bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Multi-omic Characterization of the Physiological Responses to Salt Stress in Scenedesmus obliquus UTEX393
Authors: Calhoun Sara , Kamel Bishoy , Edmundson Scott , Holguin Omar , Mach Phillip , Mckie-Krisberg Zaid , Baumgart Leo , Blaby Ian , Bowen Benjamin , Chen Cindy , Kunde Yuliya , Grimwood Jane , Lipzen Anna , Louie Katherine , Mewalal Ritesh , Gleasner Cheryl , Northen Trent , O'Malley Ronan , Talag Jayson , Gutknecht Andrew , Treen Daniel , Zhang Yu , Glaros Trevor , Polle Juergen , Umen James , Huesemann Michael , Grigoriev Igor , Starkenburg Shawn , Kruse Colin 
Published: June 2023

Abstract
Microalgae are one of the most versatile and promising organisms for biomanufacturing. To expedite research and development, we generated an improved genome assembly and annotation of the highly productive microalga Scenedesmus obliquus UTEX393. We measured the systems level, multi-omic responses during exposure to 15 ppt (high) vs 5 ppt (low/control) salt. Exposure to 15 ppt salt level resulted in a systematic dysregulation of redox balancing components, a reduction in photosynthetic components, and a concomitant increase in lipid accumulation. Using DNA affinity purification sequencing, we identified the regulatory landscape of several transcription factors. Two transcription factors were identified as sharing binding-site homology with Arabidopsis orthologs SPL12 and LHY1 and were experimentally determined to target the promoter regions of genes which encode for enzymes involved in central metabolism. Engineering the redox and metabolic pathways in Scenedesmus obliquus UTEX393 could enhance productivity under higher salt conditions.
SoyDBean: a database for cross-validated SNPs by multiple versions of soybean reference genomes
Authors: Lee Yejin , Woo Dong U , Kang Yang Jae 
Published: June 2023

Abstract
Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of “N” stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand cross-validation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting “SoyDBean” database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/.
Mifepristone followed by misoprostol for induction of second trimester abortion- what are the advantages?
Authors: Sharon Avishalom , Gumin Dina , Stave Danielle 
Published: June 2023

Abstract
Purpose
The aim of the study is to find the optimal protocol for medical second trimester abortion (2TA).
Methods
The study includes patients between gestational ages 13–23 weeks, who underwent 2TA between the years 2015–2018. A hundred and eighteen patients received Mifepristone 600 mg followed by misoprostol 800 mcg (study group), and 60 patients received misoprostol 800 mcg alone (control group).
Results
Success was observed in 80.5% of the study group versus 48.3% in the control group, with significance of p < 0.001. The control group showed much larger usage of other various modalities, a significant higher complication rate (8.3% vs 1.7%) and more decline in haemoglobin levels (11% vs 8%). Multiparous women were more likely to achieve a successful abortion, while each additional pregnancy multiplied the chance by 1.4.
Conclusion
Using mifepristone 600mg followed by misoprostol 800 mcg, significantly raises the success in 2TA, reduces the complication rate and reduces the need for other modalities.
Safe range of femoral neck system insertion and the risk of perforation
Authors: Han Mingxuan , Li Cong , Han Ning , Sun Guixin 
Published: June 2023

Abstract
Background
Internal fixation of the femoral neck carries a risk of perforation due to the presence of the isthmus of the femoral neck. At present, there are few studies on the safe and risk zones of the femoral neck system (FNS) implantation. This study aimed to recommend the safe range of injection of FNS in the lateral wall of the proximal femur, parallel to the axis of the femoral neck, during FNS treatment of femoral neck fracture (FNF).
Methods
Femoral computed tomography (CT) data of 80 patients (male: 40; female: 40) who met the inclusion criteria were collected. Mimics 21.0 software was used to complete the modeling. 3-Matic 13.0 software was used to establish the axis of the femoral neck and its vertical plane, perform the cutting of the femoral neck, and project it on the vertical plane of the femoral neck axis. After matching a rectangle for each projection map, all sample sizes (80 cases) were standardized and superimposed to obtain gradient maps of the safe zone (SZ) and dangerous zone (RZ), thereby securing edge key points and safe FNS insertion range.
Results
In the 80 samples, the mean diameter of the smallest femoral neck section was 33.87 ± 2.32 mm for men and 29.36 ± 1.92 mm for women. All 80 femoral necks had safe and risky areas. The SZ/S × 100% was 77.59 (± 2.22%), and the RS/S ×100% was 22.39% (± 2.22%). The risk area was composed of four parts: (1), (2), (3), and (4), respectively, corresponding to 3.45 ± 1.74%, 5.51 ± 2.63%, 6.22 ± 1.41%, and 7.22 ± 1.39%. Four marginal key points, perforation risk, and safe ranges (SR) of FNS were analyzed on the lateral wall of the femoral neck.
Conclusions
The SR of FNS placement was recommended by digital simulation. In addition, Regions (3) and (4) posed a higher risk of penetrating the cortex. Using the gradient map of RZ for preoperative evaluation is recommended to avoid iatrogenic perforation.
Interaction of ortho -alkenylanilines of allyl and vinyl structure with thionyl chloride
Authors: Latypova Lyaysan , Usmanova Gulsum , Salikhov Shamil , Mustafin Akhat 
Published: June 2023

AbstractDimethyl sulfoxide (DMSO) is one of the most commonly applied organic solvents in many organic reactions. It is known that DMSO/SOCl2is the efficient system for the intramolecular cyclization of 2-alkenylanilines. The interaction ofN-tosyl derivatives of 2-(cyclo)(alken-2-yl)- and 2-(cyclo)(alken-1-yl)anilines with thionyl chloride was studied in the DMSO/SOCl2system. It was established that the structure of the obtained products depends on the structure of the alenyl fragment and the reaction conditions. As a result of these reactions, methylsulfanyl(cyclo)alkyl products, indole, carbazole or oxazepine were formed. The structure of new compounds was confirmed by IR, heteronuclear NMR spectroscopy, high resolution mass spectrometry.
Improving Image Classification of Gastrointestinal Endoscopy Using Curriculum Self-Supervised Learning
Authors: Guo Han , Hosseini Ramtin , Somayajula Sai Ashish , Xie Pengtao 
Published: June 2023

Abstract
Endoscopy, a widely used medical procedure for examining the gastrointestinal (GI) tract to detect potential disorders, poses challenges in manual diagnosis due to non-specific symptoms and difficulties in accessing affected areas. While supervised machine learning models have proven effective in assisting clinical diagnosis of GI disorders, the scarcity of image-label pairs created by medical experts limits their availability. To address these limitations, we propose a curriculum self-supervised learning framework inspired by human curriculum learning. Our approach leverages the HyperKvasir dataset, which comprises 100k unlabeled GI images for pre-training and 10k labeled GI images for fine-tuning. By adopting our proposed method, we achieved an impressive top-1 accuracy of 88.92% and an F1 score of 73.39%. This represents a 2.1% increase over vanilla SimSiam for the top-1 accuracy and a 1.9% increase for the F1 score. The combination of self-supervised learning and a curriculum-based approach demonstrates the efficacy of our framework in advancing the diagnosis of GI disorders. Our study highlights the potential of curriculum self-supervised learning in utilizing unlabeled GI tract images to improve the diagnosis of GI disorders, paving the way for more accurate and efficient diagnosis in GI endoscopy.
Classification of rock facies using deep convolutional neural network
Authors: Soleimani Mohammad Hassan , Riahi Mohammad Ali , Bagheri Majid , Rahimi Mehran 
Published: June 2023

Abstract
Investigating rock facies is very important in the study of hydrocarbon reservoirs. The logs used in this research are related to facies logs from nine wells from the gas reservoir located in Kansas, USA. The rock facies identified in this study are based on a visual examination of a 4,149-foot core from 9 wells. The physical and chemical properties of stones were determined using special tools. The well-log includes five wireline logging curves (GR, resistivity log (RL), photoelectric effect (PE), difference neutron density porosity (DPHI) and average neutron density porosity (PHIA)) and two geological limiting variables (non-marine index - Nautical (NM_M) and relative position (RP)). Our goal in this paper is to develop an effective model based on deep learning for geological facies classification in wells. The classification of facies is done by studying the lithological characteristics of rocks, which are the characteristics of modern sediments accumulated in specific physical and geographical conditions. This study presents a new 1D-CNN model trained on different optimization algorithms. Using normal well-log data is one of the main advantages of the proposed model. The proposed model is compared with the support vector machine model and the nearest neighbor model and shows more accurate results compared to them. This model shows successful results in the study of well log data and therefore it can be suggested as a suitable and effective approach for processing well log data required for lithology.
Dynamic Analysis of Multi-Storey Building for Minimization of Lateral Displacement due to Earthquake using Shear Wall
Authors: Yadav Kushalkumar , Sharma R. L. 
Published: June 2023

Abstract
Shear walls are one of the most commonly used elements in Multi-Storeybuildings to resist the lateral loads due to earthquakes. In this paper, a multistorey building (with and without shear walls) is modeled and analyzed using STAAD-Pro. The prototype models are also tested on a shake table in the structural dynamics lab. The results of STAAD-Pro and Shake tables are compared. The main focus of the study is to investigate the seismic behavior of shear walls in multi-storey buildings and the applicabilty of the STAAD-Pro simulation to multi-storey buildings with shear walls. The modelling was done as per the Indian Standard Code IS 1893:2002, criteria for earthquake resistant design of structures part 1 general provisions and buildings. The materials used for modelling the building conforms to Indian Standard codes IS456:2000 and IS875:1987. The displacements and storey drifts computed using STAAD-Pro and shake table laboratory testing are compared. It has been found that there is complete agreement of the results. It is therefore concluded that the STAAD-Pro analysis can be used to analysed multi-stored buildings.
Exploring the Potential for Bamboo Agroforestry through Value Chain Approach in Thailand, using Cloud-based Data Management on Google Earth Engine
Authors: Amatyakul Wasita , Orozco Sebastian , Bunschoten Raoul 
Published: June 2023

Abstract
The global construction sector consumes almost half of the world's total material production footprint, implying it is the highest single-category material footprint across the global economy. In the search for nature-based alternatives, bamboo grass can become a mainstream building material in the global tropical belt due to significantly shorter rotation times compared to softwood or hardwood species. To determine bamboo potential within a value-chain work frame, the first step is to evaluate the potential land for cultivation. Technically driven soil selection, with optimal climatic conditions, can generate culms taller than 20 m or, on the contrary, culms of a maximum of 6 to 7 m in height. The correct choice of soil also favors the plantation owner since faster plant development will be observed; the plantation will show a higher number of culms, larger diameters, cheaper production, and shorter times until plant maturity, thus requiring less time to recover the initial investment. This research presents a remote-sensing-based tool for surveying and exploring bamboo agroforestry potential over the entire national territory of Thailand based on climatic conditions, altitude, topography, existing land cover, and soil characteristics (texture and acidity). Through the implementation of the research, a total amount of 345,838 km² with viable growth conditions was discovered. 45,968 km² (13.29%) show basic compatibility levels, 242,198 km² (70.03%) show intermediate levels and 57,672 km² (16.68%) present optimal growth conditions. The corresponding regions were located on an interactive geoportal with a 100 m-per-pixel resolution and the ability to benchmark the individual selection criteria.
Glycolysis rate-limiting enzyme PFKP: A pan-cancer predictor for prognostic significant, immunological correlation, and drug sensitivity prediction
Authors: Peng Jian , Li Pingping , Li Yuan , Quan Jichuan , Yao Yanwei , Duan Junfang , Liu Xuemei , Li Hao , Yuan Dajiang , Wang Xiaoru 
Published: June 2023

Abstract
Background
PFKP (phosphofructokinase, platelet), a rate-limiting enzyme of glycolysis, plays a decisive role in various human physio pathological processes. Multiple function of PFKP in different cancer types was reported, including lung cancer, breast cancer et al. However, systematic pan-cancer analysis of PFKP has not been performed now, which could reflect its clinically value about diagnosis, prognosis, drug sensitivity, and immunological correlation.
Methods
Systematic bioinformation analysis of PFKP was performed based on several public datasets including TCGA (The Cancer Genome Atlas), CCLE (Cancer Cell Line Encyclopedia), GTEx (Genotype-Tissue Expression Project), and HPA (Human Protein Atlas). Prospective carcinogenesis of PFKP in pan-cancer was estimated by expression analysis, effect on patients’ prognosis, diagnosis significant evaluation, and immunity regulation estimation. Then, pan-cancer function enrichment of PFKP was also accessed through its effect on signaling score and gene expression profile. Finally, upstream expressing regulation of PFKP was explored by promoter DNA methylation and transcription factors (TFs) prediction.
Results
Our analysis revealed that highly expression of PFKP was found in most cancer types. Meanwhile, high level of PFKP displayed a significant correlation with poor prognosis of patients across pan-cancer. And a fine diagnosis value of PFKP was summarized, especially in its positive correlation with PD-L1 (programmed cell death-Ligand 1). Then, we also found an obvious immunity regulating effect of PFKP in most cancer types. PFKP also had a remarkably negative correlation with several cancer drugs. Finally, ectopic expression of PFKP may depend on DNA methylation and several predicated transcription factors, including KLF (KLF transcription factor) and Sp (Sp transcription factor) family.
Conclusion
This pan-cancer analysis revealed that high expression level of PFKP might be a fine biomarker and predictor in most cancer types. Meanwhile, performance of PFKP across pan-cancer also implied its meaningful role in cancer immunity regulation even in immunotherapy and drug resistance. All in all, PFKP might be explored as an aux monitor for pan-cancer early prognosis and diagnosis.
Triple negative accessory breast cancer occurring concurrently with primary invasive breast carcinoma：a case report
Authors: Chen Ling , Wu Zujian , Guo Chi , Wan Hengjin , Wu Shouguo , Wang Guoping 
Published: June 2023

Abstract
Introduction Accessory breast cancer (ABC) is a very rare malignancy, and triple negative ABC with ipsilateral invasive in situ breast cancer is extremely infrequent. Binary breast tumors are controversial in terms of surgical methods and comprehensive treatment. Case presentation We share the case of a 64-year-old postmenopausal woman who was found to have an underarm mass for 3 months. Ultrasonography (US) and computed tomography (CT) suggested possible breast cancer with axillary lymph node metastasis. The patient underwent left modified radical mastectomy combined with axillary lymph node dissection. The postoperative pathology suggested a binary tumor, and we performed comprehensive treatment. Conclusion We share the treatment of a rare case of triple-negative para-breast cancer complicated with carcinoma in situ of the breast, hoping to have new therapeutic ideas for the treatment of this disease.
CBGA: A deep learning method for power grid communication networks service activity prediction
Authors: Liu Shangdong , Zhou Longfei , Shao Sisi , Zuo Jun , Ji Yimu 
Published: June 2023

Abstract

Power grid communication network service activity (PCNSA) refers to the active degree of access devices in the power grid communication networks that are actively providing services over a specific time period as a gauge of the operation status of power devices and load demand. Accurate monitoring of PCNSA helps optimize power dispatch, ensure supply and demand balance, and guide network planning and management. However, due to the complex nonlinear, multi-scale and multivariate characteristics of the PCNSA data, it is often difficult to capture its intrinsic patterns and dynamic changes through a simple model. To address this problem, this paper proposes a convolutional neural network(CNN), bi-directional gated recurrent unit(BiGRU), and attention mechanism(AM)-based service activity prediction method for power grid communication network, referred to as CBGA. CNN is used to extract the features of time-series data, BiGRU is used to capture the dependencies before and after the extracted data in both forward and backward directions and predict the service activity data of the next hour, and AM is used to capture the influence of feature states and enhance the extraction of important information. In this paper, experiments and comparisons are conducted on three real power grid communication network service datasets, and the experimental results demonstrate that the performance of this method is the best, with the smallest MAE and RMSE and the largest R2_score. In comparison to other models, CBGA model is better suited for the prediction of PCNSA and providing reliable data support for power communication network managers to make decisions .
A new valorization of faba bean waste: Fabrication of a low-cost adsorbent for efficient removal dyes from textile wastewater
Authors: Falil Fatima Zahra Fatima Zahra , ABOURRICHE Abdelrim , abouliatim younes , benhammou abdelaziz , Gourich Bouchaid , Allam Fouad 
Published: June 2023

Abstract
As part of the effort to extract more value from agri-food waste, innovative adsorbents have been prepared from faba bean waste (FB: Vicia Faba L) using a physical activation process at a moderate temperature of 350°C. This process, developed by the authors of the study, yields effective adsorbent materials known as HTFB. Due to the favorable physico-chemical properties of these materials, they are suitable for treating water that is contaminated with two different groups of dyes: anionic (orange G (OG)) and cationic dyes (crystal violet (CV) and methylene blue (MB)). The adsorption was carried out in batch mode to examine the influence of different operating conditions (pH, initial dye concentration, temperature, contact time, etc.) on the percentage of the removal dye. According to the experiment results, the materials developed have demonstrated a remarkable efficiency for the elimination of cationic dyes (66.86% for the crystal violet and 58.20% of the methylene blue) and a limited efficiency for anionic dyes (7.05% of the orange G) at natural pH. Kinetic studies showed that the pseudo-second-order model better described the adsorption of dyes onto the HTFB. Besides, Langmuir isotherm model fit better the equilibrium data of dyes adsorption. The maximum adsorption capacities determined from the Langmuir equation were 43.48, 32.68, and 3.51 mg/g, for CV, MB and OG, respectively.
In Vitro and In vivo approaches to evaluate Uncaria tomentosa bark extract loaded FDOFs on Osteoarthritis models
Authors: Sowjanya J. Naga , rao Raja 
Published: June 2023

Abstract
Osteoarthritis is one the leading health concerns worldwide affecting two third million with no proper treatment ensured to restore the normal function and completely relieving the joint pain. Oral fast dissolving films have promising action and targeted delivery with high drug loading capacity. The present investigation involves the study the invitro and invivo activity of developed Oral fast dissolving films of U. tomentosa bark extract with optimised F5 and F13 formulations. For invitro evaluation a three dimensional OA model was prepared with first passage chrondrocytes grown on trypsin EDTA media in 1: 3 ratio. The OA agarose model was prepared with C20A4 chondrocytes on agarose gel (25 ± 5oC) in phospahate buffer solution. Cultivation of chrondrocytes was done with 1 mL of RPMI-1640 (10% FBS) which was added with 20% (IL-1β) solution on third day of incubation and media was replaced time to time. The incubated cell line with 20,000 cells/well in 96-well plates were treated with 5 µL of 0.5% MTT reagent on fifth day of incubation and absorbance was measured at 570 nm. The effects were studied for 7, 13, 27, 35 days for the study effects of FDOFs on the cell lines were (Control, IL-1β, F5, and F13 treated IL-1β injected types). The chondrocytes in agarose constructs cultured only in media (RPMI-FBS) without IL-1b, served as control. The GAG, HYP and DNA quantitation analyses along with DNA content assay were performed to study the arthritic effect of optimized FDOF’s i.e F5. For invivo studies Monoiodoacetate (MIA) induced arthritis models which is well established to understand weight bearing and response to tactile stimuli though the ongoing procedure is not known. The invivo protocol was performed in seven week old male wistar rats with negative control of MIA and positive control as Celecoxib. The assessment of pain and thickness of the knee were estimated to be indicators of osteoarthritic potential. The study results revealed the F5 formulation has efficacy on the OA models which need a clinical investigation in humans.