bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term adjustment of the South America Atlantic Forest to atmospheric carbon dioxide concentration
Authors: Santos Thiago , Bouloubassi Ioanna , Cruz Joana , Rodrigues Alice , Ledru Marie-Pierre , Huguet Arnaud , Shimizu Marília , Lemes Murílo , Nascimento Rodrigo , Venancio Igor , Sobrinho Rodrigo , Bernardes Marcelo , Albuquerque Ana 
Published: May 2024

Abstract

The effect of CO2 fertilization on tropical forests is uncertain due to a lack of direct data and confounding effects of climate variability. Long-term proxy records could help understand the impact of elevated CO2 on tropical vegetation. We provide observationally inferred evidence that the evolution of the Atlantic Forest in SE Brazil between ~ 150 and 65 ka was influenced by CO2 variability rather than temperature or precipitation on both precessional and millennial time scales. Plant wax n-alkanes in a marine core were used to trace forest cover fluctuations and compared with continental records of fossil pollen, revealing a strong correlation with CO2 levels. This highlights CO2 fertilization as a key driver of the past Atlantic Forest evolution, emphasizing the need for protection initiatives to preserve its long-term capacity in carbon storage. Further research is needed to understand the long-term effects of CO2 on tropical forests at the ecosystem scale.
Prevention of radiotherapy-induced pro-tumorigenic microenvironment by SFK-inhibitors
Authors: Kang Keon Wook , Choi Yong June , Kim Myung Jun , Lee Young Joo , Choi Munkyung , Shim Wan Seob , Park Miso , Kim Yong-Chul 
Published: May 2024

Abstract

Radiotherapy is a widely employed technique for eradication of tumor using high-energy beams, and has been applied to approximately 50% of all solid tumor patients. However, its non-specific, cell-killing property leads to inevitable damage to surrounding normal tissues. Recent findings suggest that radiotherapy-induced tissue damage contributes to the formation of a pro-tumorigenic microenvironment. Here, we utilized mouse models to uncover the mechanisms underlying the development of such a radiation-triggered microenvironment. Radiotherapy-induced tissue damage stimulates infiltration of monocyte-derived macrophages and their differentiation into M2 macrophages, ultimately leading to fibrosis and the formation of a pro-tumorigenic microenvironment. This phenomenon was consistently observed across two mouse strains and two organ-targeted radiotherapy models. Notably, SRC family kinases (SFKs) emerged as crucial factors in the formation of the radiotherapy-induced pro-tumorigenic microenvironment. SFKs activation in epithelial cells and fibroblasts was triggered by direct exposure to irradiation or M2 macrophage cytokines. Remarkably, the administration of SFK-targeted inhibitors reversed myofibroblast activation, effectively ameliorating fibrosis and the pro-tumorigenic microenvironment in radiated tissues. Further, combined administration of radiotherapy and SFK-targeted inhibitors significantly enhanced the survival of tumor-bearing mice. In conclusion, reshaping of the tissue microenvironment by SFK-targeting is a potential strategy for prevention of metastasis and recurrence following radiotherapy.
Hindi translation and validation of Ultra Brief peripartum Mental Health Screening Tool (UBPMHST)
Authors: Harit Ishita , Kukreti Prerna , Kataria Dinesh , Puri Manju , Goel Manish Kumar , Prasad Shiv 
Published: May 2024

Abstract

Background
The peripartum period presents a critical window for identifying and addressing maternal mental health concerns. However, existing screening tools often face linguistic and cultural barriers when applied in diverse populations especially of LMIC’s. This study aimed to translate and validate an ultra brief, simple, binary-scoring, novel mental health screening tool into Hindi language, evaluating its psychometric properties and cultural relevance among Hindi-speaking women. The scale developed in 2019, includes symptoms of depressed mood, anxiety symptoms and suicidal ideation, which is possibly more feasible and acceptable for use by non-specialist health workers in busy, low-resource primary care settings. However, a Hindi translated, validated version of the scale is not yet available for use among Indian population.
Methods
As specified by the World Health organisation, the translation process involved forward and backward translations, expert panel reviews, and pilot testing to ensure linguistic equivalence and cultural appropriateness. Subsequently, the translated tool underwent psychometric validation, including exploratory factor analyses, assessment of internal consistency, concurrent validity against established measures like a widely used screening tool (Edinburgh Postnatal Depression rating scale) in the said population. The study recruited a diverse sample of 194 peripartum women seeking antenatal and postnatal care and treatment from a tertiary care healthcare setting, ensuring representation across socio-demographic variables.
Results
The findings of this study underscore the successful translation and validation of an ultra-brief peripartum mental health screening tool for common mental health disorders into Hindi language, demonstrating its reliability, validity, and clinical relevance among Hindi-speaking women. Through rigorous psychometric evaluation, the translated tool exhibited robust internal consistency (Cronbach’s α = 0.80; P < 0.001), cross language concordance (ICC ≥ 0.7), test retest reliability (ICC = 0.952; P < 0.00), factor structure, content validity (CVI = 0.911), and concurrent validity (Pearson’s correlation coefficient 0.67 in ANC/ 0.71in PNC; P < 0.05), thus providing a valuable instrument for identifying peripartum mental health concerns within this population.
Conclusion
Findings elucidated the reliability, validity, and clinical utility of the translated screening tool in screening for peripartum common mental health disorders among Hindi-speaking women, thereby facilitating timely identification and support for maternal mental health concerns.
Predicting Mechanical Properties of Non-Equimolar High-Entropy Carbides using Machine Learning
Authors: Zhao Xi , Zhao Xi , Cheng Shuguang , Cheng Shuguang , Yu Sen , Yu Sen , Zheng Jiming , Zheng Jiming , Zhang Ruizhi , Zhang Ruizhi , Guo Meng , Guo Meng 
Published: May 2024

Abstract

High-entropy carbides (HECs) have garnered significant attention due to their unique mechanic properties. However, the design of novel HECs has been limited by extensive trial-and-error strategies, along with insufficient knowledge and computational capabilities. In this work, the intrinsic correlations between elements in the high-dimensional compositional space of HECs are investigated using high-throughput density functional theory calculations and two machine learning models, which enable us to predict the Young's modulus, hardness and wear resistance only using a chemical formula. Our models demonstrate low root mean square error (11.5GPa) and mean absolute errors (9.0GPa) in predicting the mechanic properties of HECs with arbitrary non-equimolar compositions. We further establish a database of 566,370 HECs and identified 15 novel HECs with best mechanical properties. Our models can rapidly explore the mechanical properties of HECs with descriptor-property correlation analysis, and hence provide an efficient method for accelerating the design of non-equimolar high-entropy materials with desired performance.
Foliar applied silicon nanoparticles (SiNPs) imparted tolerance to arsenic toxicity by modulating physiological and antioxidant in wheat cultivars
Authors: Ahmad Zahoor , Younis Rooma , Ahmad Tanveer , Iqbal Muhammad Aamir , Artyszak Arkadiusz , Hashem Abeer , Abd_Allah Elsayed Fathi 
Published: May 2024

Abstract

Globally, heavy metals especially arsenic (As) toxicity in staple crops like wheat has posed serious threats to human health, necessitating conducting fresh studies to find out biologically viable As toxicity mitigation strategies. Therefore, this study aimed to investigate the impact of foliar-applied silicon nanoparticles (SiNPs) at the tillering stage on the activation of physiological and antioxidant regulation in wheat to induce tolerance against varying As toxicity levels. The trial comprised two promising wheat cultivars (Anaaj and Ghazi) and five SiNPs regimes including 0, 30, 60, 90, and 120 ppm doses against As toxicity levels of 0 and 25 ppm. The recorded findings depicted that SiNPs regimes significantly improved morphological characteristics such as root length, fresh and dry weight, as well as shoot length, and fresh and dry weight of wheat cultivars. Additionally, the levels of chlorophyll pigments, including chlorophyll a, chlorophyll b, and total chlorophyll contents, were significantly increased in SiNPs-treated plants, indicating improved photosynthetic activity. The enhanced antioxidant enzyme activities, such as ascorbate peroxidase (APX), superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), played a vital role in combating oxidative stress induced by As toxicity. Moreover, SiNPs application resulted in a significant reduction in As concentration in both leaves and roots, highlighting the ability of SiNPs to regulate the uptake and accumulation of arsenic and mitigate its toxic effects. In conclusion, the foliar application of SiNPs during the tillering stage of wheat effectively activated physiological and antioxidant regulation, leading to enhanced tolerance against As toxicity.
Self-assembled Aldehyde Dehydrogenase-Activatable Nano-prodrug for Cancer Stem Cell-Enriched Tumor Detection and Treatment
Authors: Liu Bin , Li Bowen , Tian Jianwu , Zhang Fu , Wu Chongzhi , Li Zhiyao , Wang Dandan , Zhuang Jiahao , Chen Siqin , Song Wentao , Tang Yufu , Ping Yuan 
Published: May 2024

Abstract

Cancer stem cells (CSCs), characterized by high tumorigenicity and drug-resistance, are often responsible for tumor progression and metastasis. Aldehyde dehydrogenases (ALDH), often overexpressed in CSC-enriched tumors, present a potential target for specific anti-CSC treatment. In this study, we report a self-assembled nano-prodrug (PS-CHO@ATRA-SS-ATRA) composed of ALDH-activatable photosensitizer (PS-CHO) and disulfide-linked all-trans retinoic acid (ATRA-SS-ATRA) for diagnose and targeted treatment of CSC-enriched tumors. The ATRA-SS-ATRA can load with PS-CHO and self-assemble into a stable nanoparticle PS-CHO@ATRA-SS-ATRA, which can be disassembled into ATRA and PS-CHO in CSC by high level of GSH. As for released PS-CHO, overexpressed ALDH catalyzes the oxidation of aldehydes (-CHO) to carboxyl (-COOH) under CSC-enriched microenvironment, activating the generation of reactive oxygen species (ROS) and fluorescence emission. This ROS generation leads to direct killing of CSCs and is accompanied by a noticeable fluorescence enhancement for real-time monitoring of the CSC-enriched microenvironment. Moreover, the released ATRA, as a differentiation agent, reduce the CSCs stemness and improve the CSC-enriched microenvironment, offering a synergistic effect for enhanced anti-CSC treatment of PS-CHO in inhibition of in vivo tumor growth and metastasis.
Development and validation of a Clinlabomics based nomogram for predicting the prognosis of small cell lung cancer in China: a multicenter, retrospective cohort study
Authors: Peng Qi , Xu Pingyao , Xu Ke , Guo Wei , wang Dongsheng , Xiang Mingfei , Yang Fang , Luo Huaichao 
Published: May 2024

Abstract

Background and Objective
Small cell lung cancer has a high incidence and mortality rate, frequently metastasizes, and is associated with a poor prognosis. However, traditional prognostic models based on stage alone cannot meet clinical needs. This study aims to establish a clinlabomics based, highly accessible prognostic model for small cell lung cancer
Methods
We conducted a multicenter observational retrospective study, enrolling clinical laboratory data of 276 small cell lung cancer patients. The cohort from Sichuan Cancer Hospital comprised a total of 196 samples. Of these, 88 samples were designated as the independent internal validation set, while 80 samples from an alternate institution were allocated as the external validation set. Utilizing univariate and multivariate Cox regression analyses, six prognostic indicators were discerned. A nomogram was subsequently developed based on these identified indicators.
Results
The analysis identified three clinlabomic biomarkers—Total Protein (TP), Aspartate Aminotransferase (AST), and Lymphocyte Ratio (Lym Ratio)—as well as three clinical indicators—Age, Stage, and Smoking History—as independent prognostic factors. Nomogram was developed based on these six indicators. The AUC of time independent ROC for 2-year and 3-year Overall survival (OS) was 0.74, 0.74 in the training cohort, and 0.64, 0.74 in the validation cohort, respectively. The novel nomogram accurately predicted the prognosis for two independent cohorts with p-values < 0.001, and performed risk adjustment, which classified patients with different OS at the same extensive stage (ES) or limited-stage (LS) .
Conclusions
Clinlabomics-based nomogram accurately predicts small cell lung cancer prognosis by leveraging blood laboratory data.
A new design for the addition order of chemotherapy drugs in glioblastoma multiforme
Authors: Liu Junjian , Tang Yifan , Lan Ting 
Published: May 2024

Abstract

An order of addition experiment is a experiment that investigates how the order of addition of materials or components affects the results, with the primary objective of predicting and determining the optimal order of addition of reactants in an optimized reaction. Order of addition experiment are also commonly used in the medical field for drug combination therapy, where experimentation with all combinations of multiple drugs and their dosages is unaffordable due to cost considerations. To solve this problem, this paper proposes a new method of design table construction, combining the partial full order of addition design table and the two-level partial analysis factor design table to form a new class of design table by matrix product method. By adding the main factor and two-factor interaction effect terms and improving the corresponding additive model, we study the effects of factor effects and the order of addition effects of factors on the results under the order of addition experiment. We prove that the relative D-efficiency of the constructed one-class design table can reach 100% and solve an explicit expression for the D-efficiency of the full design. The superiority of the new method is demonstrated by comparing the simulation experiment with the relative D-efficiency of the random design table.
Clinical and radiological features associated with rupture of pulmonary artery pseudoaneurysm: a retrospective study
Authors: liu min , liu jixiang , Yu Wei , Gao Xiaoyan , Chen Shi , Qin Wei , Zhu Ziyang , Li Chenghong , Li Fajiu , Zhai Zhenguo 
Published: May 2024

Abstract

Background
Hemoptysis resulting from rupture of the pulmonary artery pseudoaneurysm (PAP) is massive and fatal, while factor contributing to the rupture of pseudoaneurysm remains elusive. This study aimed to elucidate the clinical and radiological features of PAP and identify the risk factors associated with rupture.
Methods
Patients who developed hemoptysis with PAP were collected from January 2019 to December 2022 retrospectively. Clinical data of the demographic characteristics, radiological findings, treatment strategies, and prognosis were collected. A comparative analysis was performed on the characteristics in the ruptured and non-ruptured cases.
Results
A total of 58 PAPs were identified in the 50 patients. The most common causes were infection (86%) and cancer (8%). The PAPs were located predominantly in the upper lobes of both lungs, and 57 (99.3%) were distributed in the segmental or subsegmental pulmonary arteries. The median diameter was 6.1(4.3–8.7) mm. A total of 29 PAPs were identified adjacent to pulmonary cavitations, with the median diameter of the cavity being 18.9 (12.4–34.8) mm. Rupture of pseudoaneurysm occurred in 21 cases (42%). Compared to unruptured group, the ruptured group had a significantly higher proportion of massive hemoptysis (57.1% vs. 6.9%, p < 0.001), larger pseudoaneurysm diameter (8.1 ± 3.2 mm vs. 6.0 ± 2.3 mm, p = 0.012), higher incidence of pulmonary cavitation (76.2% vs. 44.8%, p = 0.027), and larger cavitation diameters (32.9 ± 18.8 mm vs. 15.7 ± 8.4 mm, p = 0.005). The mean pulmonary artery pressure (mPAP) in the ruptured group was also significantly higher than that in the unruptured group [23.9 ± 7.4 mmHg vs. 19.2 ± 5.0 mmHg, p = 0.011]. Endovascular treatment was successfully performed in all 21 patients with ruptured PAP, of which the clinical success rate was 96.0%. Five patients experienced recurrent hemoptysis within one year.
Conclusions
Massive hemoptysis, pseudoaneurysm diameter, pulmonary cavitation, and elevated mPAP were the risk factors for rupture of pseudoaneurysm. Our findings facilitate early identification and timely intervention of PAP at high risk of rupture.
Cyberattack Detection Using Unsupervised Learning Techniques
Authors: Islam Amanul , Rashid Md Mamunur 
Published: May 2024

Abstract

Cybersecurity threats are becoming increasingly sophisticated and challenging to detect, making it critical to develop effective and robust detection mechanisms. Unsupervised learning techniques offer a promising approach for cyberattack detection, particularly in scenarios where labeled data are scarce or unavailable. In this research, we propose a novel approach for cyberattack detection using adversarial autoencoders that combines the traditional autoencoder architecture with an additional adversarial component. The proposed approach involves data collection and preprocessing, training an adversarial autoencoder model using unsupervised learning with adversarial training, detecting anomalies, and evaluating the performance of the approach. The proposed approach offers several benefits, including the ability to capture complex relationships in the data and generate realistic reconstructions of normal data. The effectiveness and potential of the proposed approach will be evaluated through extensive experiments and comparisons with existing unsupervised learning techniques or other benchmark methods.
Development of models for the processes of primary oil refining in the atmospheric unit with a shortage and uncertainty of initial information
Authors: Orazbayev Batyr , Kuzhuhanova Zhadra , Uskenbayeva Gulzhan , Orazbayeva Kulman , Abdugulova Zhanat , Rzayeva Leila , Kurmangaziyeva Lyailya 
Published: May 2024

Abstract

In practice, when developing models of many production facilities, problems often arise related to the fuzziness of some of the initial information, affecting important indicators of the quality of the facility’s operation. The purpose of the study is to develop a systematic method for synthesizing statistical, fuzzy and linguistic models of complex objects in conditions of shortage and fuzziness of initial information. Then, using the proposed method, various models of the atmospheric unit of a primary oil refining plant are developed. At the same time, statistical models are developed on the basis of traditional methods. With crisp input and operating parameters and fuzzy output parameters, based on the proposed method, fuzzy models of the atmospheric unit are developed that determine the quality of the manufactured products. And when the input, operating and output parameters of the object are fuzzy, there have been developed linguistic models that evaluate the qualities of the target product of the atmospheric unit based on expert assessment methods, logical rules of conditional inference and the proposed method. The developed linguistic models in Fuzzy Logic Toolbox make it possible to evaluate the quality of gasoline from an atmospheric unit depending on the content of chloride salts and the mass fraction of sulfur in the raw material. The advantages of the proposed modeling method compared to known ones are shown.
The Protective Effects of Insulin on the Developing of Dementia in Chronic Kidney Disease Patients with hypertension and diabetes: A Population-Based Nationwide Study
Authors: Chen Yun-Yi , Chen Yi-Hsien , Fang Yu-Wei , Wang Jing-Tong , Tsai Ming-Hsien 
Published: May 2024

Abstract

INTRODUCTION:
The effects of insulin use on the incidence of dementia in chronic kidney disease (CKD) patients with diabetes and hypertension is limited.
METHOD
In this retrospective study, differences in the incidence of dementia between insulin users and non-users were examined with competing risk models.
RESULTS
In a follow-up period of 11 years, 1285 events of dementia were recorded and the multivariate-adjusted hazard ratio for dementia by insulin usage (yes versus non) and insulin usage per medication possession ratio (MPR) is 0.652 (95% confidence interval [CI]: 0.552–0.771) and 0.995 (95% CI: 0.993–0.998) respectively. Such a significantly negative association was consistent in almost the subgroups. Moreover, a dosing effect of insulins was noted that patients who had higher insulin MPRs generally benefited from better protection from dementia.
DISCUSSION
The CKD patients with hypertension and diabetes who received insulin therapy had a 35% decreased risk of dementia.
Understanding Emotional Flexibility in Autism: The Social Factor Matters
Authors: Lacroix Adeline , Bennetot-Deveria Yoann , Baciu Monica , Dutheil Frédéric , Magnon Valentin , Gomot Marie , Mermillod Martial 
Published: May 2024

Abstract

Autistic individuals often present difficulties in flexibly adjusting their behavior, yet laboratory experiments have yielded inconsistent results, potentially due to various influencing factors requiring precise examination. This study aimed to investigate the hypothesis that the social content of stimuli could play a specific role in some of the flexibility challenges faced by autistic individuals. We analyzed data from 256 adult participants (124 with autism), matched in age, gender, and sex, who performed an emotional shifting task involving unpredictable shifts between positive and negative stimuli. In addition, the task had a social and a non-social condition. Our results revealed a larger switch cost in the social compared to the non-social condition, which was more pronounced in autism compared to non-autistic individuals. Expanding upon previous research demonstrating a greater switch cost in autistic than non-autistic individuals for socio-emotional stimuli, our study further extends these findings by highlighting that the social context, rather than the emotional nature of the stimuli alone, could play a particular role in some of the flexibility challenges faced by autistic individuals. Nevertheless, further studies are needed to investigate if these results also apply to autistic children or autistic individuals who also have intellectual disabilities.