeb Mohammad , Wolff Antonio C. , Sledge George W. , Reid Sonya A. 
Published: April 2024

Abstract

Background
In 2008, bevacizumab received accelerated Food and Drug Administration (FDA) approval for use in human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC). Based on the preclinical and preliminary clinical activity of the trastuzumab and bevacizumab combination, ECOG-ACRIN E1105 trial was developed to determine if the addition of bevacizumab to a chemotherapy and trastuzumab combination for first-line therapy would improve progression-free survival (PFS) in patients with HER2-positive MBC.
Findings:
96 patients were randomized to receive standard first-line chemotherapy and trastuzumab with or without bevacizumab between November 2007 and October 2009, and 93 began protocol therapy. Induction therapy was given for 24 weeks, followed by maintenance trastuzumab with or without bevacizumab. 60% (56/93) began carboplatin and 74% (69/93) completed 6 cycles of induction therapy. Primary endpoint was PFS. Median PFS was 11.1 and 13.8 months for placebo and bevacizumab arms, respectively (hazard ratio [HR] 95%, Confidence Interval [Cl] for bevacizumab vs. placebo: 0.73 [0.43–1.23], p = 0.24), and at a median follow-up of 70.7 months, median survival was 49.1 and 63 months (HR [95% Cl] for OS: 1.09 [0.61–1.97], p = 0.75). The most common toxicities across both arms were neutropenia and hypertension, with left ventricular systolic dysfunction, fatigue, and sensory neuropathy reported more frequently with bevacizumab.
Conclusions
In this trial, the addition of bevacizumab did not improve outcomes in patients with metastatic HER2-positive breast cancer. Although the trial was underpowered due to smaller than anticipated sample size, these findings corroborated other clinical trials during this time.
Structural, optical and electrochemical performance of LiZnPO 4 nanoparticles for supercapacitor applications
Authors: Krishnamoorthy E. , Mariappan R. , Gowrisankar G. , Bakkiyaraj R. 
Published: April 2024

Abstract

The synthesized LiZnPO4 nanoparticles were characterized at different temperatures (500°C, 600°C, and 700°C) using various techniques including XRD, FTIR, FESEM, XPS, and electrochemical analyses. X-ray diffraction (XRD) analysis of LiZnPO4 nanoparticles sintered at temperatures from 400 to 700°C revealed well-crystallized structures at 700°C, with preferred orientations along (202) and (020) planes. The Scherrer formula was employed to determine crystallite sizes, showing an increase from 55 nm at 400°C to 85 nm at 700°C. Fourier-transform infrared spectroscopy (FTIR) confirmed characteristic bonds within LiZnPO4, while scanning electron microscopy (SEM) exhibited morphological changes with sintering temperature, emphasizing the impact on size and aggregation. Energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) confirmed elemental compositions and surface electronic states, respectively. Electrochemical experiments demonstrated promising performance, with cyclic voltammetry (CV), galvanostatic charge and discharge (GCD), and electrochemical impedance spectroscopy (EIS) revealing reversible redox processes and good rate capability.
Predicting Risk-Coping Behaviors In the Urban Relocation Process by Online Negative Emotions：A Case from Beijing
Authors: Xie Qihui , Wu Hongyu , Zhang Ruwen 
Published: April 2024

Abstract

This article explores the use of online negative emotions to predict public risk-coping behaviors during urban relocation. Through a literature review, the paper proposes hypotheses that anticipate advanced prediction of public risk-coping behaviors based on online negative emotions. The study's empirical focus is on the relocation of the Beijing municipal government, utilizing Granger causality analysis on time series data. Data on online negative emotions is sourced from Sina Weibo, while risk-coping behaviors are measured through public information search behaviors and the incidence of violent crimes. The results indicated that: 1) Online negative emotions regarding the relocation policy predict public risk-coping behaviors in advance. 2) Negative comments are more effective predictors than negative feelings; 3) Negative emotions about relocation policy formulation predict risk-coping behaviors better than those related to policy effectiveness and implementation; 4) Negative emotions from individuals better predict public risk-coping behaviors than those from institutions; 5) Negative emotions from key stakeholders better predict public risk-coping behaviors than those from non-key or marginal stakeholders. This study is expected to offer valuable insights and recommendations for institutions involved in policy formulation, implementation, and evaluation.
Comparative Analysis of Functional End-to-End and End-to-Side Anastomosis in Laparoscopic Right Hemicolectomy for Colon Cancer
Authors: Kim Seijong , Huh Jung Wook , Lee Woo Yong , Yun Seong Hyeon , Kim Hee Cheol , Cho Yong Beom , Park Yoonah , Shin Jung Kyong 
Published: April 2024

Abstract

Purpose: Despite advancements in laparoscopic right hemicolectomy for right-sided colon cancer, the choice between functional end-to-end anastomosis (FETE) and end-to-side anastomosis (ETS) remains a topic of debate. This study aimed to compare these two techniques in terms of postoperative complications and disease-free survival.
Methods: This retrospective analysis included 1202 patients who underwent laparoscopic right hemicolectomy for non-metastatic colon cancer at Samsung Medical Center between January 2007 and February 2016. The patients were divided into FETE (n = 968) and ETS (n = 234) groups based on the anastomosis technique used. Patients’ characteristics, oncologic results, operative outcomes, and postoperative complications were analyzed.
Results: The baseline characteristics were similar between the two groups, except for a higher incidence of cancer obstruction in the ETS group (p < 0.001). No significant differences were observed in operation time, blood loss, length of hospital stay, time to the first meal, or time to first flatus. Anastomotic leakage rates were comparable (FETE 0.7% vs. ETS 0.4%, p = 0.999). The FETE group had a higher rate of postoperative ileus (4.4% vs. 1.3%, p = 0.022). Multivariable analysis indicated age, sex, and anastomosis type as significant predictors of postoperative ileus.
Conclusion: The study findings demonstrate that both FETE and ETS anastomosis techniques in laparoscopic right hemicolectomy are comparable in terms of operation metrics and disease-free survival. However, FETE is associated with a higher incidence of postoperative ileus. These findings can guide surgical decision-making in the treatment of right-sided colon cancer.
Epidemiological Characteristics and Risk factors of Stroke in Pregnancy and Postpartum Women in Somalia: A Retrospective Study
Authors: Sidow Nor Osman , NAKUŞ Engin , Hassan Mohamed Sheikh , Omar Abdikarin Ali 
Published: April 2024

Abstract

Objective
Stroke in women with pregnancies and postpartum periods has a higher level of vulnerability than in other people. The aim of this study is to provide information on the burden of stroke in pregnant women and after delivery, as well as discover the most risk factors for them causing the stroke and examine the types of stroke in Mogadishu, Somalia.
Methods
This is a retrospective study. The data was obtained from the health information system documented in the 3-year period between January 2020 and December 2022. All the women with pregnancy and seven weeks after delivery presenting with stroke clinical features in the emergency are included in this study. Patients who were admitted as neurology inpatients or ICUs were identified from the data by confirming the diagnosis with a first CT brain and an MRI brain with a venogram. The risk factor was taken from the doctors and progressive notes in the system. data was analyzed using the commonly used statistical package, SPSS version 26.0.
Results
This study included 102 pregnant and postpartum women who had acute strokes in an emergency department. 90 (88.2%) had a postpartum period, and 12 (11.8%) had a pregnancy. according to the age of the participants: 46 (45.1%) between 15 and 24 years, 32 (31.4%) between 25 and 34, and 24 (23.5%) between 15 and 24 years old. 70 (68.7%) had cerebral sinus vein thrombosis (CSVT), while 21 (20.5%) had ischemic stroke (SS), and 11 (10.8%) had hemorrhagic stroke (HS). There were no differences in the location of the infarction or hemorrhage site, and the documented clinical presentation of the stroke, but the CSVT presentation was different from the other strokes; most of them, 61.1 (88%) had a seizure with focal neurological deficit. 39 (38.2%) had superior sagittal sinus thrombosis, and 17 (16.7%) had transverse sinus thrombosis. For the risk factors of the stroke, 58 (56.9%) did not have any previous risk factors related to the stroke, 10 (9.8%) had a history of abortion, 10 (9.8%) had a history of preeclampsia and eclampsia, and 5 (4.9%) had a history of contraceptive use.
Conclusion
This study showed that the most common type of stroke in pregnant and postpartum women is cerebral sinus venous thrombosis, and the greatest risk factor is the same as pregnancy and postpartum with abortion, eclampsia, and preeclampsia. So, early recognition of these strokes in women during pregnancy and postpartum helps health professionals make early diagnoses with appropriate treatment.
Development of estimating equations for glomerular filtration rate among Southeast Chinese population
Authors: Li Xiaoyun , He QiLong , Xie Jingzhi , Chen Heng-Gui , Feng Ruimei , Wang Yuanping , Lin Qiaofen , Jiang Bingjing , Du Shanshan , Ye Weimin , Xu Yanfang 
Published: April 2024

Abstract

Purpose: The accuracy of newly reported estimated glomerular filtration rate (eGFR) equations has not been evaluated among Southeast Chinese, and whether there is a better eGFR equation that could improve GFR assessment was unknown. Thus, we aimed to explore an eGFR equation with high accuracy among Southeast Chinese population.
Patients and methods: A total of 2449 Southeast Chinese participants with gold standard of measured GFR (mGFR) were enrolled. All participants were randomly divided into development and validation datasets to develop new eGFR equations by linear regression analysis. The performance of the new and reported equations was evaluated in both datasets, and subgroups with different age, sex, diabetes, and CKD status.
Results: A total of three new eGFR equations were developed, and named as SC-GFRcr, SC-CKD-EPIcr, SC-GFRcr-cys equations. The lowest bias (-0.32, 0.26 mL/min/1.73 m2) was observed for SC-GFRcr equation. The highest P30 level (79.44%, 78.45%) and lower root mean squared error (RMSE) (17.18, 17.79) were observed for SC-CKD-EPIcr equation in the development and validation datasets. The correlation coefficients between the new equations and mGFR were all >0.7, the sensitivity of SC-CKD-EPIcr equation was as high as 76.33%. Meanwhile, four previously reported equations were selected and compared with the 3 new equations. In the development and validation datasets, and subgroup analyses, newly developed SC-CKD-EPIcr equation performed superior than others, and eGFRcr was best among all previously reported equations.
Conclusions: The new-developed eGFR equation, SC-CKD-EPIcr, could improve GFR assessment, especially in Southeast China. Still, external validation of the equation is needed.
Achieving High Success in Fall Detection through Cross-Brand Inertial Sensor Utilization of Hybrid Data in Machine Learning
Authors: BUZPINAR Mehmet Akif 
Published: April 2024

Abstract

Falls can result in severe injuries and even mortality among individuals of all age groups. Hence, numerous wearable sensor-based fall monitoring systems are being developed to provide assistance. Fall detection and activity tracking have been partially successful using smartwatches, smartphones, and specialized devices. However, a comprehensive solution that combines sensor data from different brands in a single model and performs fall detection with high accuracy and at a satisfactory level has not been encountered. This study aims to bridge this research gap by combining data from two different brands of IMUs (inertial measurement units) that incorporate accelerometers, magnetometers, and gyroscopes, in order to create a hybrid dataset. To achieve accurate predictions on data from both brands, machine learning (ML) models were trained using ML algorithms. The first dataset was obtained from 14 volunteers using a commercially available activity tracking system called Motion Trackers Wireless (MTw). The second dataset was collected from 30 volunteers using a custom-designed Activity Tracking Device (ATD) specifically developed for detecting falls and daily-life activities. In both cases, the sensors from the respective brands were positioned on the waist to capture data related to falls and daily-life activities. The data was organized using a time-series style to reveal relational effect of the sequential falling data. During the modelling, ten different classifiers trained, and classification was performed on unseen data using the data splitting method. The Extra Tree algorithm emerged as the most successful model, achieving an accuracy of 99.54%, precision of 99.18%, recall of 99.79%, and an F-score of 99.49% on the hybrid dataset constructed from the MTw and ATD datasets. This study demonstrates hybrid dataset to create a successful system with high accuracy and low false alarm rates using inertial sensor data from various brands.
Re-Imagining Additive Manufacturing through Multi-Material Laser Powder Bed Fusion
Authors: Griffis Jacklyn , Shahed Kazi , Meinert Kenneth , Yilmaz Buket , Lear Matthew , Manogharan Guha 
Published: April 2024

Abstract

Multi-Material Laser Powder Bed Fusion (MM-LPBF) offers a novel approach for fabricating high-resolution components with both spatially tailored material properties and design by capitalizing on selective powder deposition (SPD) in conventional laser powder bed fusion (LPBF) processing. Advancements in multi-material additive manufacturing (AM), specifically MM-LPBF is now presenting a unique opportunity to reimagine additive manufacturing as we know today in terms of the local material assignment, AM-processing induced properties and design complexity which can help achieve functional requirements across multiple length scales.
In this study, new MM-LPBF capability to manufacture a sheet-based gyroid structure composed of 904L stainless steel and bronze (CuSn10) is studied for unique MM-LPBF signatures (e.g., melt pool characteristics, grain morphology and mechanical properties via intermittent micro-CT during flexural testing). The fracture mechanics of complex multi-material structures is investigated through multi-scale domain techniques, including mechanical testing (supported by digital image correlation (DIC), finite element analysis (FEA), and intermittent micro-CT), microstructural and morphological characterization of the bimaterial interface. This study analyzes the contribution of factors such as thermomechanical material compatibility, process-induced defects, cracking, porosity, and microstructure to determine the ultimate origin of failure and propagation patterns. Interface formation mechanisms are explored to elucidate process-structure-property framework for MM-LPBF. Findings from this study clearly demonstrate both the opportunity of MM-LPBF and current technological challenges to further advance the adoption of MM-LPF for a wide range of applications such as thermo-fluidic surfaces, solid-state energy storage, and biodegradable implants, among others.
Ultrasonographic Detection of Sarcopenia in Patients With Long-Term Gastrectomy: A Study by Using ISarcoPRM Algorithm
Authors: Sezer Semih , Demirci Selim , Kara Özgür , Kara Murat 
Published: April 2024

Abstract

Purpose
To date, the assessment of sarcopenia, which is an important indicator of quality of life in gastrectomy patients, has been performed by calculating total or appendicular skeletal muscle mass. However, as the anterior thigh (i.e. quadriceps) muscle is affected more commonly/earlier with aging and diseases, we used quadriceps muscle thickness measured by ultrasound (US) in determining regional muscle mass. In our study, we aimed to detect sarcopenia in gastrectomy patients more accurately and practically using the ISarcoPRM algorithm.
Methods
In this cross-sectional case-control study, patients who underwent total gastrectomy (N=20), distal gastrectomy (N=30), and those without gastrectomy (N=54) were included. The sonographic thickness of anterior thigh muscle adjusted by body mass index (STAR) was used. Sarcopenia was diagnosed according to the ISarcoPRM algorithm using low grip strength (<19 kg for females and <32 kg for males) and/or prolonged CST duration (≥12 seconds) with low STAR values (<1 for females and <1.4 for males).
Results
The males who underwent total gastrectomy had the lowest body mass index, quadriceps muscle thickness, and hand grip strength values among the groups (all p<0.05). According to binary logistic regression analysis in males, only total gastrectomy [OR=6.961 (95% CI: 1.342-36.092)] was independently associated with the development of sarcopenia (p<0.05).
Conclusion
By using a novel (ISarcoPRM) algorithm, we found that total (but not distal) gastrectomy seemed to be independently related to sarcopenia (about 7 times higher). We believe that sarcopenia evaluation in gastrectomy patients should be performed with US in terms of its low cost and ease of application.
Rotifer Detection and Tracking Framework Using Deep Learning for Automatic Culture Systems
Authors: Ienaga Naoto , Takashi Toshinori , Tamamizu Hitoko , Terayama Kei 
Published: April 2024

Abstract

Although rotifers (Brachionus plicatilis sp. complex) are a very important first feed source in marine fish aquaculture, the managementof rotifers is quite time consuming because their population and movements need to be monitored on a daily basis. This management is still performed manually, and automation is required. If we could make good use of recent breakthroughs in deep learning, the automation of a rotifer culture system could be realized. We propose a deep learning framework for detecting and tracking rotifers as a basis for such automation and carefully verified its accuracy. Experimental results show that a mean average precision of 88.5% was achieved for detection and a higher order tracking accuracy of 88.7% was achieved for tracking, indicating the suitability of deep learning methods for predicting the state of rotifers. In addition, this research will contribute to the development of the field by releasing the trained model and code for visualizing the tracking results as well as an annotated dataset with over 30K instances.
A longitudinal study examining PTSD and other mental health problems in NHS workers during the COVID-19 pandemic
Authors: Celik Filiz , Davies-Thompson Jodie , Quigley Martyn , Reppa Irene 
Published: April 2024

Abstract

A cross-sectional longitudinal study was conducted to examine the impact of the Covid-19 pandemic on the mental health of NHS medical staff, and its relationship with levels of social support received, and levels of Covid-19 related worries. Participants were contacted via Health Boards and Royal Colleges in England and Wales. 476 participants completed the study in Wave 1 and 129 of those completed the same survey in Wave 2 a year later. Participants completed the Crisis Support Scale, a Covid-19 Anxieties Questionnaire, the DASS-21, and the PTSD checklist. First, high levels of support during the pandemic, were associated with lower levels of depression, anxiety, stress, and PTSD. Second, high levels on the Covid-19 Anxieties Questionnaire were associated with high levels of Common Mental health Difficulties (CMDs) and PTSD scores during both waves. Third, social support led to lower Covid-19 health worries scores in Wave 1. Finally, scores on the Covid-19 anxieties questionnaire significantly reduced 12 months into the pandemic, while effects on mental health did not. Social support during the crisis can reduce anxieties about the crisis and self-reported levels of CMDs and PTSD. Even when anxieties relating to the pandemic eased, the prevalence of CMDs and PTSD were long-lasting.
Leveraging Machine Learning for Soil Fertility Prediction and Crop Management in Agriculture
Authors: Asif Mohammad , Wahid Abdul 
Published: April 2024

Abstract

This study investigates how machine learning (ML) algorithms can be used in agriculture to forecast soil fertility and maximize crop yield. Machine learning (ML) models are created to predict soil nutrient levels, pH, and organic matter content across a range of geographical locations and land-use types with high accuracy by evaluating large datasets that include soil samples, environmental conditions, and agronomic methods. The research shows the advantages of nonlinear modeling approaches in capturing complex interactions inherent in agricultural systems through a comprehensive evaluation of several machine learning techniques, including ensemble methods like AdaBoost and Extra Tree Classifier. Furthermore, immediate insights and recommendations for improving agronomic decisions are made possible by the integration of real-time sensing technologies, such as proximate sensing, distant sensing, and Internet of Things (IoT) devices. Overall, this work highlights how machine learning (ML) can completely change crop management techniques and soil fertility prediction, enabling a more resilient and sustainable agriculture sector.
Semiparametric efficient estimation of genetic relatedness with machine learning methods
Authors: Guo Xu , Qian Yiyuan , Shi Hongwei , Yang Weichao , Zhou Niwen 
Published: April 2024

Abstract

In this paper, we propose semiparametric efficient estimators of genetic related-ness between two traits in a model-free framework. Most existing methods require specifying certain parametric models involving the traits and genetic variants. However, the bias due to model misspecification may yield misleading statistical results. Moreover, the semiparametric efficient bounds for estimators of genetic relatedness are still lacking. In this paper, we develop semiparametric efficient estimators with machine learning methods and construct valid confidence intervals for two important measures of genetic relatedness: genetic covariance and genetic correlation, allowing both continuous and discrete responses. Based on the derived efficient influence functions of genetic relatedness, we propose a consistent estimator of the genetic covariance as long as one of the genetic values is consistently estimated. The data of two traits may be collected from the same group or different groups of individuals. To validate our approach, we conduct various numerical studies to illustrate the introduced estimation procedures. Additionally , we apply our proposed methodologies to analyze data from the Carworth Farms White mice genome-wide association study.