bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Nightmares of International Medical Students - A Phenomenological Study
Authors: Janjua Jamilah R. , Janjua Riaz S. , Ali Sarah , Al-Eraky Mohamed M. , Khattak Osama , Issrani Rakhi , Iqbal Azhar 
Published: September 2022

Abstract
Background: International medical students face challenges and stress in host countries, yet limited evidence is available on their perceptions of these experiences.
Objectives: This study explored the difficulties faced by international students undergoing medical studies in Pakistan, by portraying their lived experiences.
Methodology: This is a phenomenological study using semi-structured interviews with students in four different colleges of Pakistan. The participants had completed their previous schooling overseas and had families living overseas. The interviews took place face to face or through video calls.
Results: A total of 20 MBBS students were interviewed. The main stressors and difficulties faced by international medical students in Pakistan were related to cultural shock, loneliness and isolation, as well as an inability to cope. Loneliness and cultural shock were experienced by most of the participants, yet its implications were not always that severe. However, coping difficulties were experienced by a lesser number of students, yet it disturbed them to the degree that they had to get psychiatric support, and were even on the verge of dropping out and returning home.
Conclusion: The difficulties and challenges faced by international students who are in Pakistan for their studies, unless addressed, would definitely be discouraging for future generations of students, to follow in their footsteps.
Modification and application of highly active alkaline pectin lyase
Authors: Li Pi-Wu , Ma Jun , Wei Xiao-Feng , Zhang Zi-Yang , Wang Rui-Ming , Xiao Jing , Wang Jun-Qing 
Published: September 2022

Abstract
Alkaline pectate lyase has developmental prospects in the textile, pulp, paper, and food industries. In this study, we selected BacPelA, the pectin lyase with the highest expression activity from Bacillus clausii, modified and expressed in Escherichia coli BL21(DE3). Through fragment replacement, the catalytic activity of the enzyme was significantly improved. The optimum pH and temperature of the modified pectin lyase (PGLA-rep4) were 11.0 and 70℃, respectively. It also exhibited a superior ability to cleave methylated pectin. The enzyme activity of PGLA-rep4, measured at 235 nm with 0.2% apple pectin as the substrate, was 554.0 U/mL, and the specific enzyme activity after purification using a nickel column was 822.9 U/mg. After approximately 20 ns of molecular dynamics simulation, the structure of the pectin lyase PGLA-rep4 tended to be stable. The Root mean square fluctuation (RMSF) values at the key catalytically active site, LYS168, were higher than those of the wildtype PGLA. In addition, PGLA-rep4 was relatively stable in the presence of metal ions. PGLA-rep4 has good enzymatic properties and activities and maintains a high pH and temperature. This study provides a successful strategy for enhancing the catalytic activity of PGLA-rep4, making it the ultimate candidate for degumming and various uses in the pulp, paper, and textile industries.
Mapping and Forecasting the Land Surface Temperature in Response to the Land Use and Land Cover Changes using Machine Learning over the Southernmost Municipal Corporation of Tamil Nadu, India
Authors: J Aran Castro A , K Nijanthan , M Babu Vignesh , A Ganesh Kumar , P Raj Kumar , Antony Justine K , P Suganthan 
Published: September 2022

Abstract
In this decade, global warming and urbanisation have become fundamental problems. Numerous locations have experienced a temperature increase that has negatively affected the ecosystem. Land surface temperature (LST) is a valuable parameter for studying temperature variation because it is closely correlated with land use and land cover (LULC). This study combines Machine Learning, Remote Sensing and Geographic Information System (GIS) techniques to detect the spatial variation of LST and quantify its relationship with LULC in the near past, present and the near future. The Nagercoil Municipal Corporation (The Southernmost Municipal Corporation of Tamil Nadu, India) was chosen as the study area to explore the relationship between LST and LULC. The region is one of the rapidly urbanising areas in Tamil Nadu, India. From 2014 to 2022, three scenes of Landsat 8 OLI and 9 OLI-2 LULC and LST data were extracted. Markov chain analysis (MCA) is adopted in this study to predict the future LULC and LST of the study. Pearson’s correlation method has been adopted and is used in the study to determine the correlation of the LULC and LST. For the years 2014, 2017, and 2022, it was determined that the overall accuracy of the LULC map was 0.87, 0.92, and 0.88, respectively, with the Kappa coefficient of 0.85,0.91, and 0.88. The Kappa coefficient values (above 0.85) indicate that the LULC data produced by the MLC procedure have a high enough accuracy to be useful for analysing LULC and identifying changes. The correlation of LULC and LST is an essential metric for identifying and quantifying the higher temperature areas with urban development. These metrics can be incorporated into advanced UHI detection models and machine learning algorithms for more precise and accurate identification and quantification of Urban Heat Island zones. We propose that urban land use measures and urban land planning be informed by continuous and detailed Remote Sensing and GIS combined with statistical modelling and analysis of LULC and LST. Possible actions by the policymakers include the conservation of agricultural and vegetated lands, as well as the management of the reclamation of barren lands into croplands, to prevent surface impermeability loss and ecosystem fragmentation. Protecting the existing waterbodies is also advised in the study.
Amine-Functionalized Lignin as an Eco-Friendly Antioxidant for Rubber Compounds
Authors: Chung June-Young , Hwang Uiseok , Kim Junyoung , Kim Na-Yeon , Nam Jeonghyeon , Jung Jinho , Kim Sung-Hoon , Cho Jung Keun , Lee Bumhee , Park In-Kyung , Suhr Jonghwan , Nam Jae-Do 
Published: September 2022

Abstract
Although the typical antioxidant, N-(1,3-dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD), ensures high durability and long lifespan for rubber compounds, it generates a highly toxic quinone in water, causing a serious environmental pollution. Herein, as an alternative material of 6PPD, we newly introduce eco-friendly amine-functionalized lignin (AL) to be incorporated in rubber, which can provide excellent combinatorial anti-aging properties of thermal stability and ozone/fatigue resistances through radical scavenging effect. The heterolytic ring-opening reaction of AL and sulfur can accelerate curing and improve crosslink density by 28% (v, 4.107 × 10−4 mol/cm3), consequently reducing ozone vulnerable areas of the matrix, and further improving aging resistance. Notably, AL allows its rubber compound to exhibit superior anti-ozone performance after ozone aging, with the arithmetic surface roughness (Sa) of 2.077 μm, which should be compared to that of 6PPD (4.737 μm). The developed chemically modified lignin and the methodology have enormous potential as a promising additive for the future eco-friendly rubber compounds.
A novel prognostic model based on pyroptosis-related genes for multiple myeloma
Authors: Zhang Cuiling , Wu Sungui , Chen Bing 
Published: September 2022

Abstract

Background:Multiple myeloma (MM) is an incurable, relapse-prone disease with apparent prognostic heterogeneity. At present, the risk stratification of myeloma is still incomplete. Pyroptosis, a type of programmed cell death, has been shown to regulate tumor growth, and may have potential prognostic value. However, the role of pyroptosis-related genes (PRGs) in MM remains undetermined. The aim of this study was to to identify potential prognostic biomarkers and construct a predictive model related to PRGs.Methods:Sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Non-negative matrix factorization (NMF) was performed to identify molecular subtypes screening. LASSO regression was used to screen for prognostic markers. Maxstat package was utilized to calculate the optimal cutoff value for the risk score's ability. Patients were then divided into high/low risk groups depending on the cutoff value, and survival curves were plotted using the Kaplan-Meier (K-M) method. The nomogram and a calibration curve of the multi-factor model was established using the rms package.Results:A total of 33 PRGs were extracted from TCGA database underlying which 4 MM molecular subtypes were defined. Patients in cluster 1 had poorer survival than those in cluster 2 (p= 0.035), and the infiltration degree of many immune cells was the opposite in these two clusters. A total of 9 PRGs were screened out as prognostic markers, and the risk score consisting of which had the best predictive ability of 3-year survival (AUC=0.658). Patients in the high-risk group have worse survival than those in the low-risk group (p＜ 0.0001), consisting of the results verified by GSE2658 dataset. The nomogram constructed by gender, age, ISS stage and risk score had the better prognostic predictive performance with a c-index of 0.721.Conclusions:Our model could enhance the predictive ability of ISS staging and give a reference for clinical decision-making. The new prognostic pyroptosis-related markers in MM screened out by us may facilitate the development of novel risk stratification for MM.Clinical trial registration:Not applicable.
Sinularin stabilizes FOXO3 protein to trigger prostate cancer cell intrinsic apoptosis
Authors: Meng Xiang-yu , Wang Ke-jie , Ye Sha-zhou , Chen Jun-feng , Chen Zhao-yu , Zhang Zuo-yan , Li Yi , Yu Rui , Ma Qi 
Published: September 2022

AbstractBackground Sinularin, a natural product that purified from soft coral, exhibits anti-tumor effects against various human cancers. However, the mechanisms are not well understood. Methods The inhibition of cell viability by Sinularin on human prostate cancer cells were detected by MTS assay. Flow cytometry, selective caspase inhibitors, western blot, mitochondrial membrane potential (MMP, Δψm) analysis and preparation of subcellular fractions were used to detect Sinularin-induced tumor cell intrinsic apoptosis. Immunofluorescence staining analysed FOXO3 protein level and subcellular localization. FOXO3 ubiquitination and protein interction between FOXO3 and 14-3-3 were detected by immunoprecipitation. The specific protein kinase activators (unique specific AKT activator SC79, selective ERK1/2 activator TBHQ) were used to reveal whether Sinularin stabilized and up-regulated FOXO3 via AKT and ERK1/2-mediated FOXO3 phosphorylation. Results Sinularin inhibited the viability of human prostate cancer cells in a dose-dependent manner but did not show significant toxicity against normal prostate epithelial cell RWPE-1. Flow cytometry assay demonstrated that Sinularin induced tumor cell apoptosis. Further investigations revealed that Sinularin exerted anti-tumor activity through intrinsic apoptotic pathway along with up-regulation of pro-apoptotic protein Bax and PUMA, inhibition of anti-apoptotic protein Bcl-2, mitochondrial membrane potential collapses, and release of mitochondrial proteins. Furthermore, we illustrated that Sinularin induced cell apoptosis via up-regulating PUMA through inhibition of FOXO3 degradation by the ubiquitin-proteasome pathway. To explore how Sinularin suppress FOXO3 ubiquitin-proteasome degradation, we tested two important protein kinases AKT and ERK1/2 that regulate FOXO3 stabilization. The results revealed that Sinularin stabilized and up-regulated FOXO3 via inhibition of AKT- and ERK1/2-mediated FOXO3 phosphorylation and subsequent ubiquitin-proteasome degradation. Conclusions Our findings illustrated the potential mechanisms by which Sinularin induced cell apoptosis and Sinularin may be applied as a therapeutic agent for human prostate cancer.
Particles Generated from Degrading Magnesium Implants Induce Bone Resorption
Authors: Sun Yu , Yuan Kai , Lou Jie , Yu Jinlong , Yu Han , Peng Zhaoxiang , Dong Xieping , Hou Peng , Zan Rui , Peng Hongzhou , Kang Xinbao , Wang Wenhui , Song Yang , Zhang Xiaonong 
Published: September 2022

Abstract
Background
Magnesium (Mg) is regarded as “revolutionary orthopedic material” due to its excellent properties. In the frontier of clinical translation of biodegradable Mg, most researchers have found cavities between bone tissue and Mg-based implants which limit the use of Mg. These cavities were regarded to be formed due to H2 gas generated from the rapid degradation of Mg. However, this explanation still lacks direct evidence. In this study, we come up with a new hypothesis aim to explain the cavities formation around the Mg-based implants.
Methods
The slightly soluble degradation particles (DPs) of high purity magnesium (HP-Mg) were prepared by electrochemical method. The effects of DPs on osteoclasts formation, polarization, and osteoclast bone resorption in vitro and in vivo were investigated.
Results
The results revealed that DPs could induce osteoclast formation. The DPs promoted the activation of both NF-κB and MAPK signaling pathways and the expression of osteoclast-specific genes and proteins were upregulated. At the same time, DPs also could accelerate calvarial bone resorption of mice.
Conclusions
These results confirmed that the presence of DPs could induce bone resorption both in vitro and in vivo, discovering a new explanation for cavities around Mg-based implants. This discovery inspires new solutions to solve the cavity problem.
RAGE deficiency ameliorates autoimmune hepatitis involving inhibition of IL-6 production via suppressing protein Arid5a in mice
Authors: Li Xiaoxiao , Hua Shuyao , Fang Dai , Fei Xiaoyuan , Tan Zheng , Zheng Fang , Wang Weimin , Fang Min 
Published: September 2022

Abstract
Activation of T cells and pro-inflammatory cytokines are essential for human autoimmune hepatitis. The receptor for advanced glycation end-product(RAGE) is one of receptors for inflammatory alarm molecule high mobility group box 1 (HMGB1), and is involved in autoimmune hepatitis. However, the molecular mechanism of RAGE in setting of autoimmune hepatitis remains elusive. This study aimed to identify the function and mechanism of RAGE in autoimmune hepatitis. The RAGE deficient mouse was used to investigate the role and underlying mechanisms by which RAGE signaling-driven immune inflammatory response in the ConA-induced experimental hepatitis. We found that the RAGE deficiency protects the mouse from liver inflammatory injury caused by ConA challenge. mRNA expression of VCAM-1, IL-6, TNF-α within the livers is markedly decreased in RAGE-deficient mice compared to wild-type mice. In parallel, RAGE deficiency leads to reduced levels of serum pro-inflammatory cytokines IL-6, TNF-α as compared to wild type control mice. RAGE-deficient mice exhibits increased of hepatic NK cells and decreased CD4+ T cells than those of wild type control mice. Notably, in vivo blockade of IL-6 in wild type mice significantly protected mice from ConA induced hepatic injury. Furthermore, RAGE deficiency impaired IL-6 production is associated with decreased expression of Arid5a in liver tissues, a half-life IL-6 mRNA regulator. RAGE signalling is important in regulating the development of autoimmune hepatitis. Immune modulation of RAGE may represent a novel therapeutic strategy to prevent immune-mediated liver injury.
A Much Stronger Spark - the Basic Analysis about the Process of Lightning
Authors: Chang Yin , Ya-mei Li 
Published: September 2022

Abstract
Based on the ideal plate capacitor model, this article makes some basic analyses about the process of lightning. It describes the voltage, the electric charge and the electric field intensity’s changing process during the lightning. With these analyses, we can greatly improve the energy tensity of our equipment. And we will realize some purpose which we cannot achieve before, such as the nuclear fusion. At last, this article compares it with the laser fusion method.
Photobiological production of high-value pigments via compartmentalized co-cultures using Ca-alginate hydrogels
Authors: Zhao Runyu , Sengupta Annesha , Tan Albern X. , Whelan Ryan , Pinkerton Taylor , Menasalvas Javier , Eng Thomas , Mukhopadhyay Aindrila , Jun Young-Shin , Pakrasi Himadri B. , Tang Yinjie 
Published: September 2022

Abstract
Synechococcus elongatus UTEX 2973 can use light and CO2 to produce sucrose, making them promising candidates to construct cocultures with heterotrophic workhorses. This envisioned process is, however, challenging to implement because of photosynthetic oxidative stress, light shading effect by heterotrophic cells, degradation of light sensitive metabolites, and high cost to separate intracellular products. Here, we demonstrated an effective ecosystem, where the sucrose producing cyanobacterium was freely grown in photo-bioreactors (PBRs), while an engineered heterotrophic workhorse (β-carotene producing Yarrowia lipolytica or indigoidine producing Pseudomonas putida) was encapsulated in calcium-alginate hydrogel beads and then placed inside the PBRs. The compartmentalization by hydrogels prevented growth interference so that the cyanobacterial culture could reach high sucrose concentrations, resulting the production of indigoidine (7.5g/L hydrogel) and β-carotene (1.3g/L hydrogel), respectively (i.e., the titers were 15 ~ 22 folds higher than that in the free cell coculture). Moreover, 13C-metabolic analysis indicated that hydrogels provided a favorable microenvironment so that the flux network of cells inside hydrogel was similar to the free culture. Finally, this novel system allowed the heterotroph- containing hydrogel beads to be easily harvested and dissolved by an EDTA solution for product and cell recovery, while the cyanobacterial culture could be continuously used for growing the next batch of immobilized workhorse heterotrophs.
Thermal hysteresis of mesoscopic phase transitions in fluid metals: from tantalum to aluminum and gold with their critical points and non-mean-field global diagrams
Authors: Rogankov O. V. , Dragan G. S. , Rogankov V. B. 
Published: September 2022

Abstract

The light soft metal – Al-IIIB (MAl = 27 g .mol-1 ) and the heavy soft metal – Au-IB (MAu =197 g .mol -1) were analyzed within the same predictive model of fluctuation–thermodynamics (FT). The similar extrapolative approach was applied for re-establishing of the global phase diagram and non-mean-field criticality of the refractory heavy and rigid tantalum Ta-VA ( MTa =181g .mol-1) earlier. The revealed then correspondence between the onset point of nano-droplets at atmospheric pressure and the point of instability, observable at much higher pressures by the dynamic (IEX) measurements, found its confirmation for the considered metals as well. It may indicate the universality of the mentioned “dew”- point for any elements and compounds. The mesoscopic nanoscaled time- and length- simultaneous consideration matters especially for all metallic vapors at sub-atmospheric pressures ( P<P0 ) and T<Tb . The FT-predicted critical points of Al{TcAl=6518K ; ρcAl=424.5 kg.m-3 ; PcAl=1369 bar; ZcAl=0.1607} and Au{TcAu=8077 K ; ρcAu=3453 kg.m-3 ; PcAu=2135 bar; ZcAu=0.1814} are consistent with the available low-temperature thermostatic and rapid dynamic experimental data.
Effect of feeding frequency on water quality and growth of Litopenaeus vannamei fed extruded and pelleted diets
Authors: Espinoza-Ortega Manuel , Molina-Poveda César , Jover-Cerdá Miguel , Civera-Cerecedo Roberto 
Published: September 2022

Abstract

Feeding strategies have a significant impact on growth and water quality in shrimp farming. Feed management also affects health, survival, and shrimp yields. All these factors contribute to production cost-effectiveness and commercial shrimp industry sustainability. The effect of feeding frequency and two aquafeed cooking processes (extrusion and pelleting) on shrimp performance and water quality parameters were studied under controlled conditions in a 60-day trial with juvenileLitopenaeus vannameifed once (10:00 h); twice (10:00 h, 12:00 h); four (10:00 h, 12:00 h, 15:00 h, 18:00 h); and six (10:00 h, 12:00 h, 15:00 h, 18:00 h, 21:00 h, 24:00 h) times/day. No statistical differences (p > 0.05) in growth rate, survival, nor feed efficiency were observed within pelleted feed treatments at any of the frequencies tested. Growth rate was significantly higher (p < 0.05) with extruded feed when administered once or twice in daylight (10:00–12:00 h). However, at such frequencies, growth was achieved at the cost of water quality and feed conversion ratio. At higher frequencies (six times a day) with extruded diets, the results in water quality suggest a reduction in total ammonia nitrogen and nitrite-nitrogen levels as frequency increased. The outcomes of this study suggest that extruded feed with daylight feeding has the potential to improve growth rate, and an increased frequency could represent a suitable strategy to preserve water quality. This study is the first to show that the extrusion process improves water quality; thus, extruded feeds could reduce effluent pollution impact and improve shrimp farming sustainability.
Covid19 Detection using Chest X-Ray images along with corresponding metadata of the chest X-Ray
Authors: Paul Sourav , Das Ranjita , Khanal Bipal 
Published: September 2022

Abstract

Due to the rapid spread of coronavirus 2019(Covid 19) in the present situation, early detection of covid 19 is very important. As per WHO [1] as of 5:26pm CEST, 5 August 2022, there have been 579,092,623 confirmed cases of COVID-19, including 6,407,556 deaths, reported globally. Lot of works have been reported to investigate covid19 using Deep learning algorithm over chest X-ray(CXR) images but as per our knowledge all have taken image data only as input to classify .In our work we have processed CNN model which can take CXR images along with corresponding the metadata(non imaging data) available with the dataset to classify Covid 19.CNN model based on Resnet 50,Dense net 121,Mobile Net,VGG16,Inception-V3 and custom CNN have been developed to accept the multimodal data,i.e metadata along with CXR image.All the mentioned CNN have been used as feature extractor of CXR image and extracted feature have been fused with the features extracted from metadata and 1 passed through the classifier for final classification.Some state of art Deep learning models have been run to classify the covid 19 on the same data set and compared with our best model .Experiments have been done in two phases.In the 1st phase we used CNN models on CXR image only and in the 2nd phase we ran all modified CNN models over the same CXR images with their matadata.The experimental results shows that the output of 2nd phase out performs the output of 1st phase.After that we compared our best model with other state of art models.Modified custom CNN model provides best results of 99.07 % overall accuracy