bluuebunny/crossref_metadata_2025_split huggingface dataset:
Migraine prevalence, clinical characteristics, and health care-seeking practice in a sample of medical students in Egypt
Authors: Oraby Mohammed I. , Soliman Rasha H. , Mahmoud Mustafa A. , Elfar Eman , Abd ElMonem Noha A. 
Published: February 2021

Abstract
Introduction
Migraine is a common disabling primary headache disorder with significant personal and socio-economic impacts. Medical students usually have multiple triggers for migraine, particularly stress and irregular sleep.

Objective
To assess the prevalence, characteristics, and degree of disability of migraine in a sample of Egyptian medical students and to study their health care-seeking practice when having migraine

Patients and methods
A descriptive cross-sectional, questionnaire-based study included 631 undergraduate medical students enrolled in the Faculty of Medicine. Participants’ sociodemographic data, migraine prevalence, characteristic, migraine disability, and health care-seeking practice were evaluated. By using the MIDAS test in the questionnaire, we assessed the impact of migraine headache on the daily activities of the students. The severity of headache was assessed using the visual analog scale (VAS) scores.

Results
Prevalence of migraine in medical students was found to be 17.9% causing moderate disability. Migraine was significantly more prevalent and caused more disability among female students compared to males (p value 0.001 and 0.001). Only 35.4% of the migraineurs had already seen doctors for their migraine, and self-prescription of medications for migraine was practiced by 58.4%. Statistically significant positive correlation was found between migraine frequency, migraine severity, and low academic performance (p value 0.001 and 0.003 respectively).

Conclusion
Migraine is highly prevalent among medical students with predominant female prevalence and has a negative impact on their academic performance and other activities.
Development and validation of a simple and rapid ICP-OES method for quantification of elemental impurities in voriconazole drug substance
Authors: Merusomayajula Kishore V. , Tirukkovalluri Siva Rao , Kommula Rama Srinivas , Chakkirala Sathyendranath Venkata , Vundavilli Jagadeesh Kumar , Kottapalli Pavan Kumar S. R. 
Published: February 2021

Abstract
Background
The aim of the present study was to develop and validate an inductively coupled plasma optical emission spectroscopic (ICP–OES) method for quantification of elemental impurities, i.e., Lead, Palladium, and Zinc, in voriconazole drug substance, and this method was employed for the regular sample analysis of Lead, Palladium, and Zinc in voriconazole drug substance for pharmaceutical use. The method has been validated using RF power of 1150 W, auxiliary gas of 0.5 L/min, and nebulizer flow of 0.4 L/min and plasma view at axial mode for Lead and Palladium and radial mode for Zinc. The wavelength was monitored for Lead, Palladium, and Zinc at 220.3 nm, 340.4 nm, and 213.8 nm respectively.

Results
The method is selective and is capable of detecting desired elemental impurities with regulatory acceptance limits in the presence of other elements. The validation experiments involve the demonstration of system suitability, specificity, LOD and LOQ, linearity, precision, and accuracy experiments. The linearity results obtained ˃ 0.9990 for all three impurities.

Conclusion
The proposed method is simple, sensitive quality control tool for the simultaneous quantitative determination of Lead, Palladium, and Zinc at low levels in voriconazole drug substance.

Graphical abstract
Increased Mortality Risk in Patients With Primary and Secondary Adrenal Insufficiency
Authors: Ngaosuwan Kanchana , Johnston Desmond G , Godsland Ian F , Cox Jeremy , Majeed Azeem , Quint Jennifer K , Oliver Nick , Robinson Stephen 
Published: February 2021

AbstractContextMortality data in patients with adrenal insufficiency are inconsistent, possibly due to temporal and geographical differences between patients and their reference populations.ObjectiveTo compare mortality risk and causes of death in adrenal insufficiency with an individually matched reference population.MethodsA retrospective cohort study was done using a UK general practitioner database (CPRD). A total of 6821 patients with adrenal insufficiency (primary, 2052; secondary, 3948) were compared with 67564 individually-matched controls (primary, 20366; secondary, 39134). Main outcomes were all-cause and cause-specific mortality, and hospital admission from adrenal crisis.ResultsWith follow-up of 40 799 and 406 899 person-years for patients and controls respectively, the hazard ratio (HR [95% CI]) for all-cause mortality was 1.68 [1.58-1.77]. HRs were greater in primary (1.83 [1.66-2.02]) than in secondary (1.52 [1.40-1.64]) disease; primary versus secondary disease (1.16 [1.03-1.30]). The leading cause of death was cardiovascular disease (HR 1.54 [1.32-1.80]), along with malignant neoplasms and respiratory disease. Deaths from infection were also relatively high (HR 4.00 [2.15-7.46]). Adrenal crisis contributed to 10% of all deaths. In the first 2 years following diagnosis, the patients’ mortality rate and hospitalization from adrenal crisis were higher than in later years.ConclusionMortality was increased in adrenal insufficiency, especially primary, even with individual matching and was observed early in the disease course. Cardiovascular disease was the major cause but mortality from infection was also high. Adrenal crisis was a common contributor. Early education for prompt treatment of infections and avoidance of adrenal crisis hold potential to reduce mortality.
A zebrafish forward genetic screen identifies an indispensable threonine residue in the kinase domain of PRKD2
Authors: Giardoglou Panagiota , Bournele Despina , Park Misun , Kanoni Stavroula , Dedoussis George V. , Steinberg Susan F. , Deloukas Panos , Beis Dimitris 
Published: February 2021

ABSTRACT
Protein kinase D2 belongs to a family of evolutionarily conserved enzymes regulating several biological processes. In a forward genetic screen for zebrafish cardiovascular mutants, we identified a mutation in the prkd2 gene. Homozygous mutant embryos develop as wild type up to 36 h post-fertilization and initiate blood flow, but fail to maintain it, resulting in a complete outflow tract stenosis. We identified a mutation in the prkd2 gene that results in a T757A substitution at a conserved residue in the kinase domain activation loop (T714A in human PRKD2) that disrupts catalytic activity and drives this phenotype. Homozygous mutants survive without circulation for several days, allowing us to study the extreme phenotype of no intracardiac flow, in the background of a functional heart. We show dysregulation of atrioventricular and outflow tract markers in the mutants and higher sensitivity to the Calcineurin inhibitor, Cyclosporin A. Finally we identify TBX5 as a potential regulator of PRKD2. Our results implicate PRKD2 catalytic activity in outflow tract development in zebrafish.
This article has an associated First Person interview with the first author of the paper.
Tensins – emerging insights into their domain functions, biological roles and disease relevance
Authors: Liao Yi-Chun , Lo Su Hao 
Published: February 2021

ABSTRACTTensins are a family of focal adhesion proteins consisting of four members in mammals (TNS1, TNS2, TNS3 and TNS4). Their multiple domains and activities contribute to the molecular linkage between the extracellular matrix and cytoskeletal networks, as well as mediating signal transduction pathways, leading to a variety of physiological processes, including cell proliferation, attachment, migration and mechanical sensing in a cell. Tensins are required for maintaining normal tissue structures and functions, especially in the kidney and heart, as well as in muscle regeneration, in animals. This Review discusses our current understanding of the domain functions and biological roles of tensins in cells and mice, as well as highlighting their relevance to human diseases.
A retrospective study of medical emergency management in a Health Center in Greece
Authors: Kampouridou Georgia , Arkouda Amalia , Toylia Georgia , Gerogianni Georgia , Marvaki Christina 
Published: February 2021

Ιntroduction: Primary Health Centers face a plethora of emergencies of different nature and severity and it is necessary a decision -whether or not to refer patients to the nearest hospital for further treatment and investigation- to be made.Aim: The aim of the present study was to investigate the management of emergencies in a HC of regional type near a large urban center.Material and Methods: This was a retrospective study. The data of 400 randomly selected patients admitted to the health center with acute conditions during the years 2017-2018 were recorded.Results: Out of all cases examined, 22% were rated as truly medical emergencies and 44% as not; 34% were classified as urgent; 25.9% of patients had arrived within the first hour of onset of symptoms, while 81.7% had already reached within the first 24 hours. Pain and respiratory diseases were the most common problems. In 15% of cases the patient was ambulance-transported to hospital. The proportion of ambulance referral to the nearest hospital was higher in patients with comorbidities (18.8%) than in those without (14.9%); 76% of cases were treated in accordance with evidence-based practice.Conclusions: Despite the significant progress made in treating patients in the community, it is necessary to improve management of non-emergency cases, as well as to improve the procedures for emergencies management in the HCs.
Prevalence of familial hypercholesterolemia in Attica region, Greece
Authors: Pavlatou Niki , Rovina Nikoletta , Toylia Georgia , Kadda Olga , Marvaki Christina , Kapadochos Theodore , Kolovou Genovefa , Koutsoukou Antonia 
Published: February 2021

Background: Dyslipidemias are one of the major modifiable risk factors for cardiovascular disease. Familial hypercholesterolemia (FH) is the most common genetic metabolic disorder; it is estimated that around 14-34 million people worldwide have FH but only 25% of FH patients have been diagnosed. Aim: The aim of the present study was to explore the prevalence of FH in Attica region, Greece.Methods: Attica region was divided into 8 regional units. A predesigned questionnaire was used to collect demographic and clinical data. Data analysis was performed by using the Statistical Package for the Social Sciences (SPSS), ver. 20.Results: The studied sample consisted of 1578 Greek inhabitants of Attica region. The majority of the sample was women (59.9%). The mean age of the studied participants was 47.1 (±14.9) years. According to Simon Broome criteria, the probability of an FH diagnosis as unlikely is determined in 98.7% of the studied sample, probable in 0.8% of the participants or definite in 0.5% of the participants, based on this data, the prevalence of FH in Attica region, Greece is 1:200. Qualitative factors found to be associated with the onset of the disease were medication (p-value = 0.001) and hypolipidemic therapy (p-value = 0.001). The quantitative factors found to be associated with disease onset were body mass index (p-value = 0.044), and systolic (p-value = 0.001) and diastolic (p-value = 0.007) pressure.Conclusions: Based on our data, the prevalence of FH in Attica region, Greece is 1:200. Early identification of contributing factors in FH development and proper treatment is vital and reduce the risk of premature and severe atherosclerotic disease.
Case Report: Ziprasidone induced neuroleptic malignant syndrome
Authors: Sedhai Yub Raj , Atreya Alok , Phuyal Prabin , Basnyat Soney , Pokhrel Sagar 
Published: February 2021

Neuroleptic malignant syndrome (NMS) is a well-recognized neurologic emergency. It presents with classic features including hyperthermia, autonomic instability, muscle hypertonia, and mental status changes. The syndrome is potentially fatal and is associated with significant morbidity due to complications such as rhabdomyolysis, acute kidney injury, and ventricular arrhythmias due to the trans-cellular electrolyte shift. NMS is conventionally associated with the first-generation antipsychotic agents, however, has been described with the use of atypical and novel antipsychotics including Ziprasidone. A case of NMS with Ziprasidone use at the therapeutic dose is reported here.
Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-Integer Uncertainty Sets
Authors: Borrero Juan S. , Lozano Leonardo 
Published: February 2021

We study a class of sequential defender-attacker optimization problems where the defender’s objective is uncertain and depends on the operations of the attacker, which are represented by a mixed-integer uncertainty set. The defender seeks to hedge against the worst possible data realization, resulting in a robust optimization problem with a mixed-integer uncertainty set, which requires the solution of a challenging mixed-integer problem, which can be seen as a saddle-point problem over a nonconvex domain. We study two exact solution algorithms and present two feature applications for which the uncertainty is naturally modeled as a mixed-integer set. Our computational experiments show that the considered algorithms greatly outperform standard algorithms both in terms of computational time and solution quality. Moreover, our results show that modeling uncertainty with mixed-integer sets, instead of approximating the data using convex sets, results in less conservative solutions, which translates to a lower cost for the defender to protect from uncertainty. Summary of Contribution: We consider a class of defender-attacker problems where the defender has to make operational decisions that depend on uncertain actions from an adversarial attacker. Due to the type of information available to the defender, neither probabilistic modeling, nor robust optimization methods with convex uncertainty sets, are well suited to address the defender’s decision-making problem. Consequently, we frame the defender’s problem as a class of robust optimization problems with a mixed-integer uncertainty sets, and devise two exact algorithms that solve this class of problems. A comprehensive computational study shows that for the considered applications, our algorithms improves the performance of existing robust optimization approaches that can be adapted to solve this class of problems. Moreover, we show how mixed-integer uncertainty sets can reduce the level of over-conservatism that is a known issue of robust optimization approaches.
Bounded Rationality in Strategic Decisions: Undershooting in a Resource Pool-Choice Dilemma
Authors: Hsee Christopher K. , Zeng Ying , Li Xilin , Imas Alex 
Published: February 2021

This research studies a resource pool-choice dilemma, in which a group of resource seekers independently choose between a larger pool containing more resources and a smaller pool containing fewer resources, knowing that the resources in each pool will be divided equally among its choosers, so that the more (fewer) people choose a certain pool, the fewer (more) resources each of them will get. This setting corresponds to many real-world situations, ranging from students choosing majors as a function of job opportunities to entrepreneurs choosing markets as a function of customer bases. Ten studies reveal a systematic undershooting bias: fewer people choose the larger pool relative to both the normative equilibrium benchmark and chance (random choice), thus advantaging those who choose the larger pool and disadvantaging those who choose the smaller pool. We present evidence showing that the undershooting bias is driven by bounded rationality in strategic thinking and discuss the relationship between our paradigm and other coordination games. This paper was accepted by Yuval Rottenstreich, decision analysis.
Virtual exams: has COVID-19 provided the impetus to change assessment methods in medicine?
Authors: Pettit Matthew , Shukla Shivani , Zhang James , Sunil Kumar Karadi Hari , Khanduja Vikas 
Published: February 2021

AimsThe ongoing COVID-19 pandemic has disrupted and delayed medical and surgical examinations where attendance is required in person. Our article aims to outline the validity of online assessment, the range of benefits to both candidate and assessor, and the challenges to its implementation. In addition, we propose pragmatic suggestions for its introduction into medical assessment.MethodsWe reviewed the literature concerning the present status of online medical and surgical assessment to establish the perceived benefits, limitations, and potential problems with this method of assessment.ResultsGlobal experience with online, remote virtual examination has been largely successful with many benefits conferred to the trainee, and both an economic and logistical advantage conferred to the assessor or organization. Advances in online examination software and remote proctoring are overcoming practical caveats including candidate authentication, cheating prevention, cybersecurity, and IT failure.ConclusionVirtual assessment provides benefits to both trainee and assessor in medical and surgical examinations and may also result in cost savings. Virtual assessment is likely to be increasingly used in the post-COVID world and we present recommendations for the continued adoption of virtual examination. It is, however, currently unable to completely replace clinical assessment of trainees. Cite this article: Bone Jt Open 2021;2(2):111–118.
Wi-Fi for Affordable Broadband & 5G in Rural Areas
Authors: Thakur Kishore Kumar , Prasad Ramjee 
Published: February 2021

The importance of Internet in our lives today cannot be overemphasized. So much so that access to Internet has been declared a fundamental right of citizens in several countries such as Finland, Spain, and Greece [1]. In most of the developed countries, high-speed Internet connectivity is enabled through wired communication infrastructure such as Fiber-to-the-Home (FTTH) and Very high bit-rate Digital Subscriber Line (VDSL). Unfortunately, the situation is not particularly encouraging in developing countries due to non-availability of such a pervasive communication infrastructure. The difference in the fiber-deployed-to-population ratio across developed and developing countries further underscores this disparity; while this ratio is 1.2 in USA, it is barely 0.1 in India [2]. Owing to this inadequacy of fiber/DSL availability, cellular access technology has emerged as the primary broadband access mechanism in developing countries.
However, the penetration of cellular network is limited in rural areas as its deployment becomes unviable due to challenges such as low average revenue per user, sparse population density, and intermittent availability of electricity. This situation leaves majority of the rural people unconnected thereby creating a massive rural urban digital divide. The next generation cellular system along with the use of unlicensed Wi-Fi Technology can bridge this divide if we overcome the above-mentioned challenges. However, since the Fifth Generation (5G) cellular technology has focus on requirements such as 10 Gbps data rate, 1 ms latency, and very high speed mobility, the problems of coverage and affordability are likely to persist, further widening the digital divide [3]. This article explains how Wi-Fi is being used for affordable high speed broadband in rural areas. A successfully implemented case study of Jharkhand state is also presented, and it can be adopted as reliable business model for 5G or 5G type services in rural areas [4].
The Green Multi Business Model Innovation Brain
Authors: Lindgren Peter 
Published: February 2021

Advanced Green technologies integrated in Business Models and Green Multi Business Model Innovation processes introduce a new leadership and management agenda of Green Business Models. Fast innovation of sensing, persuasive and virtual Business Modelling that can operate autonomously and dynamically primarily lead by machines. Green Multi Business Model Innovation Brains will soon be the state of the art in Business that want to become Green – but also for businesses that want to do circular and/or sustainable business modelling.
Businesses will build Green Multi Business Model Innovation competence and advanced Green Multi Business Models Innovation Brains capable to innovated and operate Green Business Models to all kinds of Business Model Ecosystems. This will open up to new Green Multi Business Model Innovation potential and create a new generation or archetypes of Business Models, new practice of Multi Business Model Innovation.
The paper is a second articles and extension of a conceptual paper on Multi Business Model Brains. First paper was presented at the BIT Sindri IEEE Conference 2020 conceptualizing on how a Multi Business Model Brain could be constructed and would operate supported by advance sensor technologies, artificial intelligence technologies, deep learning, persuasive technologies, Multi Business Model Innovation pattern analysis and libraries of BM archetypes. In combination they will all be important supporting tools to the Multi Business Model Innovation Brain – but now also to the Green Multi Business Model Innovation Brain. 8 case examples shows how Green Multi Business Model Innovation Brains can work in different contexts – in physical, digital, virtual and combined Business Model ecosystems.
Optimising Indian Railways Infrastructure by AI
Authors: Prasad Chandrika , Jamuar Sudhanshu S. 
Published: February 2021

The pressure on the Indian railway (IR) networks has increased due to higher demand for mobility and growth in India’s population over past several decades. In order to meet the higher demand, IR has put priority in capacity building by increasing the number of coaches per train, running more trains, and building more tracks. Building more tracks or increasing the number of coaches or increasing the number of trains have the potential to solve the problem with high infrastructure cost. Unfortunately, it also comes with added vulnerability in safety in running the system. IR with its investment of over 5,00,000 Cr is presently struggling to make its Operating ratio (expenditure / earning) below 100 %. During the last 166 years of its operation, much technological input has been made on its Infrastructure, Locomotives and Rolling stock but its Train Control practices have remained Conventional – locally controlled and experience-based. The developments in the area of signal processing, communication systems, and artificial intelligence (AI) etc. have great potential for applications in Indian Railway right from ticketing to movement of trains, maintenance etc. The potential of AI has been felt in different applications like predicting delays, preventive maintenance of tracks and rolling stocks, forecasting algorithm for the railway systems. The use of AI in the operation of IR will improve performance by using clever algorithms with efficient software and hardware. This in turn will provide lower latency with information sharing and the use of AI in rail operation will surely improve the efficiency in train operation. This paper highlights the potential contributions of AI in improving the operation of India’s railway system and how the application of recent technological advancement in Information Science and Artificial Intelligence can bring a change in the train operation scenario at a railway station and Control Centre and add to the profitability of Indian Railways.