bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impacts of the COVID-19 Pandemic on Pediatric Type 1 Diabetes Management: A Qualitative Study
Authors: Ferguson Kacey , Moore Hailey , Kaidbey Jasmine H. , Khattak Shazmenna , Saeed Abbas , Cogen Fran R. , Streisand Randi , Sylvetsky Allison C. 
Published: September 2022

Purpose: The purpose of this study was to understand impacts of the coronavirus (COVID-19) pandemic on pediatric type 1 diabetes management. Methods: In-depth qualitative interviews were conducted with 15 parents of children (age 6-12 years) with type 1 diabetes. Parents responded to 8 open-ended questions about their experiences managing their children’s type 1 diabetes during the COVID-19 pandemic. All interviews were transcribed, coded, and analyzed using qualitative thematic methods. Results: Parents reported both positive and negative aspects of managing their children’s type 1 diabetes during the COVID-19 pandemic. Facilitators of diabetes management included spending more time together at home and enhanced convenience of telehealth appointments and online supply ordering. Parents also described difficulties managing their children’s type 1 diabetes during the COVID-19 pandemic, including a lack of structure in their child’s daily routine, which led to increases in sedentary behavior. Furthermore, they reported psychosocial challenges of type 1 diabetes management, which were exacerbated by the pandemic. Conclusion: While the COVID-19 pandemic was described as having overall positive impacts on pediatric type 1 diabetes management, efforts to support parents in increasing children’s physical activity and reducing screen time are needed, along with readily accessible mental health resources for both parents and their children with type 1 diabetes.
Persistent Mϋllerian duct syndrome presenting as bilateral cryptorchidism: a case report
Authors: Joshi Mahesh , Sahu Ramdayal , Dubey Prama , Barala Abhishek 
Published: September 2022

Abstract
Background
Persistent Mϋllerian duct syndrome is a rare condition marked by the presence of Mϋllerian duct derivatives (uterus and fallopian tubes) in males who are seemingly (phenotypically and karyotypically) normal. Diagnosis can be made with physical examination, radiological investigations and karyotyping. The management aims at preserving fertility and removing Mϋllerian duct structures.

Case presentation
We report a case of PMDS encountered in a patient presenting with bilateral non-palpable testes since birth who was treated with orchidopexy and removal of Mϋllerian duct structures.

Conclusion
A remote possibility of persistent Mϋllerian duct syndrome should be borne in mind while dealing with a case of undescended testes. If such an encounter occurs, orchidopexy with removal of Mullerian duct structures is the preferred management.
Genomic prediction with whole-genome sequence data in intensely selected pig lines
Authors: Ros-Freixedes Roger , Johnsson Martin , Whalen Andrew , Chen Ching-Yi , Valente Bruno D. , Herring William O. , Gorjanc Gregor , Hickey John M. 
Published: September 2022

Abstract
Background
Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage.

Methods
We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests.

Results
The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected.

Conclusions
Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis.
Clinlabomics: leveraging clinical laboratory data by data mining strategies
Authors: Wen Xiaoxia , Leng Ping , Wang Jiasi , Yang Guishu , Zu Ruiling , Jia Xiaojiong , Zhang Kaijiong , Mengesha Birga Anteneh , Huang Jian , Wang Dongsheng , Luo Huaichao 
Published: September 2022

AbstractThe recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.
Impact of adaptive filtering on power and false discovery rate in RNA-seq experiments
Authors: Zehetmayer Sonja , Posch Martin , Graf Alexandra 
Published: September 2022

AbstractBackgroundIn RNA-sequencing studies a large number of hypothesis tests are performed to compare the differential expression of genes between several conditions. Filtering has been proposed to remove candidate genes with a low expression level which may not be relevant and have little or no chance of showing a difference between conditions. This step may reduce the multiple testing burden and increase power.ResultsWe show in a simulation study that filtering can lead to some increase in power for RNA-sequencing data, too aggressive filtering, however, can lead to a decline. No uniformly optimal filter in terms of power exists. Depending on the scenario different filters may be optimal. We propose an adaptive filtering strategy which selects one of several filters to maximise the number of rejections. No additional adjustment for multiplicity has to be included, but a rule has to be considered if the number of rejections is too small.ConclusionsFor a large range of simulation scenarios, the adaptive filter maximises the power while the simulated False Discovery Rate is bounded by the pre-defined significance level. Using the adaptive filter, it is not necessary to pre-specify a single individual filtering method optimised for a specific scenario.
The immune subtypes and landscape of sarcomas
Authors: Weng Weiwei , Yu Lin , Li Zhang , Tan Cong , Lv Jiaojie , Lao I. Weng , Hu Wenhuo , Deng Zhenzhong , Liu Zebing , Wang Jian , Xu Midie 
Published: September 2022

Abstract
Background
Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population.

Results
By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune “hot” and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune “cold” phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance.

Conclusions
Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.
Fine mapping of the gene controlling the weeping trait of Prunus persica and its uses for MAS in progenies
Authors: Wang Luwei , Pan Lei , Niu Liang , Cui Guochao , Wei Bin , Zeng Wenfang , Wang Zhiqiang , Lu Zhenhua 
Published: September 2022

Abstract
Background
Fruit tree yield and fruit quality are affected by the tree’s growth type, and branching angle is an important agronomic trait of fruit trees, which largely determines the crown structure. The weeping type of peach tree shows good ventilation and light transmission; therefore, it is commonly cultivated. However, there is no molecular marker closely linked with peach weeping traits for target gene screening and assisted breeding.

Results
First, we confirmed that the peach weeping trait is a recessive trait controlled by a single gene by constructing segregating populations. Based on BSA-seq, we mapped the gene controlling this trait within 159 kb of physical distance on chromosome 3. We found a 35 bp deletion in the candidate area in standard type, which was not lacking in weeping type. For histological assessments, different types of branches were sliced and examined, showing fiber bundles in the secondary xylem of ordinary branches but not in weeping branches.

Conclusions
This study established a molecular marker that is firmly linked to weeping trait. This marker can be used for the selection of parents in the breeding process and the early screening of hybrid offspring to shorten the breeding cycle. Moreover, we preliminary explored histological differences between growth types. These results lay the groundwork for a better understanding of the weeping growth habit of peach trees.
A photograph of the researcher on the invitation letter did not affect the participation rate of a postal survey: a randomized study within a trial (SWAT)
Authors: Prediger Barbara , Könsgen Nadja , Bora Ana-Mihaela , Schlimbach Anna , Pieper Dawid 
Published: September 2022

Abstract
Objective
Participant recruitment is one of the main challenges in research. It is suggested that including researcher photographs might increase participation rates, but empirical evidence is lacking. This study within a trial (SWAT) aims to assess whether invitation letters including researcher photographs increase the participation rate in the context of a survey on medical second opinions.

Methods
Through 25 local register offices in Berlin and Brandenburg (Germany), we identified a random sample of 9990 persons. We randomly assigned our sample to the intervention group (IG) receiving an invitation letter with researcher photographs and control group (CG) receiving an invitation letter without photographs in a 1:1 ratio. Our primary outcome was the participation rate. Furthermore, we compared participants to non-participants’ characteristics.

Results
Of 9990 invitations, 9797 could be delivered (IG: 4890, CG: 4907). Of these, 1349 (13.8%) participated. There were 682/4890 (13.9%) participants in the IG and 662/4907 (13.5%) in the CG with an odds ratio of 1.030 (95% confidence interval: 0.918–1.156). Additional analyses on non-participant characteristics did not show any differences.

Conclusion
We could not find any difference in the participation rates. Our study does not confirm the results of previous studies. The length of our questionnaire may have affected our results.

Trial registration
Queens University Belfast – SWAT Store, SWAT 104.
Evaluating sensitivity to classification uncertainty in latent subgroup effect analyses
Authors: Loh Wen Wei , Kim Jee-Seon 
Published: September 2022

Abstract
Background
Increasing attention is being given to assessing treatment effect heterogeneity among individuals belonging to qualitatively different latent subgroups. Inference routinely proceeds by first partitioning the individuals into subgroups, then estimating the subgroup-specific average treatment effects. However, because the subgroups are only latently associated with the observed variables, the actual individual subgroup memberships are rarely known with certainty in practice and thus have to be imputed. Ignoring the uncertainty in the imputed memberships precludes misclassification errors, potentially leading to biased results and incorrect conclusions.

Methods
We propose a strategy for assessing the sensitivity of inference to classification uncertainty when using such classify-analyze approaches for subgroup effect analyses. We exploit each individual’s typically nonzero predictive or posterior subgroup membership probabilities to gauge the stability of the resultant subgroup-specific average causal effects estimates over different, carefully selected subsets of the individuals. Because the membership probabilities are subject to sampling variability, we propose Monte Carlo confidence intervals that explicitly acknowledge the imprecision in the estimated subgroup memberships via perturbations using a parametric bootstrap. The proposal is widely applicable and avoids stringent causal or structural assumptions that existing bias-adjustment or bias-correction methods rely on.

Results
Using two different publicly available real-world datasets, we illustrate how the proposed strategy supplements existing latent subgroup effect analyses to shed light on the potential impact of classification uncertainty on inference. First, individuals are partitioned into latent subgroups based on their medical and health history. Then within each fixed latent subgroup, the average treatment effect is assessed using an augmented inverse propensity score weighted estimator. Finally, utilizing the proposed sensitivity analysis reveals different subgroup-specific effects that are mostly insensitive to potential misclassification.

Conclusions
Our proposed sensitivity analysis is straightforward to implement, provides both graphical and numerical summaries, and readily permits assessing the sensitivity of any machine learning-based causal effect estimator to classification uncertainty. We recommend making such sensitivity analyses more routine in latent subgroup effect analyses.
Development and pilot implementation of guidelines for culturally tailored research recruitment materials for African Americans and Latinos
Authors: Cunningham-Erves Jennifer , Kusnoor Sheila V. , Villalta-Gil Victoria , Stallings Sarah C. , Ichimura Jabari S. , Israel Tiffany L. , Harris Paul A. , Wilkins Consuelo H. 
Published: September 2022

Abstract
Background
Previous studies support cultural tailoring of recruitment materials as a strategy to promote the enrollment of minoritized groups in clinical trials. However, there is a lack of guidance for research teams to create culturally tailored materials, potentially contributing to low recruitment rates of minoritized groups. We describe the development and pilot testing of recruitment material guidelines used to culturally tailor clinical trial recruitment materials targeting African Americans and Latinos.

Methods
The guideline development team consisted of investigators, research staff, and community leaders and members experienced in the recruitment and community engagement of minoritized groups. The recruitment material guidelines were developed using the literature, focus groups with African Americans and Latinos, the teams’ research experience, and guidance from a community advisory board. To assess the effectiveness of the guidelines, a pilot study was conducted comparing advertisement click-through rates and enrollment outcomes between two institutions differing in use of culturally tailored versus non-tailored Facebook banner ads for the “Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness” (ADAPTABLE) study.

Results
Five themes emerged from focus groups: (1) employ diversity and inclusion in recruitment efforts; (2) access multiple recruitment channels to increase reach and possible participation; (3) increase your “footwork”; (4) personalize outreach and recruitment to specific groups’ beliefs and values; (5) align recruitment messaging with language preferences and motivations for study participation; and (6) specify incentives for participation. Guidelines were: 1) be inclusive; 2) use all forms of media; 3) take a personalized approach; 4) align recruitment messaging with motivations for study participation; 5) specify incentives; and 6) get out into the community. Additional guidelines were developed addressing specific considerations for images and language when targeting African American and Latino populations. Pilot study results demonstrated that clicks per impression ratio (0.47 clicks per impression vs. 0.03 clicks per impression) and the percentage of African American enrollment were significantly higher when using tailored compared to non-tailored ads (12.8% vs. 8.3%, respectively).

Conclusion
The recruitment material guidelines offer practical recommendations to reach diverse populations for clinical trial participation more effectively. Our preliminary data supports use of these guidelines as a strategy to enhance recruitment of minoritized groups into clinical research studies.
Strongyloides stercoralis hyperinfection syndrome mimicking pseudomembranous enteritis, complicated by Escherichia coli bacteremia and Pneumocystis jirovecii pneumonia in a patient after immunosuppressive therapy: a case report
Authors: Cai De-Han , Wang Jun , Fang Xiao-Lin 
Published: September 2022

Abstract
Background
Strongyloidiasis, caused by Strongyloides stercoralis (S. stercoralis), is endemic worldwide, especially in countries with warm and humid climates. Strongyloides stercoralis hyperinfection syndrome (SHS) is an extremely serious manifestation of strongyloidiasis, which results from an acute exacerbation of auto-infection and is often fatal.

Case presentation
We present a case of SHS mimicking pseudomembranous enteritis with a final definitive diagnosis of a triple infection including S. stercoralis, Escherchia coli (E. coli) and Pneumocytis jirovecii (P. jirovecii) that occurred in a microscopic polyangiitis (MPA) patient after immunosuppressive therapy. SHS, together with E. coli bacteremia and Pneumocytis jirovecii pneumonia (PJP) in the same patient, is rare in clinical practice, which is first reported worldwide, to our knowledge. After the diagnosis was confirmed, the treatment protocol was quickly adjusted; however, the patient’s life could not be saved.

Conclusion
This case reminds us of the necessity to consider strongyloidiasis as a differential diagnosis in immunocompromised populations who live in or have visited to S. stercoralis endemic areas, especially patients with suspected pseudomembranous enteritis, even if stool examination, serological tests, and eosinophilia are negative. For this group, it is advisable to complete the relevant endoscopy and/or PCR as soon as possible. The fundamental solution to prevent this catastrophic outcome is to implement effective preventive measures at multiple levels, including physicians, patients, and relevant authorities.