bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aqueous leaf extract of Phyllanthus amarus protects against oxidative stress and misfiring of dopaminergic neurons in Paraquat-induced Parkinson’s disease-like model of adult Wistar rats
Authors: Enemali Felix , Iteire Kingsley Afoke , Uwejigho Raphael Eguono , Ogunberi Blessing 
Published: March 2023

Abstract

Background of the study: Phyllanthus amarus has high nutritional value and is beneficial in managing and treating diverse ailments. This study assessed the role of aqueous leaf extract of Phyllanthus amarus on Paraquat (PQ) induced neurotoxicity in the substantia nigra of Wistar rats.
Materials and methods: The role of aqueous leaves extract of Phyllanthus amarus was assessed using an open field test (OFT) for motor activity, oxidative stress biomarkers [Catalase (CAT), and Superoxide Dismutase (SOD)], histological examination (H and E stained) for cytoarchitectural changes and immunohistochemical studies using tyrosine hydroxylase (TH) as a marker for dopaminergic neurons. Forty-two (42) rats were categorized into six groups (n = 7); group 1: control was administered 0.5 ml/kg distilled water, group 2: received 10 mg/kg PQ + 10 mg/kg L‑dopa as reference drug, group 3; received 10 mg/kg PQ, while group 4: received 10 mg/kg PQ + 200 mg/kg P. amarus, group 5: received 10 mg/kg PQ + 300 mg/kg P. amarus, and group 6: received 10 mg/kg PQ + 400 mg/kg P. amarus respectively, for 14 days. All administrations were done orally; a significant difference was set at p<0.05.
Results and discussion: The study's open field test (OFT) revealed no motor activity deficit with Paraquat (PQ) exposure. Also, cytoarchitectural distortions were not observed with Paraquat (PQ) only treatment group compared to the control and other groups pretreated with P. amarus and L-dopa. Moreover, the Paraquat (PQ) only treatment group showed oxidative stress by significantly decreasing the antioxidant enzyme (SOD) compared to the control and L-dopa pretreated group. A significant decrease in tyrosine hydroxylase (TH) expressing dopaminergic neurons was also observed in Paraquat (PQ) only treatment. However, P. amarus treatment showed therapeutic properties by significantly increasing tyrosine hydroxylase (TH) expressing dopaminergic neuron levels relative to control.
Conclusion:Aqueous leaf extract of Phyllanthus amarus possesses therapeutic properties against Paraquat (PQ) induced changes in the substantia nigra of Wistar rats.
Data collection in pandemic times: the case of the Belgian COVID-19 Health surveys
Authors: Braekman Elise , Charafeddine Rana , Berete Finaba , Bruggeman Helena , Drieskens Sabine , Gisle Lydia , Hermans Lize , Heyden Johan Van der , Demarest Stefaan 
Published: March 2023

Abstract
Background
Survey data were needed to assess the mental and social health, health related behaviors and compliance with preventive measures of the population during the COVID-19 pandemic. Yet, the pandemic challenged classical survey methods. Time and budgetary constraints at the beginning of the pandemic led to ad hoc recruitment of participants and easily manageable data collection modes. This paper describes the methodological choices and results in terms of participation for the COVID-19 health surveys conducted in Belgium.
Methods
The COVID-19 health surveys refer to a series of ten non-probabilistic web surveys organized between April 2020 and March 2022. The applied recruitment strategies were diverse including, amongst others, a launch through the website and the social media of the organizing research institute. In addition, the survey links were shared in articles published in the national press and participants were requested to share the surveys in their network. Furthermore, participants were asked consent to be recontacted for next survey editions using e-mail invitations.
Results
These mixed approaches allowed to reach a substantial number of participants per edition ranging from 49339 in survey 1 to 13882 in survey 10. In addition, a longitudinal component was created; a large share of the same individuals were followed up over time; 12599 participants completed at least 5 surveys. There were, however, sex, age, educational level and regional differences in participation. Post-stratification weighting on socio-demographic factors was applied to at least partly take this into account.
Conclusion
The COVID-19 health surveys allowed rapid data collection after the onset of the pandemic. Data from these non-probability web surveys had their limitations in terms of representativeness due to self-selection but were an important information source as there were few alternatives. Moreover, by following-up the same individuals over time it was possible to study the effect of the different crisis phases on, amongst others, the mental health. It is important to draw lessons from these experiences: initiatives in order to create a survey infrastructure better equipped for future crises are needed.
Primary Systemic Amyloidosis Characterized by Multiple Keratinous Cysts: A Case Report
Authors: Lu Xiaoou , Fu Weiwei , Xie Demin , Zhang Jiali , Wang Da , Sun Yu , Chen Hongquan 
Published: March 2023

Abstract
Primary systemic amyloidosis (PSA) is a systemic disease caused by amyloid deposition in various tissues and organs. In the early stages of the disease, approximately 40% of patients have skin damage, which may be the only clinical manifestation. This report described the case of a 67-year-old male with PSA who presented with characteristic cutaneous manifestations. Physical examination showed seborrheic keratotic-like plaques around the orbit, purpura and ecchymosis on the neck and dorsum manus, as well as nail dystrophy. An auxiliary examination indicated a 24-h urine protein content of 2.89 g, and serum immunoelectrophoresis showed a monoclonal λ light chain. Echocardiography showed decreased left ventricular diastolic function and mild pulmonary hypertension. The dermoscopic features were multiple comedo-like openings and milia-like cysts. Histopathology showed multiple keratinous cysts in the dermis and eosinophilic, acellular, homogenous material in the dermis that was Congo red-positive. The diagnosis was confirmed through biopsy of skin lesions and kidney.Skin lesions of this case are rare.Skin lesions around the orbit need to arouse the vigilance of dermatologists. PSA should be considered if the patient with multisystemic symptoms.Skin biopsy and Congo red staining were very important for early diagnosis of PSA.
Measuring severe obesity in pediatrics: A cohort study
Authors: Ball Geoff DC , Sharma Atul K , Moore Sarah A , Metzger Dan L , Klein Doug , Morrison Katherine M 
Published: March 2023

Abstract
Purpose: To examine cross-sectional and longitudinal relationships between body mass index (BMI)-derived metrics for measuring severe obesity (SO) using the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and cardiometabolic risk factors in children and adolescents.
Methods: In this cohort study completed from 2013 to 2021, we examined data from 3- to 18-year-olds enrolled in the CANadian Pediatric Weight management Registry. Anthropometric data were used to create nine BMI-derived metrics based on the CDC and WHO references. Cardiometabolic risk factors were examined, including dysglycemia, dyslipidemia, and elevated blood pressure. Analyses included intraclass correlation coefficients (ICC) and receiver operator characteristic area-under-the-curve (ROC AUC).
Results: Our sample included 1,288 participants (n=666 [51.7%] girls; n=874 [67.9%] white), with SO of 59.9–67.0%. ICCs revealed high tracking (0.90–0.94) for most BMI-derived metrics. ROC AUC analyses showed CDC and WHO metrics discriminated the presence of cardiometabolic risk factors, which improved with increasing numbers of risk factors. Overall, most BMI-derived metrics rated poorly in identifying presence of cardiometabolic risk factors.
Conclusion: CDC BMI percent of the 95th percentile and WHO BMIz performed similarly as measures of SO, suggesting both can be used for clinical care and research in pediatrics. The latter definition may be particularly useful for clinicians and researchers from countries that recommend using the WHO growth reference.
A nomogram for predicting the risk of new vertebral compression fracture after percutaneous kyphoplasty
Authors: Zhang Aiqi , Lin Yichen , Kong Mingxiang , Chen Jiahao , Gao Wei , Fan Jiajun , Wang Junjie , Chen Zhe 
Published: March 2023

Abstract
Background
New vertebral compression fractures (NVCFs) are common adverse events in percutaneous kyphoplasty (PKP). The present study aimed to investigate risk factors for NVCFs in patients after PKP and to construct a nomogram for prediction of the risk of re-fracture.
Methods
We retrospectively analyzed medical records of patients after PKP surgery between January 2017 and December 2020. Patients were divided into an NVCF group (n = 225) and a control group (n = 94) based on the presence or absence of NVCFs at follow-up within 2 years after surgery. Lasso regression was used to screen for risk factors for re-fracture. Based on the results, a Lasso-logistic regression model was developed, and its prediction performance was evaluated using receiver operating characteristic curves, calibration, and decision curve analysis. The model was visualized, and a nomogram was constructed.
Results
A total of eight potential predictors were obtained from Lasso screening. Advanced age, low body mass index, low bone mineral density, lack of anti-osteoporosis treatment, low preoperative vertebral body height, vertebral body height recovery ≥ 2, cement leakage, and poor cement distribution were included in the logistic regression model.
Conclusions
A nomogram for predicting postoperative NVCF in PKP was developed and validated. This model can be used for rational assessment of the magnitude of the risk of developing NVCFs after PKP, and can help orthopedic surgeons make clinical decisions aimed at reducing the occurrence of NVCFs.
Face Mask Detection Model Using Convolutional Neural Network
Authors: Gomaa Mamdouh M. , Elsherif Mahmoud M. , Elnashar Alaa , Zaki Alaa M. 
Published: March 2023

Abstract
Due to the rapid global spread of the COVID-19 outbreak, people's daily lives have been severely disrupted. To manage the outbreak, one solution is to mandate the wearing of face masks in public places. A face detection system that is automated and effective is therefore essential for enforcing this requirement. This paper presents a face mask detection model for images that classifies them as either "with mask" or "without mask." The three datasets Real-World Masked Face Dataset (RMFD), Simulated Masked Face Dataset (SMFD), and Labeled Faces in the Wild (LFW) are used to train and test the model, and attained a performance accuracy rate of 99.72% for first dataset, and 100% for the second and third datasets. This work can be utilized as a digitized scanning tool in schools, hospitals, banks, and airports, and many other public or commercial locations.
Schisandrin B prevents PM2.5-induced pyroptosis by protecting cell membrane integrity
Authors: Feng Tian-yang , Liao Lian-ying , Xue Wan-ting , Li Li , guo miaomiao 
Published: March 2023

Abstract
The main active substances of Schisandra chinensis are lignans. Lignans are largely composed of schisandrin B (Sch B), which has a very high biphenyl cyclooctene content. This study was designed to evaluate the ability of Sch B to repair the particulate matter 2.5 (PM2.5)-induced THP-1 cell injury and determine the underlying mechanism of Sch B action. The results showed that Sch B significantly inhibited interleukin-1ꞵ (IL-1ꞵ) secretion and reduced PM2.5-caused cell pyroptosis. Mechanistically, Sch B reduced both cell membrane damage and the release of inflammatory factors via active reduction of caspase-1 enzyme activity and subsequent inhibition of gasdermin D (GSDMD) cleavage to N-GSDMD. In addition, Sch B treatment promoted the transcription of ALG2, ALIX, TSG101, and CHMP4B and membrane repair via ESCRT-III. Thus, we demonstrated that Sch B, the main active component of S. chinensis extracts, has anti-PM2.5 effect and elucidated the underlying mechanism of Sch B effects against THP-1 cell pyroptosis.
Disulfidptosis classification of hepatocellular carcinoma reveals correlation with clinical prognosis and immune profile
Authors: wang tianbing , Guo Kai , Zhang Di , Wang Haibo , Yin Jimin , Cui Haodong , Wu Wenyong 
Published: March 2023

Abstract
A new mode of cell death, disulfidptosis, has been discovered. Clinical prognostic significance of disulfidptosis related pattern in hepatocellular carcinoma(HCC). In this study, a risk score model was established based on disulfidptosis model to analyze the role of risk score in clinical prognosis, immune cell infiltration, drug sensitivity and immunotherapy response. Disulfidptosis subtype were constructed based on the transcriptional profiles of 15 disulfidptosis-related genes(DRGs). All 601 samples were defined as high risk group(HRG) and low risk group(LRG) based on the disulfidptosis risk score. Drug sensitivity and response to immunotherapy were calculated by immunophenotypic score(IPS), tumor prediction, tumor immune dysfunction and rejection(TIDE). RT-qPCR was used to determine the mRNA level of disulfidptosis prognostic gene. Risk groups was identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. HRG may benefit from immunotherapy. Classification is very effective in predicting the prognosis and therapeutic effect of patients, and provides a reference for accurate individualized treatment. This study suggests that new biomarkers related to Disulfidptosis can be used in clinical diagnosis of liver cancer to predict prognosis and treatment targets.
Sample-adaptive Classification Inference Network
Authors: Yang Juan , Zhou Guanghong , Wang Ronggui , Xue Lixia 
Published: March 2023

Abstract

Existing pre-trained models have yielded promising results in terms of computational time reduction. However, these models only focus on pruning simple sentences or less salient words, while neglecting the treatment of relatively complex sentences. It is frequently these sentences that cause the loss of model accuracy. This shows that the adaptation of the existing models is one-sided. To address this issue, in this paper, we propose a sample-adaptive training and inference model. Specifically, complex samples are extracted from the training datasets and a dedicated data augmentation module is trained to extract global and local semantic information of complex samples. During inference, simple samples can exit the model via the Sample Adaptive Exit Mechanism, Normal samples pass through the whole backbone model before inference, while complex samples are processed by the Characteristic Enhancement Module after passing through the backbone model. In this way, all samples are processed adaptively. Our extensive experiments on classification tasks datasets in the field of Natural Language Processing demonstrate that our method enhances model accuracy and reduces model inference time for multiple datasets. Moreover, our method is transferable and can be applied to multiple pre-trained models.
Toxicity of different doses of Diclofenac in Black Kites
Authors: Farooq Muhammad , Khan Aleem Ahmed 
Published: March 2023

Abstract
The present experimental work was conducted to assess the toxicopathological effects of three different doses of diclofenac sodium in black kites (Milvus migrans) because now there are more opportunities for other animals and raptors including black kites to feed due to population collapse of vulture throughout Asia. It is vital to assess the toxicity of diclofenac sodium in other raptors like black kites. The goal of the current investigation was to determine whether diclofenac sodium is similarly hazardous to black kites as described in vultures. For this study 08 black kites (Milvus migrans) were randomly divided into four groups. The black kites in the control group (n = 02) were not treated with diclofenac sodium and birds in the first (n = 02), second (n = 02) and third (n = 02) groups were administered diclofenac sodium at 2.5, 5 and 10 mg/kg live body weight of bird/day, respectively, every day for 10 days. The diclofenac sodium-treated black kites displayed clinical manifestations like anorexia, lethargy, depression, shrunken eyes, reduced feed and water intake, in contrast to the clinically healthy appearing birds in the control group. The mortality was 100% in second and third groups. No mortality was seen in control group and treated group first. The control group did not show any lesions of gout but black kites of treated groups showed swelling, congestion, hemorrhage, necrosis, leukocytic infiltration and deposition of white chalky urates on the surface of liver, kidney and heart.
Total Variation Method Based on Modified Barzilai-Borwein Algorithm to Noise Reduction in MRI Images
Authors: Jalilian Hamed 
Published: March 2023

Abstract
Magnetic resonance imaging (MRI), notwithstanding the vital information they provide , introduces issues in diagnostic work due to inherent noise. The poor signal-to-noise ratio (SNR) in MRI images demonstrates the importance of post-processing procedures. There are numerous strategies for reducing noise, but there is still a need for a solution that has both high accuracy and a fast convergence speed. In this study, we present a total variation (TV) method for noise reduction in MRI images utilizing a modified Barzilai-Borwein method(MBBM) algorithm. The proposed method is tested on three noisy and blurred images (IXI data set 3.1). The findings reveal that the reconstructed images have less noise and sharper edges. In comparison to similar existing iterative methods, Gradient projection method(GP) and Barzilai-Borwein method(BBM), the proposed method achieves higher accuracy in a substantially smaller number of iterations. The MBBM technique enhanced the quality metrics, Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) for the first data set (data 2a). For instance, the PSNR and SSIM for noise level 0.06 improved from 2.62 and 0.22 to 33.12 and 0.90, respectively. This improvement in rating criteria was also seen in the next two experiments(data 2b and data 2c). When compared to similar methods, experimental results reveal that the suggested method is faster, more precise, more successful at preserving edges, and less compu-tationally demanding. Consequently, the presented method is effective and reliable both quantitatively and qualitatively.
Graph Neural Networks for Fast Track Finding
Authors: Lad Nisha 
Published: March 2023

Abstract

Future upgrades to modern high-energy particle detectors will pose considerable challenges for traditional particle track reconstruction methods. Within the past two years, architectures that operate on Graph Neural Networks (GNN) have shown high degrees of promise. Presented here is a novel approach to GNN-based track finding which uses Gaussian mixture techniques to describe track parameter estimates. Unlike traditional methodologies whereby Multi-Layered Perceptrons (MLPs) are employed, the proposed GNN architecture leverages the Kalman filter as a mechanism for information aggregation, in order to iteratively improve the precision of track parameters, as well as for extraction of track candidates compatible with particle motion model. The excitation and inhibition rules of individual edge connections are designed to facilitate the “simple-to-complex” approach for “hits-to-tracks” association, such that the network starts with low hit density regions of an event and gradually progresses towards more complex areas. This paper focuses on the track finding algorithm development and its application on the publicly available dataset designed for the Kaggle TrackML challenge. The preliminary results related to track reconstruction efficiency and purity metrics are presented and discussed. The ultimate aim of this work is to develop a realistic GNN-based algorithm for fast track finding that can be deployed in future high-luminosity phases of particle detector experiments.
Alterations in gut microbiome associated with severity of atopic dermatitis in infants
Authors: Liu Xiaoyi , Cai Meiqin , Chen Meiru , Chen Ji , Zhu Tingyu , Wu Shiyin , Jia Jie 
Published: March 2023

Abstract

Background: Atopic dermatitis (AD) often arises in infancy, and gut microbial dysbiosis is associated with the development of AD. However, less is known about specific changes in early-life gut microbiome associated with AD and AD severity. This study aims to reveal the gut microbial composition and function profiles associated with the severity of AD in infants.
Methods: Sixty-two infants (mean [SD] age, 4.7[1.9] months) with different severities of AD were enrolled and divided into three groups (mild, moderate, and severe) according to the Scoring Atopic Dermatitis (SCORAD) index. The profiles of gut microbial composition and function were analyzed by sequencing 16S ribosomal RNA amplicons. Quality of life on childrenand the family were evaluated using published questionnaires.
Results: Decreased levels of Clostridium sensu stricto, Collinsellaand increased level of Parabacteroides presented in the severe AD group compared with the mild AD group after adjusting potential confounders (P <0.05). There were strong positive correlations between the Scoring Atopic Dermatitis (SCORAD) index and the relative abundance (RA) of Bacteroides and functional pathways for metabolism of sphingolipids and glycosphingolipids (P <0.05). The SCORAD index was negatively correlated with the RA of Clostridium sensu stricto (P <0.05), and was also positively correlated with the index of quality of life on children and the family (P <0.05).
Conclusion: Discrepancies in gut microbial composition and functional pathways were observed in infants with mild-to-severe AD. Alterations in butyrate-producing bacteria (Clostridium sensu stricto), sphingolipid-producing bacteria (Parabacteroides,Bacteroides), and related functional pathways were associated with the severity of AD infants.
Impact of information update generation on the radio access network of cellular Internet of Things
Authors: Vásquez Marcelo Flores , Tello-Oquendo Luis , Capella-Hernández Juan , Aranda Juan , Guamo-Morocho Andrea 
Published: March 2023

Abstract
Cellular Internet of Things (CIoT) is considered a suitable technology to provide connectivity to IoT devices and support machine type communication (MTC). CIoT relies on cellular networks, such as 5G, to handle the increased demand for data and avoid overload. However, the limited capacity of the Random Access Channel (RACH) represents a challenge for implementing real-time IoT applications in 5G Radio Access Networks (RANs). The information update generation and Random Access Protocol (RAP) play a crucial role in ensuring timely updates. This paper presents a performance analysis of the impact of information update generation patterns on the RAN in CIoT when the number of IoT devices and information update frequency increase. An extensive simulation study was conducted, considering MTC and H2H (human-to-human) traffic with varying access request intensities. We determine the maximum information update frequency to provide a highly successful access probability over the RAN.