bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genotype-specific responses to drought stress in Siberian wildrye (Elymus sibiricus): Insights from comparative physiological and transcriptomic analyses
Authors: An Yongping , Wang Qian , Cui Yannong , Liu Xin , Wang Ping , Zhou Yue , Kang Peng , Chen Youjun , Wang Zhiwei , Zhou Qingping , Wang Pei 
Published: April 2024

Abstract

Siberian wildrye (Elymus sibiricus) is a xero-mesophytic forage grass with high nutritional quality and stress tolerance. Among its numerous germplasm resources, some possess superior drought resistance. In this study, we investigated the physiological differences between drought-tolerant genotype (DT) and drought-sensitive genotype (DS) leaves under drought stress. The results showed that under drought stress, DT maintained a lower leaf water potential for water absorption, sustained higher photosynthetic efficiency, and reduced oxidative damage in leaves by efficiently maintaining the ascorbic acid-glutathione (ASA-GSH) cycle to scavenge reactive oxygen species (ROS) compared to DS. Unigene0047636 (CER1) may positively regulates the synthesis of very-long-chain (VLC) alkanes in cuticular wax biosynthesis, influencing plant responses to abiotic stresses. Correspondingly, wax monomers content showed significant induction by osmotic stress in DT but not in DS. It is suggested that limiting stomatal and cuticle transpiration under drought stress to maintain higher photosynthetic efficiency and water use efficiency (WUE) is one of the critical mechanisms that confer stronger drought resistance to DT. This study provides new insights into the molecular mechanisms underlying drought tolerance in E. sibiricus. The identified genes may provide a foundation for the selection and breeding of drought-tolerant crops.
The Tumor Risk Score (TRS) – Next level risk prediction in head and neck cancer surgery
Authors: Klausing Anne , Waschk Kristina , Far Frederick , Martini Markus , Kramer Franz-Josef 
Published: April 2024

Abstract

Purpose
Head and neck cancer surgery often requires postoperative monitoring in an intensive care unit (ICU) or intermediate care unit (IMC). With a variety of different risk scores, it is incumbent upon the investigator to plan a risk-adapted allocation of resources. Tumor surgery in the head and neck region itself offers a wide range of procedures in terms of resection extent and reconstruction methods, which can be stratified only vaguely by a cross-disciplinary score. With a variety of different risk scores we aimed to develop a new Tumor Risk Score (TRS) enabling anterograde preoperative risk evaluation, resource allocation and optimization of cost and outcome measurements in tumor surgery of the head and neck.
Methods
A collective of 547 patients (2010–2021) with intraoral tumors was studied to develop the TRS by grading the preoperative tumor size and location as well as the invasiveness of the planned surgery by means of statistical modeling. Two postoperative complications were defined: (1) prolonged postoperative stay in IMC/ICU and (2) prolonged total length of stay (LOS). Each parameter was analyzed using TRS and all preoperative patient parameters (age, sex, preoperative hemoglobin, body-mass-index, preexisting medical conditions) using predictive modeling design. Established risk scores (Charlson Comorbidity Index (CCI), ASA class (ASA), Functional Comorbidity Index (FCI)) and Patient Clinical Complexity Level (PCCL) were used as benchmarks for model performance of the TRS.
Results
The TRS is significantly correlated with surgery duration (p < 0.001) and LOS (p = 0.001). With every increase in TRS, LOS rises by 9.3% (95%CI 4.7–13.9%; p < 0.001) or 1.9 days (95%CI 1.0-2.8 days; p < 0.001), respectively. For each increase in TRS, the LOS in IMC/ICU wards increases by 0.33 days (95%CI 0.12–0.54; p = 0.002), and the probability of an overall prolonged IMC/ICU stay increased by 32.3% per TRS class (p < 0.001). Exceeding the planned IMC/ICU LOS, overall LOS increased by 7.7 days (95%CI 5.35–10.08; p < 0.001) and increases the likelihood of also exceeding the upper limit LOS by 70.1% (95%CI 1.02–2.85; p = 0.041). In terms of predictive power of a prolonged IMC/ICU stay, the TRS performs better than previously established risk scores such as ASA or CCI (p = 0.031).
Conclusion
The lack of a standardized needs assessment can lead to both under- and overutilization of the IMC/ICU and therefore increased costs and losses in total revenue. Our index helps to stratify the risk of a prolonged IMC/ICU stay preoperatively and to adjust resource allocation in major head and neck cancer surgery.
Characterization of human trabecular bone across multiple length scales: A correlative approach combining X-ray tomography with LaserFIB and plasma FIB-SEM
Authors: Tang Tengteng , Casagrande Travis , Mohammadpour Pardis , Landis William , Lievers Brent , Grandfield Kathryn 
Published: April 2024

Abstract

Three-dimensional correlative multimodal and multiscale imaging is an emerging method for investigating the complex hierarchical structure of biological materials such as bone. This approach synthesizes images acquired across multiple length scales, for the same region of interest, to provide a comprehensive view of the material structure of a sample. Here, we develop a workflow for the structural analysis of human trabecular bone using a femtosecond laser to produce a precise grid to facilitate correlation between imaging modalities and identification of structures of interest, in this case, a single trabecula within a volume of trabecular bone. Through such image registration, high resolution X-ray microscopy imaging revealed fine architectural details, including the cement line and bone cell lacunae of the selected bone unit. The selected bone volume was exposed with a combination of manual polishing and site-specific femtosecond laser ablation and then examined with plasma focused ion beam-scanning electron microscopy. This reliable and versatile correlation approach has the potential to be applied to a variety of biological tissues and traditional engineered materials. The proposed workflow has the enhanced capability for generating highly resolved structural data for a better understanding of the architectural features of a material spanning its macroscopic to nanoscopic levels.
Peroxisome proliferator-activated receptor alpha is essential factor in enhanced macrophage immune function induced by angiotensin converting enzyme
Authors: Bernstein Kenneth 
Published: April 2024

Abstract

An upregulation of angiotensin-converting enzyme (ACE) expression strengthens the immune activity of myeloid lineage cells as a natural functional regulation mechanism in our immunity. ACE10/10 mice, possessing increased ACE expression in macrophages, exhibit enhanced anti-tumor immunity and anti-bactericidal effects compared to those of wild type (WT) mice, while the detailed molecular mechanism has not been elucidated yet. In this report, we demonstrate that peroxisome proliferator-activated receptor alpha (PPARα) is a key molecule in the functional upregulation of macrophages induced by ACE. The expression of PPARα, a transcription factor regulating fatty acid metabolism-associated gene expressions, was upregulated in ACE-overexpressing macrophages. To pinpoint the role of PPARα in the enhanced immune function of ACE-overexpressing macrophages, we established a line with myeloid lineage-selective PPARα depletion employing the Lysozyme 2 (LysM)-Cre system based on ACE 10/10 mice (named A10-PPARα-Cre). Interestingly, A10-PPARα-Cre mice exhibited larger B16-F10-originated tumors than original ACE 10/10 mice. PPARα depletion impaired cytokine production and antigen-presenting activity in ACE-overexpressing macrophages, resulting in reduced tumor antigen-specific CD8+ T cell activity. Additionally, the anti-bactericidal effect was also impaired in A10-PPARα-Cre mice, resulting in similar bacterial colonization to WT mice in Methicillin-Resistant Staphylococcus aureus (MRSA) infection. PPARα depletion downregulated phagocytic activity and bacteria killing in ACE-overexpressing macrophages. Moreover, THP-1-ACE-derived macrophages, as a human model, expressing upregulated PPARα exhibited enhanced cytotoxicity against B16-F10 cells and MRSA killing. These activities were further enhanced by the PPARα agonist, WY 14643, while abolished by the antagonist, GW6471, in THP-1-ACE cells. Thus, PPARα is an indispensable molecule in ACE-dependent functional upregulation of macrophages in both mice and humans.
CT-based Deep Learning for Preoperative Prediction of Pathological Grading of Renal Clear Cell Carcinoma
Authors: Cui Zhenyu , Ma Tao , Liu Kun , Shi Bingye , Yang Wenzeng 
Published: April 2024

Abstract

Objective
To construct a model for preoperative noninvasive prediction of WHO/ISUP grading of renal clear cell carcinoma using deep learning technology combined with four-phase CT images of RCCC, and to evaluate the efficacy of the model.
Methods
CT images, pathological data and general clinical data of 158 patients with renal clear cell carcinoma (RCCC) from January 2019 to June 2021 were collected. Of these 158 patients, 128 were of low grade (WHO/ISUP grade I-II) and 34 were of high grade (WHO/ISUP grade III-IV). The patients recruited were randomly divided into the training set, the validation set and the test set at a ratio of 8:1:1, and CT images were preprocessed first. The ResNet34 network was applied to build a model for predicting WHO/ISUP grading of renal clear cell carcinoma. The validation set data was used for the tuning of model parameters during training, and then the various models built were tested using the test set images; In addition, the accuracy of the test (ACC) and the area under the receiver operating characteristic curve (AUC) were used to evaluate the model performance, and the optimal performing model was screened. Subsequently, the optimal model screened was introduced into the SENet attention mechanism module for model optimization, and the optimized model was retrained and tested; Finally, the ACC and AUC before and after model optimization were compared to further select the optimal performing prediction model.
Results
The models constructed by the ResNet34 network in the corticomedullary, parenchymal and excretory phase images presented preferable prediction validation, with a prediction accuracy greater than 0.8, while those constructed in the parenchymal phase data demonstrated optimal performance, with a prediction accuracy of 0.867, 0.857 for AUC for patients of low grade, and 0.853 for AUC for patients of high grade. After adding the SE attention mechanism, the optimized SE-ResNet34 model was obtained, and the prediction accuracy of the model improved from 0.867 to 0.878, and that of AUC improved from 0.857 to 0.929 for patients of low grade and from 0.853 to 0.927 for patients of high grade.
Conclusion
The SE-Resnet34 model based on parenchymal CT boasts a preferable differentiation of WHO/ISUP grade of clear cell renal carcinoma, providing an effective auxiliary means for noninvasive preoperative prediction of pathological grading of renal clear cell carcinoma in clinical practice.
Unlocking Trade Potential: Ethiopia’s Strategic Engagement with BRICS+ Nations
Authors: Malik Ishfaq Ahmad , Khadir Mohaideen Abdul 
Published: April 2024

Abstract

The BRICS countries, renowned for their substantial contributions to global trade, have broadened their influence by welcoming new members, including Iran, Ethiopia, Egypt, and the UAE. This study aims to empirically analyze Ethiopia's trade in goods with both BRICS and the newly admitted members, now collectively referred to as BRICS+. The Trade Complementarity Index (TCI) is computed to assess Ethiopia's export and import complementarity with BRICS + countries during the period from 2018 to 2022. Furthermore, the study utilizes the augmented gravity model of trade to identify the factors driving trade flows between Ethiopia and BRICS+. The TCI findings indicate that Ethiopia's export complementarity with BRICS + remains below 13, while import complementarity consistently exceeds 40, suggesting limited export opportunities but significant import potential. Moreover, the augmented gravity model results for total trade, exports, and imports reveal that most variables exhibit the expected sign and are statistically significant. The findings suggest that, among other variables, the GDPs of trading countries and population size can explain total trade, exports, and imports. Additionally, factors such as distance and inflation rates play crucial roles. Identifying these trade determinants can assist Ethiopia in enhancing bilateral trade flows with BRICS + members.
The effects of coagulation factors on the risk of glioma: a two-sample bi-directional Mendelian randomization study
Authors: Pan Lin , Yang Laiyu , Gao Yu , Wang Ningxin , Wang Jingning , Gao Ming , Wang Yihan , Sun Dongmei 
Published: April 2024

Abstract

Background
Traditional observational studies have shown that the levels of coagulation factors can affect the risk of glioma. It is uncertain, nevertheless, whether coagulation factor levels and various glioma subtypes are causally related. The purpose of this study was to look into any bidirectional correlations between glioma risk and coagulation factor levels.
Method
Two-sample bi-directional Mendelian randomization (MR) analysis was carried out using openly accessible genome-wide association study (GWAS) data. The data for glioma subtypes were retrieved from an enormous-scale genetic meta-analysis compiled by GWAS data from independent European lineages of glioma, including 12,488 cases and 18,169 controls. The genetic summary data for 10 coagulation factors were retrieved from different GWAS results conducted in participants of European ancestry (up to 21758 participants), involving prothrombin time (PT), activated protein C(APC), von Willebrand factor (VWF), plasmin, a disintegrin-like and metalloproteinase with thrombospondin motifs 13 (ADAMTS13), factor VII (FVII), factor VIII (FVIII), factor X (FVX), plasminogen activator inhibitor-1 (PAI-1), and thrombomodulin (TM). Weighted median estimation (WME), MR-Egger regression, and inverse variance weighting (IVW) were the MR analysis approaches that were applied. IVW was selected as the main research method. Furthermore, the Benjamini-Hochberg false discovery rate (FDR) correction and sensitivity analyses were carried out.
Results
We discovered a potential relationship between genetically predicted FVII levels and a higher risk of glioblastoma (GBM) (OR = 1.07, 95% CI: 1.01–1.14, P = 0.03). Our results also suggested that genetically predicted plasma PAI-1 level was negatively associated with the incidence of all glioma (OR = 0.85, 95%CI: 0.73–0.98, P = 0.03) and non-GBM (OR = 0.77, 95%CI: 0.63–0.92, P = 0.01). In addition, a suggestively negative correlation between genetically predicted PT level and the risk of GBM (OR = 0.72, 95%CI: 0.53–0.98, P = 0.04) was discovered. Conversely, there was insufficient evidence of a significant causal association of any examined glioma with coagulation factors.
Conclusions
Our findings suggest that coagulation factors may be important indicators for glioma treatment and may be involved in the pathophysiology of gliomas.
Reference Evapotranspiration for Sparse Data and Data Gap Filling in Python: A Study Case at Urucuia River Basin, Brazil
Authors: Corrêa Thomas Rieth , Silva Marcelo José Gama , Scariot Aldicir Osni , Matricardi Eraldo Aparecido Trondoli 
Published: April 2024

Abstract

Despite the several existing initiatives to obtain evapotranspiration data for several scientific analysis, it remains a challenge when dealing with data scarcity, especially when it is coupled with many data gaps of long-time climatological data series. In this study, we developed two Python scripts to perform reference evapotranspiration calculations in data scarcity conditions, filling potential data gaps, and testing them in the Urucuia River watershed.The first script (ETO_calc.py) is able to calculate evapotranspiration both by the Penman-Monteith method, adapting it according to user data availability, and by the Hargreaves-Samani method. The second script (Filling_gaps.py) fills out potential data gaps based on input from neighboring stations and tests the adequacy of the filling. The first script was tested by comparing the data generated by it with the online calculator 'ETCalc', while the second was tested by filling in a station's data from five neighboring stations, comparing the original data with the filled data. The output of the first script was practically identical to the online calculator used for comparison, which confirms the adequacy of the estimation made by ETO_calc.py. As for the second script, the regional weighting method and both linear and multiple regression methods were the methods that best filled in the missing data for the main station. This is due to their better fit to the historical variation of the data compared to the other tested methods. The results allow us to conclude that both scripts proved to be suitable tools for estimating evapotranspiration data.
Doc2TeX: A Novel Approach To Convert Written Documents To LaTeX
Authors: Keshavaprasad Sutejas , Shishir Vrishank , Niranjan Tanmai , Chandra Kavuri Sharad , D Uma 
Published: April 2024

Abstract

Although Handwritten Mathematical Expression Recognition (HMER) tasks are a subset of the Optical Character Recognition (OCR) process, both of them have remained predominantly exclusive to each other. Owing to the widespread increase and progress in Artificial Intelligence and Machine Learning, both fields have benefited greatly, with state-of-the-art architectures being used. This domain is further accentuated by the fact that conversion of math-based handwritten literature to a digital format is extremely time-consuming and is often a manual procedure. HMER in particular, has remained a challenging problem ever since its realization, with several worldwide competitions such as the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) showcasing the fact that progress in this field is extremely slow. This is attributed to the fact that the Mathematical 'language' has an enormous amount of variables and spatial dependencies. To this end, the authors would like to present Doc2Tex, a novel approach in converting handwritten math-based documents to a digital format, with an expression rate (0-error) of up to 64.58%. The proposed approach aims to solve this issue by making use of two aspects: Implementing a model which leverages the Transformer architecture for both image understanding and wordpiece-level text generation (fine-tuned and vanilla), and using a suitable probability indicator to differentiate between mathematical expressions and the English language. The approach put forth in this paper encompasses a wide variety of mathematical symbols and expressions in its vocabulary including complex symbols such as those from calculus and statistical probability domains. The inclusion of a wide variety of complex symbols in the vocabulary has not been done in most of the previous literary works examined by the authors. Metrics of the approach presented in this paper compared to the meta in HMER and OCR tasks have been provided.
Twenty-Seven-Gauge Needle-Assisted Technique for Repositioning of Late Luxated or Subluxated Capsular Bag-Intraocular Lens Complex: Inverted Scleral Tunnel for Flanged Polypropylene Suture Technique
Authors: Doganay Selim , Erdem Duygu , Doganay Derya , Kiristioglu Mehmet Omer 
Published: April 2024

Abstract

Purpose: To describe a minimally invasive and atraumatic technique for managing a polypropylene suture-assisted scleral fixation intraocular lens-capsular bag complex (IOL-CBC) or artificial iris-intraocular lens complex for repositioning late luxated or subluxated intraocular lens-capsular bags and artificial iris-intraocular lens complexes.
Methods: This was a retrospective, single-center and observational study. We evaluated 11 patients, including 10 with capsular bag-lens complex subluxation or luxation into the vitreous cavity and one with an aniridia-intraocular lens complex. The patients were operated on following standard aseptic protocols, including retrobulbar anesthesia, scleral marking, and fixation of IOL-CBC haptics using a novel 6-0 polypropylene suture technique, followed by cauterization and intrascleral burrying with polyglactin sutures.
Results: This study analyzed 11 patients with dislocated or dropped IOL-CBC. The median age of the patients was 67 (44-78) years, with a median follow-up period of 10 (4-16) months. Among them, 8 (72%) were male and 3 (27%) were female. Conjunctival peritomy was performed in 4 (36%) patients, while opening was not required in 7 (63%) patients. Predominantly, preoperative diagnoses indicated 7 (63%) patients with dislocated IOL-CBC, primarily involving three-piece lenses. The IOL-CBCs were centralized in all patients, and optical coherence tomography confirmed accurate suture positioning within the sclera. No suture-related complications were detected throughout the follow-up period. No vision-threatening complications were reported during the postoperative follow-up.
Conclusions: Our technique offers a simple, effective solution for treating decentralized or dislocated IOL-bag complexes, eliminating the need for complex interventions such as large corneal wounds, scleral flaps, IOL exchange, or IOL externalization.
Surface plasmon excitation as a tool to find optimal grating parameters for quantum well infrared photodetectors
Authors: kour Sandeep , Das Sona , Singh Jaget , Gupta Sudipto Das 
Published: April 2024

Abstract

A simple transmission measurement technique in order to find the optimal metallic grating parameters for quantum well infrared photodetectors is presented. The excitation of localized surface plasmons in the metallic gratings results in dips in the transmission and it allows us to find an effective range of operating wavelengths for a particular grating period for utilizing the first order diffracted waves as well as to find an optimal grating period when utilizes the non-propagating plasmonic mode. The enhancement in absorption in the quantum well absorber layer due to the effect of grating is also studied theoretically. This simple transmission measurement technique is believed to be a promising tool for finding optimal grating parameters for the quantum well infrared photodetectors without detector fabrication and low temperature characterization.
Optimizing E-waste management through neutrosophic applications: A comprehensive analysis of factors based on Superiority and Inferiority Ranking (SIR)
Authors: Rajadurai Muthunandhini , Kaliyaperumal Palanivel 
Published: April 2024

Abstract
This study delves into the intricacies of e-waste management control by introducing a novel approach that leverages neutrosophic numbers. Focusing on crucial factors such as environmental impact, resource recovery, social impact, and economic viability, our research employs a superiority and inferiority ranking method enhanced by neutrosophic numbers. This methodology enables a nuanced and flexible evaluation of electronic products, considering the inherent uncertainties and indeterminacies associated with sustainability metrics. By incorporating neutrosophic numbers into the ranking process, the study aims to provide a more robust framework for assessing and prioritizing e-waste management strategies. The outcomes of this research contribute to advancing the understanding of e-waste management by incorporating the inherent uncertainties within a neutrosophic framework. This approach not only enhances the accuracy of ranking electronic products but also facilitates more adaptive and informed decision-making processes in the pursuit of sustainable e-waste management practices. Additionally, we conduct a comparative analysis by evaluating the performances by utilizing various Multi-Criteria Decision-Making (MCDM) methods. Further the comparative assessment aims to elucidate the strengths and limitations of neutrosophic-based ranking in contrast to other established decision-making approaches.