bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy and safety of combined anti-vascular and two-staged stereotactic radiosurgery therapy for brain metastases with brainstem compression: a retrospective multicenter study
Authors: Zhu Xiuming , Zhou Jia , Chen Qun , Chen Haining , Li Renli , Zhu Yucun , Wang Zheng 
Published: June 2024

Abstract

Stereotactic radiosurgery poses a significant risk when treating brain metastases in close proximity to the brainstem. To address this issue, a novel approach known as "combined anti-vascular therapy" has been devised for these metastases. This treatment regimen involves a one-week course of two-staged stereotactic radiosurgery (2-SSRS), supplemented with the administration of the anti-vascular agent bevacizumab during the radiosurgery interval. The objective of this study is to assess the efficacy and safety of a combined anti-vascular and two-staged stereotactic radiosurgery therapy for brain metastases with brainstem compression. A retrospective analysis was conducted on patients treated at five gamma knife treatment centers to assess changes in tumor size and peritumoral edema volume. Clinical symptom changes were evaluated using the Headache Scale (VAS), Dizziness Disorder Inventory (DHI), Vomiting Scale (VS), and Glasgow Coma Scale (GCS). The Karnofsky Task Scale (KPS) and Barthel Index (BI) were used to assess overall physical fitness and physical activity rehabilitation. Tumor local control (TLC) and overall survival (OS) rate were also calculated for the patients. Among the 36 patients with brain metastases with brainstem compression, 36 received combined anti-vascular therapy. Both edema volume and tumor volume significantly decreased during the treatment period and post-treatment 3 months (p < 0.01). Clinical symptoms, as indicated by median scores of VAS, DHI, VS, and GCS, showed significant improvement during treatment and at the 3-month follow-up (p < 0.01). Median changes in KPS and BI, reflecting overall physical fitness and physical activity rehabilitation, were also similar and statistically significant (p < 0.01). The patient cohort exhibited a median overall survival of 14.2 months, with corresponding 6-month and 12-month survival rates of 91.7% and 80.0%, respectively. Tumor local control rates at 6 and 12 months were 94.7% and 78.9%, respectively.The combination of anti-vascular therapy with 2-SSRS demonstrates safety and efficacy in treating patients with brain metastases with brainstem compression. This approach rapidly alleviates patient symptoms, effectively manages tumor progression, extends overall survival, and exhibits manageable adverse effects.
Development of an in Vitro Model of the Neurovascular Unit for BBB Permeability Linked Neuroactivity Screening
Authors: Lubin Kelsey E. , Xu Zhuangyan (Monica) , Sluka James P. , Knipp Gregory 
Published: June 2024

Abstract

Many potential neurotherapeutic agents fail in the later stages during development due to insufficient blood-brain barrier (BBB) permeability or neurotoxic effects. To address this, we developed an in vitro model incorporating the neurovascular unit (NVU) — astrocytes, pericytes, neurons, and brain microvessel endothelial cells — designed to simulate the in vivo BBB and improve early drug screening. This model uses a direct contact triculture system enhanced by integrating SH-SY5Y neuron-like cells, enabling the study of permeability-linked neuronal responses. Our results show that this expanded NVU model, employing a Transwell® system, enhances the BBB’s restrictive properties and neuronal viability, potentially due to improved cell-cell signaling. Additionally, the model demonstrated increased efflux transporter expression, providing a more physiologically relevant assessment of neuroactivity in relation to BBB permeability. This innovative NVU model offers a predictive and robust tool for evaluating neurotherapeutic agents, facilitating the prioritization of candidates in large compound libraries and potentially reducing attrition rates in drug development. It represents a significant advancement in the methodology for early-stage neurotherapeutic screening, aligning in vitro findings more closely with in vivo responses.
Grid cell populations maintain their hexagonal firing patterns on a circular track
Authors: Yim Man Yi , Walton Steven , Hedrick Kathryn 
Published: June 2024

Abstract

In an open 2D environment, grid cells in the medial entorhinal cortex are known to be active in multiple locations, displaying a striking periodic hexagonal firing pattern covering the space. According to attractor network theory, grid cell activity in any stable 1D environment is a slice through an underlying 2D hexagonal pattern, but this underlying pattern has not been observed in some experimental studies on a circular track. Grid cells are believed to play a fundamental role in path integration, and understanding their behavior in various environments is crucial for understanding the flow of information through the entorhinal-hippocampal system. We analyzed the activity of grid cells when rats traversed a circular track. A previous study involving this data set analyzed individual grid cell activity patterns separately, but we found that individual grid cells provide insufficient data for determining the underlying spatial activity pattern. To circumvent this, we compute the population autocorrelation, which pools together population responses from grid cells within the same module. This novel approach recovers the underlying six-peak hexagonal pattern that was not observable in the individual autocorrelations. We also use the population autocorrelation to infer the population lattice properties, revealing how the lattice differs across environments. Furthermore, the population autocorrelation of the linearized track reveals that at the population level, grid cells have an allocentric code for space. These results are strong support for the attractor network theory for grid cells, and our novel approach can be used to analyze grid cell activity in undersampled environments.
Insights into structural features and phylogenetic implications of the complete mitochondrial genome of Fasin rainbow fish (Melanotaenia fasinensis)
Authors: Marnis Huria , Syahputra Khairul , Kadarusman Kadarusman , Darmawan Jadmiko , Cartealy Imam Civi , Larashati Sekar , Kusuma Wahyu Endra , Hayuningtyas Erma Primanita , Iswanto Bambang , Asaf Ruzkiah , Muchlies Admi Athirah , Subangkit Arsad Tirta , Sularto Sularto , Indrawati Indrawati 
Published: June 2024

Abstract

The Fasin Rainbow fish, scientifically known as Melanotaenia fasinensis, is highly sought after by aquarium enthusiasts due to its vibrant colors and adaptability to artificial aquatic environments. This species is endemic to the karst landscape of the Bird’s Head region in Papua, Indonesia, and belongs to the Melanotaeniidae family. Discovered relatively recently in 2010, it has been designated as endangered by the International Union for Conservation of Nature (IUCN) in 2021. However, there is currently insufficient data regarding its phylogenetic positioning. To address this gap, our study employed next-generation sequencing to analyze the entire mitochondrial genome of M. fasinensis. The mitochondrial genome consists of 13 protein-coding genes, 22 transfer RNA genes, and two ribosomal RNA genes, with a total length of 16,731 base pairs. The base composition of the mitogenome revealed percentages of 27.76% adenine (A), 27.34% thymine (T), 16.15% guanine (G), and 28.75% cytosine (C). Our phylogenetic analysis, based on nucleotide sequences mitogenome, indicated that M. fasinensis occupies a relatively basal position within the Melanotaenia genus. This study provides valuable molecular insights for further exploration of phylogeography and evolutionary history, not only for M. fasinensis but also for other members of the Melanotaenia genus.
Predictive Failure Mode Identification in Reinforced Concrete Flat Slabs Using Advanced Ensemble Neural Networks
Authors: Barkhordari Mohammad Sadegh , Fattahi Hadi , Armaghani Danial Jahed , Khan Naseer Muhammad , Afrazi Mohammad , Asteris Panagiotis G. 
Published: June 2024

Abstract

Reinforced concrete (RC) flat slabs without transverse reinforcement are commonly used in RC buildings. Despite their appeal and widespread use, these slabs are susceptible to brittle shear failure. While most previous research has focused on estimating the punching shear strength (PSS) of RC flat slabs, accurately identifying their failure modes is crucial for effective design and reinforcement. This paper presents an analysis of ensemble neural network and ensemble deep neural network models, including bagging neural network (BaggingNN), model averaging (MA), separate stacking (SS), and integrated stacking (IS) algorithms, to develop a predictive model for failure mode identification. The results of this new model are compared with those of earlier studies. To evaluate how variables such as concrete strength and reinforcement ratio impact the failure modes of RC flat slabs, the model's prediction process is examined using the SHapley Additive exPlanation (SHAP) method. Findings indicate that the SI algorithm outperformed the BaggingNN, MA, and SS algorithms, and also surpassed models from previous research.
Analysis of the impact of the COVID-19 pandemic lockdown on the spatiotemporal variations in water quality in three wetland areas in Oran, western Algeria
Authors: BENDIB Abdelhalim , BOUTRID Mohamed Lamine 
Published: June 2024

Abstract

In arid regions, water is a scarce and invaluable resource. Moreover, with urban expansions and socioeconomic changes, its quality has become a matter of significance and an indicator of environmental preservation. The objective of this study was to shed light on the impact of the COVID-19 pandemic on three wetlands in Oran, western Algeria (Lake of Dayet Oum Rhalez (DORh), Lake of Dhayat Morasli (DMo), and Lake of Sidi Chahmi (SCh)). Three parameters, namely, the chlorophyll-a concentration (Chl-a), trophic state index (TSI), and Secchi depth (SD), were selected and calculated for the period from 2019–2022. The results showed that, except for DORh, the Chl-a concentration decreased from 41.73 µg/l to 21.01 µg/l for DMo and from 42.82 µg/l to 23.08 µg/l for SCh between 2019 and 2021. The TSI decreased from 5.67 to 5.32 for DORh, from 5.95 to 5.36 for DMo, and from 5.32 to 4.12 for SCh. These results are also validated by the SD values, with an improvement in water transparency from 1.16 m to 2.61 m for DORh, from 1.31 m to 2.75 m for DMo, and from 1.4 m to 2.07 m for SCh. This reduction in biological activity justifies the impact of the applied lockdown on the improvement of water quality. Additionally, despite this improvement, the overall health of the three studied wetlands remains concerning (eutrophic ecological characteristics), and water quality is often mediocre. This study, in its entirety, can contribute to better decision-making and targeted actions for the preservation of these ecosystems.
Incorporating Mobility on Demand into Public Transit in Suburban Areas: A Comparative Evaluation of Cost-Effectiveness
Authors: Cai Mingming , Ashour Lamis Abu , Shen Qing , Chen Cynthia 
Published: June 2024

Abstract

Traditional fixed-route transit services are inefficient in low-density areas due to limited and dispersed service demand. Many transit agencies look for effective alternatives to provide adequate transportation services in these areas, especially by leveraging mobile ICT-enabled new mobility services. This study evaluates the cost-effectiveness of transit incorporating mobility-on-demand (TIMOD) compared to fixed-route bus transit, driving, and commercial ride-hailing services in suburban areas. It extends a comprehensive analytical framework to evaluate the cost-effectiveness of TIMOD and other alternatives from a societal perspective by considering transportation externalities. The analysis accounts for travelers’ monetary and time costs, service providers’ operating costs, and external costs to society. Using real-world data from a TIMOD program, Metro Flex, in the Seattle region and estimates based on simulation, the study compares the economic cost of TIMOD trips with counterfactuals by other travel modes within two separate suburban case areas. The results indicate that, in our study areas, TIMOD trips have a total generalized cost for travelers that is higher than driving but lower than fixed-route transit trips and ride-hailing trips, owing to its on-demand nature coupled with subsidized fare. Compared to TNCs, TIMOD’s more common shared rides contribute to its lower external costs by reducing vehicle miles traveled per person. Adding service operation, TIMOD in the suburban areas becomes less cost-effective due to high operating costs. However, the disparity is slight in comparison to fixed-route transit. Our findings also show that areas with higher population densities result in lower operation costs per rider of TIMOD. Riders living in higher income areas with lower population densities and more limited transit services benefit more from TIMOD services with a higher reduction in travelers’ generalized cost compared to fixed-route transit. The study highlights the potential benefits and tradeoffs of providing TIMOD services in suburban areas, shedding light on the conditions under which such services are economically competitive.
Real-Time IoT Solutions for Automating Occupational Safety in 3rd World Industries
Authors: Gharami Kanchon , Islam Mazharul , Barai Anirban , Rahman Md. Asifur , Shovan S.M. , Sri Md. Azmain Yakin 
Published: June 2024

Abstract

Occupational safety and health is an essential part of the work setting and so with effective monitoring measures it has the potential to significantly enhance workers' quality of life, decrease the financial consequences of workplace incidents, and boost efficiency. However, ensuring occupational safety and health in 3rd world industries is a challenging task due to lack of regular monitoring, proper emergency response system, and awareness. Integration of Internet of Things (IoT) technology can offer new opportunities for monitoring and management of occupational safety and health risks. To this end, this paper presents an affordable IoT-based real-time occupational safety and health monitoring system that is suitable for garment industries. The proposed monitoring and emergency alert system has the capability to detect potential hazardous conditions by analyzing data gathered from five interlinked modules that continuously monitor the work environment through various sensors. To assess the effectiveness of the proposed IoT system, this study conducted individual module tests in appropriate settings and compared their performance with standard equipment readily available on the market.
Absorption, Metabolism, and Excretion of Oral [14C] Radiolabeled Donafenib: An Open-Label, Phase I, Single-Dose Study in Humans
Authors: Ma Sheng , Yi Ling , Bian Yicong , Lv Binhua , Zhang Cong , Zhang Hua , Miao Liyan 
Published: June 2024

Abstract

Donafenib, a deuterated derivative of Sorafenib, exhibited significant efficacy and improved safety for the treatment of hepatocellular carcinoma (HCC) in clinical trials. In this study, the absorption, metabolism, and excretion of donafenib were investigated in six healthy Chinese male volunteers after administration of a single oral dose of 300 mg of [14C]donafenib (120 µCi). Mean recovery of total radioactivity was 97.31% of the dose. A total of 6 metabolites were identified in plasma, urine and feces. The parent drug was the major radioactive component detected in the plasma and feces, accounting for 67.52% of total radioactivity and 83.17% of the dose, respectively. M2, the N-oxidation metabolite was a major metabolite in human plasma. Overall, donafenib was excreted mainly by feces through liver metabolism and less by kidney. The metabolic pathways of donafenib identified were similar to those of sorafenib, but metabolite profiles in plasma, urine and feces were quantitatively different, and especially the amide hydrolysis metabolite M6 in sorafenib was not detectable in donafenib. The difference of metabolic characteristics between donafenib and sorafenib, due to the deuterium isotope effect, may partially explain the better safety and efficacy of donafenib as the treatment of advanced HCC.
Variational Bayesian Inference for Modelswith Nuisance Parameters and an Intractable Likelihood
Authors: Tseng Yu-Hsiu , Tran Minh-Ngoc , Kohn Robert 
Published: June 2024

Abstract

A primary challenge in Bayesian analysis lies in computing the posterior distributionof model parameters, a task that becomes more challenging for models with a largenumber of parameters or when the likelihood is intractable; as seen in Bayesian Lassoand state-space models. Often, the focus of the analysis is on a subset of the parameters,with the remainder regarded as nuisance parameters, which are either not of inferen-tial interest or are introduced to simplify computational processes. This complexitynecessitates more refined computational methods. Variational Bayesian inference (VB) has emerged as a powerful solution, enhancing computational efficiency by recastinginference as an optimization problem within a family of tractable distributions. How-ever, common VB techniques sometimes fall short, especially for models with nuisanceparameters or intractable likelihoods. To overcome these limitations, we introduce a uni-fied VB framework, termed Hybrid Variational Bayes (HVB), designed to achieve moreprecise Bayesian inference in such scenarios. This framework innovatively leverages ahybrid variational structure between the parameters of interest and nuisance parame-ters. A significant contribution of this work is the development of two robust gradientapproaches that effectively reduce variance, enhancing reliability in gradient-based op-timization algorithms for approximating complex posterior distributions. Furthermore,we link our strategy to Fisher’s identity, providing deeper theoretical insights. We alsoestablish a method to treat the stochastic element of likelihood estimation as a nuisanceparameter in models with intractable likelihoods due to complexity or computationaldemands. Through theoretical exploration and a series of illustrative examples, ourapproach demonstrates notable improvements over traditional VB methods.
Association of MnSOD, CAT, and GPx1 gene polymorphism with risk of diabetic nephropathy in South Indian patients – A case control study
Authors: Begum Farhana , Lakshamanan Karpagavel 
Published: June 2024

Abstract

Purpose:
Diabetic nephropathy (DN) is a remarkable complication of type 2 diabetes mellitus (T2DM), mediated by oxidative stress playing a key role. The antioxidants gene polymorphism (MnSOD, CAT, GPx1) have been interconnected to T2DM and DN. The role of these genes in the pathogenesis of DN among T2DM individuals in the South Indian population is investigated in this study. It clarifies the importance of early manifestation and reliable genetic indicators modulating the mechanism of oxidative stress in DN.
Methods:
The voluntary participants were divided and grouped as Group 1: Control, Group 2: T2DM without DN, and Group 3: T2DM with DN (n = 100 in each group). The levels of blood glucose, HbA1c, renal profile, plasma SOD, CAT, GPx1, MDA, and TAS were assessed. MnSOD, CAT, and GPx1 were genotyped via Tetra-arms PCR.
Results:
All the genotypic models of GPx1 depicts a significant role in the progression of T2DM patients with nephropathy (Co-dominant [OR: 2.134; 95%CI (1.202–3.788), p < 0.01], dominant [OR: 2.015; 95%CI (1.117–3.634), p = 0.02], and recessive model [OR: 2.215; 95%CI (1.235–3.972), p = 0.008]) but is not associated with T2DM without DN individuals; while MnSOD and CAT genotypes are not associated with the development of the disease. This data suggest that genotypes of GPx1 are at higher risk of developing DN in T2DM individuals. Moreover, MnSOD and GPx1 genotypes show significant difference in the antioxidant parameters compared to CAT genotypes.
Conclusion:
In contradiction to earlier studies, our study have demonstrated that compared to MnSOD and CAT genotypes, GPx1 genotypes can be considered as a influential component for higher susceptibility and risk of DN in T2DM patients among South Indian population.
Large Language Model Understands Chinese Better with Mega Tokenization
Authors: Lu Xinyu , Wang Qizhen , Liu Xian 
Published: June 2024

Abstract

The rapid evolution of natural language processing has seen significant advancements in language models, particularly for languages with simpler orthographies. However, challenges persist in accurately processing and understanding languages with complex morphological structures, such as Chinese, due to the limitations of traditional tokenization methods. Introducing mega tokenization, which involves significantly larger tokens, represents a novel and transformative approach that enhances semantic preservation and contextual coherence in sophisticated character sequences. The study compares the performance of an adapted language model with mega tokenization against a standard model, demonstrating substantial improvements across tasks such as machine translation, text summarisation, and question answering. Through rigorous evaluation and statistical analysis, the adapted model shows superior performance metrics, indicating the effectiveness of mega tokenization in addressing the unique challenges posed by the Chinese language. The implications of this approach extend to various applications, underscoring its potential to revolutionise language processing in multilingual and high-stakes environments. Future research directions are proposed to further optimise and expand the applicability of mega tokenization across diverse linguistic contexts.
Curved Nanomagnets: An Experimental Archetype for Skyrmion Stabilization
Authors: Dugato Danian A. , Jalil Wesley , Cardias Ramon , Albuquerque Marcelo , Costa Marcio , Garcia Flavio 
Published: June 2024

Abstract

In the fields of nanomagnetism and spintronics, the controlled stabilization of mag- netic skyrmions is a topic of great interest for potential applications in data storage and innovative computing systems. This study delves into the intriguing phenomenon of skyrmions on a hexagonal array of curved nanomagnets. Through a combination of atomistic calculation, micromagnetic simulations, and experimental observations, we thoroughly explore the intricate interplay between magnetic parameters, curvature, and interfacial Dzyaloshinskii-Moriya interaction (iDMI) in the formation of these topolog- ically non-trivial magnetic structures. We have observed the spontaneous formation of isolated skyrmions (<150 nm) on a curved nanomagnet matrix of symmetric Pt/Co/Pt multilayer without the necessity of applied fields. Our research sheds light on the pro- found impact of geometric curvature on iDMI, offering invaluable insights for engi- neering and controlling skyrmionic configurations. This work advances nanomagnetism knowledge and sets the stage for designing skyrmion-based technologies.