bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of Lead Clamps Used in Roman Period Buildings in the Ancient City of Anavarza With Pb Isotope Analysis
Authors: AKYILDIZ Mustafa , AYNA Erkan 
Published: June 2024

Abstract

The ancient city of Anavarza is one of the most important cities of the Roman Period, established in the Cilicia region of Ovalık, within the borders of Anatolia. The center of the city is built on a land of approximately 4000 acres, on a plain with an altitude of 33 meters. The ancient city of Anavarza is divided into two parts: the lower city, surrounded by walls, and the upper city, built on the rocks. The Romans used clamps and iron to connect the columns and their capitals to each other. The clamping bars, which are curved at both ends, were added horizontally to the stone wall and inserted into the cavities created in the stone in order to strengthen the joined part, and the curved ends were covered with lead pouring. Bright section, SEM-EDX and Pb isotope analyzes were performed on the lead samples to determine the source of the lead used here. Primary galena mineral was detected in bright sections. According to EDX analysis results, 41.98 Pb, 15.48 O, 19.43 C, 13.66 Si, 4.45 Fe, 3.89 Al, 0.4 Co elements were detected. When comparing Pb isotope analyzes made from Pb-Zn deposits in regions close to the ancient city of Anavarza, it is thought that lead was supplied from the vicinity of Aladağ and Horzum, close to the region.
N6-methyladenosine-modified circRPS6KC1 regulated cell senescence in prostate cancer via FOXM1/PCNA axis
Authors: Shu Xuan , Yi Jiahe , Li Jiangfeng , Ying Yufan , Tang Yijie , Chen Ziyan , Wang Jiaming , Zhang Fenghao , Lu Dingheng , Wu Yuqing , Sun Jiazhu , Lin Shen , Qi Zhixiang , Chen Danni , Wang Xiao , Chen Hong , Xie Liping , Ma Xueyou , Luo Jindan 
Published: June 2024

Abstract

Background
Prostate cancer (PCa) gradually becomes the most common cancer in men in many countries, of which circRNAs and methylated modification exert an essential role in prostate cancer progression. However, the concrete mechanism of N6-methyladenosine (m6A) modification of circRNAs in prostate cancer remains unclear.
Methods
circRNA-seq and bioinformatic analysis reveal the novel up-regulated circRPS6KC1 in PCa. Function experiments in vitro and in vivo, such as colony formation assay, cell counting kit-8 assay, cell cycle analysis, EdU assays, senescence associated β-galactosidase staining and subcutaneous xenograft tumor models, were conducted to show the effect of circRPS6KC1 on prostate cancer cell senescence. RNA Immunoprecipitation (RIP), methylated RNA Immunoprecipitation (MeRIP), RNA pull-down, chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays were performed to explore the regulatory mechanism.
Results
We identified a novel circRNA, circRPS6KC1, which was significantly up-regulated in prostate cancer cells and clinical tissues. METTL3/YTHDF1 participated in the m6A modification of circRPS6KC1 and stabilized it. Suppression of circRPS6KC1 contributed to cell senescence in prostate cancer. Mechanically, circRPS6KC1 acted as the miR-761 sponge to regulate the FOXM1 expression. FOXM1 mediated the transcription of PCNA and influenced the p21 degradation, which resulted in p21 up-regulation induced in a p53-independent manner.
Conclusion
N6-methyladenosine modification by METTL3/YTHDF1 stabilized circRPS6KC1, and circRPS6KC1 regulated cell senescence in prostate cancer via FOXM1/PCNA axis in a p53-independent manner.
A Multi-level Deep Neural Network to Diagnose Coronavirus Disease with Imbalanced Data
Authors: Zabbah Iman , Layeghi Kamran , Ebrahimpour Reza 
Published: June 2024

Abstract

One of the main challenges of medical data mining is the classification of imbalanced datasets. Often the data which are used for training classification is of no proper distribution. It occurs when a class has few samples in nature inclining the learner model to the major class. This imbalance is quite obvious in the data X-ray image of coronavirous, due to its newness, so the samples of healthy and pneumonia are more than COVID- 19 ones. Here we proposed a multi-level model that improves diagnosis of the disease using data augmentation in the minor class of coronavirous cases. The model contains a deep feature extractor, a novel algorithem to find the scatter topolgy of the minor class, a mechanism to selectively generate synthetic samples and finally clasify input data. Coronavirous images are fed to a deep neural networks as a feature estractor. Then, finding scatter topology of the minor class, synthetic samples are generated in the feature space and evaluated by some expertes so that the synthetic samples resemble real ones mostly. Finally, the pool of synthetic and real samples of each classes are transferred to a discriminator network after the dataset is balanced. Results indicate that the production of samples by the framework not only improves classification performance but also has a more desirable performance than other data augmentation methods.
Equal Work, Unequal Pay: Gender Wage Discrimination in India
Authors: Taneja Arz , Batra Rachel 
Published: June 2024

Abstract

This paper investigates gender wage discrimination in India using data from the nationally representative Indian Human Development Survey round I (IHDS 2005) as well as round II (IHDS 2011). We examine the gender wage gap in the country across rural and urban areas separately as well as at an aggregate level. Controlling for financial and household characteristics, we employ a modified Mincer regression for men and women. We then breakdown the wage differential into explainable and unexplainable components using the Blinder–Oaxaca methodology. We find that education and experience significantly influence wages across genders in both rural and urban areas, while their affect is more prominent in urban areas. Through the decomposition analysis, we find that although the log wage differential decreased between 2005 and 2011, this reduction is overshadowed by a larger portion of the differential being attributed to different treatment of the same skills, indicative of potential discrimination.
Water structure and dynamics in microporous mordenite
Authors: Egorov Andrei V. , Egorova Maria I. , Mizyulin Dmitry A. , Shelyapina Marina G. 
Published: June 2024

Abstract

The local ordering and features of the molecular mobility of water confined in voids of a pure silica mordenite was studied using the molecular dynamics simulation over a temperature range from 298 to 163 K. The simulated system was a fragment of mordenite consisted of 2×2×4 unit cells filled with 384 water molecules. Three different water models: SPCE, SPCF, and TIP5P were considered. To study the effect of nanoconfinment the results were compared with bulk water. The modelling suggests that at room temperature a 2D (in c and b directions of the mordenite cell) water diffusion takes place, while upon cooling the diffusion in b direction essentially slows down. The analysis of microstructure shows that the pores prevent the formation of a full tetrahedral structure of water environment that results in formation of several water substructures. A detailed analysis of water reorientational motion was carried out and the activation energies were determined from temperature dependence of the correlation times. Of the three water models considered, SPCE demonstrated the best performance. The results obtained can be helpful for interpretation of experimental temperature dependence of NMR relaxation rates for water molecules confined in porous media with complex topology.
Voltammetric sensor for Tyramine based on poly (L-Aspartic acid) modified Glassy carbon electrode
Authors: Anand Sanu K. , Mathew Manna Rachel , Krishnapillai Girish Kumar 
Published: June 2024

Abstract

This paper details the use of poly (L-Aspartic acid) modified glassy carbon electrode (p(L-Asp)/GCE) for the sensitive voltammetric determination of tyramine (TYM). The studies reveal that the sensor exhibits high electro catalytic activity towards the electro oxidation of TYM. Under optimum experimental conditions, the determination of TYM has been attained in the range 6.00 × 10− 6 to 5.00 × 10− 7 M with a limit of detection 6.55 × 10− 8 M. At the modified electrode, the electro oxidation was found to be a diffusion controlled process which involves one proton and one electron. The reliability of the proposed method has been verified in physiological fluids.
Ethnomedical knowledge of plants used in alternative medicine for the treatment of hemorrhoids in Lubumbashi, Haut-Katanga Province, Southern DR Congo
Authors: Valentin Bashige Chiribagula , Philippe Okusa Ndjolo , Melman Muhona , Henry Manya Mboni , Salvius Bakari Amuri , Baptiste Lumbu Simbi Jean 
Published: June 2024

Abstract

Background
A variety of medicinal plants are used in traditional medicine in Lubumbashi for the management of hemorrhoidal diseases. However, no investigation has been conducted to gather the knowledge required for this type of management in the region. The present study was conducted to inventory the plants used in Lubumbashi to treat hemorrhoidal diseases and to relate their ethnomedical characteristics.
Methods
This study was conducted between March 2022 and February 2023 using semi-structured interviews with households (n = 1520), herbalists (n = 25), and traditional healers : THs (n = 59).
Results
The 1,604 respondents (sex ratio M/F = 0.9; mean age: 56 ± 3 years; experience: 12 ± 3 years) provided information on 100 taxa, 84 of which are used against internal hemorrhoids, Phyllanthus amarus being the most cited (Citation Index, CI: 0.76). Most of them are trees (38%) or shrubs (32%), belonging to 90 genera and 45 families dominated by the Fabaceae (10%) and Asteraceae (9%). They are indicated in 76 other pathologies, dominated by gastrointestinal disorders (GID), wounds and sexually transmitted infections (CI > 0.57). From these 100 taxa, 117 anti-hemorrhoidal formulations were derived, 11 of which combined more than one plant. In all these recipes, the leaf is the most commonly used part (> 60%) and the liniment (> 45%) is the most popular form of application. For the first time, this study reports 14 taxa as plants used in the treatment of hemorrhoids for which some evidence of hemorrhoidal activity has been reported. Among these taxa, Ficus stuhlmannii, Ficus laurifolia, and Ocimum centraliafricanum are listed as medicinal plants for the first time. Khaya nyasica, and Syzygium cordatum, each with 11 uses, have the highest traditional medicinal value.
Conclusion
The findings of this study indicate that a significant number of medicinal plants are used in traditional medicine in Lubumbashi for the treatment of hemorrhoidal diseases. Some of these plants are endemic to the biodiversity area, while others are shared with other cultures and regions. A series of pharmacological studies is currently underway with the objective of validating the anti-hemorrhoidal properties of these plants and in order to identify phytochemical compounds responsible of this activity.
Structural basis for synthase activation and cellulose modification in the
E. coli Type II Bcs secretion system
Authors: KRASTEVA Petya , Anso Itxaso , Sana Thibault , Zouhir Samira 
Published: June 2024

Abstract

Bacterial cellulosic polymers constitute a prevalent class of biofilm matrix exopolysaccharides that rely on conserved cyclic diguanylate (c-di-GMP)-dependent cellulose synthases. Polymer structure and modifications, however, depend on the ensemble of synthase modules and accessory subunits, thus defining several types of bacterial cellulose secretion (Bcs) systems. In E. coli, a BcsRQABEFG macrocomplex, encompassing the inner membrane and cytosolic subunits, and an outer membrane porin, BcsC, secure the biogenesis of phosphoethanolamine (pEtN)-modified cellulose. Resolution-limited studies have proposed different macrocomplex stoichiometries and its assembly and regulation have remained elusive. Using cryo-EM, we visualize the molecular mechanisms of BcsA-dependent recruitment and stabilization of a trimeric BcsG pEtN-transferase for polymer modification and a dimeric BcsF-dependent recruitment of an otherwise cytosolic BcsE2R2Q2 regulatory complex. We further demonstrate that BcsE, a secondary c-di-GMP sensor, remains dinucleotide-bound and retains the essential-for-secretion BcsRQ partners onto the synthase even in the absence of direct c-di-GMP-synthase complexation, likely lowering the threshold for c-di-GMP-dependent synthase activation. Such ‘activation-by-proxy’ mechanism could allow Bcs secretion system activation even in the absence of dramatic intracellular c-di-GMP increase and is reminiscent of other widespread synthase-dependent polysaccharide secretion systems where c-di-GMP sensing and/or synthase stabilization are carried out by key co-polymerase subunits.
The Transnational Mental Health Burden of Haiti's Alleged Collapse: Preliminary Findings from the Haitian Well-Being Study
Authors: Blanc Judite , Carrenard Niara J. , Auguste Evan , Luma Sherryn , Francois Laura , Bigdeli Tim , Jean-Louis Girardin , Duthely Lunthita 
Published: June 2024

Abstract

Background
Transnational drug trafficking, political unrest, gang violence, and paramilitarism, which are pervasive in Haiti, have resulted in a mental health crisis for the broader Haitian community. This study explores the mental well-being of Haitians in Haiti and the United States by identifying barriers and facilitators to mental health through the lived experiences of men and women.
Method
Four Focus group discussions conducted in April and November 2023 engaged 28 participants (20 women and eight men) aged between 23 and 60 years from locations in Haiti (Port-au-Prince, Cite Soleil, Cayes, Cap-Haitien, Saint-Marc) and the United States. Discussions revolved around the definition of mental health, stressors, coping mechanisms, risk and protective factors, and barriers to mental health care.
Results
Six principal themes emerged: 1- Chronic Traumatic Stress: continued violence, political instability, unemployment, lack of social support, adverse childhood experiences, family separation, and forced displacement were significant sources of stress. 2- Increased Health Burden: Participants reported experiencing chronic physical and psychological symptoms (i.e., hypertension, anxiety, depression, sleep issues, substance abuse, suicidal ideations, characteristics of post-traumatic stress disorder [PTSD]), which were attributed to Haiti's social, political, and infrastructure collapse. 3- Risk Factors: limited access to mental health services, pervasive hopelessness, scarcity of opportunities, and stigma were identified as significant risks. 4- Future Uncertainty: widespread concerns regarding the future predominated. 5- Multigenerational Concerns: Significant anxiety concerning the mental health and development of children, as well as the functionality of mental health practitioners, was noted. 6- Coping and Protective Factors: Effective coping strategies include mental stimulation, peer support, managing digital consumption, engaging in leisurely activities, such as listening to music, and faith/spirituality.
Conclusion
The study's findings underscore the sociopolitical and economic crisis in Haiti, which has resulted in violence and a collapse of political, educational, financial, and health infrastructures. These factors were identified as the primary source of chronic distress, contributing to widespread mental health issues, adverse physical symptoms, and disruption in daily life. The implications for practice, healing, research & policy are discussed.
Two-component systems interface discrimination in Actinobacillus pleuropneumoniae
Authors: Martin Eduardo M , Guerrero-Barrera Alma L , Avelar-Gonzalez F Javier , Salinas-Gutierrez Rogelio , Jacques Mario 
Published: June 2024

Abstract

Background
Pathogenic bacteria grow in different environments and have developed signaling systems known as two-component systems that allow them to thrive in distinct habitats efficiently. Actinobacillus pleuropneumoniae is an obligate pig pathogen that colonizes its host and survives outside it by forming biofilms. The small number of the two-component systems in this pathogen makes it a suitable model to assess the interaction specificity of these systems.
Results
This was done through multiple sequence alignments, mutual information, heterodimer modeling, structural data, molecular dynamics, and the interface coupling index, which were used to evaluate molecular recognition. For the study, more than two thousand homologue sequences were collected from a diverse range of bacteria. Four different clusters of specificity-determining residues were found for all evaluated systems. The system-wide discrimination capability of twocomponent systems relies on the composition of these clusters composed of 3, 3, 4, and 5 residue pairs, from systems CpxAR, NarQP, PhoRB, and QseCB, respectively. These residue pairs are spatially nearby, the shape and composition of each cluster are systemspecific and have minimal overlap among them.
Conclusions
The interaction interface composition of the twocomponent systems network in A. pleuropneumoniae was defined and their discriminatory components were described. In summary, molecular recognition depends on specific components from the interaction interface called orthologue interaction specificity clusters. These clusters enable the emergence of specificity, which allows the system to differentiate between cognate and non-cognate components, thereby enabling the system to recognize highly similar components through molecular recognition.
Topic Composition in AEA Journals
Authors: Hong Dian 
Published: June 2024

Abstract

This paper utilizes data from the official American Economic Association (AEA) website, previously unexplored in literature, to investigate the choice of economic topics across all AEA journals. Employing bibliometric analysis and Journal of Economic Literature (JEL) Codes, we discern that micro-related papers are more prominently featured in AEA journals. Furthermore, through an examination of selected topic trends over time, we observe a sustained increase in the proportion of papers related to microeconomics and mathematical and quantitative methods in the American Economic Review (AER). Overall, our findings suggest that researchers should take into account the topic preferences of specific journals when selecting journals for paper submission, even those purportedly accepting papers on a wide range of economic topics. Additionally, for success in academia, junior researchers should start considering aligning their research interests with prevailing hot topics in academic journals.
JEL Codes: A11, A14
A Comprehensive Systematic Review and Meta-Analysis: Evaluating the Effectiveness and Integration Obstacles of Artificial Intelligence (AI) within Anesthesia Departments.
Authors: Zaki Hany A. , Shaban Eman E. , Shallik Nabil , Shaban Ahmed , Shaban Amira , Elgassim Mohamed 
Published: June 2024

Abstract

Background
Artificial intelligence (AI) is a multidisciplinary field focusing on expanding and generating intelligent computer algorithms to carry out simple to more complex tasks traditionally performed using human intelligence. In anesthesia, AI is rapidly becoming a transformative technology. However, its efficacy in anesthesia is still unknown. Therefore, the current study analyzed the efficacy of AI in anesthesia by studying two main applications of AI, i.e., predicting events related to anesthesia and assisting anesthesia-related procedures. Furthermore, this study explored some of the challenges of integrating AI in the anesthesia field.
Methods
PubMed, Google Scholar, IEEE Xplore, and Web of Science databases were thoroughly searched for articles relevant to the objective of the current study. The Comprehensive Meta-analysis software and STATA 16.0 were used for statistical analyses, while the Newcastle Ottawa Scale was used for quality evaluation.
Results
Twenty studies satisfying the eligibility criteria were used for review and analysis. A subgroup analysis showed that models incorporating machine learning algorithms were superior in predicting postinduction hypotension (AUROC: 0.93). ANN and SANN models also showed a good discriminatory capacity in predicting postinduction hypotension (AUROC: 0.82 and 0.80, respectively). Similarly, the subgroup analysis showed that ANN and GBM models had a good discriminatory capacity when predicting hypoxemia (AUROC: 0.8 and 0.81, respectively). Furthermore, SVM, ANN, and fuzzy logic models had a relatively good differentiation ability in predicting postoperative nausea and vomiting (AUROC: 0.93, 0.77, and 0.72, respectively). On the other hand, the subgroup analysis showed that robotically-assisted tracheal intubations were highly successful in both mannikins and humans (success rate: 98% and 92%, respectively). Similarly, robotically-assisted ultrasound-guided nerve blocks were highly successful in mannikins and humans (Success rate: 96% for humans and mannikins, respectively).
Conclusion
The current study suggests that AI is useful in predicting anesthesia-related events and automating procedures such as tracheal intubation and ultrasound-guided nerve block. However, there are multiple barriers hindering the integration of AI in anesthesia that need to be addressed.