bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alternative Thoracic Drainage Strategy Alleviates Perioperative Pain After Lung Wedge Resection: A Randomized Controlled Trial
Authors: Wei Shoucun , Zhang Guangyan , Ma Jue , Nong Lidan , Zhang Jiatao , Zhong Wenzhao , Cui Jianxiu 
Published: January 2021

Abstract
Background: Indwelling thoracic drainage tube is one of the leading causes of postoperative pain after thoracotomy. Currently, limited evidence exists on evaluating the acute and chronic pain resulting from chest tube after video-assisted thoracic surgery (VATS). Herein, we intended to explore an alternative drainage method and its impact on acute and chronic pain after VATS. Methods: For this purpose, ninety-two patients undergoing lung wedge resection were selected and randomly assigned to conventional chest tube (CT) group and venous catheter (VC) group, respectively. Then, the numeric rating scale (NRS) and pain DETECT questionnaire were applied to evaluate the level and characteristics of postoperative pain. Results: Our data showed that the NRS scores of the VC group during hospitalization were significantly lower than those of the CT group 6 hours after surgery, at postoperative day 1, at postoperative day 2, and at the moment of drainage tube removal), respectively. Moreover, the number of postoperative salvage analgesics such as nonsteroidal anti-inflammatory drugs (NSAIDs) used in the VC group and postoperative hospitalization days were notably reduced compared with the CT group. However, no significant difference was observed in terms of NRS pain scores between the two groups of patients during the follow-up for chronic pain at 3 months and 6 months. Conclusion: Taken together, the drainage strategy mentioned in this article is effective in relieving perioperative acute pain and reducing the use of salvage analgesics in selected patients undergoing VATS wedge resection, which is beneficial for the rapid recovery of patients after surgery.Trial registration: ClinicalTrials.gov, NCT03230019. Registered July 23, 2017
Machine Learning Guided Postnatal Gestational Age Assessment Using Newborn Screening Metabolomic Data in South Asia and Sub-Saharan Africa
Authors: Sazawal Sunil , Ryckman Kelli , Das Sayan , Khanam Rasheda , Nisar Imran , Jasper Elizabeth , Dutta Arup , Rahman Sayedur , Mehmood Usma , Bedell Bruce , Deb Saikat , Chowdhury Nabidul , Barkat Amina , Mittal Harshita , Ahmed Salahuddin , Khalid Farah , Raqib Rubhana , Manu Alexander , Yoshida Sachiyo , Ali Said , Baqui Abdullah , Jehan Fyezah , Dhingra Usha , Bahl Rajiv , Ilyas Muhammad , Nizar Ambreen 
Published: January 2021

Abstract
Background: Babies born early and/or small for gestational age in Low- and Middle-income countries (LMIC) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, advocacy, resources allocation and program evaluation and at an individual level for targeted care. Early prenatal ultrasound is not available in these settings, gestational age (GA) is estimated using newborn assessment, LMP recalls and birth weight, which are unreliable. Algorithms in developed settings, using metabolic screen data, provided GA estimates within 1-2 weeks of ultrasound-based GA. We sought to leverage machine learning algorithms to improve accuracy and applicability of this approach to LMIC settings.Methods: This study uses data from AMANHI-ACT prospective pregnancy cohorts in Asia and Africa where early pregnancy ultrasound estimated GA and birth weight are available and metabolite screening data in a subset of 1318 newborn are available. We utilized this opportunity to develop machine learning (ML) algorithms. Random Forest Regressor was used where data was randomly split into model-building and model-testing dataset. Mean absolute error (MAE) and root mean square error (RSME) were used to evaluate performance. Bootstrap procedures were used to estimate confidence intervals (CI) for RMSE and MAE. For pre-term birth identification ROC analysis with bootstrap and exact estimation of CI for area under curve (AUC) were performed.Results: Overall model estimated GA, had MAE of 5.8 days (95%CI 5.6-6.3), which was similar to performance in SGA, MAE 6.3 days (95%CI 5.6-7.0). GA was correctly estimated to within 1 week for 70.9% (95%CI 67.9-73.7). For preterm birth classification, AUC in ROC analysis was 92.6% (95%CI 87.5-96.1; p<0.001). This model performed better than Iowa regression, AUC Difference 2.8% (95%CI 0.9-11.8%; p=0.021).Conclusions: Machine learning algorithms and models applied to metabolomic gestational age dating offer a ladder of opportunity for providing accurate population-level gestational age estimates in LMIC settings. These findings also point to an opportunity for investigation of region-specific models, more focused feasible analyte models, and broad untargeted metabolome investigation.
Selenium-Related Nutritional Status in Patients With Common Variable Immunodeficiency: Association With Oxidative Stress and Atherosclerosis Risk
Authors: Andrade Itana , Suano-Souza Fabíola , Fonseca Fernando , Lago Carolina , Sarni Roseli 
Published: January 2021

Abstract
Background: Common variable immunodeficiency (CVID) is an innate immunity error, possibly associated with recurrent or chronic infections and autoimmune / inflammatory diseases and neoplasms. It is suggested that these conditions lead to persistent immune stimulation and increased oxidative stress. A positive impact on the survival of patients with an inborn errors of immunity was observed with advanced clinical care protocols, thus raising concerns about the risk of developing other associated chronic diseases, such as atherosclerosis. Studies suggest that selenium (Se) is a protective trace element against damage caused by oxidative stress. Thus, it is postulated that adequate consumption reduces the risk of some chronic diseases. Results: The median age of CVID patients was 36.8 years, with a female predominance. Low concentrations of GPx, Se and apo A-1 were observed in the patients, besides the presence of dyslipidemia and higher concentrations of adiponectin, us-CRP, and LDLox. There was no association between the concentrations of Se and GPx and the biomarkers of lipid metabolism involved in atherosclerosis risk, except for a positive association with apo A-1 and HDL. The median of polyunsaturated fat was lower in CVID patients and the intake of zinc and retinol was higher among them when compared to controls. Conclusion: The study showed a higher risk of cardiovascular disease in CVID patients. The presence of low selenium in CVID patients points to the importance of assessing the selenium-related nutritional status in these patients.
Non-Linear Relationship Between High-Density Lipoprotein Cholesterol and Incident of Diabetes Mellitus: A Secondary Retrospective Analysis Based on A Japanese Cohort Study
Authors: Cao Changchun , Hu Haofei , Zheng Xiaodan , Wang xinyu , Wang Yulong , He Yongcheng 
Published: January 2021

Abstract
Background and Objective High-density lipoprotein cholesterol (HDL-C) may be directly involved in glucose metabolism by enhancing insulin sensitivity and insulin secretion. This current study aimed to explore the association between HDL-C and the risk of diabetes mellitus (DM) in Japanese population. Methods This retrospective cohort study was based on a publicly available DRYAD dataset. A total of 15388 study participants from Murakami Memorial Hospital in Japan included all medical records for participants who received medical examinations from 2004 to 2015. The target-independent variable and the dependent variable were HDL-C measured at baseline, and DM incident appeared during follow-up, respectively. Covariates involved in this study included gender, age, ethanol consumption, smoking status, regular exerciser, systolic blood pressures, diastolic blood pressures, body mass index, waist circumference, fatty liver, total cholesterol, triglycerides, hemoglobin A1c, fasting plasma glucose. Cox proportional-hazards regression was used to investigate the association between HDL-C and DM, generalized additive models to identify non-linear relationships.Results After adjusting for gender, age, ethanol consumption, smoking status, regular exerciser, systolic blood pressures, diastolic blood pressures, body mass index, waist circumference, total cholesterol, triglycerides, hemoglobin A1c, fasting plasma glucose, the result showed HDL-C was negatively associated with incident of DM (HR = 0.54, 95%CI (0.35, 0.82)). The results remained robust in a series of sensitive analysis. A non-linear relationship was detected between HDL-C and incident of DM, which had an inflection point of HDL-C was 1.72mmol/L. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 0.36 (0.21, 0.59) and 2.90 (0.96, 8.75). Subgroup analysis showed a stronger association could be found in the population with the ex-smoker and current-smoker. The same trend was also seen in the community with hypertension (P for interaction = 0.010, HR = 1.324). Conclusion: HDL-C is negatively associated with DM risk. The relationship between HDL-C and incident of DM is also non-linear. HDL-C was strongly negatively related to the incident of diabetes when HDL-C is less than 1.72mmol/L.
Caution for liver injury after bariatric surgery: logistic regression of risk factors for early elevation of liver enzymes after surgery
Authors: Zhang Yu , Yang Huawu , Zhan Dafang , Liu Xiaoxiao , Xu Chenxin , Zhang Tongtong , Liu Yanjun 
Published: January 2021

Abstract
The reasons for the influence of bariatric surgery (BS) on the early abnormal increase of liver enzymes and liver injury remain unclear. We found abnormal elevation of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in liver chemistry early after BS. To investigate the risk factors for early elevation of ALT and AST after BS, we performed a regression analysis of 177 patients who underwent BS at our center. Follow-up data before and after BS were collected and divided into two groups according to whether ALT and/or AST increased and exceeded the clinical threshold one month after BS. Logistic regression analysis was used, and independent risk factors were screened. Waist circumference (WC) before BS was an independent risk factor (P < 0.05) for increased ALT and AST after BS, but other factors (P > 0.05), such as sex, type of BS, or body mass index (BMI), were not. The cutoff of WC to predict abnormal elevation of ALT and AST after BS was 117.35 cm (sensitivity, 0.75; specificity, 0.62) and 113.65 cm (sensitivity, 0.88; specificity, 0.48), respectively. WC is an independent risk factor for early liver injury after BS. Long-term liver-related follow-up is necessary.
Identification of Key Methylation Differentially Expressed Genes in Posterior Fossa Ependymoma Based on Epigenomic and Transcriptome Analysis
Authors: Wang Guanyi , Jia Yibin , Ye Yuqing , Kang Enming , Chen Huijun , Wang Jiayou , He Xiaosheng 
Published: January 2021

Abstract
BackgroundPosterior fossa ependymoma (EPN-PF) can be classified into Group A posterior fossa ependymoma(EPN-PFA) and Group B posterior fossa ependymoma (EPN-PFB) according to DNA CpG island methylation profile status and gene expression. EPN-PFA usually occurs in children younger than 5 years and has a poor prognosis. MethodsUsing epigenome and transcriptome microarray data, a multi-component weighted gene co-expression network analysis (WGCNA) was used to systematically identify the hub genes of EPN-PF. We downloaded two microarray datasets (GSE66354 and GSE114523) from the Gene Expression Omnibus (GEO) database. The Limma R package was used to identify differentially expressed genes (DEGs), and ChAMP R was used to analyze the differential methylation genes (DMGs) between EPN-PFA and EPN-PFB. GO and KEGG enrichment analyses were performed using the Metascape database. ResultsGO analysis showed that enriched genes were significantly enriched in the extracellular matrix organization, adaptive immune response, membrane raft, focal adhesion, NF-kappa B pathway, and axon guidance, as suggested by KEGG analysis. Through WGCNA, we found that MEblue had a significant correlation with EPN-PF (R=0.69, P=1 x 10-08) and selected the 180 hub genes in the blue module. By comparing the DEGs, DMGs, and hub genes in the co-expression network, we identified five hypermethylated, lower expressed genes in EPN-PFA (ATP4B, CCDC151, DMKN, SCN4B, and TUBA4B), and three of them were confirmed by IHC. ConclusionssGSEA and GSVA analysis indicated that these five hub genes could lead to poor prognosis by inducing hypoxia, PI3K-Akt-mTOR, and TNFα-NFKB pathways. Further study of these dysmethylated hub genes in EPN-PF and the pathways they participate in may provides new ideas for EPN-PF treatment.
Digitalisation of Energy Systems within the Context of Existing Policy Frameworks: An Assessment of Sustainable Energy Transitions in Africa
Authors: Nwaiwu Fortune 
Published: January 2021

Abstract
BackgroundDigital technologies have unique characteristics for achieving radically disruptive transitions within the energy sector. They provide opportunities for new production and consumption models between micro producers and consumers of electricity within communities in a way that transforms the traditional energy generation and consumption model. The study critically assessed the digitalisation of energy systems in Africa within the context of existing policy frameworks in the quest to achieve sustainable energy transitions in Africa. It investigated how digital technologies such as blockchain, digital platforms and smart grids were adopted and implemented within the energy sector in achieving new energy production and consumption models that are both environmentally sustainable and socially inclusive, this assessment was done within the context of existing policy and regulatory frameworks of the society where the use cases were domiciled. MethodsThe research adopted a qualitative methodological approach which was done in three stages - a document analysis that reviewed relevant literature on the energy sector and policies within the sector for Nigeria and South Africa; the next step involved a comparative case study is conducted to assess the characteristics of how digital technologies was deployed in mediating sustainable energy transitions; finally, the outcomes of the comparative case studies was then situated within the context of existing policies within the countries covered by the study ResultsResults from the research indicate that Africa is still in the early stages of adoption and application of digital technologies such as blockchain and smart grids within the energy sector, the results also showed the disconnect between policy environment and industry efforts in achieving digital technologies mediated sustainable energy transitions in Africa. The current applications as exemplified in the use cases by the three companies covered in this study indicates that Africa's sustainable energy transitions is in a rudimentary or early adoption stage, and they are not currently aided by the policy environments in which such projects are domiciled.ConclusionsThe research provides deep insights into the current state and developments within the energy sector especially in relations to how digital technologies are being adopted and implemented in solving the energy poverty prevalent across sub-Saharan Africa.
Lycopus lucidus Turcz exerts neuroprotective effect against H2O2‑induced neuroinflammation by inhibiting NLRP3 inflammasome activation in cortical neurons
Authors: Kim Hyunseong , Hong Jin Young , Jeon Wan-Jin , Lee Junseon , Baek Seung Ho , Ha In-Hyuk 
Published: January 2021

Abstract
Background

Central nervous system (CNS) injuries are a leading cause of permanent functional impairment in humans. Nerve damage can be aggravated by neuroinflammation mediated by protein complexes known as inflammasomes, such as the NLRP3 inflammasome which is a key mediator of caspase-1 and interleukin-1β (IL-1β) /interleukin-18 (IL-18) activation. Lycopus lucidus Turcz (LLT) is a traditional medicinal herb that exerts therapeutic effects against oxidative stress, inflammation, and angiogenesis; however, it remains unclear whether LLT can directly protect neurons against damage, and the underlying molecular mechanisms are poorly understood.
Methods

We investigated the neuroprotective effect of LLT against hydrogen peroxide (H2O2)-induced neuronal damage in cultured primary rat cortical neurons, as well as the potential underlying mechanisms. Neuronal viability and cell death assays were used to determine the effects of LLT on neuroprotection, while the mode of cell death was confirmed using flow cytometry. Changes in the expression of inflammatory factors involved in activation of the NLRP3 inflammasome were measured using immunocytochemistry (ICC) and confirmed by real-time PCR. And, we analyzed that the effect of LLT on neurotrophic factors secretion and synaptic connectivity using ICC in H2O2-induced neuron at 7 days in vitro.
Results

LLT effectively protected cultured rat cortical neurons from H2O2-induced injury by significantly inhibiting NLRP3 inflammasome activation. In addition, LLT significantly reduced caspase1 activation, which is known to be induced by inflammasome formation, and consequently regulated the secretion of IL-1β/IL-18. We demonstrated that LLT enhances axonal elongation and synaptic connectivity against H2O2-induced injury of rat primary cortical neuron.
Conclusions

Together, these results demonstrate that LLT can directly protect cultured cortical neurons from H2O2-induced neuronal damage by inhibiting NLRP3 inflammasome activation and the secretion of caspase-1 and IL-1β/IL-18. Thus, our study provides new insights into the therapeutic mechanisms of LLT and suggests that the NLRP3 inflammasome could be a promising target for treating neurological diseases.
Prognostic Value of Variations in Serum Biomarkers and Prognostic Scores Values between Admission and Second day in Intensive Care Unit Septic patients
Authors: Rios-Toro Juan Jesus , Guzman Maria Dolores Pola-Gallego de , Guerrero-Marin Maria , Rodríguez-Rubio David , Ruiz-Garcia Maria-Isabel , Aguilar-Alonso Eduardo , Rivera-Fernandez Ricardo 
Published: January 2021

Abstract
Background: To determinate the prognostic value of procalcitonin (PCT) and C-reactive protein (CRP) changes during the first two days of admission to the ICU with sepsis and/or septic shock, and to compare it with changes in Acute Physiology And Chronic Health Evaluation II (APACHE-II) and Sepsis-related Organ Failure Assessment (SOFA) prognostic scores. Methods: Prospective cohort observational study. 50 consecutive patients admitted to a single-center ICU. Results: Aged 67(52-75) years with APACHE-II 19(14-25) and SOFA scores 7(5-11) points on admission, and a recorded 28-day mortality of 42%. There were no significant differences observed between APACHE II, SOFA, PCR nor PCT in the survival versus the non-survival group on the day of admission. APACHE II (p=0,001) and SOFA (p=0,002) between admission and second day raised significantly in no survivors, with no significant changes in CRP and PCT. Mortality was significantly associated with a raise in APACHE-II and SOFA scores between admission and second day (OR:2.13,1.18-3.86) but not with PCT nor CRP changes.Conclusions: Changes in SOFA and APACHE II scores between admission and second day in ICU septic patients are more sensitive mortality predictors than the observed changes in CRP and PCT values.
Model to Predict Cause-specific Mortality in Patients With Olfactory Neuroblastoma: A Competing Risk Analysis
Authors: Liu Lipin , Zhong Qiuzi , Zhao Ting , Chen Dazhi , Xu Yonggang , Li Gaofeng 
Published: January 2021

Abstract
Purpose: The main objective of this study was to evaluate the cumulative incidence of cause-specific mortality and other causes of mortality for patients with olfactory neuroblastoma (ONB). The secondary aim was to model the probability of cause-specific death and build a competing risk nomogram to predict cause-specific mortality for this disease.Methods: Patients with ONB from 1975 to 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. We estimated the cumulative incidence function (CIF) for cause-specific mortality and other causes of mortality, and constructed the Fine and Gray’s proportional subdistribution hazard model, as well as a competing-risk nomogram based on Fine and Gray’s model, to predict the probability of cause-specific mortality for patients with ONB.Results: After data selection, 826 cases were included for analysis. Five-year cumulative incidence of cause-specific mortality was 19.5% and cumulative incidence of other causes of mortality was 11.3%. Predictors of cause-specific mortality for ONB included tumor stage, surgery and chemotherapy. Age was most strongly predictive of other causes of mortality: patients aged >60 years exhibited subdistribution hazard ratios (SHRs) of 1.063 (95% confidence interval [CI], 1.05-1.08; p =0.001). The competing risk nomogram for cause-specific mortality was well-calibrated, and had good discriminative ability (concordance index=0.79).Conclusion: We calculated the CIF of cause-specific mortality and other causes of mortality in patients with the rare malignancy ONB. We also built the first competing risk nomogram to provide useful individualized predictive information for patients with ONB.
Joint Replacement Registries Significantly Reduce Revision Rates
Authors: Okafor Charles Ebuka , Nghiem Son , Vertullo Christopher , Byrnes Joshua 
Published: January 2021

Abstract
BackgroundDespite the rapid establishment of joint replacement registries (JRR), its effect on key outcomes such as revision rates is uncertain. While some countries with JRR have recorded reductions in revision rates, other countries without JRR also have reported similar reductions. This study evaluated the impact of JRR on revision rates across countries while controlling for non-JRR related factors and JRR outcomes transfer (to non-registry countries) that could contribute to reduction in revision rates. MethodsThis assessment was performed by a difference-in-differences statistical approach using a panel regression model. We compared revision rates of non-registry countries to registry countries, and further compared non-registry period revision rates to registry period (of registry countries) revision rates. We controlled for non-JRR related factors and JRR outcomes transfer by the inclusion of a linear trend in the model. Data were collected from 1980 – 2018. Registry data were obtained from JRR databases while non-registry data were obtained from literature search in Medline and Google Scholar. ResultsThe average difference in revision rates between registry countries compared to non-registry countries was not statistically significant for hip (p-value = 0.056) and knee (p-value = 0.501) respectively. The average difference in revision rate in the registry period of registry countries relative to the non-registry periods was statistically significant for hip (p-value < 0.0001) and knee (p-value = 0.004) respectively. The impact of JRR on revision rate reduction as a percentage was 19.23% (95% CI: 10.86 – 31.55%) and 13.07% (95% CI: 3.28 – 31.18%) for hip and knee respectively. ConclusionsJoint replacement registries cause significant reduction in revision rates and its effect on this outcome may be further improved by increasing surgeons’ participation. Establishment of JRR in countries or regions yet to would be a worthwhile decision.