bluuebunny/crossref_metadata_2025_split huggingface dataset:
KarXT Combines the Partial Benefits of Haloperidol for Positive Symptoms and Sulpiride for Negative Symptoms: Evidence from Computational Biology
Authors: Zhuo Chuanjun , Li Chao , Ma Xiaoyan , Li Ranli , Chen Ximing , Li Yachen , Zhang Qiuyu , Yang Lei , Tian Hongjun , Wang Lina 
Published: December 2024

Abstract

The new drug KarXT is a combination of xanomeline and trospium. KarXT is a unique antipsychotic that targets muscarinic receptors to reduce the positive and negative symptoms of schizophrenia. Haloperidol affects the positive symptoms and sulpiride affects the negative symptoms of schizophrenia. The shared and distinct molecular mechanisms of these three drugs are unclear. The objective of this study is to identify the potential molecular mechanisms underlying the effects of KarXT on schizophrenia and determine if the mechanism for KarXT overlaps with the benefits of haloperidol for positive symptoms and sulpiride for negative symptoms. The putative target genes for haloperidol, sulpiride, and KarXT were identified using PharmMapper, SwissTargetPrediction, GeneCards, CTD, and SuperPred. Targets associated with positive and negative symptoms of schizophrenia were selected from GeneCards and OMIM. A protein-protein interaction (PPI) network was constructed to identify core targets and GO and KEGG pathway enrichment analyses of the top 20 core targets were conducted using DAVID. A drug-pathway-target-disease network was constructed using Cytoscape. The search yielded 179 common targets for haloperidol against positive symptoms, 96 targets for sulpiride against negative symptoms, and 99 targets for KarXT against schizophrenia. Based on the PPI network and KEGG enrichment analyses, haloperidol affects positive symptoms by targeting the IL-17 signaling pathway via TNF, IL6, IL1B, MAPK3, and CASP3, and sulpiride affects negative symptoms by targeting the PI3K-AKT signaling pathway via BDNF, INS, AKT1, IGF1, and BCL2. KarXT affects schizophrenia by targeting the MAPK signaling pathway via AKT1, FOS, CASP3, NFKB1, and IGF1. Molecular docking revealed good binding affinities between the drugs and the potential core targets. This study provides insights into the distinct molecular mechanisms by which haloperidol and sulpiride affect distinct symptoms of schizophrenia. KarXT integrates the partial effects of both drugs, including CASP3 with haloperidol and AKT1 and IGF1 with sulpiride. Our results provide a theoretical basis for clinical applications and new directions for drug development.
The influence of lead brass alloys sampling parameters on the surface properties and mechanical responses
Authors: Hammi Maryama , Bourakadi Khadija El , Dahhou Mohammed , Lazrak Charaf , Eddaoui Abderrahim , Haimeur Amine El 
Published: December 2024

Abstract

Leaded brass alloys are widely used in mechanical applications, making the examination of their surface and mechanical characteristics crucial. This study aims to assess the resistance and mechanical response of leaded brass alloys cast in thermally conductive molds, with a focus on the β’-phase formation during casting.To investigate the mechanical properties, the samples undergo hardness testing, with von Mise stress calculation employed for mechanical visualization. X-ray diffraction (XRD) analysis is conducted to validate the observations and refine the impact of lead content. The study employs chill molds made of steel, iron, silica sand, marble, and clay to achieve a homogeneous, stress-free alloy. Mechanical preparation involves fine particle size (SiC1000) and chemical surface treatment, including electrolytic polishing and metallographic etching.Surface analysis reveals the presence of an α + β’ dual phase in all samples. The microstructure is found to be controllable through cooling speed, influenced by the thermal conductivity and heat transfer rate at the material/mold interface. Micro-hardness calculation indicates a correlation between hardness and microstructure, particularly an increase in the β’ phase. The findings suggest that controlling the cooling speed during casting can significantly influence the microstructure and mechanical properties of leaded brass alloys. This insight can inform the optimization of casting processes to achieve desired material characteristics, enhancing the performance and durability of brass components in mechanical applications.
An Optimization Protocol for MRI Examination Resource Allocation Based on Demand Forecasting and Linear Programming
Authors: Zhou Zhongbin , Zhou Hanyu , Qiao Yuanyuan , Gao Zhihan , Yang Ying 
Published: December 2024

Abstract

Objective: The accessibility of medical services in Mainland China had been on the rise, leading to a surge in the number of Magnetic Resonance Imaging (MRI) scans. This increase had caused substantial delays in MRI examination queues at large hospitals. With MRI equipment and exams being costly, over-purchasing machines could lead to underutilization of resources. It was, therefore, crucial to devise a comprehensive method that could shorten patient wait times and optimize the use of medical resources within hospitals.
Method: The research had utilized daily MRI examination application data from a hospital covering the period from July 1, 2017, to November 30, 2022. The Autoregressive Integrated Moving Average (ARIMA) model and the AutoRegressive Integrated Moving Average with exogenous (ARIMAX) model were developed using SAS (version 9.3) software. Moreover, Non-AutoRegressive (NAR) and Non-AutoRegressive with exogenous (NARX) models were built using MATLAB (version R2015b) to forecast future MRI examination demands. The predictive accuracy of these models was then assessed and compared. Based on the prediction outcomes, an Integer Linear Programming model was employed to calculate the optimal number of MRI examinations per machine per day, targeting cost reduction. An optimization flowchart for MRI examination resource allocation was developed by integrating critical process components, thus streamlining and systematizing the optimization process to improve efficiency.
Results: Analysis of the data revealed a weekly cyclical trend in MRI examination applications. Among the ARIMA, ARIMAX, NAR, and NARX models evaluated for their predictive skills, the NARX model emerged as the most accurate for forecasting. An Integer Linear Programming (ILP) model was utilized to plan the number of examinations for each MRI machine, effectively reducing costs. An optimization flowchart was developed to integrate key factors in MRI examination resource allocation, streamlining and systematizing the optimization process to enhance work efficiency.
Conclusion: This study offers a comprehensive protocol for optimizing MRI examination resource allocation, combining the predictive power of the NARX model, the planning capabilities of the Integer Linear Programming model, and the integration of other relevant factors via an optimization flowchart.
Clinical trial number: not applicable.
Evaluation of yeast extract, chitosan, and pectin as easy and cost-effective applications to increase indirubin and indigotin accumulation in Isatis tinctoria root cultures
Authors: CESSUR Alper , Baydar Nilgün Göktürk 
Published: December 2024

Abstract

This study was carried out to determine the effects of yeast extract, chitosan, and pectin as simple and cost-effective biotic elicitors on root growth and the accumulation of indigotin and indirubin in the root of Isatis tinctoia. For this purpose, different concentrations of yeast extract (1, 2, 3, and 4 g L− 1), chitosan (100, 150, 200, and 250 mg L− 1), and pectin (0.5, 1, 2, and 3%) were applied to 21 days old roots for 7 days. After harvest, roots were evaluated regarding fresh root weight, root growth index, dry root weight, and contents of indigotin and indirubin. As a result of the study, it was determined that yeast extract showed positive effects on root growth while chitosan inhibited. On the other hand, pectin had no positive or negative impact on root growth parameters. Yeast extract and chitosan increased indigotin accumulation in roots compared to control roots while indigotin amounts decreased with the pectin. Within yeast extract applications, the highest indirubin contents were obtained from the roots applied with 3 and 4 g L− 1 of yeast extract. All chitosan applications enhanced the indirubin accumulation compared to control. The effect of pectin on indirubin accumulation was changed depending on its concentrations. Pectin at 0.5 and 1% increased indirubin contents compared to control. In conclusion, 1 g L− 1 of yeast extract for root growth and 100 mg L− 1 of chitosan for indigotin and indirubin contents were selected as the most appropriate applications supplying the highest values.
Synchronous activation of striatal cholinergic interneurons induces local serotonin release
Authors: Matityahu Lior , Hobel Zachary B. , Berkowitz Noa , Malgady Jeffrey M. , Gilin Naomi , Plotkin Joshua L. , Goldberg Joshua A. 
Published: December 2024

Abstract

Striatal cholinergic interneurons (CINs) activate nicotinic acetylcholine receptors on dopamine axons to extend the range of dopamine release. Here we show that synchronous activation of CINs induces and extends the range of local serotonin release via a similar mechanism. This process is exaggerated in the hypercholinergic striatum of a mouse model of OCD-like behavior, implicating CINs as critical regulators of serotonin levels in the healthy and pathological striatum.
The Impact of Regional Integration Policies on Innovation Efficiency--The Case of the Yangtze River Delta Urban Agglomeration
Authors: Xie Wengjing , Xiao chengyou , Zhong Hong 
Published: December 2024

Abstract

Can regional integration policies enhance the efficiency of urban innovation? To this end, this study employs a multi-period PSM-DID approach based on data from 285 prefecture-level cities in China from 2004 to 2020 and a quasi-natural experiment on regional integration in the Yangtze River Delta (YRD) region to assess the impact of the implementation of regional integration policies on the innovation efficiency of cities. The results show that (1) the impact of regional integration policies on urban innovation efficiency (TE) is positively facilitated.(2) This paper further discusses the impact of regional integration policies on innovation efficiency by taking into account the upgrading of industrial structure in Chinese regions and using industrial structure upgrading as a moderating variable, and the results show that upgrading of urban industrial structure enhances the impact of regional integration policies on urban innovation efficiency.(3) Based on the perspective of heterogeneity, in cities with smaller population size, lower economic development level and weaker transportation accessibility, regional integration policy has a more significant effect on the enhancement of urban innovation efficiency, which shows that regional integration policy can effectively bring into play the technological diffusion effect of the central cities such as Shanghai, Hangzhou and Nanjing.
Efficient Remote Sensing Image Classification using the Novel STConvNeXt Convolutional Network
Authors: Liu Bo , Zhan Chenmei , Guo Cheng , Liu Xiaobo , Ruan Shufen 
Published: December 2024

Abstract

Remote sensing image classification poses significant challenges due to complex spatial organization, high inter-class similarity, and large intra-class variance. To address these issues, we propose STConvNeXt, a novel pure convolutional neural network specifically tailored for efficient remote sensing image classification. STConvNeXt integrates a split-based mobile convolutional module, a tree structure, and a fast pyramid pooling module to achieve residual connectivity. Additionally, we introduce a threshold loss function to stabilize model training and improve classification accuracy. Comprehensive experiments on multiple remote sensing datasets demonstrate that STConvNeXt achieves a 56.49% reduction in parameters and a 49.89% decrease in computational load compared to ConvNeXt, while maintaining state-of-the-art classification accuracy. Our results highlight the effectiveness of STConvNeXt in extracting robust features from remote sensing images, advancing the frontiers of deep learning-based remote sensing analysis.
Study on the Destruction Resistance of Collaborative Innovation Networks in City Clusters under Subject Failure Scenarios: Simulation Analysis Based on Network Cascade Failure Models
Authors: Du Danli , Wang Jiahe , Ding Kaixing , Jin Yufeng , Wang Xinyi 
Published: December 2024

Abstract

As the interdependence within inter-city collaborative innovation networks intensifies, the threat posed by subject failures triggered by external shocks to the effective functioning of these networks becomes increasingly critical. This paper delves into the impact of various types of subject failures on the resilience of city cluster collaborative innovation networks. By categorizing subject failures into nine distinct modes, this study integrates two pivotal aspects of innovation network resilience—structure and function—into a unified research framework. Structural resilience is assessed through the maximum connectivity subgraph, while functional resilience is gauged using network efficiency. The findings reveal notable variations in the structure of collaborative innovation networks across different fields, alongside differing sensitivities to the network’s resistance to destruction due to subject failures. Moreover, it was observed that random subject failures associated with high city clustering coefficients exert minimal impact on the network's structural and functional destructiveness, whereas those linked to larger city degree centrality significantly disrupt both network structure and function. Furthermore, the V index is employed to compare the effects of subject failure indicators across nine modes, indicating that cities with higher degrees of centrality have the most profound impact on network resilience. Significantly, when subject failures reach a threshold of 10%, both the structural and functional aspects of the city cluster collaborative innovation network approach a collapse threshold. The outcomes of this research highlight the destructive characteristics of city cluster collaborative innovation networks and offer a theoretical foundation for developing targeted risk management strategies to ensure the network's sustainable development.
Heat tolerance and thermal scope are evolutionarily constrained in Greenlandic terrestrial arthropods
Authors: Wesseltoft Jonas , Ørsted Michael , Jonge Nadieh , Hansen Michael , Høye Toke , Kristensen Torsten 
Published: December 2024

Abstract

Temperatures in the Arctic currently rise at four times the global average, making it of utmost importance to understand the thermal biology of species in these sensitive environments. For arctic ectotherms in particular, thermal tolerance limits and adaptive potential are mostly unknown. Such knowledge is urgently needed to predict climate change impacts on future distributions of biodiversity in these rapidly changing environments. Here, we provide new data on upper and lower thermal limits of 93 Greenlandic species of insects, arachnids, and collembolans identified using barcode sequencing representing ~8% of described terrestrial Greenlandic arthropod species. We found pronounced differences in heat and cold tolerance among species and a strong phylogenetic signal for both heat tolerance and thermal scope (difference between upper and lower thermal limits), suggesting that terrestrial Greenlandic arthropods are evolutionarily constrained in their capacity to cope with increasing and more variable future temperatures. Further, with projected future increases in microclimatic temperatures induced by climate change, we reveal a marked increase in the number of species that will experience potentially stressful temperatures for prolonged periods of time. Together, our results suggest that climate change will likely result in substantial changes in distributions and abundances of Greenlandic terrestrial arthropods.
Vagal AF Induction Test (VAFIT): A New Endpoint for Optimizing Atrial Fibrillation Ablation through Cardioneuroablation
Authors: Pachon-M JC , Pachon-M Enrique I , santillana-P Tomas G , Lobo Tasso J , Cunha-P Carlos T , Pachon-M Juan Carlos , Cunha-P Maria Zelia , Clark John 
Published: December 2024

Abstract

Introduction Currently, there is no reliable endpoint for the conclusion of atrial fibrillation (AF) ablation. Atrial burst pacing and/or isoproterenol challenge are poor diagnostic tools. A newly proposed Vagal AF Induction Test(VAFIT) uses effective atrial refractory period measurement, simultaneously with extra-cardiac vagal stimulation(ECVS) to study AF inducibility pre and post-ablation. This is a prospective study in patients submitted to radiofrequency catheter pulmonary vein isolation(PVI) plus cardioneuroablation(CNA) evaluating the VAFIT result before and at the end of the procedure with AF recurrence. Methods Prospective study of 142 patients, 57.5[48.9–70.2] years-old, 71% males, with symptomatic AF (79.6% paroxysmal/20.4% persistent), left atrium diameter of 38.0[35.0-41.2] mm, and left ventricular ejection fraction of 63.0 [62.0-68.2]. VAFIT was considered positive or negative depending on whether AF induction occurred. It was performed at baseline and after PVI + CNA, with a single atrial extra stimulus during ECVS (5s/50Hz/1V/kg up to 70V/Pulse Width = 50 µs). Patients were followed for a median of 15.0[7.0–20.0] months. The association of VAFIT-positive status at the end of the procedure with AF recurrence was investigated by univariate and multivariate Cox regression analysis. Results Pre-ablation VAFIT was positive in all cases and became negative in 62.9% of patients. AF recurrence: 18.7% in VAFIT-positive and 5.6% in VAFIT-negative patients(p = 0.012). VAFIT-positivity was associated with AF recurrence (HR: 4.56(1.37–15.23,p = 0.014). Conclusion A VAFIT-positive status following PVI + CNA was strongly and independently associated with AF recurrence. It remains to be investigated in randomized studies whether achieving VAFIT-negativity at the end of the procedure, as demonstrated in this study, would lead to better clinical outcomes.
Evaluation of Er,Cr:YSGG laser activation, manual dynamic and conventional irrigation for smear layer removal using different sodium hypochlorite irrigating solutions
Authors: Abaza Muhammad Mahmoud , Harhash Tarek Abd ElHamid 
Published: December 2024

Abstract

Background
The purpose of the present study was to microscopically evaluate the influence of Er,Cr:YSGG laser, manual dynamic, and conventional methods on smear layer removal of different NaOCl solutions at the apical, middle, and coronal regions of root canal walls.
Methods
One hundred & eight freshly extracted human single-canal anterior teeth were enrolled in this study. The teeth were decapitated & their canals were instrumented to size X4, 0.06 taper using rotary files of ProTaper Next® system. According to type of agitation technique, the teeth were classified into three groups (36 teeth each); no activation (traditional), manual dynamic, & Er,Cr:YSGG laser-activated techniques. Each group were further subdivided into four subgroups based on the irrigant type & concentration (n = 9); saline and 1%, 2.5%, and 5.25% NaOCl. Samples were gently split, longitudinally for SEM evaluation. Kruskal-Wallis and Mann-Whitney tests were used for statistical analysis.
Results
Regardless the irrigant type & concentration, Er,Cr:YSGG Laser-activated & manual dynamic groups showed better smear layer removal values than that of conventional group.
Conclusion
Er,Cr:YSGG laser-activated irrigation can eliminates more smear layer compared manual dynamic, & conventional techniques which increasing the cleaning capacity of different root canal irrigants.
Accumulation and distribution of mercury in cacao (Theobroma cacao) grown in artisanal small-scale gold mining areas, Ashanti Region, Ghana
Authors: Poku patrick Adu Adu , Margaret Boohene , Sylvester Addai-Arhin , Elwaleed Ahmed , Tia Agustiani , Jeong Huiho , Agusa Tetsuro , Ishibashi Yasuhiro , Kobayashi Jun 
Published: December 2024

Abstract

Cacao is an important agricultural crop in Ghana, but is grown even in artisanal small scale gold mining (ASGM) area using mercury (Hg) during the amalgamation process. This study investigated Hg concentration in agricultural soil and cacao plant in three ASGM communities in the Ashanti Region of Ghana to evaluate transfer of Hg from soil to cacao and health risk by ingesting of cacao beans. As for the soil samples, the mean Hg concentration was 76 ± 36 µg/kg dw (n = 42), corresponding to moderate contamination by the contamination factor. As for the cacao samples (n = 12 each), the highest mean Hg concentration was found in roots (211 µg/kg dw) and followed by leaves (138 µg/kg dw), pods (40 µg/kg dw) and beans (27 µg/kg dw). Significant correlations were observed between the cacao samples (p < 0.05), but not with the soil samples. indicating accumulation does not only depend on contaminated soil but also the type of plant, its ability to absorb and atmospheric deposition. Data analysis using the bioaccumulation factor (BAF) and the transfer factor (TF) indicated that Hg was highly accumulated from the soil to the root of cacao (BAF = 3.1) but did not highly transfer from the root to the aerial parts (TF < 1). The health risk assessment for ingestion of cacao beans showed that the hazard quotient was less than 1, indicating that there is no possibility of non-carcinogenic health effect.
Correction method for scale bias in GNSS-IR sea level retrieval
Authors: Wang Xiaolei , Song Minfeng , He Xiufeng 
Published: December 2024

Abstract

Since the principles and methods of Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) sea level monitoring technology based on geodetic receivers were first proposed, the technology has undergone over a decade of development. Currently, this method typically utilizes the frequency of the SNR signal, converts it into the reflector height (RH), and further derives the sea level. Height variation error and tropospheric delay error are widely recognized as systematic errors. Both have corresponding mathematical models that can be used for error mitigation. Random errors and gross errors are generally handled or constrained through quality control or multi-GNSS combination methods. In 2024, a correction method based on the initial phase of the SNR arc was proposed, and related studies suggest it may exhibit superior performance in correcting errors. Beyond the aforementioned errors, many studies have observed a scale bias in inversion results that appears to be correlated with sea-level magnitude. This bias is generally believed to be related to tropospheric delay error, as the magnitude of the tropospheric delay is associated with RH magnitude. However, in many studies, the magnitude of the scale bias exceeds the magnitude of tropospheric delay model value. Through analysis, we infer that the scale bias in some studies is related to the assumption of uniform sea level changes within the time windows during multi-GNSS combination processing. This assumption introduces errors, leading to underestimation of tidal peaks and overestimation of tidal troughs. The primary objective of this paper is to correct scale biases in GNSS-IR sea level retrieval, including those exhibited by raw RHs and those observed in combined RHs. Considering that stations with larger tidal amplitudes tend to show more significant scale biases, GNSS data from two such stations, BRST and HKQT, were used. The results indicate that the phase-based error correction method is more effective than traditional correction method in reducing scale bias in raw RHs. Additionally, we propose a method to mitigate scale bias caused by the assumption of uniform changes. Results indicate that this method effectively corrects scale bias in the combined RHs.