bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic epidemiology approach to estimating birth incidence and current disease prevalence for rhizomelic chondrodysplasia punctata
Authors: Luisman Tarik , Smith Tara , Ritchie Shawn , Malone Karen E. 
Published: July 2021

Abstract
Background
Rhizomelic chondrodysplasia punctata (RCDP) is an inherited ultra-rare disease which results in severely impaired physical and mental development. Mutations in one of five genes involved in plasmalogen biosynthesis have been reported to drive disease pathology. Estimates of disease incidence have been extremely challenging due to the rarity of the disorder, preventing an understanding of the unmet medical need. To address this, we have prepared a disease incidence and prevalence model based on genetic epidemiology approaches to estimate the total number of RCDP patients affected, and their demographic characteristics.

Results
Extraction of allelic frequencies for known and predicted pathogenic variants in PEX7, GNPAT, AGPS, FAR1, PEX5 (limited to the PTS2 domain encoding region) genes, from large-scale human genetic diversity datasets (TopMed and gnomAD) revealed the mutational landscape contributing to the RCDP patient population in the US and Europe. We computed genetic prevalence to derive birth incidence for RCDP and modeled the impact to life expectancy to obtain high confidence estimates of disease prevalence. Our population genetics-based model indicates PEX7 variants are expected to contribute to the majority of RCDP cases in both the US and Europe; closely aligning with clinical reports. Furthermore, this model provides estimates for RCDP subtypes due to mutations in other genes, including exceedingly rare subtypes.

Conclusion
In total, the estimated number of RCDP patients in the US and the five largest European countries (UK, Germany, France, Italy and Spain) is between 516 and 847 patients, all under the age of 35 years old. This model provides a quantitative framework for better understanding the unmet medical need in RCDP, to help guide disease awareness and diagnosis efforts for this specific patient group.
Infectious disease-associated encephalopathies
Authors: Barbosa-Silva Maria C. , Lima Maiara N. , Battaglini Denise , Robba Chiara , Pelosi Paolo , Rocco Patricia R. M. , Maron-Gutierrez Tatiana 
Published: July 2021

AbstractInfectious diseases may affect brain function and cause encephalopathy even when the pathogen does not directly infect the central nervous system, known as infectious disease-associated encephalopathy. The systemic inflammatory process may result in neuroinflammation, with glial cell activation and increased levels of cytokines, reduced neurotrophic factors, blood–brain barrier dysfunction, neurotransmitter metabolism imbalances, and neurotoxicity, and behavioral and cognitive impairments often occur in the late course. Even though infectious disease-associated encephalopathies may cause devastating neurologic and cognitive deficits, the concept of infectious disease-associated encephalopathies is still under-investigated; knowledge of the underlying mechanisms, which may be distinct from those of encephalopathies of non-infectious cause, is still limited. In this review, we focus on the pathophysiology of encephalopathies associated with peripheral (sepsis, malaria, influenza, and COVID-19), emerging therapeutic strategies, and the role of neuroinflammation.
Graphic abstract
Machine learning model for identifying important clinical features for predicting remission in patients with rheumatoid arthritis treated with biologics
Authors: Koo Bon San , Eun Seongho , Shin Kichul , Yoon Hyemin , Hong Chaelin , Kim Do-Hoon , Hong Seokchan , Kim Yong-Gil , Lee Chang-Keun , Yoo Bin , Oh Ji Seon 
Published: July 2021

Abstract
Background
We developed a model to predict remissions in patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs) and to identify important clinical features associated with remission using explainable artificial intelligence (XAI).

Methods
We gathered the follow-up data of 1204 patients treated with bDMARDs (etanercept, adalimumab, golimumab, infliximab, abatacept, and tocilizumab) from the Korean College of Rheumatology Biologics and Targeted Therapy Registry. Remission was predicted at 1-year follow-up using baseline clinical data obtained at the time of enrollment. Machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost) were used for the predictions. The Shapley additive explanation (SHAP) value was used for interpretability of the predictions.

Results
The ranges for accuracy and area under the receiver operating characteristic of the newly developed machine learning model for predicting remission were 52.8–72.9% and 0.511–0.694, respectively. The Shapley plot in XAI showed that the impacts of the variables on predicting remission differed for each bDMARD. The most important features were age for adalimumab, rheumatoid factor for etanercept, erythrocyte sedimentation rate for infliximab and golimumab, disease duration for abatacept, and C-reactive protein for tocilizumab, with mean SHAP values of − 0.250, − 0.234, − 0.514, − 0.227, − 0.804, and 0.135, respectively.

Conclusions
Our proposed machine learning model successfully identified clinical features that were predictive of remission in each of the bDMARDs. This approach may be useful for improving treatment outcomes by identifying clinical information related to remissions in patients with rheumatoid arthritis.
Intra- and intersession reliability and agreement of the Unilateral Seated Shot-Put Test outcome measures in healthy male athletes
Authors: Degot Matthieu , Blache Yoann , Vigne Grégory , Franger Gabriel , Neyton Lionel , Rogowski Isabelle 
Published: July 2021

Abstract
Background
The Unilateral Seated Shot-Put Test (USSPT) consists of pushing an overweight ball as far as possible to assess upper extremity power unilaterally and bilateral symmetry. Literature however reports various body positions and upper limb pushing patterns to perform USSPT, demanding to provide additional guideline to achieve overweight ball push. This study therefore aimed at assessing the reliability and agreement of USSPT outcome measures when pushing an overweight ball in a horizontal direction.

Methods
Twenty-seven healthy male athletes performed two sessions, one week apart, of three unilateral pushes per upper limb using a 3-kg medicine ball, for which the distances were measured. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), minimum detectable change at a 95 % confidence level (MDC95 %) and coefficient of variation (CV) were assessed for the pushing distances based on one, two or three trials per side to produce two outcome measures: the pushing distance per limb and USSPT Limb Symmetry Index (LSI) when dividing pushing distance of the dominant side by that of the non-dominant side.

Results
The most reliable pushing distance per limb was obtained when averaging three pushing distances, normalized by body mass with the exponent 0.35. The mean USSPT LSI was 1.09 ± 0.10 for the first session and 1.08 ± 0.10 for the second session, highlighting good reliability and agreement (ICC = 0.82; SEM = 0.045; MDC95 % = 0.124; CV = 5.02 %).

Conclusions
When the overweight ball is pushed in a horizontal direction, averaging the distances of three trials for both the dominant and non-dominant limbs is advised to provide the most reliable USSPT distance per limb and USSPT LSI.
A case report: anaphylaxis to cefazolin during renal transplant surgery
Authors: Hemati Kaveh , Gierat Shelley , Roll Garrett R. , Barreto Chang Odmara L. 
Published: July 2021

Abstract
Background
While there exist case reports of anaphylaxis occurring during renal transplant surgery, descriptions of continuing transplant surgery post-anaphylaxis have been scarce. Anaphylactic reactions that present solely with hypotension without pulmonary or mucocutaneous signs have yet to be described during renal transplant surgery.

Case presentation
Here we report a case of a 33-year-old female with end-stage renal disease who underwent cadaveric renal transplant. She developed anaphylaxis following the administration of cefazolin. Despite this reaction, the surgery was ultimately completed after patient stabilization, and the patient had excellent graft function postoperatively. The patient had an elevated tryptase at the time of the reaction and postoperative allergy testing revealed a positive intradermal test to cefazolin. Written informed consent was obtained from the patient for all procedures, studies, and publication of this case report.

Conclusions
This is the first case of a successful zero-mismatch cadaveric renal transplant following an anaphylactic reaction to cefazolin. Although anaphylaxis during transplant surgery typically warrants cancellation due to the hemodynamic effects that may lead to graft dysfunction, here we describe a case where surgery was continued following patient stabilization. The decision to proceed with surgery despite an intraoperative emergency along with the management and workup of intraoperative anaphylaxis are described, which can be beneficial for others who are presented with similar scenarios in the future.
DctR contributes to the virulence of avian pathogenic Escherichia coli through regulation of type III secretion system 2 expression
Authors: Zhang Yaodong , Wang Yao , Zhu Hong , Yi Zhengfei , Afayibo Dossêh Jean Apôtre , Tao Chenglin , Li Tao , Tian Mingxing , Qi Jingjing , Ding Chan , Yu Shengqing , Wang Shaohui 
Published: July 2021

AbstractPathogens could precisely alter their gene expression to facilitate their survival and successful infection. The LuxR family transcriptional regulator DctR (also known as YhiF) was shown to participate in the regulation of acid fitness and adhesion of enterohemorrhagic E. coli (EHEC) O157:H7. Avian pathogenic Escherichia coli (APEC) causes significant economic losses to the poultry industries and also potentially threatens human health. However, the effects of DctR on the fitness and virulence of APEC have not been investigated yet. To assess the function of DctR in APEC, the dctR gene mutant and complemented strains were constructed and biologically characterized. Our results show that inactivation of the dctR gene led to decreased biofilm formation, diminished serum resistance, reduced adherence capacity, attenuated colonization and virulence of APEC in ducks. The altered capacities of the mutant strain were restored by genetic complementation. In addition, we found that DctR positively regulates the expression of E. coli type III secretion system 2 (ETT2) core genes in APEC. The expression of the inflammatory cytokines interleukin (IL)-1β and IL-8 were decreased in HD-11 macrophages infected with the mutant strain compared with the wild-type strain. These observations indicate that regulator DctR contributes to the virulence of APEC through regulation of ETT2 expression.
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network
Authors: Chen Yourong , Chen Hao , Han Meng , Liu Banteng , Chen Qiuxia , Ma Zhenghua , Wang Zhangquan 
Published: July 2021

AbstractIn order to improve the revenue of attacking mining pools and miners under block withholding attack, we propose the miner revenue optimization algorithm (MROA) based on Pareto artificial bee colony in blockchain network. MROA establishes the revenue optimization model of each attacking mining pool and revenue optimization model of entire attacking mining pools under block withholding attack with the mathematical formulas such as attacking mining pool selection, effective computing power, mining cost and revenue. Then, MROA solves the model by using the modified artificial bee colony algorithm based on the Pareto method. Namely, the employed bee operations include evaluation value calculation, selection probability calculation, crossover operation, mutation operation and Pareto dominance method, and can update each food source. The onlooker bee operations include confirmation probability calculation, crowding degree calculation, neighborhood crossover operation, neighborhood mutation operation and Pareto dominance method, and can find the optimal food source in multidimensional space with smaller distribution density. The scout bee operations delete the local optimal food source that cannot produce new food sources to ensure the diversity of solutions. The simulation results show that no matter how the number of attacking mining pools and the number of miners change, MROA can find a reasonable miner work plan for each attacking mining pool, which increases minimum revenue, average revenue and the evaluation value of optimal solution, and reduces the spacing value and variance of revenue solution set. MROA outperforms the state of the arts such as ABC, NSGA2 and MOPSO.
Fine-grained load balancing with traffic-aware rerouting in datacenter networks
Authors: Zhang Tao , Lei Yasi , Zhang Qianqiang , Zou Shaojun , Huang Juan , Li Fangmin 
Published: July 2021

AbstractModern datacenters provide a wide variety of application services, which generate a mix of delay-sensitive short flows and throughput-oriented long flows, transmitting in the multi-path datacenter network. Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. To address these inefficiency, we design a fine-grained load balancing scheme, namely TR (Traffic-aware Rerouting), which identifies flow types and executes flexible and traffic-aware rerouting to balance the performances of both short and long flows. Besides, to avoid packet reordering, TR leverages the reverse ACKs to estimate the switch-to-switch delay, thus excluding paths that potentially cause packet reordering. Moreover, TR is only deployed on the switch without any modification on end-hosts. The experimental results of large-scale NS2 simulations show that TR reduces the average and tail flow completion time for short flows by up to 60% and 80%, as well as provides up to 3.02x gain in throughput of long flows compared to the state-of-the-art load balancing schemes.
Metal(loid) speciation and transformation by aerobic methanotrophs
Authors: Karthikeyan Obulisamy Parthiba , Smith Thomas J. , Dandare Shamsudeen Umar , Parwin Kamaludeen Sara , Singh Heetasmin , Loh Hui Xin , Cunningham Mark R , Williams Paul Nicholas , Nichol Tim , Subramanian Avudainayagam , Ramasamy Kumarasamy , Kumaresan Deepak 
Published: July 2021

AbstractManufacturing and resource industries are the key drivers for economic growth with a huge environmental cost (e.g. discharge of industrial effluents and post-mining substrates). Pollutants from waste streams, either organic or inorganic (e.g. heavy metals), are prone to interact with their physical environment that not only affects the ecosystem health but also the livelihood of local communities. Unlike organic pollutants, heavy metals or trace metals (e.g. chromium, mercury) are non-biodegradable, bioaccumulate through food-web interactions and are likely to have a long-term impact on ecosystem health. Microorganisms provide varied ecosystem services including climate regulation, purification of groundwater, rehabilitation of contaminated sites by detoxifying pollutants. Recent studies have highlighted the potential of methanotrophs, a group of bacteria that can use methane as a sole carbon and energy source, to transform toxic metal (loids) such as chromium, mercury and selenium. In this review, we synthesise recent advances in the role of essential metals (e.g. copper) for methanotroph activity, uptake mechanisms alongside their potential to transform toxic heavy metal (loids). Case studies are presented on chromium, selenium and mercury pollution from the tanneries, coal burning and artisanal gold mining, respectively, which are particular problems in the developing economy that we propose may be suitable for remediation by methanotrophs.
Human-derived acellular dermal matrix may be an alternative to autologous grafts in tympanic membrane reconstruction: Systematic review and meta-analysis
Authors: Xu Shan , Sun Xia , Yang Ning , Yan Aihui 
Published: July 2021

Background Human-derived acellular dermal matrix (ADM) has been widely used as an effective alternative to autologous grafts in tympanoplasty. However, evidence of ADM as an alternative to autologous grafts in the repair of tympanic membrane (TM) perforation still lacks adequate empirical evidence. Objectives To determine the clinical safety and efficacy of human-derived ADM as TM graft material for tympanoplasty. Data sources The PubMed, EMBASE, Cochrane Library, EBSCO, Ovid, Scopus, and Web of Science databases and reference lists of the retrieved articles were searched, with no language restriction. Selection criteria All randomized controlled trials and retrospective cohort studies that compared the use of human-derived ADM and autologous grafts in tympanoplasty for TM perforation were included. Data collection and analysis Two review authors independently assessed risk of bias in the included studies and extracted data. The pooled results for continuous data were reported as a mean difference (MD) and 95% confidence intervals (CI). For dichotomous data, odds risk (OR) with 95% CI was used. ChI2 statistic and Galbraith plots were used to assess the heterogeneity. Publication bias was assessed with a funnel plot and Egger's test. Main results Five retrospective cohort studies and four randomized controlled studies with a total of 610 participants were included in the meta-analysis. No significant differences in graft success (OR: 0.71 [0.39, 1.29], p = 0.26), air-bone gap (ABG) reduction (MD: − 0.59 [− 3.81, 1.19], p = 0.51), or complications (OR: 1.23 [0.07, 20.64], p = 0.89) were found between the ADM group and autologous graft group. The use of ADM significantly shortened tympanoplasty surgery time (MD: − 16.14 [− 21.22, − 11.07], p < 0.00001) and reduced postoperative pain (MD: − 2.57 [− 3.57, − 1.58], p < 0.00001) compared with the autologous graft group. Conclusion Human-derived ADM might be an effective alternative to autologous grafts for tympanoplasty. However, some of the studies that were included in the present meta-analysis had rather low methodological quality, and more adequately designed clinical trials should be performed in the future. Graphical abstract
Big data quality framework: a holistic approach to continuous quality management
Authors: Taleb Ikbal , Serhani Mohamed Adel , Bouhaddioui Chafik , Dssouli Rachida 
Published: July 2021

AbstractBig Data is an essential research area for governments, institutions, and private agencies to support their analytics decisions. Big Data refers to all about data, how it is collected, processed, and analyzed to generate value-added data-driven insights and decisions. Degradation in Data Quality may result in unpredictable consequences. In this case, confidence and worthiness in the data and its source are lost. In the Big Data context, data characteristics, such as volume, multi-heterogeneous data sources, and fast data generation, increase the risk of quality degradation and require efficient mechanisms to check data worthiness. However, ensuring Big Data Quality (BDQ) is a very costly and time-consuming process, since excessive computing resources are required. Maintaining Quality through the Big Data lifecycle requires quality profiling and verification before its processing decision. A BDQ Management Framework for enhancing the pre-processing activities while strengthening data control is proposed. The proposed framework uses a new concept called Big Data Quality Profile. This concept captures quality outline, requirements, attributes, dimensions, scores, and rules. Using Big Data profiling and sampling components of the framework, a faster and efficient data quality estimation is initiated before and after an intermediate pre-processing phase. The exploratory profiling component of the framework plays an initial role in quality profiling; it uses a set of predefined quality metrics to evaluate important data quality dimensions. It generates quality rules by applying various pre-processing activities and their related functions. These rules mainly aim at the Data Quality Profile and result in quality scores for the selected quality attributes. The framework implementation and dataflow management across various quality management processes have been discussed, further some ongoing work on framework evaluation and deployment to support quality evaluation decisions conclude the paper.
Accuracy improvements for cold-start recommendation problem using indirect relations in social networks
Authors: Tey Fu Jie , Wu Tin-Yu , Lin Chiao-Ling , Chen Jiann-Liang 
Published: July 2021

AbstractRecent advances in Internet applications have facilitated information spreading and, thanks to a wide variety of mobile devices and the burgeoning 5G networks, users easily and quickly gain access to information. Great amounts of digital information moreover have contributed to the emergence of recommender systems that help to filter information. When the rise of mobile networks has pushed forward the growth of social media networks and users get used to posting whatever they do and wherever they visit on the Web, such quick social media updates already make it difficult for users to find historical data. For this reason, this paper presents a social network-based recommender system. Our purpose is to build a user-centered recommender system to exclude the products that users are disinterested in according to user preferences and their friends' shopping experiences so as to make recommendations effective. Since there might be no corresponding reference value for new products or services, we use indirect relations between friends and “friends’ friends” as well as sentinel friends to improve the recommendation accuracy. The simulation result has proven that our proposed mechanism is efficient in enhancing recommendation accuracy.
Development and comparison of cell-free protein synthesis systems derived from typical bacterial chassis
Authors: Zhang Liyuan , Lin Xiaomei , Wang Ting , Guo Wei , Lu Yuan 
Published: July 2021

AbstractCell-free protein synthesis (CFPS) systems have become an ideal choice for pathway prototyping, protein production, and biosensing, due to their high controllability, tolerance, stability, and ability to produce proteins in a short time. At present, the widely used CFPS systems are mainly based on Escherichia coli strain. Bacillus subtilis, Corynebacterium glutamate, and Vibrio natriegens are potential chassis cells for many biotechnological applications with their respective characteristics. Therefore, to expand the platform of the CFPS systems and options for protein production, four prokaryotes, E. coli, B. subtilis, C. glutamate, and V. natriegens were selected as host organisms to construct the CFPS systems and be compared. Moreover, the process parameters of the CFPS system were optimized, including the codon usage, plasmid synthesis competent cell selection, plasmid concentration, ribosomal binding site (RBS), and CFPS system reagent components. By optimizing and comparing the main influencing factors of different CFPS systems, the systems can be optimized directly for the most influential factors to further improve the protein yield of the systems. In addition, to demonstrate the applicability of the CFPS systems, it was proved that the four CFPS systems all had the potential to produce therapeutic proteins, and they could produce the receptor-binding domain (RBD) protein of SARS-CoV-2 with functional activity. They not only could expand the potential options for in vitro protein production, but also could increase the application range of the system by expanding the cell-free protein synthesis platform.