bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Machine Learning Algorithm for the Detection of Paroxysmal Nocturnal Haemoglobinuria (PNH) in UK Primary Care Electronic Health Records
Authors: Worker Amanda , Mahon Hadley , Sams Jack , Boardman-Pretty Freya , Marchini Elena , Dubis Rand , Warren Alan , Stockdale Jez , Kumar Jyothika , Varones Elizabeth , Ollerenshaw Daniel , Grant Calum , Fish Peter , Kelly Richard J 
Published: September 2024

Abstract

Background
Paroxysmal Nocturnal Haemoglobinuria (PNH) is an ultra-rare, acquired disorder that is challenging to diagnose due to varied symptoms, heterogeneous patient presentations, and lack of awareness among healthcare professionals. This leads to frequent misdiagnosis and delays in diagnosis. This study evaluated the feasibility of a machine learning model to identify undiagnosed PNH patients using structured electronic health records.
Methods
The study used data from the Optimum Patient Care Research Database, which contains electronic health records from general practitioner (GP) practices across the United Kingdom. PNH patients were identified by the presence, and control patients by the absence of a PNH diagnosis code in their records. Clinical features (symptoms, diagnoses, healthcare utilisation) from 131 patients in the PNH group and 593,838 patients in the control group, were inputted to a tree-based XGBoost machine learning model to classify patients as either “positive” or “negative” for PNH suspicion. The algorithm was finalised after additional exclusions and inclusions applied. Performance was assessed using positive predictive value (PPV), recall and specificity. As the sample used to develop the algorithm was not representative of the true population prevalence, PPV was additionally adjusted to reflect performance in the wider population.
Results
Of all the patients in the PNH group, 27% were classified as positive (recall). 99.99% of the control group were classified as negative (specificity). Of all the patients classified as positive, 60.4% had a diagnosis of PNH in their record (PPV). The PPV adjusted for the population prevalence of PNH was 19.59 suggesting nearly 1 in 5 patients flagged may warrant further PNH investigation. The key clinical features in the model were aplastic anaemia, pancytopenia, haemolytic anaemia, myelodysplastic syndrome, and Budd-Chiari syndrome.
Conclusion
This is the first study to combine clinical understanding of PNH with machine learning, demonstrating the ability to discriminate between PNH and control patients in retrospective electronic health records. With further investigation and validation, this algorithm could be deployed on live health data, potentially leading to earlier diagnosis for patients who currently experience long diagnostic delays or remain undiagnosed.
Enhancing Cardiovascular Disease Diagnosis through Bioinformatics and Machine Learning
Authors: J Dafni Rose , A Mohanaprakash T , H Jeyamohan , J Jerusalin Carol 
Published: September 2024

Abstract

Bioinformatics is an interdisciplinary field that uses computer and statistical methods to analyze biological data. This article shows how bioinformatics can be used to diagnose cardiovascular disease. Heart disease affects millions worldwide, making it a serious global health concern. Nowadays, cardiovascular disease affects many more individuals than any other major cause on World. Primary diagnosis of heart disease is crucial because it can reduce the risk of fatal complications like heart attacks, strokes, and death. The detection and treatment of cardiac disease could be dramatically improved by applying machine learning, a promising new technology. The current method uses a machine learning technique called FCMIM-SVM (Fast Conditional Mutual Information-Support vector machine) to diagnose cardiac disease. An optimized chi-squared (CS) mechanism is a machine learning algorithm proposed in this paper for diagnosing heart disease. The CS mechanism is mostly utilized for feature selection. The proposed system uses the GNB (Gaussian Naive Bayes) machine learning model to overcome the limitations in the current technique, which requires less time to train the data. The highest accuracy score is attained using GNB's k-fold cross-validation. The proposed CS-GNB mechanism will achieve maximum accuracy when processing the huge dataset in comparison to the FCMIM-SVM method. This research contrasts the relative contributions of several risk factors for cardiovascular disease, such as age, family history, hypertension, cholesterol levels, smoking, diabetes, obesity, and lack of exercise. Heart disease diagnostics has a bright future. Doctors can diagnose cardiac problems earlier and more precisely than ever with emerging technologies like machine learning. Patients will benefit from earlier therapy and better results as a result.
International Labor Migration Decision in Eastern Amhara, Ethiopia.
Authors: Degfachew Tegegn Nigussie , Dilnesaw Melkamu Mada , Massa Malebo Mancha 
Published: September 2024

Abstract

Using a combination of quantitative and qualitative research approaches, the study aimed to analyze the factors influencing decisions about international labor migration in the North Shewa zone, Eastern Amhara, Ethiopia. The data for the analysis came from 384 samples that were selected using a multi-stage sampling technique. The quantitative analysis included multinomial logistic regression models, while the qualitative data came from focused group discussions and key informant interviews. The results of the multinomial logistic regression model indicated that various factors were either positively or negatively affecting decisions about international migration. The factors that affect international migration decisions positively include local ethnic conflicts for illegal migrants, drought, migrant’s network, family size for illegal migrants and age of household head. The factors that affect international migration decisions negatively include alternative income sources, participation in irrigation, access to credit for legal migrants, land quality, education level of migrants and cultivated land size for legal migrants were found the significant factors for migration decisions at a different significant level. As per the research results the researchers recommended that promoting rural entrepreneurship to have alternative income sources, improving the land quality, increasing irrigation use of farmers to mitigate the effect of drought and ceasing the local ethnic conflicts are the possible solutions for the problem of international labor migration in the study area.
Unlocking the Antiparasitic Potential of Apiaceae: The Promise of Geraniol for Scabies Treatment
Authors: Khallaf Iman S. A. , Malak Lourin G. , Bayoumi Soad A. L. , Farag Salwa F. , Sayed Ahmed M. , Mohamed Sara A.A. , Nasr Asmaa A. E. , Ibrahim Radwa Y. , Zahran Eman M. , Bringmann Gerhard , Abdelmohsen Usama Ramadan 
Published: September 2024

Abstract

Sarcoptic mange, also referred to as scabies in humans, is a highly contagious skin condition caused by the burrowing mite Sarcoptes scabiei (Astigmata: Sarcoptinae). This parasitic disease significantly affects livestock production and poses a substantial threat to both animal and human health. The current treatment methods primarily involve synthetic acaricides like permethrin and ivermectin. However, these medications have several limitations, including a lack of ovicidal activity, concerns about toxicity, potential parasite resistance, residues in animal products, and environmental contamination, making them less than ideal. Volatile constituents derived from Apiaceae plants, especially essential oils, present a promising alternative. In this study, we have, first, reviewed all previously (until June 2024) reported volatile constituent from Apiaceae plants. Second, we carried out a comprehensive in silico-based investigations on the collected compounds to suggest a new potential antiparasitic or insecticidal agent derived from Apiaceae volatile oils. Geraniol, among other possible candidates, was found to be a potential acaricidal agent that might be used as a natural safe alternative. Furthermore, it showed a promising inhibitory activity against S. scabiei, both in vitro and in vivo. Geraniol demonstrated acaricidal activity, achieving a 100% mortality rate at high concentrations and significant effectiveness even at a lower concentration of 6.25%. In vivo studies on rabbits confirmed the efficacy of geraniol, showing complete clinical recovery, including the disappearance of scabies lesions and an improved skin health. Histopathological analysis indicated skin regeneration in the geraniol-treated group compared to the control group. These results suggest that geraniol could be a viable natural option for scabies treatment, likely due to its ability to disrupt mite nerve function by targeting acetylcholinesterase (AChE). Further research is necessary to determine the optimal formulation and delivery methods for geraniol-based treatments for scabies.
Evaluating the Environmental Impact of Fertilizers Derived from Various Production Processes and Biomass Sources
Authors: Maffia Angela , Marra Federica , Oliva Mariateresa , Canino Francesco , Mallamaci Carmelo , Muscolo Adele 
Published: September 2024

Abstract

The growing global food demand increased the use of chemical fertilizers, causing environmental issues. This study explores fertilizers from agro-industrial waste materials on the basis of different percentage of food wastes, focusing on their environmental and soil impact, particularly on global warming potential (GWP). The fertilizers investigated include vermicompost (VC, 70% wood sawdust + 30% food wastes); compost 1 (C1, 50% wood sawdust + 50% food wastes); compost 2 (C2, 10% straw + 90% food wastes); sulfur bentonite (SBC, 90% SB + 10% food wastes). Six months post-fertilization, the soil's chemical and biological properties, revealed significant improvements in respect to unfertilized soil (control). A Life Cycle Assessment (LCA) methodology was used to comprehensively evaluate the entire life cycle of these fertilizers, from production and application to their environmental effects. Our findings highlighted the different environmental impact of these fertilizers. Vermicompost demonstrated lower CO2 equivalent emissions during the vermicomposting process, emphasizing its environmental sustainability. It also showed positive effects on soil chemical and biological properties, enhancing soil health and fertility. Despite SBC positively affected soil properties, it was identified as the fertilizer with the greatest environmental impact. Consequently, from a benefit-cost perspective, the ranking of the fertilizers was VC > C2 > C1 > SBC. These findings underscore that it is possible and necessary transitioning towards sustainable fertilizers derived from waste materials to mitigate the environmental degradation associated with the production and use of conventional fertilizers. By adopting circular economy principles and promoting the use of organic fertilizers, the agricultural sector can enhance productivity while adhering to environmental sustainability standards.
Impact of EV Interfacing on Peak-Shelving &amp; Frequency Regulation in a Microgrid
Authors: Shrivastava Sharika , Khalid Saifullah , Nishad D. K. 
Published: September 2024

Abstract

A "vehicle-to-grid system" enables electric vehicles to be charged by the grid and to discharge electricity back into it when required. This paper presents the performance of a microgrid under the condition of interfacing the electric vehicle with a typical microgrid, which consists of solar, wind, and diesel power generation along with residential and industrial loads. In this research, the V2G effect on chopping the peak of load and on the regulation of frequency is observed. Diverse practical situations are considered to find the effect under a wide range of scenarios. The complete Phasor model is modelled and simulated in MATLAB/Simulink. Simulation results show that for a wide range of inputs V2G effectively regulated the grid frequency and reduced the peak of power demand.
Exploring Nutrition and Lifestyle Modifications Among Women Post Bariatric Surgery: A Qualitative Study
Authors: Güney Hilal Doğan , Göbel Pınar 
Published: September 2024

Abstract

Introduction: To better understand the factors that contribute to long-term weight change in women who have undergone bariatric surgery, this qualitative study will focus on eating behavior and examine the impact of patients' social environment, psychological factors, and behavioral patterns.
Method: In this qualitative study, we adopted a phenomenological approach to the exploration of women's experiences of bariatric surgery. We conducted in-depth individual semi-structured interviews to explore their perceptions, feelings, and ideas regarding post-surgical support. The study was conducted between November and December 2023 and included 20 female participants who were over 18 years old, had undergone bariatric surgery at least two years prior, and had experienced a weight gain of at least 10% 2-3 years after their surgery.
Results: Notably, the last recorded BMI was 31.3 kg/m2. The study findings indicate that overfeeding was a common occurrence among the participants, with 60% reporting overeating due to enjoyment and 40% due to necessity. Before the operation, 40% of the participants had a healthy diet, while 60% had a high consumption of unhealthy snacks. 50% of individuals who had an unhealthy diet before the operation adopted healthy nutrition as a lifestyle. Additionally, 70% had a family history of obesity problems, 60% had struggled with weight management since childhood, and 80% had health problems that required obesity-related operations.
Conclusion: The study revealed that all participants experienced positive changes in their lives after surgery. Larger-scale studies are necessary to evaluate post-operative eating behaviors after bariatric surgery.
Laryngeal and pleural ultrasound and elastography (ARFI) in dogs with brachycephalic obstructive airway syndrome
Authors: Rein Ariadne , Facin Andréia Coutinho , Fabris Isabella Almeida , Lima Bruna Bressianini , Gasser Beatriz , Aires Luiz Paulo Nogueira , Uscategui Ricardo Andres Ramirez , Feliciano Marcus Antônio Rossi , Moraes Paola Castro 
Published: September 2024

Abstract

The aim of the present study is to evaluate pleural thickness and stiffness and the laryngeal stiffness in dogs clinically affected by brachycephalic obstructive airway syndrome using B-mode ultrasound and acoustic radiation force impulse elastography. Fifty-two brachycephalic, pugs and French bulldog, clinically classified as brachycephalic obstructive airway syndrome (BOAS) grades 0, I, II and III were included and 15 mesocephalic beagle dogs used as a control group. All animals underwent B-mode ultrasound and subsequent elastography of the pleura and arytenoid cartilage of the larynx. Brachycephalic dogs showed greater pleural thickness over mesocephalic group (p = 0.04). Also showed lower pleural shear wave velocity than the mesocephalic group (p = 0.04), The larynx shear wave velocity was similar between types of skull and BOAS grades (p = 0.80). Measurements of pleural line thickness and pleural stiffness showed moderate capacity for diagnosing brachycephalic syndrome (p = 0.01, cut-off value of > 0.82 mm and p = 0.04, cutoff value 3.29 m/s), with low sensitivity and good specificity. However, shear wave velocity measurements of the larynx were not statistically significant for the diagnosis of brachycephalic syndrome. The results suggest a secondary change to the inspiratory effort, at the tissue level of the pleura in dogs clinically affected by BOAS, which can be identified by B-mode ultrasound and elastography methods, but it was not possible to diagnose changes in the arytenoid cartilage.
Proteomic characterization between males and females with moderate-to-severe psoriasis
Authors: Yang Xin , Cen Chen , Xie Bibo , Hu Lihua , Huang Jia , Shen Ningning , Li Yi , Dong Qiang 
Published: September 2024

Abstract

Men often presented with higher severity of psoriasis than women, but the underlying reasons are still unclear. In this study, we evaluate proteomic differences in psoriatic lesions between men and women with moderate-to-severe psoriasis and explore possible protective and risk proteins using data-independent acquisition mass spectrometry (DIA-MS) and verified by 4D-parallel reaction monitoring (4D-PRM). 416 differentially expressed proteins (DEPs) were identified between two groups. Among them, 94 proteins were upregulated, while 322 were down-regulated. Some DEPs were enriched to pathways associated with psoriasis, such as the IL − 17 signalling pathway, T cell receptor signalling pathway, Th17 cell differentiation, Oxidative phosphorylation, PI3K − Akt signalling pathway, and MAPK signalling pathway; meanwhile, numerous pathways associated with infection. Nine DEPs (KRT36, KRT13, KRT15, SHC1, GNAI1, SRC, HSPA6, HSPA1L, and HSP90AB4P) were involved in the estrogen pathway, which was predicted to be activated in males. Through Ingenuity pathway Analysis (IPA), our data also identified three upstream regulators (TNF, KRAS, TGFB1). 4D-PRM suggested that HMGB2 and PML were upregulated, while LAMTOR3 was downregulated in male group compared to female one. Our study suggests that sex may influence protein changes in psoriasis, pathogenesis and disease severity. Targeting these molecules may improve the severity and therapeutic efficacy of psoriasis.
In-depth evaluation of pyran derivatives for mild steel corrosion protection in 1.0 M HCl: An experimental and theoretical analysis
Authors: karkouri A. El , Dahmani K. , Kharbouch O. , Khattabi M. , hajri F. El , Galai M. , Cherkaoui M. , Chafiq M. , Chaouiki A. , Alharbi S.M. , Boukhris S. 
Published: September 2024

Abstract

The corrosion inhibition properties of two inhibitors, 2-Amino-4-(4-chlorophenyl)-3-cyano-7,7-dimethyl-5-oxo-4H-5,6,7-tetrahydrobenzo[b] pyran (ZE1-4-Cl) and 2-Amino-3-cyano-4-(4-nitrophenyl)-7,7-dimethyl-5-oxo-4H-5,6,7,8-tetrahydrobenzo[b] pyran (ZE2-4- NO2), on mild steel in a 1.0 M HCl solution was evaluated using Tafel polarization and Electrochemical Impedance Spectroscopy (EIS). The inhibitory efficiency increases with decreasing temperature. Additionally, the inhibitory efficiency also increases with increasing inhibitor concentration. Notably, the better inhibitor of the two (ZE2-4- NO2) achieves an efficiency of 93.7% at a temperature of 298 K and an optimal concentration of 10− 3M. The adsorption of both inhibitors on the steel surface was found to follow the Langmuir model, and the polarization study shows that both compounds are adsorbed to the metal surface through chemical bonding (chemisorption) following the Langmuir isotherm. The experimental results reveal that these organic compounds are effective corrosion inhibitors in a 1.0 M HCl solution. SEM and Energy Dispersive X-Ray Analysis (EDS) were employed to confirm the presence of a barrier layer enveloping the mild steel, contributing to surface characterization. Notably, interactions with the iron surface are primarily facilitated by inhibitors possessing electron-accepting properties, as evidenced by DFT results and molecular dynamic (MD) simulations.
Synergistic impacts of plant growth promoting Pseudomonas geniculata TIU16A3 and green-synthesized iron-oxide nanoparticles from Eichhornia crassipes for the amelioration of heavy metal stress in Vigna radiata L.
Authors: Madhogaria Barkha , Banerjee Sangeeta , Chakraborty Sohini , Dhak Prasanta , Kundu Atreyee 
Published: September 2024

Abstract

Plants are often affected by deleterious effects of heavy metals (HM). This HM stress leads to growth and production capacity issues. The most hazardous trace metals in agricultural areas are lead (Pb), cadmium (Cd), and chromium (Cr). It is not only carcinogenic to humans, but also negatively affects plants' phenotypic, biochemical, and genetic properties. Bioremediation can be used to economically remove contamination of heavy metals. The study aims to test the bioremediation potential of biogenic iron oxide nanoparticles (Fe-O-NP) along with Pseudomonas geniculata strain TIU16A3 (accession number OR507186). Plants of Eichhornia crassipes were used to create Fe-O-NP. Individually iron oxide nanoparticles exhibited enhancement of phenotypic traits in Vigna Radiata L. under heavy metal stress. We used four concentrations (10, 20, 40, and 80 mg/L) of Cr, Cd, and Pb for stress conditions. Biogenic nanoparticles and TIU16A3 in combination act synergistically with the increase in the amount of chlorophyll content and growth in distinct phenotypic traits. In plants, under HM stress, levels of antioxidant enzymes were observed to be high including superoxide dismutase, peroxidase, and catalase and H2O2 content and electrolyte leakage, when they were treated with biogenic NPs and TIU16A3 together the antioxidants decreased significantly. TIU16A3 and Fe-O-NP synergistically in the presence of Cd and Cr enhanced the expression of the Aux/IAA gene more than the expression observed in the presence of Fe-O-NP only. Due to the enhancement of intrinsic properties, and ability to remove Cr, and Cd by TIU16A3 when used in combination with Fe-O-NP for bioremediation exhibits promising results.
Hydrogen peroxide foliar spray alleviates chromium toxicity through modulation of antioxidant defence mechanism, photosynthetic machinery and ions regulation in Brassica oleracea L.
Authors: Shehzadi Nimra , Shah Anis Ali , Usman Sheeraz , Ahmed Shakil , Kaleem Muhammad , Shafique Shiffa , Gatasheh Mansour K. 
Published: September 2024

Abstract

The economy of Pakistan largely depends on agriculture. Agriculture lands are facing the challenges of heavy metals contamination. Soil is an important source of nutrients which is continuously polluted with heavy metal due to anthropogenic activities. In this study the effect of hydrogen peroxide in mitigating chromium contamination in cabbage (Brassica oleracea var. capitate) was evaluated. Brassica oleracea var. capitata is a crop that is vulnerable to Cr toxicity. In order to reduce Cr contamination in B. oleracea, this study explored use of hydrogen peroxide (H2O2) as a signalling molecule. Plants were subjected to 100 and 200 µM of Cr stress, and they were either treated with H2O2 (10 mM) or in combination with Cr. Our studies suggested that H2O2 greatly enhanced morphological characters, such as plant growth and development in Cr-stressed environment. Antioxidant activity elevated in response to Cr stress and the use of H2O2 enhanced it further. Biochemical factors, such as enzyme activity, elevated under Cr stress but maintained in response to H2O2 foliar application. Chromium stress reduced physiological parameters like photosynthesis and water use efficiency, but H2O2 treatment upgraded them. With the application of H2O2, inorganic ionic strength and gas exchange parameters showed a significant improvement. According to our research, H2O2 is efficient for reducing Cr stress in B. oleracea as it boosted physiological, antioxidant, and morphological characteristics. This suggests a possible method for promoting crop tolerance to heavy metal stress.