bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative analysis of the forest climatic standards REDD+
Authors: Лобовиков М. А. , Прядилина Н. К. 
Published: July 2024

Стандарт по выбросам парниковых газов подразумевает набор правил и процедур для оценки выбросов парниковых газов (ПГ). Наиболее известные стандарты включают VCS (Верифицированный углеродный стандарт), CCB (Климат, сообщество и биоразнообразие), VCS+CCB, платформу REDD.plus механизма REDD+, FCPF Всемирного банка (Фонд партнерства по лесному углероду), ART TREES (Стандарт экологического совершенства REDD+ под управлением корпорации Архитектура для Транзакций REDD+), CAR (Регистр по борьбе с изменением климата) и GS (Золотой стандарт). Для сравнительного анализа эти стандарты анализируются и оцениваются по ряду критериев и индикаторов (КиИ). Критериями являются: базовый уровень, дополнительность, постоянство, утечка, неопределенность, гнездование (нестинг), двойной учет, гарантии, регистр, мониторинг и проверка, управление и учет, права человека. Сравнительный анализ обеспечивает основу для качественной оценки углеродных квот, продаваемых на мировых углеродных рынках.
The GHG standard implies a set of rules and procedures for the greenhouse gas (GHG) assessment. The most prominent standards include VCS (Verified Carbon Standard), CCB (Climate, Community and Biodiversity), VCS+CCB, REDD.plus platform of the REDD+ mechanism, World Bank FCPF (Forest Carbon Partnership Facility), ART (Architecture for REDD+ Transactions) TREES (The REDD+ Environmental Excellence Standard), CAR (Climate Action Reserve), and GS (Gold Standard). For comparative analysis, these standards are analyzed and evaluated against a series of criteria. These criteria are: Baseline, Additionality, Permanence, Leakage, Uncertainty, Nesting, Double Counting, Safeguards, Registry, Monitoring and Verification, Governance and Accounting, Human Rights. Comparative analysis provides basis for the evaluation of the carbon credits traded in the current carbon markets.
Heavy metal accumulation in the phytomass of plants in the Bolshoy Yugan River valley, Surgut District, Khanty-Mansi Autonomous Okrug–Yugra
Authors: Kravchenko I. V. , Mulyukin M. A. , Petrova Yu. Yu. , Shepeleva L. F. 
Published: July 2024

Processes of heavy metal accumulation in plants are increasingly attracting research attention due to the high toxicity of such substances. The pollutants accumulated in the aerial (green leaves, stems, inflorescences) and underground (roots) mass of plants cause oxidative stress associated with the production of reactive oxygen species. In this work, we investigate the accumulation of heavy metals (nickel, lead, chromium, and cadmium) in the aerial mass of plants growing in the Surgut district of Khanty-Mansi Autonomous Okrug–Yugra. In total, leaves from 15 plant species widespread in the studied area were collected for elemental analysis by atomic absorption spectroscopy. About 6–7 mg/kg of nickel was found in the green mass of reed canary grass and heal-all (Prunella vulgaris), which exceeds significantly the nickel amount in the aerial mass of сouch grass, marsh bedstraw, and broadleaf plantain. The aerial parts of reed canary grass and broadleaf plantain were found to accumulate more than 4 mg/kg of lead, while those of bladder sedge, сouch grass, and marsh bedstraw accumulate about 2–3 mg/kg of chromium. More than 2 mg/kg of cadmium was found in сouch grass. The results obtained were used to compile series of accumulation of elements in the aerial parts of floodplain plant species. The content of the studied heavy metals in the aerial phytomass of all studied plants, except for сouch grass, ranges within standard values, corresponding to their maximum permissible concentrations.
Regularities in mercury cation sorption by a lignin-based sulfur-containing sorbent
Authors: Aslamova V. S. , Golovkova E. A. , Shneygelberger E. A. , Aslamov A. A. 
Published: July 2024

The unfavorable environmental situation in the town of Usolye-Sibirskoye (Irkutsk Oblast, Russia) determines the relevance of investigating and applying a new lignin-based sulfur-containing sorbent for purification of groundwater from mercury compounds. The sorbent was synthesized on the basis of waste products of epichlorohydrin (1,2,3-trichloropropane), sulfur, and lignin. The IR spectrum of the sorbent under study showed the presence of an S–S bond in the region of 445–465 cm-1. Intensive absorption of Hg2+ ions in the regions of 2800–2950 cm-1 (valence vibrations of C–H bonds in CH and CH2 groups) and 1460 cm-1 (deformation vibrations in CH2 group) was observed. Absorption of Hg2+ ions by lignin fragments was accompanied by a change in the vibration band of S–S bonds, which splits into two bands of higher frequencies than the νS–S band in the original sorbent. The optimum sulfur content, which ensures the maximum sorption activity of the sorbent, was found to be 53.25%. The mercury sorption isotherms at 20 and 60 °C are described by parabolic dependencies with determination coefficients of 98.9 and 98.6 %, respectively. The kinetic curve at 20 °C and 40 °C is approximated by a hyperbola and a cubic polynomial with determination coefficients of 97.9 and 96.2 %, respectively. The reaction order (first order at 20 °C and second order at 40 °C) and the reaction rate constant (0.0876 min-1 at 20 °C and 0.00014 min-1 at 40 °C) were determined. At 20 °C, the sorption rate of Hg2+ was established to be significantly higher and the sorption time to be faster than those at 40 °C. Therefore, mercury sorption by the proposed sorbent should be carried out at 20 °C in order to reduce energy consumption.
Value of Mac-2 Binding Protein Glycosylation Isomer (M2BPGi) in Assessing Liver Fibrosis in Metabolic Dysfunction-Associated Liver Disease: A Comprehensive Review of its Serum Biomarker Role
Authors: Sotoudeheian Mohammadjavad 
Published: July 2024

Abstract:
Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) is a broad condition
characterized by lipid accumulation in the liver tissue, which can progress to fibrosis and cirrhosis
if left untreated. Traditionally, liver biopsy is the gold standard for evaluating fibrosis. However,
non-invasive biomarkers of liver fibrosis are developed to assess the fibrosis without the risk of
biopsy complications. Novel serum biomarkers have emerged as a promising tool for non-invasive
assessment of liver fibrosis in MAFLD patients. Several studies have shown that elevated levels
of Mac-2 binding protein glycosylation isomer (M2BPGi) are associated with increased liver fibrosis
severity in MAFLD patients. This suggests that M2BPGi could serve as a reliable marker for
identifying individuals at higher risk of disease progression. Furthermore, the use of M2BPGi offers
a non-invasive alternative to liver biopsy, which is invasive and prone to sampling errors.
Overall, the usage of M2BPGi in assessing liver fibrosis in MAFLD holds great promise for improving
risk stratification and monitoring disease progression in affected individuals. Further research
is needed to validate its utility in clinical practice and establish standardized protocols for
its implementation.
The Imidazacridine Derivative LPSF/AC-05 Induces Apoptosis, Cell Cycle Arrest, and Topoisomerase II Inhibition in Breast Cancer, Leukemia, and Lymphoma
Authors: de Oliveira Chagas Mardonny Bruno , Mendonca da Costa Valecia de Cassia , Montenegro Claudio , de Lima Maria do Carmo Alves , da Rosa Michelle Melgarejo , Pereira Michelly Cristiny , de Melo Rego Moacyr Jesus Barreto , da Rocha Pitta Maira Galdino 
Published: July 2024

Introduction:
Cancer is one of the major causes of morbidity and mortality worldwide. Current treatments for both solid and hematological tumors are associated with severe adverse effects and drug resistance, necessitating the development of novel selective antineoplastic drugs

Methods:
The present study describes the antitumor activity of the imidazacridine derivative 5-acridin-9-ylmethylidene-2-thioxoimidazolidin-4-one (LPSF/AC05) in breast cancer, leukemia, and lymphoma cells. Cytotoxicity assays were performed in PBMC and in breast cancer, leukemia, and lymphoma cell lines using the MTT method. Changes in cell cycle progression and apoptosis were assessed using flow cytometry. Moreover, topoisomerase II inhibition assays were performed. LPSF/AC05 exhibited cytotoxicity in six of the nine cell lines tested.

Results:
The best results for leukemia and lymphoma were observed in the Toledo, Jurkat, and Raji cell lines (IC50 = 27.18, 31.04, and 33.36 M, respectively). For breast cancer, the best results were observed in the triple-negative cell line MDA-MB-231 (IC50 = 27.54 μM). The compound showed good selectivity, with no toxicity to normal human cells (IC50 > 100M; selectivity index > 3). Cell death was primarily induced by apoptosis in all cell lines. Furthermore, LPSF/AC05 treatment induced cell cycle arrest at the G0/G1 phase in leukemia/lymphoma and at the G2/M phase in breast cancer. Finally, topoisomerase II was inhibited.

Conclusion:
These results indicate the potential application of LPSF/AC05 in cancer therapy.
New Progress on DNA Primase Subunit Enzymes Research and Link to
Cancer Development and Treatment Approaches
Authors: Liu Bingbing , Yan Jingjing , Guo Zhanfei , Chen Xiaodan , Zhang Zhiwei 
Published: July 2024

Abstract:
In eukaryotic cells, primases are the key polymerase during DNA replication and DNA
damage repair, which includes primase subunit 1 (PRIM1) and primase subunit 2 (PRIM2). Recent
studies reported that the aberrant expression and activity of PRIM enzymes are closely associated
with the carcinogenesis and development of various cancers. PRIM1 is overexpressed in hepatocellular
carcinoma, breast cancer, and other cancers, while PRIM2 is highly expressed in lung
cancer, gastrointestinal cancer, and other cancers. Further studies revealed that the knockdown of
PRIM1 promoted the apoptosis of liver cancer cells, while Dihydroartemisinin (DHA) can inhibit
PRIM2 expression, suppress lung cancer cell proliferation, and result in ferroptosis. The present review
summarized the recent advancements in the research of the aberrant expression of PRIM1
and PRIM2 and their activity in DNA replication, DNA damage repair, and carcinogenesis. Furthermore,
the strategies targeting PRIM1 or/and PRIM2 become potential therapeutic approaches
in cancer treatment.
The Value of Radiomics Features Based on HRCT in Predicting whether the
Lung Sub-Centimeter Pure Ground Glass Nodule is Benign or Malignant
Authors: Ping Xiaoxia , Liu Yuanqing , Hong Rong , Hu Su , Hu Chunhong 
Published: July 2024

Objective::
In this study, a radiomics model was created based on High-Resolution Computed Tomography (HRCT) images to noninvasively predict whether
the sub-centimeter pure Ground Glass Nodule (pGGN) is benign or malignant.

Methods::
A total of 235 patients (251 sub-centimeter pGGNs) who underwent preoperative HRCT scans and had postoperative pathology results were
retrospectively evaluated. The nodules were randomized in a 7:3 ratio to the training (n=175) and the validation cohort (n=76). The volume of
interest was delineated in the thin-slice lung window, from which 1316 radiomics features were extracted. The Least Absolute Shrinkage and
Selection Operator (LASSO) was used to select the radiomics features. Univariate and multivariable logistic regression were used to evaluate the
independent risk variables. The performance was assessed by obtaining Receiver Operating Characteristic (ROC) curves for the clinical, radiomics,
and combined models, and then the Decision Curve Analysis (DCA) assessed the clinical applicability of each model.

Results::
Sex, volume, shape, and intensity mean were chosen by univariate analysis to establish the clinical model. Two radiomics features were retained by
LASSO regression to build the radiomics model. In the training cohort, the Area Under the Curve (AUC) of the radiomics (AUC=0.844) and
combined model (AUC=0.871) was higher than the clinical model (AUC=0.773). In evaluating whether or not the sub-centimeter pGGN is benign,
the DCA demonstrated that the radiomics and combined model had a greater overall net benefit than the clinical model.

Conclusion::
The radiomics model may be useful in predicting the benign and malignant sub-centimeter pGGN before surgery.
Automatic Detection of Standard Planes in Fetal Ultrasound Images based on Convolutional Neural Networks and Ensemble Learning
Authors: Zhu Baoping , Yang Fan , Duan Hongliang , Gao Zhipeng 
Published: July 2024

aims:
This study aims to leverage artificial intelligence for enhancing medical diagnosis, focusing on ultrasound evaluation of fetal development and detection of fetal diseases.

background:
Traditional diagnostic methods in ultrasound are known for being time-consuming and laborious, prompting the need for more efficient approaches.

objective:
The objective of this research is to develop an end-to-end automatic diagnosis system using convolutional neural networks with ensemble learning to enhance robustness and accuracy in classifying ultrasound images.

method:
The study involves constructing and implementing the automatic diagnosis system, training it on a diverse dataset encompassing six categories: abdomen, brain, femur, thorax, maternal cervix, and other planes.

result:
Experimental results demonstrate that the proposed end-to-end system significantly improves the detection accuracy of the standard plane in ultrasound images.

conclusion:
The application of artificial intelligence through an ensemble learning-based automatic diagnosis system shows promise in advancing ultrasound-based medical diagnosis, particularly in fetal development assessment.

other:
This research contributes to the ongoing efforts in leveraging technology for more efficient and accurate medical diagnostic processes.
Molecular Actions of Enicostemma hyssopifolium Whole Plant Extract on HPV18-Infected Human Cervical Cancer (HeLa) Cells
Authors: Koralahalli Komal Parameshwarappa , Hussain Sardar , Devarajan David Wilson , Siddikuzzaman  , Mariammal Berlin Grace Viswanathan 
Published: July 2024

Objective:
Enicostemma hyssopifolium (E. hyssopifolium) contains several bioactive compounds with
anti-cancer activities. This study was performed to investigate the molecular effects of E. hyssopifolium on
HPV18-containing HeLa cells.

Methods:
The methanol extract of E. hyssopifolium whole plant was tested for cytotoxicity by MTT assay. A
lower and higher dose (80 and 160 μg/mL) to IC50 were analyzed for colonization inhibition (Clonogenic assay),
cell cycle arrest (FACS analysis), and induction of apoptosis (AO/EtBr staining fluorescent microscopy and
FACS analysis) and DNA fragmentation (comet assay). The HPV 18 E6 gene expression in treated cells was
analyzed using RT-PCR and qPCR.

Results:
A significant dose-dependent anti-proliferative activity (IC50 - 108.25±2 μg/mL) and inhibition of colony
formation cell line were observed using both treatments. Treatment with 80 μg/mL of extract was found to result
in a higher percent of cell cycle arrest at G0/G1 and G2M phases with more early apoptosis, while 160 μg/mL
resulted in more cell cycle arrest at SUBG0 and S phases with late apoptosis for control. The comet assay also
demonstrated a highly significant increase in DNA fragmentation after treatment with 160 μg/mL of extract (tail
moments-19.536 ± 17.8), while 80 μg/mL of extract treatment showed non-significant tail moment (8.152 ± 13.0)
compared to control (8.038 ± 12.0). The RT-PCR and qPCR results showed a significant reduction in the expression
of the HPV18 E6 gene in HeLa cells treated with 160 μg/mL of extract, while 80 μg/mL did not show a
significant reduction.

Conclusion:
The 160 μg/mL methanol extract of E. hyssopifolium demonstrated highly significant anti-cancer
molecular effects in HeLa cells.
Quantification of Lobeglitazone Sulfate in Bulk and Tablet Dosage Form by a Validated UV Spectroscopy Method: A New Thiazolidinedione Anti-diabetic Drug
Authors: Mudaliar Saradhkumar , Sharma Sanjay 
Published: July 2024

Background:
Lobeglitazone sulfate is a novel thiazolidinedione drug used for the therapy of type 2 diabetes. Recent pre-clinical studies show that the drug is also effective in attenuating mucus hypersecretion and airway inflammation caused due to ovalbumin-induced asthma.

Objective:
This study aimed to develop an accurate, simple, and cost-effective analytical method for the quantification of lobeglitazone sulfate in bulk and pharmaceutical dosage forms by UV spectrophotometric technique.

Methods:
The drug was identified by FTIR (ATR) instrument and the method development was performed with methanol as the solvent. In compliance with the ICH Q2(R2) guidelines, all the important validation parameters, such as linearity, accuracy, Limit of Detection (LOD), precision, specificity, Limit of Quantification (LOQ), and robustness were deter-mined.

Results:
The maximum absorption wavelength of lobeglitazone sulfate was found to be 248 nm. The linearity range was established from 2-14 μg/mL with a linearity equation of y = 0.0361x + 0.0024 and r² = 0.9987. The accuracy of the analytical method was found to be in the range of 99.37-100.41%. The precision studies were performed under three subsets of re-peatability, intra-day, and inter-day, and the results recorded were within the acceptance lim-its, i.e., %RSD (<2%). The developed analytical method's Limit of Detection (LOD) and Limit of Quantification (LOQ) values were 0.07 μg/mL and 0.22 μg/mL, respectively.

Conclusion:
The developed analytical method has been found to be valuable in regular qual-ity control analysis of lobeglitazone sulfate in pharmaceutical industries. The adopted ap-proach of the developed method has been found to be facile, accurate, precise, and economi-cal.
Selection of Building Materials Using Fuzzy Analytical Hierarchy Process
Authors: Reddy L. Sudheer , Murthy N.R.D. , Srikanth M. , Reddy S. Sunil Pratap , Keerthana D. Mani 
Published: July 2024

Introduction
Building materials play a vital role in the construction industry as they are directly related to quality, cost, constructability, and location-specific availability of material and skill. Selection of building materials is critical when there are too many alternatives. Multi Criteria Decision Making (MCDM) techniques are widely used to make such decisions simpler. For accurate decision-making, the selection of the appropriate MCDM method is very important. Most of the researchers used TOPSIS or AHP as MCDM techniques for decision-making in the construction industry.

Methods
In the present study, the fuzzy analytical hierarchy process (AHP) was used as an MCDM technique. The criteria and alternatives were identified for decision-making. The alternatives selected were locations specific to Hanamkonda, Telangana state, India. The criteria and alternatives were chosen for the building materials like cement, bricks, sand, doors, pipes, and tiles. The weights were calculated for each alternative fuzzy AHP geometric mean method. The weights of alternatives were evaluated and ranked.

Results
The best materials for cement, bricks, sand, doors, pipes, and tiles were Portland pozzolana, burnt clay bricks, river sand, UPVC, UPVC/CPVC, and marble, respectively.

Conclusion
Thus, building materials can be selected using fuzzy AHP by the client for the successful execution of a project based on his/her preferences and the location of that project.
Obtaining the Most Accurate, Explainable Model for Predicting Chronic Obstructive Pulmonary Disease: Triangulation of Multiple Linear Regression and Machine Learning Methods
Authors: Kamis Arnold , Gadia Nidhi , Luo Zilin , Ng Shu Xin , Thumbar Mansi 
Published: July 2024

Background
Lung disease is a severe problem in the United States. Despite the decreasing rates of cigarette smoking, chronic obstructive pulmonary disease (COPD) continues to be a health burden in the United States. In this paper, we focus on COPD in the United States from 2016 to 2019.

Objective
We gathered a diverse set of non–personally identifiable information from public data sources to better understand and predict COPD rates at the core-based statistical area (CBSA) level in the United States. Our objective was to compare linear models with machine learning models to obtain the most accurate and interpretable model of COPD.

Methods
We integrated non–personally identifiable information from multiple Centers for Disease Control and Prevention sources and used them to analyze COPD with different types of methods. We included cigarette smoking, a well-known contributing factor, and race/ethnicity because health disparities among different races and ethnicities in the United States are also well known. The models also included the air quality index, education, employment, and economic variables. We fitted models with both multiple linear regression and machine learning methods.

Results
The most accurate multiple linear regression model has variance explained of 81.1%, mean absolute error of 0.591, and symmetric mean absolute percentage error of 9.666. The most accurate machine learning model has variance explained of 85.7%, mean absolute error of 0.456, and symmetric mean absolute percentage error of 6.956. Overall, cigarette smoking and household income are the strongest predictor variables. Moderately strong predictors include education level and unemployment level, as well as American Indian or Alaska Native, Black, and Hispanic population percentages, all measured at the CBSA level.

Conclusions
This research highlights the importance of using diverse data sources as well as multiple methods to understand and predict COPD. The most accurate model was a gradient boosted tree, which captured nonlinearities in a model whose accuracy is superior to the best multiple linear regression. Our interpretable models suggest ways that individual predictor variables can be used in tailored interventions aimed at decreasing COPD rates in specific demographic and ethnographic communities. Gaps in understanding the health impacts of poor air quality, particularly in relation to climate change, suggest a need for further research to design interventions and improve public health.