bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remission and low disease activity state prevent hospitalizations in systemic lupus erythematosus patients
Authors: Reátegui-Sokolova C , Rodríguez-Bellido Z , Gamboa-Cárdenas R V , Medina M , Zevallos F , Pimentel-Quiroz V R , Elera-Fitzcarrald C , Cucho-Venegas M , Pastor-Asurza C A , Perich-Campos R , Alarcón G S , Ugarte-Gil M F 
Published: September 2019

Objective The aim of this study was to determine whether remission and low disease activity state protect systemic lupus erythematosus patients from being hospitalized. Materials and methods Patients from the Almenara Lupus Cohort were included. Visits were performed every 6 months. Variables were measured at each visit. Hospitalizations were evaluated in the interval between two visits. Remission was defined as: a SLEDAI-2 K of 0, prednisone ≤5 mg/day and immunosuppressants on maintenance dose; low disease activity state as: a SLEDAI-2 K of ≤4, prednisone ≤7.5 mg/day and immunosuppressants on maintenance dose. Univariable and multivariable interval-censored survival regression models were used. In multivariable analysis, possible confounders were gender, age at diagnosis, socioeconomic status, educational level, disease duration, antimalarial use, the Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage index (SDI) and Charlson comorbidity index. Confounders were determined in the same visit as disease activity state. Results Of the 308 patients, 92.5% of them ( n = 285) were women, had a mean age at diagnosis of 34.8 (13.4) years and a disease duration of 7.7 (6.5) years. At baseline the mean SDI was 1.13 (1.34). A total of 163 of the patients were hospitalized. In the multivariable analysis remission (hazard ratio 0.445 (0.274–0.725), P = 0.001) and low disease activity state (relative risk 0.504 (0.336–0.757), P = 0.001) at baseline were found to decrease the risk of hospitalization in systemic lupus erythematosus patients. A total of 158 hospitalizations presented a discernible cause. Disease activity was the most common cause of hospitalization, with 84 admissions (53.16%), the majority, 38, was due to active kidney disease (45.23%). Conclusion Remission and low disease activity state decreased the risk of hospitalizations in these systemic lupus erythematosus patients. Disease activity, particularly renal, was the most frequent cause of hospitalization.
Understanding lung cancer screening behaviour using path analysis
Authors: Carter-Harris Lisa , Slaven James E , Monahan Patrick O , Draucker Claire Burke , Vode Emilee , Rawl Susan M 
Published: September 2019

Objective Understanding lung cancer screening behaviour is crucial to identifying potentially modifiable factors for future intervention. Qualititative work has explored attitudes and beliefs about lung cancer screening from the perspective of the participant, but the theoretically grounded factors that influence screening-eligible individuals to screen are unknown. We tested an explanatory framework for lung cancer screening participation from the individual’s perspective. Methods Data were collected as part of a sequential explanatory mixed methods study, the quantitative component of which is reported here. A national purposive sample of 515 screening-eligible participants in the United States was recruited using Facebook-targeted advertisement. Participants completed surveys assessing constructs of the Conceptual Model for Lung Cancer Screening Participation. Path analysis was used to assess the relationships between variables. Results Path analyses revealed that a clinician recommendation to screen, higher self-efficacy scores, and lower mistrust scores were directly associated with screening participation (p < 0.05). However, the link between screening behaviour and self-efficacy appeared to be fully mediated by fatalism, lung cancer fear, lung cancer family history, knowledge of lung cancer risk and screening, income, clinician recommendation, and social influence (p < 0.05). Conclusions This study found that medical mistrust, self-efficacy, and clinician recommendation were significant in the decision of whether to screen for lung cancer. These findings offer insight into potentially modifiable targets most appropriate on which to intervene. This understanding is critical to design meaningful clinician- and patient-focused interventions.
Linkages Between Large-scale Infrastructure Development and Conflict Dynamics in East Africa
Authors: Unruh Jon , Pritchard Matthew , Savage Emily , Wade Chris , Nair Priya , Adenwala Ammar , Lee Lowan , Malloy Max , Taner Irmak , Frilander Mads 
Published: September 2019

With the rapid increase in the number of mega-infrastructure projects underway across East Africa, how the social, economic, political and environmental repercussions of these projects intersect with ongoing conflict dynamics is a poorly understood topic. Although recent interest in large-scale land acquisitions has led to a number of detailed investigations into specific projects and trends, there has not yet been a broad, systematic review of how large-scale infrastructure developments in East Africa interact with previous, ongoing and potential conflict in their areas of operation. The objective of this article is to report on an analysis of 26 mega-infrastructure projects across Kenya, Tanzania, Ethiopia and Uganda, with an explicit focus on the common tension points that contribute to security dynamics. The methodology used involved two composite indicators of risk—a conflict risk score and a project impact score. The study found seven common tensions across all projects: in-migration, population displacement and relocation, a negative history of community relations with previous or follow-on developments, land rights, securitisation, environmental degradation and expectations of the local population relative to benefits delivered by the project. The study recommends increased attention on prior assessments that focus on the broader and more interconnected impacts in addition to those confined to the immediate project location, as well as in-depth examination of possible mitigation measures. JEL Classification: O1, O2, Q2, Q3, Q4, R1, R4
The Surgical Risk Preoperative Assessment System: Determining which predictor variables can be automatically obtained from the electronic health record
Authors: Meguid Robert A , Bronsert Michael R , Hammermeister Karl E , Kao David P , Lambert-Kerzner Anne , Sinex Jacob A , Myers Jody M , Henderson William G 
Published: September 2019

Introduction The Surgical Risk Preoperative Assessment System is a parsimonious, universal surgical risk calculator integrated into our local electronic health record. We determined how many of its eight preoperative risk predictor variables could be automatically obtained from the electronic health record. This has implications for the usability and adoption of Surgical Risk Preoperative Assessment System, serving as an example of use of electronic health record data for populating clinical decision support tools. Methods We quantified the availability and accuracy in the electronic health record of the eight Surgical Risk Preoperative Assessment System predictor variables (patient age, American Society of Anesthesiology physical status classification, functional health status, sepsis, work Relative Value Unit, in-/outpatient operation, surgeon specialty, emergency status) at the patient’s preoperative encounter of 5205 patients entered into the American College of Surgeons National Surgical Quality Improvement Program. Accuracy was determined by comparing the electronic health record data to the same patient’s National Surgical Quality Improvement Program data, used as the “gold standard.” Acceptable accuracy was defined as a Kappa statistic or Pearson correlation coefficient ≥0.8 when comparing electronic health record and National Surgical Quality Improvement Program data. Acceptable availability was defined as presence of the variable in the electronic health record at the preoperative encounter ≥95% of the time. Results Of the eight predictor variables, six had acceptable accuracy. Only preoperative sepsis and functional health status had Kappa statistics <0.8. However, only patient age and surgeon specialty were ≥95% available in the electronic health record at the preoperative visit. Conclusions Processes need to be developed to populate more of the Surgical Risk Preoperative Assessment System preoperative predictor variables in the patient’s electronic health record prior to the preoperative visit to lessen the burden on the busy surgeon and encourage more widespread use of Surgical Risk Preoperative Assessment System.
The accessibility of data on environmental risk assessment of pharmaceuticals: Is the marketing authorisation procedure in conflict with the international right of access to environmental information?
Authors: Oelkers Kim , Floeter Carolin 
Published: September 2019

AbstractBackgroundFor a large part of the active pharmaceutical ingredients (APIs) available on the market, there is no or no comprehensive environmental risk assessment (ERA) existent/available. Existing ERAs are, moreover, treated as commercially/industrial confidential information (CCI) and the information content on the ERAs contained in the Public Assessment Reports is very limited. Thus, neither the public can inform itself sufficient nor environmental authorities can use the ERAs to compile environmental quality standards. Environmental information law, on the other hand, requires the general accessibility of environmental information. Against this background, this investigation examines the following questions in conformity with the environmental information law: Which environmental information on pharmaceuticals is generated in the marketing authorisation? Which of the environmental information generated in the marketing authorisation is available to the public? Does the environmental information on pharmaceuticals concern CCI?ResultsAccording to international and European environmental information law, there is in principal a right of access to the ERAs of pharmaceuticals (environmental information according to Art. 2(3)(b) Aarhus Convention), which is ineffective due to product-based data and allegedly conflicting CCI. The practised blanket classification of CCI by the marketing authorisation holders is in conflict with the principle of transparency of environmental information law. In any case, the outcomes of the ERA (in particular the ecotoxicity endpoints) may not be classified as CCI. Furthermore, the publicly accessible information in the format of the Public Assessment Report does not sufficiently reflect the information from ERAs and thus does not fulfil the mandate of active access to information (Art. 5 Aarhus Convention). The conflict between the actual accessibility of environmental information on pharmaceuticals and the requirements of environmental information law could be resolved through an API-based publicly accessible database with the outcomes of the ERAs (including all underlying ecotoxicity endpoints). To fulfil the right of access to environmental information effectively, the database also needs to be extended to “old” APIs for which environmental risk assessments have not yet been carried out. This would be the basis for prioritisation of API and establishing a monograph system.ConclusionThe environmental information law requires an improved accessibility of ERAs that could be achieved through an API-based publicly accessible database.
NfiS, a species-specific regulatory noncoding RNA of Pseudomonas stutzeri, enhances oxidative stress tolerance in Escherichia coli
Authors: Hu Guihua , Hu Tao , Zhan Yuhua , Lu Wei , Lin Min , Huang Yunhong , Yan Yongliang 
Published: September 2019

AbstractNoncoding RNAs (ncRNAs) can finely control the expression of target genes at the posttranscriptional level in prokaryotes. Regulatory small RNAs (sRNAs) designed to control target gene expression for applications in metabolic engineering and synthetic biology have been successfully developed and used. However, the effect on the heterologous expression of species- or strain-specific ncRNAs in other bacterial strains remains poorly understood. In this work, aPseudomonas stutzerispecies-specific regulatory ncRNA, NfiS, which has been shown to play an important role in the response to oxidative stress as well as osmotic stress inP. stutzeriA1501, was cloned and transferred to theEscherichia colistrain Trans10. Recombinant NfiS-expressingE. coli, namely, Trans10-nfiS, exhibited significant enhancement of tolerance to oxidative stress. To map the possible gene regulatory networks mediated by NfiS inE. coliunder oxidative stress, a microarray assay was performed to delineate the transcriptomic differences between Trans10-nfiSand wild-typeE. coliunder H2O2shock treatment conditions. In all, 1184 genes were found to be significantly altered, and these genes were divided into mainly five functional categories: stress response, regulation, metabolism related, transport or membrane protein and unknown function. Our results suggest that theP. stutzerispecies-specific ncRNA NfiS acts as a regulator that integrates adaptation to H2O2with other cellular stress responses and helps protectE. colicells against oxidative damage.
Genomics of rare genetic diseases—experiences from India
Authors:   The GUaRDIAN Consortium, Sivasubbu Sridhar , Scaria Vinod 
Published: September 2019

AbstractHome to a culturally heterogeneous population, India is also a melting pot of genetic diversity. The population architecture characterized by multiple endogamous groups with specific marriage patterns, including the widely prevalent practice of consanguinity, not only makes the Indian population distinct from rest of the world but also provides a unique advantage and niche to understand genetic diseases. Centuries of genetic isolation of population groups have amplified the founder effects, contributing to high prevalence of recessive alleles, which translates into genetic diseases, including rare genetic diseases in India.Rare genetic diseases are becoming a public health concern in India because a large population size of close to a billion people would essentially translate to a huge disease burden for even the rarest of the rare diseases. Genomics-based approaches have been demonstrated to accelerate the diagnosis of rare genetic diseases and reduce the socio-economic burden. The Genomics for Understanding Rare Diseases: India Alliance Network (GUaRDIAN) stands for providing genomic solutions for rare diseases in India. The consortium aims to establish a unique collaborative framework in health care planning, implementation, and delivery in the specific area of rare genetic diseases. It is a nation-wide collaborative research initiative catering to rare diseases across multiple cohorts, with over 240 clinician/scientist collaborators across 70 major medical/research centers. Within the GUaRDIAN framework, clinicians refer rare disease patients, generate whole genome or exome datasets followed by computational analysis of the data for identifying the causal pathogenic variations. The outcomes of GUaRDIAN are being translated as community services through a suitable platform providing low-cost diagnostic assays in India. In addition to GUaRDIAN, several genomic investigations for diseased and healthy population are being undertaken in the country to solve the rare disease dilemma.In summary, rare diseases contribute to a significant disease burden in India. Genomics-based solutions can enable accelerated diagnosis and management of rare diseases. We discuss how a collaborative research initiative such as GUaRDIAN can provide a nation-wide framework to cater to the rare disease community of India.
Protection of lead in an environment containing acetic acid vapour by using adsorbents and their characterization
Authors: Msallamova Sarka , Kouril Milan , Strachotova Kristyna Charlotte , Stoulil Jan , Popova Kateryna , Dvorakova Pavla , Lhotka Miloslav 
Published: September 2019

Abstract
Historical museums and depositories contain collections with a number of lead objects or historical documents with lead seals. Lead is a metal which has good corrosion resistance under atmospheric conditions. On the other hand, lead corrodes in an activity in an environment which contains volatile organic compounds (mainly acetic acid and formic acid). In a depository environment, sources of volatile compounds can be the historical documents themselves, wood, plastics (those made from cellulose acetate), polyvinyl acetate adhesives, varnishes, oil or emulsion paints, etc. The aim of this work was to compare the efficiency of commercial adsorbents (activated carbon, activated alumina, zeolite, and bentonite) in the acetic acid vapours. The lead corrosion rates were determined by using lead resistometric probes. Activated alumina and activated carbon were found to be the most effective adsorbents of acetic acid vapours. On the other hand, the available zeolite had the worst sorption ability compared with the other tested substances.
Geriatric Nutritional Risk Index and Controlling Nutritional Status Score can predict postoperative 180-day mortality in hip fracture surgeries
Authors: Kotera Atsushi 
Published: September 2019

Abstract

Background
The Geriatric Nutritional Risk Index (GNRI) based on serum albumin level and body weight and the Controlling Nutritional Status Score (CONUT) based on serum albumin level, total cholesterol level, and total lymphocyte count were created to evaluate objectively a patient’s nutritional status in 2005. Here we validated the usefulness of the GNRI and the CONUT as a prognostic factor of the 180-day mortality in patients who underwent hip fracture surgeries.
We retrospectively collected data from patients with hip surgeries performed from January 2012 to December 2018. The variables required for the GNRI and the CONUT and the factors presumably associated with postoperative mortality including the patients’ characteristics were collected from the medical charts. Intergroup differences were assessed with the χ2 test with Yates’ correlation for continuity in category variables. The Mann-Whitney U test was used to test for differences in continuous variables. We validated the power of the GNRI and the CONUT values to distinguish patients who died ≤ 180 days post-surgery from those who did not, by calculating the area under the receiver operating characteristic curve (AUC). The correlation between these two models was analyzed by Spearman’s rank correlation (ρ).

Results
We retrospectively examined the cases of 607 patients aged 87 ± 6 (range 70–102) years old. The 180-day mortality rate was 5.4% (n = 33 non-survivors). The GNRI value in the non-survivors was 83 ± 9 (range 66–111), which was significantly lower than that in the survivors at 92 ± 9 (range 64–120). The CONUT value in the non-survivors was 6 ± 3 (range 1–11), which was significantly higher than that in the survivors at 4 ± 2 (range 0–11). The AUC value to predict the 180-day mortality was 0.74 for the GNRI and 0.72 for the CONUT. The ρ value between these two models was 0.61 in the total of 607 patients and was 0.78 in the 33 non-survivors.

Conclusions
Our results suggest that the GNRI and the CONUT are a simple and useful tool to predict the 180-day mortality in patients who have undergone a hip surgery.
Homeostatic activity regulation as a mechanism underlying the effect of brain stimulation
Authors: Chai Zhi , Ma Cungen , Jin Xiaoming 
Published: September 2019

Abstract
Hyperexcitability of the neural network often occurs after brain injuries or degeneration and is a key pathophysiological feature in certain neurological diseases such as epilepsy, neuropathic pain, and tinnitus. Although the standard approach of pharmacological treatments is to directly suppress the hyperexcitability through reducing excitation or enhancing inhibition, different techniques for stimulating brain activity are often used to treat refractory neurological conditions. However, it is unclear why stimulating brain activity would be effective for controlling hyperexcitability. Recent studies suggest that the pathogenesis in these disorders exhibits a transition from an initial activity loss after acute injury or progressive neurodegeneration to subsequent development of hyperexcitability. This process mimics homeostatic activity regulation and may contribute to developing network hyperexcitability that underlies neurological symptoms. This hypothesis also predicts that stimulating brain activity should be effective in reducing hyperexcitability due to homeostatic activity regulation and in relieving symptoms. Here we review current evidence of homeostatic plasticity in the development of hyperexcitability in some neurological diseases and the effects of brain stimulation. The homeostatic plasticity hypothesis may provide new insights into the pathophysiology of neurological diseases and may guide the use of brain stimulation techniques for treating them.
Detection of stretch reflex onset based on empirical mode decomposition and modified sample entropy
Authors: Du Mingjia , Hu Baohua , Xiao Feiyun , Wu Ming , Zhu Zongjun , Wang Yong 
Published: September 2019

Abstract

Background
Accurate spasticity assessment provides an objective evaluation index for the rehabilitation treatment of patients with spasticity, and the key is detecting stretch reflex onset. The surface electromyogram of patients with spasticity is prone to false peaks, and its data length is unstable. These conditions decrease signal differences before and after stretch reflex onset. Therefore, a method for detecting stretch reflex onset based on empirical mode decomposition denoising and modified sample entropy recognition is proposed in this study.

Results
The empirical mode decomposition algorithm is better than the wavelet threshold algorithm in denoising surface electromyogram signal. Without adding Gaussian white noise to the electromyogram signal, the stretch reflex onset recognition rate of the electromyogram signal before and after empirical mode decomposition denoising was increased by 56%. In particular, the recognition rate of stretch reflex onset under the optimal parameter of the modified sample entropy can reach up to 100% and the average recognition rate is 93%.

Conclusions
The empirical mode decomposition algorithm can eliminate the baseline activity of the surface electromyogram signal before stretch reflex onset and effectively remove noise from the signal. The identification of stretch reflex onset using combined empirical mode decomposition and modified sample entropy is better than that via modified sample entropy alone, and stretch reflex onset can be accurately determined.