bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Left Heart Function in Heart Failure Patients with different types of Ejection Fraction using Transthoracic Three-Dimensional Echocardiography Heart-Model
Authors: Li Shen-Yi , Zhang Yi , Long Qing-Qing , Chen Ming-Juan , Wang Si-Yu 
Published: June 2024

Abstract

Purpose
Heart failure (HF) can be classified into three types based on left ventricular ejection fraction (LVEF). The newly developed transthoracic three-dimensional (3D) echocardiography-Heart-Model (HM) can be used to quickly analyze the volume and function of the left atrium (LA) and left ventricle (LV). This study aimed to evaluate the value of HM in HF patients.
Methods
117 patients with HF were included. Participants were divided into three groups: HFpEF (EF ≥ 50%), HFmrEF (EF = 41–49%), and HFrEF (EF ≤ 40%). HM was used to analyze the 3D cardiac functional parameters. LVEF was also obtained using the biplane Simpson’s method. NT-proBNP concentrations were measured.
Results
There were significant differences in age, female proportion, body mass index, and comorbidities among the three groups. The 3D volumetric parameters of the LA and LV increased while the LVEF decreased from HFpEF to HFmrEF, then to HFrEF. The LV E/e' in HFrEF patients was significantly higher than that of HFpEF patients. The time required to measure LVEF using HM was significantly shorter than using the conventional biplane Simpson’s method. The increases in NT-proBNP concentrations followed a pattern: HFrEF > HFmrEF > HFpEF. The concentration of NT-proBNP was positively correlated with LV volumes, and negatively correlated with LVEF using both HM and the biplane Simpson's method.
Conclusions
LA and LV volumes increase and the derived LV systolic function decrease with the severity of HF types determined by HM. The functional parameters measured with HM are associated with laboratory indicators. HM is feasible for routine clinical application.
The chronic toxicity and intergenerational effects of environmental concentration of N-(1,3-dimethylbutyl)-N’- phenyl-p-phenylenediamine (6PPD) alone and the mixture of 6PPD and Zn 2+ to Daphnia magna (Cladocera)
Authors: Yang Liu , Liu Kexin , Shi Lina , Chen Ming , Liu Junyan , Dai Shiniu , Xi Yilong , Wen Xinli L. 
Published: June 2024

Abstract

N-(1,3-dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD) and Zn2+ extensively used in the manufacturing process of tires, can be frequently detected in freshwater. However, the chronic toxicity of environmental 6PPD concentrations remains uncertain, and the intergenerational effects of single treatment of 6PPD and joint exposure of 6PPD and Zn2+ at environmental level are still unknown. In this study, the chronic toxicity and intergenerational effects of environmental concentrations of 6PPD (0.02-20 µg/L) and the mixture of 6PPD and Zn2+ (5 µg/L) were conducted based on three-generation bioassays using Daphnia magna. In F0, 6PPD produced a hormesis effect on reproduction of D. magna, and a dose-response relationship was observed for the total number of offspring. In the presence of Zn2+, the reproduction toxicity of 6PPD was exacerbated. Across three generations, the degenerative maternal effect was concurrently observed in the 0.02 µg/L 6PPD alone and the combined treatment of 0.02 µg/L 6PPD and Zn2+, but the adaptive maternal effect was simultaneously shown in the single and the joint exposures with 20 µg/L 6PPD. However, the grandmaternal effect only occurred in the co-exposure treatment with 20 µg/L 6PPD, suggesting that Zn2+ could be capable to stimulate the potential toxicity of 6PPD. Our study would provide the first insight into the intergenerational effects of 6PPD alone and the mixture of 6PPD and heavy metal at environmentally relevant concentrations, and could be conducive to understand the environmental risk of tire-derived chemicals due to the synergistic effect of 6PPD and Zn2+ and the delayed toxicity effect across generations.
The role of postoperative blood pressure management in early postoperative hemorrhage in awake craniotomy glioma patients
Authors: Demetz Matthias , Krigers Aleksandrs , Uribe-Pacheco Rodrigo , Pinggera Daniel , Klingenschmid Julia , Thomé Claudius , Freyschlag Christian F. , Kerschbaumer Johannes 
Published: June 2024

Abstract

Purpose:
Postoperative hemorrhage can severely affect the patients’ neurological outcome after awake craniotomy. Higher postoperative blood pressure can increase the risk of postoperative hemorrhage. The aim of this study was to investigate the role of postoperative blood pressure and other common radiological and epidemiological features with the incidence of postoperative hemorrhage.
Material & methods:
In this retrospective analysis, we included patients who underwent awake surgery at our institution. We assessed the blood pressure both intra- and postoperatively as well as the heart rate for the first 12 hours. We compared a cohort with postoperative hemorrhage, who required further treatment (surgical revision or intravenous antihypertensive therapy), with a cohort with no postoperative hemorrhage.
Results:
We included 48 patients with a median age of 39 years. 9 patients (19%) required further treatment due to postoperative hemorrhage, which was surgery in 2 cases and intensive blood pressure measurements in 7 cases. However, with early treatment, no significant difference in Performance scores at follow-up could be found.
Patients with postoperative hemorrhage showed significantly higher postoperative systolic blood pressure during the hours 3-12 (p<0.05) as well as intraoperatively throughout the procedure (p<0.05).
In ROC and Youden Test, a strong impact of systolic blood pressure over 140mmHg during the early postoperative course could be shown.
Discussion:
Postoperative hemorrhage is a rare but possible complication in awake surgery glioma patients. To avoid postoperative hemorrhage, treating physicians should aim strictly on systolic blood pressure of under 140mmHg for the postoperative course.
Utilizing Vortex pulse and suitable focus distance to improve the stability of laser-induced breakdown spectral (LIBS)
Authors: Gao Jian , Chen Yang , Yang Jiaxing , Sun ShaoHua , Hu Bitao , Liu ZuoYe 
Published: June 2024

Abstract

In order to study the signal stability of reheated double pulse laser-induced breakdown spectroscopy (LIBS). Utilizing single Gaussian and Vortex pulse, the distance between the lens and sample is changed to exam the focus position effect by measuring the plasma emission spectrum. The maximum signal intensity is achieved when the focal point is behind the target. In the double Gaussian and Vortex-Gaussian LIBS schemes, the variation of spectral intensity with the inter-pulse delay time are also investigated. The change of spectral intensity with the inter-pulse delay time has a great correlation with the energy of Vortex pulse and presents a completely different trend with a low, medium and high laser pulse energy. The spectral intensity of plasma emission is closely related to the plasma temperature. Meanwhile, the Vortex-Gaussian scheme can significantly improve the spectral stability at low laser energy flux. These results show that the combination of Vortex beam and Gaussian beam can greatly enhance the spectral intensity and detection stability, presenting a strong application prospect in nondestructive detection.
A new dynamic shift mechanism based on cyclic group theory for continuous attractor neural networks
Authors: Zhang Zhihui , Tang Fengzhen , Zhao Hangpiao , Li Yiping , Feng Xisheng 
Published: June 2024

Abstract

Spatial cognition plays a crucial role in enabling animals to navigate effectively, whether hunting prey or exploring for food. Continuous attractor neural networks (CANNs) have been developed to model spatial cells, such as head direction cells, place cells and grid cells. However, how to maintain long-term spatial memory and accurately transfer network activity in CANNs is still unclear. We design a modified version of CANNs that can maintain long-term spatial memory without external cues. Based on this redesigned CANN, we propose a novel dynamic shift mechanism. It leverages cyclic group theory to dynamically adjust connections between neurons. These synaptic changes effectively shift the network activity according to speed information. Interestingly, our method exhibits anticipatory and delayed transfers, analogous to the predictive coding observed in the brain's entorhinal speed cells and grid cells. Compared to the existing biological shift mechanism, our method demonstrates significant advantages in both computation speed and path-integration accuracy. Notably, our approach facilitates vector-based navigation with high accuracy. We rigorously verified its effectiveness through mathematical analysis and further validated it with simulated and real-world data. Experimental results demonstrate that our method accurately determines the navigation vector, enabling precise navigation between the current location and the target position. This work has established a comprehensive theoretical framework encompassing the entire process from inputs to cognition coding, and further extending to vector-based navigation, laying the foundation for practical implementation in bio-inspired robot navigation systems.
Zebrafish casr affects swim bladder inflation by regulating heart development
Authors: Liu Ling , Hu Yuyao , Xie Binling , Zhu Junwei , Zeng Ting , Huang Wen , Huang Jian , Lu Xiaochun , Yang Chengbo , Li Jianzhong , Chen Xiangding , Xie Huaping 
Published: June 2024

Abstract

Background: Calcium is fundamental to biological processes, and the Calcium sensing receptor (CaSR) plays a key role in maintaining calcium homeostasis. This process is intimately related to numerous cardiovascular diseases and various types of cancers. However, the role of CaSR in heart development is yet to be thoroughly understood. To delve into this, we conducted a casr gene knockout experiment, analyzed cardiac physiological functions, and performed transcriptomics to investigate the mechanism of the casr gene in zebrafish heart development.
Results: We successfully established casr gene knockout lines in zebrafish with Tuebingen (TU) backgrounds. Compared to the control, casr mutant embryos exhibited a smaller heart size, reduced heart rate, and diminished cardiac output. Additionally, these mutants exhibited a curved body structure and a mal-developed swim bladder. Zebrafish larvae began to die at 11 days post-fertilization (dpf). Subsequent transcriptome sequencing andbioinformatics analysis revealed that the loss of casr disrupts cardiac muscle contraction, leading to defective swim bladder inflation and ultimately death. Furthermore, we crossbred casr mutant lines with Tupfel long-fin (TL) background nkx2.5: ZsYellow transgenic lines, and subsequently obtained a casr-/- line where the swim bladder developed normally. Furthermore, qPCR results indicated that the expression of genes linked to cardiac muscle contraction turned to normal. Further experimental results demonstrated that the survival rate of casr mutants was influenced by the TL background.
Conclusions: Taken together, casr is vital for zebrafish swim bladder inflation and heart development, exerting its regulatory role through the Wnt signaling pathway and the cardiac muscle contraction. Importantly, the TL background significantly impacts the development of casr zebrafish mutant embryos.
A Comparative Study of RT-PCR, FISH, and Karyotyping for t(9;22) Positive Leukemias, and Their Outcomes in Pediatric Patients in a Low Middle-Income Country (LMIC)
Authors: Bukhari Syed Ibrahim , Altaf Sadaf , Saleem Hira , Fadoo Zehra , Belgaumi Asim Fakhruddin , Moatter Tariq , Ansar Zeeshan 
Published: June 2024

Abstract

Objectives: Various diagnostic tests are available for detecting t(9;22) transcripts in acute and chronic leukemia. This study aims to determine the most effective and cost-efficient testing strategy. Additionally, we analyzed the outcomes of Ph+ leukemias in our population.
Methods: Retrospective cohort study was conducted at a tertiary care center in a LMIC. Online and paper charts from January 2011 till December 2022, of patients <18 years of age were reviewed. The sensitivity (SS), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) of RT-PCR, FISH, and karyotyping were compared. Survival analysis was performed using the Kaplan-Meier method.
Results: The cohort consisted of 13 ALL and 10 CML. The median time and cost for RT-PCR results were 7 days (IQR: 7-9) and $93, respectively. All patients were positive on RT-PCR. Three patients initially categorized as ALL were re-categorized as CML after transcript variant verification by RT-PCR.
The SS, SP, PPV, and NPV of RT-PCR relative to FISH were 100%, 0%, 82.6%, and 0%, respectively. Compared to cytogenetics, these values were 100%, 0%, 73.9%, and 0%, respectively. The median time and cost for cytogenetics results were 14 days (IQR: 12-15) and $48, respectively. The SS, SP, PPV, and NPV of cytogenetics relative to RT-PCR were 73.9%, 0%, 100%, and 0%, respectively. For FISH, these values were 84.2%, 78%, 94%, and 50%, respectively. The median time and cost for FISH results were 10 days (IQR: 9-12) and $57, respectively. The SS, SP, PPV, and NPV of FISH relative to RT-PCR were 82.6%, 0%, 100%, and 0%, respectively, while for cytogenetics, these values were 94%, 50%, 84.2%, and 75%, respectively.
The median survival rate for ALL and CML patients was 44.4% and 78% respectively. A significant survival difference was observed between those who received TKI and those who did not (68.8% vs. 0%; P=0.001).
Conclusions: Qualitative RT-PCR was found to be the most effective and cost-friendly tool for the accurate and timely diagnosis of Ph+ leukemias, in low resource setting. The outcomes in our patients can be improved by timely diagnosis, early initiation of TKIs, treatment compliance, and preventing infections.
Low complexity vector magnetic information detection method based on diamond NV color center
Authors: Ni Zhaoheng , chen Huan , Huang Yuhan , Wang Aoxue , Yang Kai , Chen Peng 
Published: June 2024

Abstract

This paper introduces a low-complexity vector magnetic field solution based on a diamond NV ensemble. Firstly, the bias magnetic field of the diamond NV colour centre equifrequency difference optical detection magnetic resonance (ODMR) spectrum is adjusted, and the conversion matrix is derived by utilising the projection of the external magnetic field on the NV axis of the diamond, which exhibits an equal probability distribution, and the preset magnetic field to be measured. The vector magnetic field information solution model is then constructed. Subsequently, the pulse timing system is employed to regulate the antenna, enabling the generation of microwave pulse signals with uniform timing and frequency difference. Finally, the accuracy of the vector magnetic information solution is verified by the established model and the entire detection system. The final vector magnetic field detection exhibits the amplitude difference of coil calculation results is less than 3.6%, and the angle difference of coil calculation results is less than 1.8◦. In comparison to alternative methodologies, the amplitude and angle discrepancies in coil calculation outcomes are simultaneously minimized.
AI-assisted cervical cytology precancerous screening for high-risk population in resource limited regions using compact microscope
Authors: Liu Xiuli , Bai Jiaxin , Li Ning , Ye Hua , Li Xu , Chen Li , Hu Junbo , Pang Baochuan , Chen Xiaodong , Rao Gong , Hu Qinglei , Liu Shijie , Sun Si , Li Cheng , Lv Xiaohua , zeng Shaoqun , Cai Jing , Cheng Shenghua 
Published: June 2024

Abstract

The insufficient coverage of cervical cytology screening in underdeveloped countries or remote areas is currently the bottleneck hurdle to its widespread implementation. Conventional centralized medical screening methods are heavily dependent on sizable, costly investments as well as sufficient qualified pathologists. In this paper, we have developed a cervical precancerous assisted-screening system for identifying high-risk squamous intraepithelial lesion (SIL) cases in regions with limited resources. This system utilizes a low-cost miniature microscope and a low-pathologist-reliance artificial intelligence algorithm. We design a low-cost compact microscope with pixel resolution about 0.87 mm/pixel for imaging cytology slides. To tackle the challenge of sparely-distributed lesion cells in cytology whole slide images (WSIs), we have developed a dual-stage slide classification model. In first stage, we train an instance-level classifier by self-supervised pretraining on large-number unlabeled cervical images and transfer learning on small-number labeled images, aiming to reduce negative cells within a slide. In the second stage, we employ our proposed Att-Transformer, which aggregates deep features extracted from the top 200 lesion probabilities instances, for slide-level classification. We train and validate our model on 3,510 low-resolution WSIs collected from four different centers, and evaluate our model on 364 slides from two external centers in remote areas, achieving AUC (area under receiver operating characteristic curve) of 0.87 and 0.89 respectively for screening high risk cases. We also evaluate it on new independent cohorts of 391 slides from the original four centers and achieve AUC of 0.89. Overall, all the results indicate that integration of our innovative algorithm together with the compact microscope represents a promising approach to cervical cytology precancerous screening for high-risk population in medical resource limited regions. This affordable and accessible screening is significant as it contributes towards the goal of eliminating cervical cancer worldwide.
Metabolic interactions underpinning high methane fluxes across terrestrial freshwater wetlands
Authors: Wilkins Michael , Bechtold Emily , Ellenbogen Jared , Villa Jorge , Ferreira Djennyffer de Melo , Oliverio Angela , Kostka Joel , Rich Virginia , Varner Ruth , Bansal Sheel , Ward Eric , Bohrer Gil , Borton Mikayla , Wrighton Kelly 
Published: June 2024

Abstract

Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms mediate methane cycling, yet knowledge of their conservation across wetlands remains scarce. To address this, we integrated 1,118 16S rRNA amplicon datasets (116 new), 305 metagenomes (20 new) that yielded 4,745 medium and high-quality metagenome assembled genomes (MAGs; 617 new), 133 metatranscriptomes, and annual methane flux data across 9 wetlands to create the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This new resource was leveraged to link microbiome compositional profiles to encoded functions and emissions, with specific focus on methane-cycling populations and the microbial carbon decomposition networks that fuel them. We identified eight methane-cycling genera that were conserved across wetlands, and deciphered wetland specific metabolic interactions across marshes, revealing low methanogen-methanotroph connectivity in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and was a strong predictor of methane flux, demonstrating the potential broad relevance of methylotrophic methanogenesis in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux and provide an extensive publicly available database to advance future wetland research.
Rapid response to pressure variations in water distribution networks through machine learning-enhanced data acquisition
Authors: Kim Hyunjun , Jung K. J. , Lee S. , Jeong E. H. 
Published: June 2024

ABSTRACT

This study investigates rapid dynamic pressure variations in water distribution networks due to critical incidents such as pipe bursts and valve operations. We developed and implemented a machine learning (ML)-based methodology that surpasses traditional slow cycles of pressure data acquisition, facilitating the efficient capture of transient phenomena. Employing the Orion ML library, which features advanced algorithms including long short-term memory dynamic threshold, autoencoder with regression, and time series anomaly detection using generative adversarial networks, we engineered a system that dynamically adjusts data acquisition frequencies to enhance the detection and analysis of anomalies indicative of system failures. The system's performance was extensively tested using a pilot-scale water distribution network across diverse operational conditions, yielding significant enhancements in detecting leaks, blockages, and other anomalies. The effectiveness of this approach was further confirmed in real-world settings, demonstrating its operational feasibility and potential for integration into existing water distribution infrastructures. By optimizing data acquisition based on learned data patterns and detected anomalies, our approach introduces a novel solution to the conventionally resource-intensive practice of high-frequency monitoring. This study underscores the critical role of advanced ML techniques in water network management and explores future possibilities for adaptive monitoring systems across various infrastructural applications.
Assessment of soil erosion and sediment yield in the Peddavagu watershed, India, using a revised universal soil loss equation model (RUSLE) and GIS techniques
Authors: Shekar Padala Raja , Mathew Aneesh 
Published: June 2024

ABSTRACT

The present investigation was carried out within the Peddavagu watershed, which is located in India. The necessary datasets, including soil, land use land cover, rainfall, and digital elevation model, were processed and analysed within a Geographic Information System framework. To evaluate soil loss within the watershed, the present investigation employed the revised universal soil loss equation (RUSLE) model. Subsequently, the sediment yield is estimated based on the sediment delivery ratio (SDR). The average annual soil loss was estimated at 17.91 tonnes/hectare/year, which is high soil erosion risk. The RUSLE model's accuracy is 82.1%. Moreover, the findings revealed that sub-watersheds (SW) 9 and SW 3 exhibited the maximum and minimum average annual soil loss. The Peddavagu watershed's SDR was 0.210. Annually, 3.76 tonnes/hectare/year of sediment were transported to the Peddavagu watershed outlet. The findings revealed that SW 9 and SW 5 exhibited the maximum and minimum average annual sediment yield. The model's performance was evaluated by comparing its predictions with gauge data for validation. The observed actual data indicated a yield of 3.66 tonnes/hectare/year, while the model predicted a yield of 3.76 tonnes/hectare/year. This resource offers significant insights for policymakers and decision-makers on sustainable watershed management techniques.