bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chylothorax after Retrocrural Lymphadectomy and Consideration of Ultraradical Surgery in Ovarian Cancer: A case report
Authors: Huo Yanqin , Wu Qingyun , Zhang Fang , Gao Fufeng , Wu Jianlei , Chen Liang 
Published: June 2023

Abstract
Purpose:
Retrocrural lymph node resection has not yet been reported in patients with ovarian cancer. We tried to do so.
Patients and Methods:
This report presents one ovarian cancer patient, complicated by multiple distant lymph node metastases in PET/CT imaging. Ovarian cancer reduction surgery was performed, and retrocrural lymph nodes were removed. However, the patient developed a chylothorax after surgery. Thoracotomy was performed after failed interventional therapy and a clear leakage point was identified. Subsequently, the peripheral diaphragm was sutured and filled with gel sponge.
Results:
The chylothorax was cured, and the patient continues to receive chemotherapy.
Conclusions:
There is a critical need to identify an effective approach to perform systemic R0 surgery with fewer complications.
Quantifying the impact of AI recommendations with explanations on prescription decision making: an interactive vignette study
Authors: Nagendran Myura , Festor Paul , Komorowski Matthieu , Gordon Anthony , Faisal Aldo 
Published: June 2023

Abstract
Background: The challenge of responsibly guiding clinicians to incorporate AI recommendations and explanations into their day-to-day practice has thus far neglected the realm of decisions outside of diagnosis (where there is no gold standard to compare against). We assess how clinicians' decisions may be influenced by additional information more broadly, and how this influence can be modified by either the source of the information (human peers or AI) and the presence or absence of an AI explanation (XAI, here using simple feature importance).

Methods: We conducted a human-AI interaction study with ICU doctors using a modified between-subjects design. Doctors were presented on a computer for each of 16 trials with a patient case and prompted to prescribe continuous values for IV fluid and vasopressor. We used a multi-factorial experimental design with four arms, where each clinician experienced all four arms on different subsets of our 24 patients. The four arms were (i) baseline (control), (ii) peer human clinician scenario showing what doses had been prescribed by other doctors, (iii) AI suggestion and (iv) XAI suggestion.

Findings: Among 86 ICU doctors we had four key findings. First, additional information (peer, AI or XAI) had a strong influence on prescriptions (significantly for AI, not so for peers) but XAI did not have higher influence than AI alone. Second, inter-clinician prescription variability was affected differentially according to whether the recommendation (whether peer, AI or XAI) was higher or lower than what subjects in the baseline arm did. Third, there was no correlation between attitudes to AI or clinical experience on the AI-supported decisions. Fourth, there was no correlation between what doctors self-reported about how useful they found the XAI and whether the XAI actually influenced their prescriptions.

Interpretation: Taken together, our findings on a comparatively large clinical expert population raise important questions for the meaning and design of medical XAI systems. Specifically, we show that the marginal impact of XAI as currently formulated is low in a medical population. We also cast doubt on the utility of self-reports as a valid metric for assessing XAI in clinical experts vs our more objective behavioural response paradigm. Further work in this area could look to higher fidelity and more granular markers that assess the natural behaviour of clinicians when they interact with decision support tools.
Effects of low LH serum levels on oocyte retrieval, fertilization rate and embryo quality during controlled ovarian stimulation: results from a prospective cohort analysis
Authors: Dragotto Jessica , Buzzaccarini Giovanni , Etrusco Andrea , Laganà Antonio Simone , Chiantera Vito , Terzic Sanja , Dellino Miriam , Margioula-Siarkou Chrysoula , Unfer Vittorio , Bianco Bianca , Casadio Paolo , Bracchitta Giovanni 
Published: June 2023

Abstract
Luteinizing hormone plays a key role in normal follicular development and oocyte maturation in controlled ovarian stimulation. Luteinizing hormone stimulates the proliferation and differentiation of theca cells for the secretion of androgens, synergistically increasing estrogen production. This study aimed to investigate the effects of low luteinizing hormone concentrations on oocyte retrieval, fertilization and embryo development in patients undergoing in vitro fertilization/intracytoplasmic sperm injection. We prospectively analyzed patients undergoing in vitro fertilization/intracytoplasmic sperm injection, subdividing them into three groups according to their age. Serum luteinizing hormone levels were evaluated on day 3, during stimulation (day 10) and before ovulation induction (day 12). Our data analysis suggests that serum luteinizing hormone levels progressively decrease during controlled ovarian stimulation, and this effect is more evident in the early phase of this procedure. From this perspective, circulating luteinizing hormone levels may significantly decrease during the late follicular phase due to the negative feedback of ovarian hormones from multiple follicular developments or after the suppressive effects of gonadotropin releasing hormone antagonist. Based on these findings, exogenous luteinizing hormone may be considered a strategy in women with a decrease in luteinizing hormone levels during ovarian stimulation in order to improve oocyte quality and reproductive outcome.
Palliative care for children: Methodology for the development of a clinical practice guideline
Authors: Teunenbroek Kim C. van , Kremer Leontien C. M. , Verhagen A. A. Eduard , Verheijden Johannes M. A. , Rippen Hester , Borggreve Brigitt C. M. , Michiels Erna M. C. , Mulder Renée L. 
Published: June 2023

Abstract
Background
Provision of paediatric palliative care for children with life-threatening or life-limiting conditions and their families is often complex. Guidelines can support professionals to deliver high quality care. Stakeholders expressed the need to update the first Dutch paediatric palliative care guideline with new scientific literature and new topics. This paper provides an overview of the methodology that is used for the revision of the Dutch paediatric palliative care guideline and a brief presentation of the identified evidence.
Methods
The revised paediatric palliative care guideline was developed with a multidisciplinary guideline panel of 72 experts in paediatric palliative care and nine (bereaved) parents of children with life-threatening or life-limiting conditions. The guideline covered multiple topics related to (refractory) symptom treatment, advance care planning and shared-decision making, organisation of care, psychosocial care, and loss and bereavement. We established six main working groups that formulated 38 clinical questions for which we identified evidence by updating two existing systematic literature searches. The GRADE (CERQual) methodology was used for appraisal of evidence. Furthermore, we searched for additional literature such as existing guidelines and textbooks to deal with lack of evidence.
Results
The two systematic literature searches yielded a total of 29 RCTs or systematic reviews of RCTs on paediatric palliative care interventions and 22 qualitative studies on barriers and facilitators of advance care planning and shared decision-making. We identified evidence for 14 out of 38 clinical questions. Furthermore, we were able to select additional literature (29 guidelines, two textbooks, and 10 systematic reviews) to deal with lack of evidence.
Conclusions
The revised Dutch paediatric palliative care guideline addresses many topics. However, there is limited evidence to base recommendations upon. Our methodology will combine the existing evidence in scientific literature, additional literature, expert knowledge, and perspectives of patients and their families to provide recommendations.
Development of a process-based model for revealing role of silicon in regulating metal stress in roots
Authors: Pang Zhihao , Luo Zhongkui , Guan Dong-Xing , Zhao Enqiang , Li Tingqiang , Liang Yongchao 
Published: June 2023

Abstract
Soil contamination by heavy metals has become a severe threat to the global food security. To mitigate metal toxicity in plants, the use of Si has been widely studied. Despite its ability to reduce the accumulation of metal in leaves, the mechanism by which Si influences the entry of metals into roots remains incompletely understood. To address this issue and explain the conflicting results observed in Si supplementation experiments, a process-based model was proposed to depict metal diffusion and adsorption in root cell wall. Using trivalent chromium (Cr[III]) as an example metal, the model was applied to explain the observed relation between Cr(III) and Si in rice roots considering Cr(III) concentration, stress duration, and Si concentration. Furthermore, we designed a device to simulate cell walls and protoplasts to analyze the switch of dual role of Si from increasing adsorption to blocking diffusion. The adsorption–diffusion model fitted well (R2 > 0.9) with the experimental results. The model revealed that Si increased metal adsorption onto cell walls but blocked diffusion into protoplasts, which was also confirmed by simulations in the device. The results deepen our understanding of the role of Si in mitigating metal stress in roots, broaden our knowledge about how Si influences plant growth, and provide a theoretical reference for future research on and applications of Si intervention.
Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units
Authors: Eftekhari Seyedeh Hajar , Memariani Mahmoud , Maleki Zahra , Aleali Mohsen , Kianoush Pooria 
Published: June 2023

Abstract
Rock types are the reservoir's most essential properties and show special facies with a defined range of porosity and permeability. This study used the fuzzy c-means clustering technique to identify rock types in 280 core samples from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. Four hydraulic flow units were determined for studied data after classifying the flow zone index with histogram analysis, normal probability analysis, and the sum of square error methods. Then the two methods of flow zone index and fuzzy c-means clustering were used to determine the rock types in given wells according to the results obtained from the implementation of these two methods in-depth, and continuity index acts, the fuzzy c-means methods with continuity number 3.12 compared to flow zone index with continuity number 2.77 shows more continuity in depth. The relationship between porosity and permeability improved using hydraulic flow unit techniques significantly. In this study, the correlation coefficient between porosity and permeability improves and increases in each hydraulic flow unit using the flow zone index method. So that in the general case, all samples increased from 0.55 to 0.81 in the first hydraulic flow unit and finally 0.94 in the fourth hydraulic flow unit. The samples were characterized by similar flow properties in a hydraulic flow unit. In comparison, the correlation coefficient is obtained less than the general case in the fuzzy c-means method in all hydraulic flow units.
Localization of Seismic Waves in Submarine Fiber Optics Using Polarization-only Measurements
Authors: Costa Luis , Varughese Siddharth , Mertz Pierre , Kamalov Valey , Zhan Zhongwen 
Published: June 2023

Abstract
Monitoring seismic activity on the ocean floor is a critical yet challenging task, largely due to the difficulties of physical deployment and maintenance of sensors in these remote areas. Optical fiber sensing techniques are well-suited for this task, given the presence of existing transoceanic telecommunication cables. However, current techniques capable of interrogating the entire length of transoceanic fibers are either incompatible with conventional telecommunication lasers or are limited in their ability to identify the position of the seismic wave. In this work, we propose and demonstrate a method to measure and localize seismic waves in transoceanic cables using only conventional telecommunication transponders and detectors, by launching pulses of changing polarization. We demonstrate our technique by measuring and localizing seismic waves from a magnitude Mw 6.0 earthquake (Guerrero, Mexico) using a submarine cable connecting Los Angeles, California and Santiago, Chile.
Our approach introduces a cost-effective and practical solution that can potentially increase the density of geophysical measurements in hard-to-reach regions, improving disaster preparedness and response, with minimal additional demands on existing infrastructure.
ElegansAI: how a biological neural network would compare with artificial networks?
Authors: Bardozzo Francesco , Terlizzi Andrea , Lio Pietro , Tagliaferri Roberto 
Published: June 2023

Abstract
This paper presents ElegansAI, a neural network model that leverages the connectome topology of the Caenorhabditis elegans to design and generate advanced learning systems. The objective of this approach is to integrate the intricate circuitry of biological neuronal networks into artificial ones, with the aim of exploring the advantages of incorporating bio-plausible connectome topology in deep learning models. ElegansAI outperforms randomly wired tensor networks, simulated bio-plausible networks, and state-of-the-art models such as transformers and attention-enforced autoencoders. The models achieve a top-1 accuracy of $99.99\%$ on Cifar10 and $99.84\%$ on MNIST Unsup in supervised image classification tasks and unsupervised handwritten digit reconstruction, respectively. The proposed method offers a unique approach to designing and generating connectome-inspired learning systems that harness the functional distribution of biological neuron circuitry. It is shown how bio-plausible structures integrated into artificial neural networks efficiently tackle complex tasks by evaluating evolutionary optimized neuronal motifs.
Knowledge, attitudes and practices of Chagas a Neglected Tropical Disease in rural communities of the Colombian Caribbean, CHAGCOV study.
Authors: Ochoa Margarita Maria , Orozco-Garcia Daniela , Fernandez-Vasquez Ronald S. , Eyes-Escalante Melisa 
Published: June 2023

Abstract
Purpose
Chagas disease (CD) a Neglected Tropical Diseases is an important public health issue in countries where is still endemic, included in the Sustainable Development Goals (SDG). Traditionally restricted to rural areas with diverse routes of transmissions from vectorial to oral with acute manifestations but being more common diagnosed in chronic stages. The aim of this investigation was to characterize the Knowledge, Attitudes and Practices (KAP) related to Chagas disease (CD) in two rural settlements of the Colombian Caribbean with previous records of the disease and/or the parasite.
Methods
A cross-sectional descriptive study was made in two rural settlements in Colombia and surveillance instrument was developed to measure Knowledge, Attitudes and Practices (KAP) related to Chagas disease (CD)
Results
In a population with > 60% women and access to social security around 66.5%; 81,6% were homeowners with access to water and electricity > 90% but only 9% of sewerage. The level of knowledge about CD was around 62% but lack of specificity about comprehension of transmission routes (74,6%), and symptoms (85,3%) were found; concluding that 86% of the surveyed sample had very poor level of knowledge about the disease despite preventive campaigns carried out in the two communities studied.
Conclusions
Despite of a low frequency of CD in this Caribbean areas, the presence of vector, risk factors plus poor level of knowledge about the disease justify that public health intervention strategies should be implemented and monitored over time to maintain uninterrupted surveillance of Chagas Disease.
Left atrial giant myxoma with mitral valve obstruction: A case-report
Authors: Escobar Johao , Rivera Mario Rodriguez , Aguiluz Andrea , Larios Javier 
Published: June 2023

Abstract
Background
Myxomas are the most common primary cardiac tumors, predominantly found in the left atrium. They can present with various symptoms, including cardiac manifestations such as heart failure, arrhythmias, stroke, and systemic findings. Surgical resection of myxomas has a favorable prognosis with low complication rates.
Case presentation
We present a case of a 41-year-old man with dyspnea, abdominal distension, and edema diagnosed with a giant left atrial myxoma.
Results
Successful surgical removal resulted in symptom resolution.
Conclusions
Cardiac myxomas are rare in the general population. Echocardiography is essential for diagnosis, while additional imaging techniques such as computed tomography (CT) scanning and magnetic resonance imaging (MRI) can provide further information. Surgical excision is typically necessary to prevent embolization, with favorable outcomes, although there is a risk of arrhythmias, conduction abnormalities, recurrence, and development of new lesions.
U2S-CNN 3-phase defect detection system, from anomaly detection to defect classification
Authors: Klarák Jaromír , Andok Robert , Malík Peter , Kuric Ivan , Ritomský Mário , Klačková Ivana , Tsai Hung-Yin 
Published: June 2023

Abstract
The manuscript proposes the new 3-step universal defect detection system U2S-CNN tuned with visual data containing gear wheel images. The main advantage of the system is the detection capability of even unknown patterns of defects occurring in datasets. The object detection and defect detection approaches differ significantly in the basic principle. The precisely specified objects or patterns are sought in object detection and in the case of defect detection, patterns of different shape, orientation, color, character, etc. are sought. The problem of searching unknown objects is solved by defining the correct areas on the controlled object by using an asymmetric autoencoder of our own design. Subsequently, the differences between the original and autoenconder generated image are produced. The differences are divided into clusters using the DBSCAN method. Based on the clusters, regions of interest are defined, which are then classified using the pretrained Xception network classifier fined tuned with our data. The result is a 3-phase system capable of focusing even on unknown defects not occurring in the dataset using the sequence of Unsupervised learning – Unsupervised learning – Supervised learning methods. The proposed system is inspired by similarly designed systems used for the detection of anomalies or tumors in MRI or CT images, where U-networks or autoencoders are used. From the point of view of the nature of the issue, these problems can be considered very similar.
Preventing viral relapse with prophylactic tenofovir in hepatitis B carriers receiving chemotherapy: A phase IV randomized study in Taiwan
Authors: Hsu Chao Wei , Chen Shin-Cheh , Wang Po-Nan , Wang Hung-Ming , Chen Yi-Cheng , Yeh Chau-Ting 
Published: June 2023

Abstract
Background & Aims:
This study aimed to compare the efficacy of shorter vs. longer tenofovir disoproxil fumarate (TDF) prophylaxis in preventing hepatitis B virus (HBV) relapse in cancer patients with chronic hepatitis B (CHB) undergoing chemotherapy.
Methods
This phase IV, prospective randomized trial enrolled cancer patients with CHB from 2014 to 2019 in Taiwan. Included patients were randomized to receive either 24- (Arm A) or 48-week (Arm B) post-chemotherapy TDF and compared for cumulative incidence of virological and clinical relapse. Logistic regressions were conducted to determine the factors associated with HBV relapse.
Results
One hundred patients were randomized, and 41 patients in Arm A and 46 in Arm B completed the TDF treatment. No significant difference were found in cumulative incidence of virological relapse (Arm A: 94.4%, Arm B: 93.1%, p = 0.110) or clinical relapse among patients with baseline HBV DNA > 2,000 IU/mL (Arm A: 38.9%, Arm B: 26.7%, p = 0.420) between the two arms. High baseline HBV DNA ≥ 10,000 IU/mL (OR = 51.22) and HBsAg ≥ 1,000 IU/mL (OR = 8.64) were independently associated with an increased virological relapse. Alanine aminotransferase (ALT), serum phosphorus, vitamin D, and estimated glomerular filtration rate (eGFR) remained stable throughout the study.
Conclusions
The 24-week preventative TDF has comparable efficacy to the 48-week treatment in virologic and clinical relapse. High baseline HBsAg or HBV DNA are associated with a higher risk of HBV relapse. These findings imply a 24-week duration of TDF treatment with a close monitor for patients with a high baseline viral load.
Lay summary: Hepatitis B virus infection is a prominent cause of liver cancer and chronic liver disease and affected millions of people worldwide. When HBV-infected people are exposed to immunosuppressive medication or chemotherapy for cancer, the chance of HBV reactivation rise considerably. This trial showed 24-week tenofovir disoproxil fumarate (TDF) may be sufficient for preventing HBV relapse in cancer patients receiving chemotherapy.
Clinical Trial registration number: NCT02081469
An Infant with Galactosemia: A Case Report
Authors: Gul Fahad , Qudrat Syeda Mamoona , Khan Hashim , Ashraf Muhammad , Basit Jawad , Nashwan Abdulqadir J. 
Published: June 2023

Abstract
Classic galactosemia is a rare inborn error of galactose metabolism which is caused by a deficiency of an enzyme known as galactose-1-phosphate uridyl transferase (GALT). A 4-month-old male infant presented with yellowish discoloration of the skin and eyes (jaundice) and clay-colored stools. On examination, the baby has normal development and no signs of chronic liver disease. Blood tests and ultrasound show raised bilirubin and liver enzymes, but no structural abnormality or biliary atresia. However, urine sugar chromatography detected galactose and lactose, and a direct enzyme assay confirmed a deficiency of galactose-1-phosphate uridyl transferase. The patient was treated with a galactosemia-based diet, non-lactose milk, and vitamin supplements and showed improvement. The patient is currently on follow-up for monitoring.
Fast and Global Maximum Power Point Tracking of Photovoltaic Array Based on Potential Zones Firefly algorithm
Authors: Pi Linlin 
Published: June 2023

Abstract
Under partial shading conditions (PSC), conventional maximum power point tracking (MPPT) methods of photovoltaic array (PV) cannot be used to extract the global maximum power point (GMPP). Under uniform conditions (UIC), intelligent MPPT methods are time-consuming for tracking the MPP. This paper describes a potential zones firefly algorithm (PZFA) that can rapidly and accurately extract the GMPP under partial shading conditions and uniform conditions. The algorithm introduces the conceptions of potential and non potential zones；and devises zones maximum power estimation mechanism. Based on the zones maximum power estimation mechanism, the iterative mechanism of PZFA is designed, which can avoid the algorithm searching in non potential zones, quickly narrow the search zones of the algorithm, and ensure that the algorithm converges to GMPP quickly. Finally, simulation results indicate that the promoted PZFA can immediately and accurately track the GMPP under under partial shading conditions and uniform conditions, and the array output efficiency can be improved.