bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Parenteral Trace Element Supplementation on the RNA-sequencing Profile of Peripheral Blood in Peripartum Dairy Cows
Authors: Calcaterra Francisco , Fernández María Elena , Olivera Leónidas Hernán , Loza Ana Guzmán , Giovambattista Guillermo , Picco Sebastián Julio 
Published: May 2023

Abstract
The transition period is the most critical stage in the lactation cycle of dairy cattle. During this period, cows are subjected to high levels of oxidative stress (OS). One way of managing OS is through mineral supplementation with antioxidant micronutrients. The aim of this study was to evaluate the gene expression of transition dairy cows supplemented with the antioxidant trace elements copper (Cu), zinc (Zn), manganese (Mn) and selenium (Se). The study was carried out in a commercial Holstein dairy farm located in General Belgrano, province of Buenos Aires, Argentina. Cows (n = 200) were randomly assigned to either a supplemented or a control group. Blood samples were obtained seven days after calving and used to determine superoxide dismutase (SOD) and glutathione peroxidase activity, antioxidant capacity (AC) and thiobarbituric acid reactive substances. Additionally, RNA-sequencing analysis was performed. The OS index, SOD activity and AC differed significantly between groups, despite only two differentially expressed genes codified for second messengers (adjusted p value < 0.05). This would suggest that trace mineral supplementation of transition dairy cows would not induce changes in gene expression profiles in pathways associated with OS and immune function, since their expression is already high in response to the high OS levels and the dietary changes associated with this period. Nevertheless, considering the role of these minerals as cofactors, a higher availability in the supplemented group would increase antioxidant enzyme activity.
Spectrum of congenital anomalies of the kidney and urinary tract (CAKUT) including renal parenchymal malformations during fetal life and the implementation of prenatal exome sequencing (WES)
Authors: Koenigbauer Josefine Theresia , Laura Fangmann , Charlotte Reinhardt , Wolfgang Henrich , Weichert Alexander , Saskia Biskup , Heinz-Dieter Gabriel 
Published: May 2023

Abstract
Objectives and Background: Congenital malformations of the kidney and urinary tract (CAKUT) have a prevalence of 4-60 in 10,000livebirths and constitute for 40-50% of all end stage pediatric kidney disease. CAKUT can have a genetic background due to monogenetic inherited disease such as PKD or ciliopathies. They can also be found in combination with extra-renal findings as part of a syndrome. Upon detection of genitourinary malformations during the fetal anomaly scan the question arises if further genetic testing is required. The purpose of this study was to determine the phenotypic presentation of CAKUT cases and the results of exome analysis (WES).
Methods: This is a retrospective analysis of 63 fetal cases with a diagnosis of CAKUT or DSD at a single center between August 2018 and December 2022.
Results: A total of 63 cases (5.6%) out of 1123 matched CAKUT phenotypes including renal parenchyma malformations. In 15out of 63WES analysis a pathogenic variant was detected (23.8%). In fetuses with isolated CAKUT the rate of detecting a pathogenic variant on exome sequencing was five out of 44 (11.4%). Ten out of 19 fetuses (52.6%) that displayed extra-renal findings in combination with CAKUT were diagnosed with a pathogenic variant.
Conclusion: WES provides an increase in diagnosing pathogenic variants in cases of prenatally detected CAKUT. Especially in fetuses with extra-renal malformations, WES facilitates a gain in information on the fetal genotype to enhance prenatal counselling and management.
A new traffic flow prediction based on multi-scale convolutional neural network combined with LSTM neural network
Authors: Zhao Zichen , Pan Xiangyan 
Published: May 2023

Abstract
In this study, we proposed a novel traffic flow prediction model aimed at providing more accurate and effective traffic information. The proposed model utilized a multi-scale convolutional neural network in conjunction with a long short-term memory (LSTM) neural network to efficiently extract spatial and temporal features from the data. The network model was trained using the L1 loss function to optimize its performance.To evaluate the performance of the proposed model, we conducted experiments on two public datasets, PeMSD4 and PeMSD8. The results demonstrated the model's strong competitiveness in the field of traffic flow prediction. Specifically, on the PeMSD4 dataset, our model achieved a mean absolute error (MAE) of 20.94, a mean absolute percentage error (MAPE) of 13.32%, and a root mean square error (RMSE) of 30.96. These findings suggested that the proposed model hold significant promise in the realm of traffic flow forecasting.
Cytoskeleton Related Protein KIF9：A Potential Biomarker of Prognosis, 5- Fluorouracil Chemoresistance and Response to Immunotherapy for Patients with Colorectal Cancer
Authors: Zhao Zongxian , Ma Hongyu , Fan Xijie , Hu Zongju , Zhu Shu , Xu Shun , Liu Qinlingfei , Yao Yuan , Wang Fusheng 
Published: May 2023

Abstract
One important clinical predicament and treatment challenge of colorectal cancer (CRC) is chemoresistance of 5-Fluorouracil (5-Fu), affecting the prognosis of patients seriously. The resistant of colorectal cancer to 5-Fu based therapy involves multiple intricate molecular mechanisms and unclear pivotal genes. Kinesin family member 9 (KIF9) is one member of KIFs, a kind of cytoskeleton related protein, which has not been studied in colorectal cancer. In this research, we aimed to explore and elucidate the expression level, the clinical characteristics (age, gender, TNM stage, MSI state, BRAF/P53 mutation) and functions (immune infiltration, prognosis) of KIF9 in colorectal cancer. Furthermore, we found that KIF9 high expression was associated with the response to treatment of 5-Fluorouracil and immunotherapy. The gene and protein expression level of KIF9 was detected by using qRT-PCR and IHC for verification. And we evaluated and predicted the biofunction and pathways of KIF9 in CRC by gene set enrichment analysis. Thus, this article provided a comprehensive and systematic understanding of the biofunctions of KIF9 in colorectal cancer, and we elucidated the role of KIF9 as a biomarker for predicting treatment response of 5-Fluorouracil and immunotherapy.
M1 macrophages deliver CASC19 via exosomes to inhibit the proliferation and migration of colon cancer cells
Authors: Teng Shuo , Ge Jiang , Cui Zilu , Yang Yi , Min Li , Li Wenkun , Yang Guodong , Liu Kuiliang , Wu Jing 
Published: May 2023

Abstract
Background
Here we aim to reveal the mechanism of how lncRNA CASC19 in exosomes from macrophages in the tumor microenvironment affects the proliferation and migration of colon cancer.
Methods
The expression levels of CASC19 and its putative target miR-410-3p were detected by reverse-transcription polymerase chain reaction (RT-qPCR).Cell proliferation and migration were evaluated by MTS and transwell assays. The characterization of exosome was conducted by western-blot, nanoSight particle tracking analysis, and electron microscope imaging. The interaction between CASC19 and miR-410-3p was detected by the pull-down assay.
Results
The non-contact inhibition of M1 macrophages on the proliferation of colon cancer cells is largely dependent on the CASC19 released from their exosomes. M1 exosomes successfully delivered CASC19 to colon cancer cells, exerting an inhibitory effect on cell proliferation and migration. The exosomes secreted by M1 cells with CASC19 knock down showed less inhibition on cell proliferation and migration. CASC19 exerted an inhibitory effect on colon cancer cells by sponging miR-410-3p.
Conclusion
CASC19 in M1 macrophages is delivered into colon cancer cells via exosomes, exerting an inhibitory effect on their proliferation and migration by sponging miR-410-3p.
Leveraging Quantum Annealing for Ligand Modelling in Drug Discovery
Authors: Shetty Harshith , Joshi Aayush , Mehta Akshat , Kumbhar Rutuja , Sayyad Shahzia 
Published: May 2023

Abstract
Drug discovery is an intricate and multifaceted process that necessitates the identification and development of novel medications to combat various illnesses. This convoluted procedure typically encompasses various stages, including fundamental research, preclinical research, clinical research, and FDA approval. Notwithstanding the indispensability of the drug discovery process, it is time-consuming and exorbitant, with low success rates often being the norm. In this paper, we endeavour to provide a comprehensive appraisal of the divergent methodologies employed in drug discovery, inclusive of the wet lab approach and the classical computer-based approach. The wet lab approach requires extensive experimentation within laboratory settings to pinpoint potential drug candidates, whereas the classical computer-based approach employs computational techniques to simulate and prognosticate the properties of potential drug compounds. Despite the merits of both approaches, they are not without limitations, which we shall delve into in the course of this discourse. The multifariousness of the drug discovery process and the sheer volume of data generated during the course of experimentation necessitate the use of advanced technologies and algorithms in enhancing the process's performance. This paper aims to furnish an overview of the present state of drug discovery, while also underscoring the need for relentless research and innovation in this domain.
Propafenone versus Amiodarone for Supraventricular Arrhythmias in Septic Shock: A Randomised Controlled Trial
Authors: Balik Martin , Maly Michal , Brozek Tomas , Rulisek Jan , Porizka Michal , Sachl Robert , Otahal Michal , Brestovansky Petr , Flaksa Marek , Horejsek Jan , Svobodova Eva , Stach Zdenek , Volny Lukas , Jurisinova Ivana , Novotny Adam , Trachta Pavel , Kunstyr Jan , Kopecky Petr , Tencer Tomas , Pazout Jaroslav , Belohlavek Jan , Duska Frantisek , Krajcova Adela , Waldauf Petr 
Published: May 2023

Abstract
Purpose
Acute onset supraventricular arrhythmias contribute to haemodynamic compromise in septic shock. Both amiodarone and propafenone are drugs of choice, but their clinical effects have not yet been directly compared.
Methods
Two-centre, randomised prospective controlled parallel group double blind trial recruited 209 septic shock patients with new-onset arrhythmia and a left ventricular ejection fraction above 35%. The patients were randomly assigned in a 1:1 ratio to receive either intravenous propafenone (70mg bolus followed by 400-840mg/24h) or amiodarone (300mg bolus followed by 600-1800mg/24h). The primary outcomes were the proportion of patients who had sinus rhythm 24 hours after the start of the infusion, time to restoration of the first sinus rhythm and the proportion of patients with arrhythmia recurrence.
Results
Out of 209 randomized patients, 200(96%) received the study drug. After 24 hours, 77(72.8%) and 71(67.3%) were in sinus rhythm (p = 0.40), restored after a median of 4.3h (95%CI 2.8;7.3) and 7.8h (95%CI 5.9;11), p = 0.03, with propafenone and amiodarone, respectively. The arrhythmia recurred at least once in 54(52%) patients treated with propafenone and in 80(76%) with amiodarone, p˂0.001. Patients with a dilated left atrium had better rhythm control with amiodarone (6.4h (95%CI 3.5;14.1) until cardioversion vs 14.1h (95%CI 2.8;24.7) in propafenone, p = 0.05).
Conclusion
Propafenone administration in patients with septic shock does not provide better rhythm control at 24 hours yet offers faster cardioversion with fewer arrhythmia recurrences than with amiodarone, especially in patients with a non-dilated left atrium. Both drugs did not differ in their impacts on short- and long-term outcomes.
Trial registration:
ClinicalTrials.gov Identifier: NCT03029169, registered on 24th of January 2017
ACE2, ACE, DPPIV, PREP and CAT L enzymatic activities in COVID-19: imbalance of ACE2/ACE ratio and potential RAS dysregulation in severe cases
Authors: Neves Raquel Leão , Branquinho Jéssica , Arata Júlia Galanakis , Bittencourt Clarissa Azevedo , Perez Caio Gomes , Riguetti Michelle , Mata Gustavo Ferreira , Fernandes Danilo Euclides , Icimoto Marcelo Yudi , Kirsztajn Gianna Mastroianni , Pesquero João Bosco 
Published: May 2023

Abstract
Objective and design: Several proteases have drawn attention as potential targets to control the SARS-CoV-2 infection (COVID-19), thus circulating enzymatic activity and RAS regulation in severe hospitalized patients still remain to be determined.
Material or subjects: 164 patients with COVID-19-like symptoms were grouped according to the severity of symptoms (COVID-19 negative, mild, moderate and severe).
Methods: Patients were subjected to biochemical analyzes and to enzymatic activities of ACE2, ACE, DPPIV, PREP and CAT L, evaluated in serum samples. One-way ANOVA and multivariate logistic regression analysis were used. Statistical significance was accepted at p<0.05.
Results: We show a correlation among comorbidities, elevated C-reactive protein (CRP) levels and disease severity. Additionally, concomitant high levels of D-dimer and CRP could be as prognostic for severe conditions. Assays of enzymatic activities revealed that, according to disease severity, both ACE2 and CAT L were statistically increased, while ACE, DPPIV and PREP activities were significantly reduced. Notably, analysis of ACE2/ACE ratio suggest a possible imbalance of Ang II/Ang1-7 ratio in severe patients.
Conclusion: Our findings reveal the correlation between protease activity and the severity of COVID-19, in addition to highlighting the imbalance of ACE2/ACE ratio, predicting RAS dysregulation, closely related with a poor outcome of disease.
The dynamic functional connectivity of the left rostral hippocampus involved in mediating the association between hippocampal volume and antidepressant efficacy in major depressive disorder
Authors: Kuai Changxiao , Pu Jiayong , Wang Donglin , Tan Zhonglin , Wang Yan , Xue Shao-Wei 
Published: May 2023

Abstract
The hippocampus is highly involved in the pathophysiology of major depressive disorder (MDD), indicating some changes in hippocampal structure and function during MDD condition and also due to antidepressant treatment. However, it is unclear whether structure factors of the hippocampus can effectively impact antidepressant responses by hippocampal functional activity in MDD patients. The longitudinal data were collected from 36 MDD patients before and after 3 months of antidepressant pharmacotherapy. Baseline data from 43 sex- and age-matched healthy controls were also acquired. The dynamic functional connectivity (dFC) of the hippocampal subregions was estimated via a sliding-window method based on resting-state functional magnetic resonance imaging (rs-fMRI). The voxel-based morphometry (VBM) was used to calculate the gray matter volume. The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus when compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate (RR%), and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that hippocampal functional activity in MDD might continue to act on its structure and further affect antidepressant performance, which provided a novel insight into the neurobiological mechanism of the development route of the therapeutic process for MDD.
Intrusion Detection System for Detection of DDoS Attacks in Cloud Environment
Authors: V Jyothsna , C Manisha , BS NanduSri , K Poorna Chandhu , A Leela Rama Seshu , G Mahalakshmi Manasvi 
Published: May 2023

Abstract
A modern technology which enables users to construct services on demand is cloud computing. Due to its self-service functionality and on demand offerings, cloud computing has seen success. Some security-related risks are brought on by remote cloud-based data evaluation and maintenance, particularly with DDoS Attacks. These assaults are the result of intrusion efforts or hacker attempts to access data stored on the main server or moving between the client and server. Without the data owner's knowledge, the attacker acquires the data and alters it as needed. For the widespread adoption of cloud computing, it is crucial to develop defences against this assault. Over the past few years, intrusion detection (ID) in a cloud setting has drawn a lot of attention. Machine learning-based ID methods are among the most recent techniques that enable us to find unidentified assaults. However, building a cloud based ID system (IDS) that is resistant to a broad variety of unknown attacks remains difficult due to the scarcity of malicious samples and the quick evolution of diverse attacks. This study creates a deep feedforward neural network algorithm-based intruder detection system using Bat optimization. The CICDDOS2019 dataset is used by the suggested technique to analyze performance.
2D Image to 3D Box with Deep Learning Method
Authors: WU DONGJUN 
Published: May 2023

Abstract
This article will show you a method for converting 2d images into 3d bounding boxes. The idea is to split the task into two steps. Firstly, we use neural network to output 3D object features displayed in 2D images. Then, we combine the boundary information of 2D objects in the images to generate geometric constraints on 3D objects, so as to get a complete 3D boundary box. In the first step, we defined an innovative loss function called combined_orientation_loss. This loss function took into account both the cosine distance and Euclidean distance, so that the length of the direction vector could also be reflected in the loss, which could enhance the sensitivity of the model to the prediction accuracy. In the second step, we return to the dimensions of 3D objects, which are relatively stable and therefore suitable for predicting a wide range of object types. Combining these two steps and the translation constraints of the object in the 2D image, we can accurately and stably restore its 3D border shape. We evaluated our approach on the KITTI target detection benchmark, including the official measure of 3D direction estimates and the accuracy of the resulting 3D bounding box. In the case of low calculation requirements achieved good results.
Overexpression of glycosyltransferase genes enhance the production of extracellular polysaccharides in Cordyceps militaris
Authors: Xu De , Yan Bai , Yang Shengli , Zhang Hui 
Published: May 2023

Abstract
This study aimed to increase the production of extracellular polysaccharides in Cordyceps militaris by overexpressing polysaccharide transferase genes, including alpha-1,2-mannosyltransferase (Kre5), alpha-1,3-mannosyltransferase (CMT1), alpha-1,6-mannosyltransferase subunit (A16), and alpha-1,2-mannosyltransferase (A12) genes. The research data showed that, except for the CM-CMT1 strain, the extracellular polysaccharides (EPS) content of the other seven recombinant strains was higher than that of the wild-type strain, indicating that overexpression of key enzyme genes increased polysaccharide production. Among the single-gene recombinant strains, the CM-Kre5 strain had the highest EPS production, reaching 3.27 ± 0.18 g/L, which was 23.3% higher than that of the CM-WT strain, indicating that the Kre5 gene had the greatest impact on Cordyceps militaris polysaccharide biosynthesis. Among the combination gene recombinant strains, the CM-Kre5-CMT1-A16 strain had the highest EPS production, reaching 4.22 ± 0.35 g/L, which was 59.2% higher than that of the CM-WT strain, indicating that gene combination expression can further increase Cordyceps militaris polysaccharide production. Therefore, this study provides a new way for the development of EPSs and their downstream products in Cordyceps militaris.
Fabrication of Highly Porous MOF/Cellulose Beads for Sustained Degradation of Dye
Authors: Wu Yuhang , Li Yuwen , Zheng Yanchun , Yao Juming , Gao Junkuo 
Published: May 2023

Abstract
Metal-organic frameworks (MOFs) have received widespread attention in recent years. However, the powder form of MOFs limits their large-scale applications. To facilitate the application of MOFs, mass production and shaped manufacturing of MOFs is significantly effective. Herein, a generic method based on a simple polymerization technique is proposed to prepare highly porous MOF-cellulose composite beads and the application of these composite beads in dye removal and recovery is displayed. Non-toxic solvent water and biodegradable sodium carboxymethylcellulose (CMC) were used as raw materials in the synthesis method. In addition to maintaining the crystallinity and porosity of the MOFs embedded in the cellulose matrix, the unique three-dimensional (3D) lamellar interconnected structure provides good mechanical properties for the composite beads. To demonstrate the practicality of these composite beads, a recycling processing system was built as a proof-of-concept device. MIL-100/CMC-HD can effectively degrade more than 95% of the dye and can be recycled multiple times. The superiority of the MOF-cellulose composite beads is highlighted by their ease of recycling and storage compared to MOF powder.
Peripheral CD8 + PD-1 + T cells as novel biomarker for neoadjuvant chemoimmunotherapy in humanized mice of non-small cell lung cancer
Authors: Guo Wenwen , Qiao Tianyun , Li Hui , Zhao Yong , Qin Jing , Zhang Caiqin , Shi Changhong 
Published: May 2023

Abstract

Background
Neoadjuvant immunotherapy has shown promising clinical activity in the treatment of early non-small cell lung cancer (NSCLC); however, further clarification of the specific mechanism and identification of biomarkers are imperative prior to implementing it as a daily practice.
Methods
We investigated the impact of neoadjuvant chemoimmunotherapy (combining cisplatin with pembrolizumab) on an established preclinical NSCLC mouse model engrafted with human immune system, and explored its potential mechanism. We further explored potential biomarkers for neoadjuvant therapy and conducted in vivo validation using the model. In addition, both peripheral blood and tumor specimens from 14 patients undergoing neoadjuvant chemoimmunotherapy were analyzed to validate our findings.
Results
Neoadjuvant chemoimmunotherapy could prevent postoperative recurrence and metastasis by increasing the frequency and activation of CD8+ T cells in both peripheral blood and tumor immune microenvironment (TIME). The kinetics of peripheral CD8+PD-1+ T cells reflected the changes in the TIME and pathological responses, ultimately predicting survival outcome of mice. Further analysis of clinical specimens not only confirmed the reprogramming of TIME, but also validated CD8+PD-1+ T cells as rational biomarker.
Conclusions
The kinetics of peripheral CD8+ T cells can serve as a predictor for changes in TIME and overall antitumor immune responses, ultimately reflecting the outcomes of neoadjuvant chemoimmunotherapy in both preclinical and clinical setting. Our findings establish a theoretical foundation for the clinical translation of this promising biomarker.