bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the use of non-concurrent controls in platform trials: a scoping review
Authors: Bofill Roig Marta , Burgwinkel Cora , Garczarek Ursula , Koenig Franz , Posch Martin , Nguyen Quynh , Hees Katharina 
Published: June 2023

Abstract
Background
Platform trials gained popularity during the last few years as they increase flexibility compared to multi-arm trials by allowing new experimental arms entering when the trial already started. Using a shared control group in platform trials increases the trial efficiency compared to separate trials. Because of the later entry of some of the experimental treatment arms, the shared control group includes concurrent and non-concurrent control data. For a given experimental arm, non-concurrent controls refer to patients allocated to the control arm before the arm enters the trial, while concurrent controls refer to control patients that are randomised concurrently to the experimental arm. Using non-concurrent controls can result in bias in the estimate in case of time trends if the appropriate methodology is not used and the assumptions are not met.

Methods
We conducted two reviews on the use of non-concurrent controls in platform trials: one on statistical methodology and one on regulatory guidance. We broadened our searches to the use of external and historical control data. We conducted our review on the statistical methodology in 43 articles identified through a systematic search in PubMed and performed a review on regulatory guidance on the use of non-concurrent controls in 37 guidelines published on the EMA and FDA websites.

Results
Only 7/43 of the methodological articles and 4/37 guidelines focused on platform trials. With respect to the statistical methodology, in 28/43 articles, a Bayesian approach was used to incorporate external/non-concurrent controls while 7/43 used a frequentist approach and 8/43 considered both. The majority of the articles considered a method that downweights the non-concurrent control in favour of concurrent control data (34/43), using for instance meta-analytic or propensity score approaches, and 11/43 considered a modelling-based approach, using regression models to incorporate non-concurrent control data. In regulatory guidelines, the use of non-concurrent control data was considered critical but was deemed acceptable for rare diseases in 12/37 guidelines or was accepted in specific indications (12/37). Non-comparability (30/37) and bias (16/37) were raised most often as the general concerns with non-concurrent controls. Indication specific guidelines were found to be most instructive.

Conclusions
Statistical methods for incorporating non-concurrent controls are available in the literature, either by means of methods originally proposed for the incorporation of external controls or non-concurrent controls in platform trials. Methods mainly differ with respect to how the concurrent and non-concurrent data are combined and temporary changes handled. Regulatory guidance for non-concurrent controls in platform trials are currently still limited.
GO-Tibia: a masked, randomized control trial evaluating gentamicin versus saline in open tibia fractures
Authors: Haonga Billy T. , O’Marr Jamieson M. , Ngunyale Patrick , Ngahyoma Joshua , Kessey Justin , Sasillo Ibrahim , Rodarte Patricia , Belaye Tigist , Berhaneselase Eleni , Eliezer Edmund , Porco Travis C. , Morshed Saam , Shearer David W. 
Published: June 2023

Abstract
Background
The rate of open tibia fractures is rapidly increasing across the globe due to a recent rise in road traffic accidents, predominantly in low- and low-middle-income countries. These injuries are orthopedic emergencies associated with infection rates as high as 40% despite the use of systemic antibiotics and surgical debridement. The use of local antibiotics has shown some promise in reducing the burden of infection in these injuries due to increasing local tissue availability; however, no trial has yet been appropriately powered to evaluate for definitive evidence and the majority of current studies have taken place in a high-resource countries where resources and the bio-burden may be different.

Methods
This is a prospective randomized, masked, placebo-controlled superiority trial designed to evaluate the efficacy of locally administered gentamicin versus placebo in the prevention of fracture-related infection in adults (age > 18 years) with primarily closeable Gustillo-Anderson class I, II, and IIIA open tibia fractures. Eight hundred ninety patients will be randomized to receive an injection of either gentamicin (treatment group) or saline (control group) at the site of their primarily closed open fracture. The primary outcome will be the occurrence of a fracture-related infection occurring during the course of the 12-month follow-up.

Discussion
This study will definitively assess the effectiveness of local gentamicin for the prevention of fracture-related infections in adults with open tibia fractures in Tanzania. The results of this study have the potential to demonstrate a low-cost, widely available intervention for the reduction of infection in open tibia fractures.

Trial registration
Clinicaltrials.gov NCT05157126. Registered on December 14, 2021.
Indole-carbohydrazide linked phenoxy-1,2,3-triazole-N-phenylacetamide derivatives as potent α-glucosidase inhibitors: design, synthesis, in vitro α-glucosidase inhibition, and computational studies
Authors: Emadi Mehdi , Mosavizadeh-Marvest Fahimeh , Asadipour Ali , Pourshojaei Yaghoub , Hosseini Samanesadat , Mojtabavi Somayeh , Faramarzi Mohammad Ali , Larijani Bagher , Mohammadi-Khanaposhtani Maryam , Mahdavi Mohammad 
Published: June 2023

Abstract
Background
A new series of indole-carbohydrazide-phenoxy-1,2,3-triazole-N-phenylacetamide hybrids 11a–o was designed based on molecular hybridization of the active pharmacophores of the potent α-glucosidase inhibitors. These compounds were synthesized and evaluated against α-glucosidase.

Methods
The 15 various derivatives of indole-carbohydrazide-phenoxy-1,2,3-triazole-N-phenylacetamide scaffold were synthesized, purified, and fully characterized. These derivatives were evaluated against yeast α-glucosidase in vitro and in silico. ADMET properties of the most potent compounds were also predicted.

Results
All new derivatives 11a–o (IC50 values = 6.31 ± 0.03–49.89 ± 0.09 µM) are excellent α-glucosidase inhibitors in comparison to acarbose (IC50 value = 750.0 ± 10.0 µM) that was used as a positive control. Representatively, (E)-2-(4-((4-((2-(1H-indole-2-carbonyl)hydrazono)methyl) phenoxy)methyl)-1H-1,2,3-triazol-1-yl)-N-(4-methoxyphenyl)acetamide 11d with IC50 = 6.31 µM against MCF-7 cells, was 118.8-times more potent than acarbose. This compound is an uncompetitive inhibitor against α-glucosidase and showed the lowest binding energy at the active site of this enzyme in comparison to other potent compounds. Furthermore, computational calculations predicted that compound 11d can be an orally active compound.

Conclusion
According to obtained data, compound 11d can be a valuable lead compound for further structural development and assessments to obtain effective and potent new α-glucosidase inhibitors.
Immediate word recall in cognitive assessment can predict dementia using machine learning techniques
Authors: Fayemiwo Michael Adebisi , Olowookere Toluwase Ayobami , Olaniyan Oluwabunmi Omobolanle , Ojewumi Theresa Omolayo , Oyetade Idowu Sunday , Freeman Shannon , Jackson Piper 
Published: June 2023

Abstract

Background

Dementia, one of the fastest-growing public health problems, is a cognitive disorder known to increase in prevalence as age increases. Several approaches had been used to predict dementia, especially in building machine learning (ML) models. However, previous research showed that most models developed had high accuracies, and they suffered from considerably low sensitivities. The authors discovered that the nature and the scope of the data used in this study had not been explored to predict dementia based on cognitive assessment using ML techniques. Therefore, we hypothesized that using word-recall cognitive features could help develop models for the prediction of dementia through ML techniques and emphasized assessing the models’ sensitivity performance.

Methods
Nine distinct experiments were conducted to determine which responses from either sample person (SP)’s or proxy’s responses in the “word-delay,” “tell-words-you-can-recall,” and “immediate-word-recall” tasks are essential in the prediction of dementia cases, and to what extent the combination of the SP’s or proxy’s responses can be helpful in the prediction of dementia. Four ML algorithms (K-nearest neighbors (KNN), decision tree, random forest, and artificial neural networks (ANN)) were used in all the experiments to build predictive models using data from the National Health and Aging Trends Study (NHATS).

Results
In the first scenario of experiments using “word-delay” cognitive assessment, the highest sensitivity (0.60) was obtained from combining the responses from both SP and proxies trained KNN, random forest, and ANN models. Also, in the second scenario of experiments using the “tell-words-you-can-recall” cognitive assessment, the highest sensitivity (0.60) was obtained by combining the responses from both SP and proxies trained KNN model. From the third set of experiments performed in this study on the use of “Word-recall” cognitive assessment, it was equally discovered that the use of combined responses from both SP and proxies trained models gave the highest sensitivity of 1.00 (as obtained from all the four models).

Conclusion
It can be concluded that the combination of responses in a word recall task as obtained from the SP and proxies in the dementia study (based on the NHATS dataset) is clinically useful in predicting dementia cases. Also, the use of “word-delay” and “tell-words-you-can-recall” cannot reliably predict dementia as they resulted in poor performances in all the developed models, as shown in all the experiments. However, immediate-word recall is reliable in predicting dementia, as seen in all the experiments. This, therefore, shows the significance of immediate-word-recall cognitive assessment in predicting dementia and the efficiency of combining responses from both SP and proxies in the immediate-word-recall task.
Refractory secondary pneumothorax complicated with lung cancer treated by bronchial occlusion: a case report
Authors: Kato Yuto , Okuda Miyuki , Fukuda Koji , Tanaka Nobuya , Nobuyama Seiichi 
Published: June 2023

Abstract
Background
Pneumothorax is defined as the presence of air or gas in the pleural cavity. Secondary pneumothorax usually occurs in patients with overt underlying lung disease, most commonly chronic obstructive pulmonary disease (COPD). Patients with poor lung function often suffer from pneumothorax with a persistent air leak. Various strategies have been employed in the treatment of such refractory pneumothorax. Bronchial occlusion with an Endobronchial Watanabe Spigot (EWS) (Novatech, Grasse, France) has been shown to be useful in treating prolonged bronchopleural fistulas. Although the effects of bronchial occlusion with EWS are known, refractory pneumothorax often involves multiple affected bronchi, and in some cases the affected bronchi cannot be easily identified. In addition, secondary pneumothorax associated with advanced lung cancer often prolongs the treatment of pneumothorax, which can significantly reduce patients’ quality of life and prognosis.

Case presentation
We report a case of refractory pneumothorax where collateral ventilation was successfully treated by bronchial occlusion of the affected bronchi using multiple methods. In August 2019, an 80-year-old Japanese man with asthma and COPD overlap was admitted for exacerbation triggered by respiratory tract infection. During hospitalization, he presented with chest pain due to pneumothorax. Subsequently, a chest drain tube was inserted and pleurodesis was performed; however, the lung could not be sufficiently expanded and an air leak remained. Further investigation revealed a tumor suspicious for lung cancer at the entrance of the left upper lobe bronchus. Due to poor lung function, surgical treatments were deemed high risk. Therefore, we performed bronchial occlusion using the Endobronchial Watanabe Spigot (EWS). Because we could not determine the affected bronchi by computed tomography (CT), we located the affected bronchi by balloon occlusion test and bronchography with iopamidol. After occlusion, the air leak decreased but still persisted. Thus, we performed pleurodesis twice, and the air leak ceased completely.

Conclusions
Refractory secondary pneumothorax, which affected multiple bronchi and developed into collateral ventilation due to lung cancer, was treated successfully with bronchial occlusion and EWS. In cases where the affected bronchi cannot be determined by the balloon occlusion test, bronchography with iopamidol might be an effective treatment.
Are we moving the dial? Canadian health research funding trends for women’s health, 2S/LGBTQ + health, sex, or gender considerations
Authors: Stranges Tori N. , Namchuk Amanda B. , Splinter Tallinn F. L. , Moore Katherine N. , Galea Liisa A. M. 
Published: June 2023

Abstract
Background
Sex and gender impacts health outcomes and disease risk throughout life. The health of women and members of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning (2S/LGBTQ +) community is often compromised as they experience delays in diagnosis. Distinct knowledge gaps in the health of these populations have prompted funding agencies to mandate incorporation of sex and gender into research. Sex- and gender-informed research perspectives and methodology increases rigor, promotes discovery, and expands the relevance of health research. Thus, the Canadian Institutes of Health Research (CIHR) implemented a sex and gender-based analysis (SGBA) framework recommending the inclusion of SGBA in project proposals in 2010 and then mandating the incorporation of SGBA into grant proposals in 2019. To examine whether this mandate resulted in increased mention of sex or gender in funded research abstracts, we searched the publicly available database of grant abstracts funded by CIHR to analyze the percentage of abstracts that mentioned sex or gender of the population to be studied in the funded research. To better understand broader health equity issues we also examined whether the funded grant abstracts mentioned either female-specific health research or research within the 2S/LGBTQ + community.

Results
We categorized a total of 8,964 Project and Operating grant abstracts awarded from 2009 to 2020 based on their study of female-specific or a 2S/LGBTQ + populations or their mention of sex or gender. Overall, under 3% of grant abstracts funded by CIHR explicitly mentioned sex and/or gender, as 1.94% of grant abstracts mentioned sex, and 0.66% mentioned gender. As one of the goals of SGBA is to inform on health equity and understudied populations with respect to SGBA, we also found that 5.92% of grant abstracts mentioned female-specific outcomes, and 0.35% of grant abstracts focused on the 2S/LGBTQ + community.

Conclusions
Although there was an increased number of funded grants with abstracts that mentioned sex and 2S/LGBTQ + health across time, these increases were less than 2% between 2009 and 2020. The percentage of funded grants with abstracts mentioning female-specific health or gender differences did not change significantly over time. The percentage of funding dollars allocated to grants in which the abstracts mentioned sex or gender also did not change substantially from 2009 to 2020, with grant abstracts mentioning sex or female-specific research increasing by 1.26% and 3.47%, respectively, funding allocated to research mentioning gender decreasing by 0.49% and no change for 2S/LGBTQ +-specific health. Our findings suggest more work needs to be done to ensure the public can evaluate what populations will be examined with the funded research with respect to sex and gender to advance awareness and health equity in research.
Liver-specific in vivo base editing of Angptl3 via AAV delivery efficiently lowers blood lipid levels in mice
Authors: Zuo Yuanbojiao , Zhang Chen , Zhou Yuan , Li Haiwen , Xiao Weidong , Herzog Roland W. , Xu Jie , Zhang Jifeng , Chen Y. Eugene , Han Renzhi 
Published: June 2023

Abstract
Background
Gene editing has emerged as an exciting therapeutic development platform for numerous genetic and nongenetic diseases. Targeting lipid-modulating genes such as angiopoietin-related protein 3 (ANGPTL3) with gene editing offers hope for a permanent solution to lower cardiovascular disease risks associated with hypercholesterolemia.

Results
In this study, we developed a hepatocyte-specific base editing therapeutic approach delivered by dual adeno-associated virus (AAV) to enable hepatocyte-specific targeting of Angptl3 to lower blood lipid levels. Systemic AAV9-mediated delivery of AncBE4max, a cytosine base editor (CBE), targeting mouse Angptl3 resulted in the installation of a premature stop codon in Angptl3 with an average efficiency of 63.3 ± 2.3% in the bulk liver tissue. A near-complete knockout of the ANGPTL3 protein in the circulation were observed within 2–4 weeks following AAV administration. Furthermore, the serum levels of triglyceride (TG) and total cholesterol (TC) were decreased by approximately 58% and 61%, respectively, at 4 weeks after treatment.

Conclusions
These results highlight the promise of liver-targeted Angptl3 base editing for blood lipid control.
A large-scale data security detection method based on continuous time graph embedding framework
Authors: Liu Zhaowei , Che Weishuai , Wang Shenqiang , Xu Jindong , Yin Haoyu 
Published: June 2023

AbstractGraph representation learning has made significant strides in various fields, including sociology and biology, in recent years. However, the majority of research has focused on static graphs, neglecting the temporality and continuity of edges in dynamic graphs. Furthermore, dynamic data are vulnerable to various security threats, such as data privacy breaches and confidentiality attacks. To tackle this issue, the present paper proposes a data security detection method based on a continuous-time graph embedding framework (CTDGE). The framework models temporal dependencies and embeds data using a graph representation learning method. A machine learning algorithm is then employed to classify and predict the embedded data to detect if it is secure or not. Experimental results show that this method performs well in data security detection, surpassing several dynamic graph embedding methods by 5% in terms of AUC metrics. Furthermore, the proposed framework outperforms other dynamic baseline methods in the node classification task of large-scale graphs containing 4321477 temporal information edges, resulting in a 10% improvement in the F1 score metric. The framework is also robust and scalable for application in various data security domains. This work is important for promoting the use of continuous-time graph embedding framework in the field of data security.
Ensuring security in edge computing through effective blockchain node detection
Authors: Wang Shenqiang , Liu Zhaowei , Wang Haiyang , Wang Jianping 
Published: June 2023

AbstractThe rapid development of blockchain technology has garnered increasing attention, particularly in the field of edge computing. It has become a significant subject of research in this area due to its ability to protect the privacy of data. Despite the advantages that blockchain technology offers, there are also security threats that must be addressed. Attackers may manipulate certain nodes in the blockchain network, which can result in tampering with transaction records or other malicious activities. Moreover, the creation of a large number of false nodes can be utilized to gain control and manipulate transaction records of the blockchain network, which can compromise the reliability and security of edge computing. This paper proposes a blockchain node detection method named $$T^2A2vec$$

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that provides a more secure, credible, and reliable solution to address these challenges. In order to achieve $$T^2A2vec$$

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, a transaction dataset that is evenly distributed in both space and time was collected. The transaction dataset is constructed as a transaction graph, where nodes represent accounts and edges describe transactions. BP neural network is used to extract account features, and a random walk strategy based on transaction time, type, and amount is used to extract transaction features. The obtained account features and transaction features are fused to obtain account representation. Finally, the obtained node representation is fed into different classifiers to identify malicious nodes.
Effects of DIF in MST routing in ILSAs
Authors: Valdivia Medinaceli Montserrat , Rutkowski Leslie , Svetina Valdivia Dubravka , Rutkowski David 
Published: June 2023

AbstractThe advance and access to technology have allowed for the implementation of adaptive testing in international large-scale assessments (ILSAs). Multistage testing (MST) in ILSAs offers opportunities and advantages compared to linear testing. However, when dozens of highly heterogeneous systems participate in ILSAs, the sources of heterogeneity pose challenges to any cross-cultural measurement endeavor. With the recent implementation of adaptive designs in ILSAs, little is known about differential item functioning (DIF) effects, mainly when an MST design is used in an ILSA context. Through a simulation study grounded on the empirical basis of the Trends in International Mathematics and Science Study (TIMSS) data, this paper examines the impact of DIF in MST routing in ILSA under different routing strategies. Results showed that Merit routing is highly accurate even when the amount and magnitude of DIF is high, whereas suboptimal routing showed poor accuracy across DIF conditions. As expected, Merit routing has better proficiency recovery parameters than a suboptimal routing mechanism. Implications and recommendations for test developers are included in the discussion section.
The effect of embedded structures on cognitive load for novice learners during block-based code comprehension
Authors: Hao Xiaoxin , Xu Zhiyi , Guo Mingyue , Hu Yuzheng , Geng Fengji 
Published: June 2023

Abstract
Background
Coding has become an integral part of STEM education. However, novice learners face difficulties in processing codes within embedded structures (also termed nested structures). This study aimed to investigate the cognitive mechanism underlying the processing of embedded coding structures based on hierarchical complexity theory, which suggests that more complex hierarchies are involved in embedded versus sequential coding structures. Hierarchical processing is expected to place a great load on the working memory system to maintain, update, and manipulate information. We therefore examined the difference in cognitive load induced by embedded versus sequential structures, and the relations between the difference in cognitive load and working memory capacity.

Results
The results of Experiment 1 did not fully support our hypotheses, possibly due to the unexpected use of cognitive strategies and the way stimuli were presented. With these factors well controlled, a new paradigm was designed in Experiment 2. Results indicate that the cognitive load, as measured by the accuracy and response times of a code comprehension task, was greater in embedded versus sequential conditions. Additionally, the extra cognitive load induced by embedded coding structures was significantly related to working memory capacity.

Conclusions
The findings of these analyses suggest that processing embedded coding structures exerts great demands on the working memory system to maintain and manipulate hierarchical information. It is therefore important to provide scaffolding strategies to help novice learners process codes across different hierarchical levels within embedded coding structures.