bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the contribution of structural diversity to stand biomass for carbon management of mixed forests using machine learning algorithms
Authors: He Xiao , Lei Xiangdong , Liu Di , Lei Yuancai , Gao Wenqiang , Lan Jie 
Published: June 2024

Abstract

The structural properties of mixed stands and their effects on forest carbon sink function have attracted the attention of forest managers. Understanding the comprehensive effects of stand factors and structure on forest biomass is critical for better carbon management. However, data and information on biomass variability and its relationships to stand structural features are still insufficient. The purpose of this study was to develop models linking stand-level biomass with stand factors and structure, and to quantify the effects of each variable on stand biomass in natural mixed forests, especially stand structure. Four machine learning (ML) algorithms named Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF) and Boosted Regression Trees (BRT) were adapted. The results showed that SVM and ANN outperformed RF and BRT algorithms in stand biomass estimation. ANN with tree size diversity as the input had the highest accuracy (R2=0.9255±0.0421) among the models. Furthermore, structural diversity was a reliable predictor of mixed stand biomass estimation which is superior to the stand average height traditionally used. The positive correlation between stand biomass and structural diversity suggested that the complex stand structure promoted the accumulation of stand biomass. Thus, our study offered a ML protocol for predicting stand biomass of natural coniferous-broadleaved mixed forests, and suggested that using comprehensive management measures such as properly promoting tree differentiation can help forest managers enhance ecosystem carbon.
Global burden of viral infectious diseases of poverty based on GBD 2021
Authors: LI Xinchen , ZHANG Yanyan , ZHANG Qiyu , LIU Jingshu , RAN Jinjun , HAN Lefei , ZHANG Xiaoxi 
Published: June 2024

Abstract

Background
Viral infectious diseases of poverty (vIDPs) remain a significant global health challenge. Despite their profound impact, the burden of these diseases is not comprehensively quantified. This study aims to analyze the global burden of six major vIDPs, including COVID-19, HIV/AIDS, acute hepatitis, dengue, rabies, and Ebola, by using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021).
Methods
Following the methodological framework and analytical strategies of the GBD 2021, we analyzed the incidence, mortality, and disability-adjusted life years (DALYs) of the six vIDPs across 204 countries and territories from 1990 to 2021. We also examined the association between the Socio-Demographic Index (SDI) and the burden of vIDPs. All estimates were reported as numbers and rates per 100,000 population, with 95% uncertainty intervals (UI).
Results
In 2021, the total deaths due to vIDPs were approximately 8.7 million, and the DALYs were approximately 259.2 million, accounting for 12.8% and 9.0% of the global all-cause totals, respectively. Globally, the burden of vIDPs varied significantly. COVID-19 was the most impactful, with approximately 7.9 million (95% UI 7.5-8.4) deaths and 212.0 million (95% UI 197.9-234.7) DALYs in 2021. Acute hepatitis had the second-highest age-standardized incidence rate, while HIV/AIDS had a high age-standardized prevalence rate. The incidence of dengue significantly increased, with cases rising from 26.5 million (95% UI 3.9-51.9) in 1990 to 59.0 million (95% UI 15.5-106.9) in 2021. Rabies, although reduced in prevalence, continued to pose a significant mortality risk. Ebola had the lowest overall burden but showed significant impacts during outbreaks. Analysis revealed a negative correlation between SDI and DALYs for rabies, acute hepatitis, and HIV/AIDS, whereas dengue, Ebola, and COVID-19 showed no direct correlation with SDI.
Conclusions
vIDPs pose major public health challenges worldwide, with significant regional, age, and gender disparities. The results underscore the need for targeted public health interventions and international cooperation to mitigate the burden of these diseases. Policymakers can use these findings to implement cost-effective interventions and improve health outcomes, particularly in regions with high or increasing burdens.
Exploring neuronal markers and early social environment influence in divergent quail lines selected for social motivation
Authors: Court Lucas , Talbottier Laura , Lemarchand Julie , Cornilleau Fabien , Pecnard Emmanuel , Blache Marie-Claire , Balthazart Jacques , Cornil Charlotte Anne , Keller Matthieu , Calandreau Ludovic , Pellissier Lucie 
Published: June 2024

Abstract

Vertebrates, including humans exhibit a wide range of social behaviors that are crucial for the adaptation and survival of most species. The brain organization and function are shaped by genetic and environmental factors, although their precise contributions have been poorly explored in the context of artificial selection. We used divergent lines of quail selected on their high versus low level of motivation to approach a group of conspecifics (S+ and S-, respectively) to investigate the influence of genetic selection and early social environment on sociability. We observed distinct sex- and brain-region-specific expression patterns of three neuronal markers: mesotocin, and vasotocin, the avian homologues of mammalian oxytocin and vasopressin, as well as aromatase, the enzyme that converts androgens into estrogens. These markers displayed pronounced and neuroanatomically specific differences between S+ and S- quail. Additionally, we assessed the influence of early social environment on social skills in adolescent birds. Mixing S+ and S- resulted in more S- males approaching the group without affecting the sociability of S+ or other behaviors, suggesting that the early social environment may influence the results of genetic selection. In conclusion, the divergent quail lines offer a valuable model for unraveling the neuronal and behavioral mechanisms underlying social behaviors.
The maturation of affective responses: physiological, behavioral, and self-reported emotions in children and youth
Authors: Konopkina Kseniia , Hirvaskoski Hilla , Hietanen Jari K. , Saarimäki Heini 
Published: June 2024

Abstract

Investigating age-related shifts in affective responses to emotionally salient stimuli is key to comprehending emotional development during childhood and adolescence. Most of the research regarding emotional experiences has focused on adults, while the understanding of the development of emotional experiences across childhood remains elusive. To address this gap, we explored whether physiological and behavioral responses as well as self-reported emotions elicited in children and adolescents by naturalistic stimuli differ from those in adults. We developed a set of emotional videos to elicit different emotions – fear, joy, anger, sadness, amusement, and tenderness - and measured emotional intensity ratings, electrocardiography, and eye movements from 8–15-year-old children and adults during the viewing of the videos. We identified an age-related maturation in all measured responses. Emotional intensity and behavioral responses varied across emotion categories. Furthermore, specific emotions showed different maturation patterns. The study highlights the importance of a multi-component approach to accurately discern and understand emotional states.
Invariance Compensation Pid Control for a Proportional Valve-controlled Asymmetric Cylinder System
Authors: XU Wenbin , ZENG Le 
Published: June 2024

Abstract

A load flow model of a proportional valve-controlled asymmetric cylinder system is developed to assess inconsistent dynamic properties. The load flow property is analyzed, and the basic state is defined for the system. In addition, an invariance compensation method is proposed that considers the structure and load effect. If any asymmetric state of the system is equivalent to the basic state through invariance compensation, then the symmetrical load flow property is obtained, which is verified through simulation. Proportion–integration–differentiation (PID) control based on invariant compensation is used in the system, and the dynamic characteristics are almost the same. The experimental results show that the flow error between the load state and the basic state is less than 11% in the linear region of the proportional valve for the asymmetric cylinder system when the system load pressure is less than half of the pump pressure. The response error is approximately 0.04 s between the forward and reverse directions under the given asymmetric load.
A novel polypeptide encoded by the circRACK1 suppresses gastric cancer via cytoskeleton remodeling
Authors: Qiao Lei , Zhou Zhengyang , Cheng Yanan , Pan Wen , Han Yueting , Zhu Qihang , Zhang Haiyang , Ba Yi 
Published: June 2024

Abstract

Gastric cancer (GC), particularly prevalent in China, is associated with high rates of morbidity and mortality. This study focuses on the role and mechanistic pathways of a novel 127-amino acid peptide, circR-127aa, encoded by hsa_circ_0075402 (circRACK1) in GC cells, exploring its implications in cancer development. Circular RNAs (circRNAs), which vary in expression across different cancers, contribute to tumorigenesis via mechanisms such as miRNA sponging, protein binding, and influencing transcription and translation.
Our research involved an extensive analysis of circRNAs ribo-seq data, complemented by mass spectrometry, Western blotting, and immunofluorescence to validate the encoding of circR-127aa by circRACK1. We explored the functional impact of circR-127aa, examining its effects on cell proliferation, apoptosis, and tumor formation in nude mice. A critical aspect of this study was investigating the interaction between circR-127aa and Vimentin, a significant player in cytoskeleton remodeling and cellular mobility during epithelial-mesenchymal transition (EMT). The findings reveal that the circRACK1-encoded peptide functions as a tumor suppressor, facilitating Vimentin ubiquitination, highlighting its potential as a novel therapeutic target and biomarker in GC treatment.
In conclusion, this research unveils a groundbreaking role of the circRACK1-encoded peptide, circR-127aa, in GC, emphasizing its tumor-suppressing function through the ubiquitination of Vimentin. This discovery enhances our understanding of GC progression and presents circR-127aa as a valuable candidate for therapeutic strategies and as a biomarker in GC treatment.
Autoimmune thyroid disease and pituitary adenoma in a female patient with 18p deletion syndrome: a case report and review of the literature
Authors: Ye Jingwen , Shu Yi , Wang Mingzhu , Luo Haizhao , Liang Weiqiang , Lu Qiuping , Mei Wen , Deng Jiajin 
Published: June 2024

Abstract

Background
18p deletion (18p-) syndrome is a rare chromosomal abnormality with a wide range of phenotypes. Its main clinical features are short stature, intellectual disability, and facial dysmorphism, which are rarely accompanied by autoimmune thyroid disease (ATD) or pituitary abnormalities. Herein, we report the first Chinese patient with a de novo 18p deletion who presented with ATD.
Case presentation:
A 24-year-old female patient presented with severe ptosis, intellectual disability, hypothyroidism associated with Hashimoto’s thyroiditis, and a non-functional pituitary adenoma. Deletion of the short arm of chromosome 18 was detected in a G-banded karyotyping (46, XX, del [18] [p11.1]). Chromosomal microarray analysis revealed a 14.9Mb deletion in chromosome 18p11.32p11.21, defined as arr[GRCh38]18p11.32p11.21(136227–15079295)x1. The literature review indicated that patients with 18p- syndrome presenting with ATD were mainly female with early disease onset (mean age: 15 years).
Conclusions
18p- syndrome is associated with ATD and pituitary abnormalities. Therefore, examining the endocrine system and detecting defective genes in the 18p breakpoint region are crucial in predicting prognosis.
Negative bronchoscopy or computed tomography radiation in children with suspected foreign body aspiration? Pros and cons
Authors: Çelikkaya Mehmet Emin , Atıcı Ahmet , Korkmaz İnan , El Çiğdem , Karadağ Mehmet , Akçora Bülent 
Published: June 2024

Abstract

Purpose: Foreign body aspiration(FBA) remains an important cause of morbidity and mortality in childhood. Unfortunately, the clinical picture is often unclear and the clinician must decide which patients should undergo bronchoscopic evaluation. The aim of this study was to analyse patients who underwent bronchoscopy for suspected foreign body aspiration and to evaluate the properties of computed tomography(CT) in preventing unnecessary bronchoscopy, which carries the risk of serious complications.
Methods:All patients younger than 18 years of age who were evaluated for foreign body aspiration at a tertiary children's hospital between June 2014 and February 2023 were included in the retrospective review.
Results:A total of 165 children who underwent bronchoscopy were included in this study. 59.4% (n=98) of the cases were girls and 40.6% (n=67) were boys. The median age of the cases was 2 years, ranging from 0.5 to 18 years, and the interquartile range (Q3-Q1) value was 2. X-ray was performed in 100% of the cases (n=165) and CT scan was performed in 26.1% (n=43). In Group II (CT ± Bronchoscopy), the detection rate of FBA was 93%, whereas in Group I (only Bronchoscopy), it was significantly higher at 77.9% compared to 77.9%. Additionally, the negative diagnosis rate in Group II was significantly higher compared to Group I
Conclusions: Low-dose chest CT is a highly effective imaging modality with high sensitivity and specificity for the diagnosis of FBA in children. Since it can be performed rapidly with minimal radiation exposure and can prevent unnecessary bronchoscopies in suspicious cases.
Measuring Accuracy in AI-Generated Definitions: A Comparison Among Select GPTs Using Cosine Similarity Index
Authors: Patra Niyasha , Sharma Suraj , Ray Nilanjan , Bera Debkumar 
Published: June 2024

Abstract

Information generation are highly taking place now-a-days using generative pre-trained transformer (GPT). GPT is widely used in search engines, which generates texts, based on instructions given by humans. ChatGPT, Gemini, Pi and Perplexity are some applications of natural language processing which are widely based on GPT. It is a pre-trained model that uses artificial neural networks to generate the texts in a pattern. These programs are widely used in vast disciplines, most widely in academics. Hence it is imperative to understand the authenticity of the generated texts. The present study uses cosine similarity index to understand the similarity of the texts generated using ChatGPT, Gemini, Perplexity and Pi, along with that of the ground truth. Definitions of some science and social science subjects were generated using the GPT tools used in the present study and the true values were taken as definition provided in the Britannica encyclopedia. The present study opens the avenues for comparing the discipline wise knowledge of these GPT based software using a broader set of keywords.
Comparative assessment of rcd1 specific wwe domain in making evolutionary patterns against conserved genomic regions
Authors: Siddiqua Beena , Qamarunnisa Syeda , Azhar Abid 
Published: June 2024

Abstract

Conserved genomic sequences are of evolutionary importance, as they give information regarding speciation and divergence of taxa. Some sequences that have been used in the determination of plant taxonomic relationships through DNA are rbcL, MatK, atpB-rbcL intergenic spacer with varying success. With the increase in genomic data, the sro family of genes have been found conserved within the kingdom plantae. Among a subset of sro members, the wwe is a domain encoding short stretch of nucleotides that is easily amplified and exists in low copy number per genome. The nucleotides of this domain vary between different species of a plant family while it clusters plants belonging to a same family into statistically supported clades during phylogenetic analyses. This fact raised a need to identify the relationships it forms phylogenetically. To achieve this end, the plants belonging to diverse genera were analysed using wwe, rbcL and rcd1 sequences after amplification from genome and sequence retrieval from online databases. It was found that the plants were clustered by the wwe sequences into their taxonomic families with high bootstrap support. The trees were constructed by using Physcomitrella patens as outgroup as it belongs to order Funariales which is quite divergent to the angiosperms that harbour monocots and dicots. The results demonstrate a potential for using the wwe domain specific to sro family as a molecular marker either alone or in combination with other markers in DNA barcoding and phylogenetics studies, as it has shown to resolve all analysed plants at sub-familial level with high bootstrap support.
A Deep Learning Approach for Prediction of Heart Disease using Ensemble Learning Techniques
Authors: Hayat Mudasir , Javaid Nadeem , Nazir Amna , Alrajeh Nabil , Shafiq Muhammad , Choi Jin-Ghoo 
Published: June 2024

Abstract

Heart Disease (HD) stands as a significant contributor to escalating mortality rates worldwide, impacting communities on a vast scale. While numerous Deep Learning (DL) methodologies have been proposed for HD detection and diagnosis, prior studies have encountered limitations, notably small dataset sizes leading to overfitting. To address these challenges, we present novel ensemble learning approaches aimed at enhancing the authenticity and accuracy of HD prediction. Our work introduces two ensemble techniques, blending and voting, leveraging a combination of Multi-Layer Perceptron, AlexNet, and Deep Belief Network models. Utilizing the heart-disease-health-indicators-BRFSS2015 dataset, characterized by significant imbalances, we employ Adaptive Synthetic oversampling technique to balance the data. Results demonstrate the superior performance of our ensemble models over individual models. The blending model achieves an accuracy of 90.0%, precision of 90.1%, recall of 90.0%, and an F1-score of 90.0%. The voting model attains an accuracy score of 89.3%, precision of 92.2%, recall of 85.9%, and an F1-score of 88.9%. The blending model exhibits superior classification ability compared to the voting model. To assess the generalizability and validate results, K-Fold Cross Validation is employed. For model interpretability and explainability, we utilize an eXplainable Artificial Intelligence technique, Shapley Additive Explanations.
In vitro inhibitory activities of indolealkaloid derivatives against porcine epidemic diarrhea virus
Authors: Jian Yaoying , Dong Siqi , Zhang Qianyi , Pan Jiali , Hu Ruimin , Ding Zhen , Wu Huansheng , Ke Shaoyong , Chen Zheng 
Published: June 2024

Abstract

Porcine Epidemic diarrhea virus (PEDV) is an enteric coronavirus, which can cause acute diarrhea, vomiting, dehydration and high mortality of newborn piglets, and leading to huge economic losses to the world pig industry. Given the limited efficacy of current PEDV vaccines, there is an urgent need for the development of antiviral drugs. In this study, the antiviral effects of 17 synthesized indole alkaloid derivatives against PEDV were investigated. It was observed that the No.14 indole alkaloid derivative exhibited significant inhibition of PEDV replication in a dose-dependent manner. Furthermore, through time-of-addition assays and RT-qPCR, it was determined that delayed administration of the No.14 indole alkaloid derivative resulted in weaker inhibitory effects on PEDV compared to early treatment. Mechanistic analysis revealed that the No.14 indole alkaloid derivative exerts its inhibitory effects during the entry stage of the PEDV life cycle. This study demonstrates the anti-PEDV effects of the No.14 indole alkaloid derivative, suggesting its potential as a candidate drug for treating PEDV infections.
Pathogen-specific IgE-reactive cytosolic allergenic epitopes of Aspergillus fumigatus for immunodiagnostic/immunotherapeutic applications against allergic aspergillosis
Authors: Singh Bharat , Koundal Priya , Manhas Sunita , Dangi Mehak , Sharma Gainda L. , Oellerich Michael , Bhadoria Dharam P. , Tuli Hardeep S. , Haque Shafiul , Mathkor Darin M. , Ramniwas Seema , Asif Abdul R. 
Published: June 2024

Abstract

Aspergillus fumigatus is the causative agent of a global infectious respiratory disease (aspergillosis). Its accurate diagnosis is difficult due to overlapping clinical/radiological features with other respiratory infections. Thus, to identify A. fumigatus-specific entities for more comprehensive use in the immunodiagnosis/immunotherapy of aspergillosis, this work was conducted. We recruited aspergillosis patients after clinical diagnosis; the results included immunoreactivity to A. fumigatus crude/recombinant allergens. Furthermore, 2DE immunoblotting of the A. fumigatus cytosolic fraction was performed with the sera of 10 individual patients, and subsequent Q-TOF analysis of the corresponding IgE-reactive spots from the 2DE-gles identified 18 proteins. These 18 allergenic proteins included 2 known (Asp-f12 and Asp-f22) and 3 predicted allergens (sorbitol/xylulose-reductase, Hsp70-chaperone Hsp88, and Hsp70) of A. fumigatus that exhibited cross-reactivity with other fungal allergens. However, 11 other 13 allergenic proteins from A. fumigatus contained significant immunoreactivity to aspergillosis patient sera. Furthermore, in silico analysis of the antigenic epitopes and cross-reactivity predictions revealed A. fumigatus-specific 9/B-cell and 4/T-cell epitopes. Subsequent docking of representative B-cell and T-cell epitopes with the respective B-cell receptor and MHC-II complex also confirmed receptor-specific binding. These identified pathogen-specific allergens and epitopes could be valuable for future immunodiagnostic and immunotherapeutic applications for better management of aspergillosis and for reducing the disease burden globally.