bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research integrity in clinical trials: innocent errors and spin versus scientific misconduct
Authors: Núñez-Núñez María , Andrews Jeffrey C. , Fawzy Mohamed , Bueno-Cavanillas Aurora , Khan Khalid Saeed 
Published: July 2022

Purpose of review
High-quality research underpins the best healthcare practice. This article focuses on analyzing the current literature to promote research integrity across clinical trials.

Recent findings
Recent admissions of questionable practices by researchers have undermined practitioner and public confidence. There is limited evidence specifically for ethical and professional standards in clinical trials to guide researchers and institutions to embed integrity into research practice.

Summary
Unintentional errors and spin in research are not uncommon as training in design and conduct of clinical trials is not part of health education for medical and allied health professions. There is unfamiliarity with procedures, such as prospective registration, a priori documentation of statistical analysis plans, openness in data sharing, and so forth. This, combined with the academic culture of secrecy, has led to an environment where scientific suspicion, instead of trust, is the norm. Existing science integrity documents are devoid of specific recommendations about how to translate any guidance into clinical trial practice. There is a need for constructive, supportive and multidisciplinary approaches based on open dialogue and continuous training, targeting the research environment. Research integrity now needs to take centre stage to re-instill confidence in randomized trial evidence to inform clinical practice.
An update of diagnostic efficacy of ultrasound and magnetic resonance imaging in the diagnosis of clinically significant placenta accreta spectrum disorders
Authors: Fratelli Nicola , Fichera Anna , Prefumo Federico 
Published: July 2022

Purpose of review
Systematic screening and diagnosis of placenta accreta spectrum disorder (PAS) either by ultrasound or magnetic resonance imaging (MRI) would allow referral of high-risk women to specialized multidisciplinary teams. We aimed to report recent findings regarding the diagnostic accuracy of ultrasound and magnetic resonance imaging in the diagnosis of PAS.

Recent findings
Recent evidence from the literature shows that both ultrasound and MRI are good tests to identify PAS in high-risk populations. Ultrasound can also be used safely to guide management decisions, concentrating greater resources in patients with the higher risk of clinically significant PAS requiring complex peripartum management. Moreover, there are increasing data showing that routine contingent screening for PAS disorders based on the finding of a placenta implanted low in the uterine cavity and previous uterine surgery is effective in a public healthcare setting. A contingent screening strategy for PAS is feasible if placental location is routinely assessed during routine scans, and may even start from the first trimester of pregnancy.

Summary
Ultrasound is an effective tool to screen pregnancies at high risk of PAS. In such pregnancies, ultrasound and MRI are effective imaging modalities for guiding management.
Liver cirrhosis prediction for patients with Wilson disease based on machine learning: a case–control study from southwest China
Authors: Chen Ke , Wan Yang , Mao Ju , Lai Yuqing , Zhuo-ma Gesang , Hong Peiwei 
Published: July 2022

Objectives
Wilson disease (WD) is a rare autosomal recessive disease caused by an ATP7B gene mutation. Liver cirrhosis is an important issue that affects the clinical management and prognosis of WD patients. Blood routine examination is a potential biomarker for predicting the occurrence of liver cirrhosis in WD. We aim to construct a predictive model for the occurrence of liver cirrhosis using general clinical information, blood routine examination, urine copper, and serum ceruloplasmin through a machine learning approach.

Methods
Case–control study of WD patients admitted to West China Fourth Hospital between 2005 and 2020. Patients with a score of at least four in scoring system of WD were enrolled. A machine learning model was constructed by EmpowerStats software according to the general clinical data, blood routine examination, 24 h urinary copper, and serum ceruloplasmin.

Results
This study analyzed 346 WD patients, of which 246 were without liver cirrhosis. And we found platelet large cell count (P-LCC), red cell distribution width CV (RDW-CV), serum ceruloplasmin, age at diagnosis, and mean corpuscular volume (MCV) were the top five important predictors. Moreover, the model was of high accuracy, with an area under the receiver operating characteristic curve of 0.9998 in the training set and 0.7873 in the testing set.

Conclusions
In conclusion, the predictive model for predicting liver cirrhosis in WD, constructed by machine learning, had a higher accuracy. And the most important indices in the predictive model were P-LCC, RDW-CV, serum ceruloplasmin, age at diagnosis, and MCV.
Macronutrient and Micronutrient Intake in Adolescents With Non‐alcoholic Fatty Liver Disease
Authors: Porto Ariel , Pan Zhaoxing , Zhou Wenru , Sokol Ronald J. , Klaczkiewicz Kelly , Sundaram Shikha S. 
Published: July 2022

Objectives:While dietary changes are recommended to treat pediatric non‐alcoholic fatty liver disease (NAFLD), the role of specific nutrients in disease progression is unclear. The objective of this study is to (1) assess the macronutrient and micronutrient intake in adolescents with liver biopsy proven NAFLD [with and without non‐alcoholic steatohepatitis (NASH)] and lean controls; (2) determine nutritional predictors of disease severity amongst these groups.Methods:Adolescents with biopsy‐proven NAFLD and lean controls completed the Harvard Food Frequency Questionnaire.Results:Twenty‐eight NAFLD and 15 lean controls were studied. NAFLD with (n = 20) and without NASH (n = 8) had similar total calorie, protein, fat, and carbohydrate intake. Subjects with NASH had higher total sugar (122.3 ± 48.3 vs 83.1 ± 38.8 g), glucose (24.3 ± 9.3 vs 15.2 ± 7.5 g), sucrose (42.3 ± 16.9 vs 28.8 ± 11.7 g), and fructose (29.4 ± 12.5 vs 18.1 ± 8.0 g) intake than those with NAFLD but without NASH (P < 0.05). Both NAFLD groups had similar micronutrient intake. Alanine aminotransferase (ALT) correlated with total caloric intake (ρ = 0.4; P = 0.04). Total carbohydrate calories correlated with a higher NAS summary score (ρ = 0.38; P = 0.04) and lobular inflammation (ρ = 0.50; P = 0.007). Percent calories from added sugar and glucose correlated with worsening NAS summary score (ρ = 0.44, P = 0.02; ρ = 0.48, P = 0.009) and lobular inflammation (ρ = 0.51, P = 0.006; ρ = 0.53, P = 0.004). Percent calories from fructose correlated with lobular inflammation (ρ = 0.56; P = 0.002). Total daily calories, protein, fat, carbohydrate, and micronutrient intake were similar between NAFLD and lean controls.Conclusions:NASH patients consume similar total calories, protein, and fat as those without NASH, but have significantly higher sugar intake. NAFLD and lean children, however, have similar macro/micronutrient intake. Histologic disease severity correlates with total carbohydrate and added sugar intake, supporting a role for simple sugar intake in NAFLD progression.
Adult mortality before and during the COVID-19 pandemic in nine communities of Yemen: a key informant study
Authors: Alhaffar Mervat , BaSaleem Huda , Othman Fouad , Alsakkaf Khaled , Mohsen Alkhteeb Sena Mohammed , Kolaise Hussein , Babattah Abdullah K. , Mahyoub Salem Yaseen Abdulmalik , Brindle Hannah , Yahya Najwa , Pepe Pasquale , Checchi Francesco 
Published: July 2022

AbstractIntroductionWidespread armed conflict has affected Yemen since 2014. To date, the mortality toll of seven years of crisis, and any excess due to the COVID-19 pandemic, are not well quantified. We attempted to estimate population mortality during the pre-pandemic and pandemic periods in nine purposively selected urban and rural communities of southern and central Yemen (Aden and Ta’iz governorates), totalling > 100,000 people.MethodsWithin each study site, we collected lists of decedents between January 2014-March 2021 by interviewing different categories of key community informants, including community leaders, imams, healthcare workers, senior citizens and others. After linking records across lists based on key variables, we applied two-, three- or four-list capture-recapture analysis to estimate total death tolls. We also computed death rates by combining these estimates with population denominators, themselves subject to estimation.ResultsAfter interviewing 138 disproportionately (74.6%) male informants, we identified 2445 unique decedents. While informants recalled deaths throughout the study period, reported deaths among children were sparse: we thus restricted analysis to persons aged ≥15 years old. We noted a peak in reported deaths during May-July 2020, plausibly coinciding with the first COVID-19 wave. Death rate estimates featured uninformatively large confidence intervals, but appeared elevated compared to the non-crisis baseline, particularly in two sites where a large proportion of deaths were attributed to war injuries. There was no clear-cut evidence of excess mortality during the pandemic period.ConclusionsWe found some evidence of a peak in mortality during the early phase of the pandemic, but death rate estimates were otherwise too imprecise to enable strong inference on trends. Estimates suggested substantial mortality elevations from baseline during the crisis period, but are subject to serious potential biases. The study highlighted challenges of data collection in this insecure, politically contested environment.
Phenotypic similarity is a measure of functional redundancy within homologous gene families
Authors: Comstock Jessica A. , Asp Merrill E. , Bahar Fatmagül , Lee Isabella , Patteson Alison E. , Welch Roy D. 
Published: July 2022

AbstractRobustness to the impact of mutation can mitigate phenotypes that have the potential to inform gene function. This robustness is often encoded into the genome through gene duplication, among other mechanisms. Duplication is a source of structurally similar genes that can retain some functional overlap as they diverge, and as such contribute to functional redundancy in the face of mutation. While redundancies have been explored in groups of two or three paralogs by generating double and triple mutants, it is unclear to what extent larger homologous gene families contribute to robustness through functional redundancy. Here, we used phenotypic similarity as an indicator of functional redundancy to explore the extent to which homologous gene families contribute to redundancy in function. We hypothesize that, since functional redundancy is more likely to occur within gene families where genes are structurally similar, mutant strains within the same gene families would be more phenotypically similar. We generated 265 single-gene disruptions in four homologous gene families of Myxococcus xanthus, used time-lapse microscopy to generate time series of multicellular development, and developed an image analysis pipeline to compare phenotypic characteristics among different strains. We show that mutant strains cluster by gene family in the phenotypic feature space with principal component analysis, demonstrating that families of homologs can contain extensive functional redundancy networks.
Comparative Analysis of three machine learning models for Early Prediction of Skeletal Class-III Malocclusion from Profile Photos
Authors: Kiliç Banu , Önal-Süzek Tuğba , Aksoy Selahattin 
Published: July 2022

AbstractThe pre-adolescent growth period is the best time for the skeletal Class-III malocclusion treatment. Diagnosis and treatment during this period continue to be a complex orthodontic problem. Class-III malocclusion is complicated to treat with braces frequently requiring surgical intervention after a pubertal growth spurt. In addition, delayed recognition of the problem will yield significant functional, aesthetic, and psychological concerns. This study presents the first fully automated machine learning method to accurately diagnose Class-III malocclusion applied across mobile images, to the best of our knowledge. For this purpose, we comparatively evaluated three machine learning approaches: a deep learning algorithm, a machine learning algorithm, and a rule-based algorithm. We collected a novel profile image data set for this analysis along with their formal diagnosis from 435 orthodontics patients. The most successful method among the three was the machine learning method, with an accuracy of %76.
Malaria parasite centrins assemble by Ca2+-inducible condensation
Authors: Voß Yannik , Klaus Severina , Lichti Nicolas P. , Ganter Markus , Guizetti Julien 
Published: July 2022

AbstractRapid proliferation of the malaria-causing parasitePlasmodium falciparumin the human blood depends on a particularly divergent and acentriolar centrosome, which incorporates several essential centrins. Centrins are small calcium-binding proteins that have a variety of roles and are universally associated with eukaryotic centrosomes. Their precise mode of action, however, remains unclear. In this study calcium-inducible liquid-liquid phase separation is revealed as an evolutionary conserved principle of assembly forPlasmodiumand human centrins. Furthermore, the disordered N-terminus and calcium-binding motifs are defined as essential features for reversible biomolecular condensation and demonstrate that certain centrins can co-condensate. In vivo analysis using live-cell STED microscopy shows liquid-like dynamics of centrosomal centrin. Additionally, implementation of an inducible protein overexpression system reveals concentration-dependent formation of extra-centrosomal centrin assemblies with condensate-like properties. The timing of foci formation and dissolution suggests that centrin assembly is regulated. This study thereby provides a new model for centrin accumulation at eukaryotic centrosomes.
Automated container-less cell processing method for single-cell proteomics
Authors: Matsumoto Cory , Shao Xinhao , Bogosavljevic Marko , Chen Liang , Gao Yu 
Published: July 2022

AbstractSingle-cell genomics and transcriptomics studies enabled us to characterize cell heterogeneity in various tissues, which helped us to better understand the biological system and disease progression. Single-cell proteomics, which directly measures the protein expression level, has the potential to further enhance our knowledge by providing not only a more direct measurement but also crucial information cannot be captured by genomics or transcriptomics study, such as protein activation states and post-translation modification events. One of the main challenges of single-cell proteomics is the large sample loss during sample preparation, which is largely unavoidable using standard proteomics protocols. Protein and peptide loss to the container surface is a well-known phenomenon but often overlooked in larger-scale (>1 µg) proteomics experiments. When it comes to single-cell proteomics with only picograms of protein samples, this loss becomes non-negligible and often dictates the outcomes of the experiment. More importantly, sample processing through multiple pipette tips and containers often introduces random errors, which undermine the ability to detect true heterogenous cellular events. To solve these problems and further improve the throughput and reproducibility of the single-cell proteomics experiments, we developed an automated container-less cell processing platform, utilizing acoustic levitation to process cell samples in the air. Our platform automatically performs cell lysis, protein reduction, alkylation, digestion, and peptide labeling in the air, without any sample transfer step or container. The digested and labeled peptides are then directly injected into the capillary LC-MS/MS system for analysis, eliminating manual steps and conserving most of the sample materials for proteomics analysis. Our initial test shows at least 30% improvement in peptide signals over conventional methods. This process can be performed in parallel to further improve sample processing throughput.
Large-scale web scraping for problem gambling research: a case study of COVID-19 lockdown effects in Germany
Authors: Smith Elke , Michalski Simon , Knauth Kilian H. K. , Kaspar Kai , Reiter Nils , Peters Jan 
Published: July 2022

AbstractThe COVID-19 pandemic and the measures to prevent its spread have had a negative impact on substance use behaviour and posed a special threat for individuals at risk. Problem gambling is a major public health concern, and it is likely that the lockdown and social distancing measures have altered gambling behaviour, for instance shifting from land-based to online gambling. In this study, we used large-scale web scraping to analyse posting behaviour on a major German online gambling forum, gathering a database of more than 200k posts. We examined the relative usage of different subforums, i.e. terrestrial, online gambling and problem gambling sections, posting frequency, and changes in posting behaviour related to the casino closures that were part of the nationwide restrictions in Germany in 2020. There was a marked increase in the number of newly registered users during the first lockdown compared to the weeks prior to the lockdown, which may reflect a shift from terrestrial to online gambling. Further, there was an increase in the number of posts in the online gambling subforum with a concurrent decrease in the number of posts in the terrestrial gambling subforum. An analysis of user types revealed that a substantial number of users who posted in both the online and terrestrial forum contributed at least once to the problem gambling subforum. This subforum contained the longest posts, which were on average twice as long as the average post. Modelling the relationship between reply frequency and latency between initial posts and replies showed that the number of short-latency replies (i.e. replies posted within seven hours after the initial post) was substantially higher during the first lockdown compared to the preceding weeks. The increase during the first lockdown may reflect the general marked increase in screen time and/or usage of online platforms and media after the onset of the global COVID-19 pandemic. The analyses may help to identify lockdown-related effects on gambling behaviour. These potentially detrimental effects on mental health, including addiction and problem gambling, may require monitoring and special public health measures.
Human Milk Oligosaccharide 2’-fucosyllactose inhibits ligand binding to C-type lectin DC-SIGN but not to Langerin
Authors: Mukherjee Reshmi , Somovilla Victor J. , Chiodo Fabrizio , Bruijns Sven , Pieters Roland J , Garssen Johan , Kooyk Yvette van , Kraneveld Aletta D , Bergenhenegouwen Jeroen van 
Published: July 2022

AbstractHuman milk oligosaccharides (HMOs) and its most abundant component, 2’-Fucosyllactose (2’-FL), are known to be immunomodulatory. Previously, it was shown that HMOs and 2’-FL bind to the C-type lectin receptor DC-SIGN. Here we show, using a ligand-receptor competition assay, that a whole mixture of HMOs from pooled human milk (HMOS) and 2’-FL inhibit the binding of the carbohydrate-binding receptor DC-SIGN to its prototypical ligands, fucose and the oligosaccharide Lewis-B, (Leb) in a dose-dependent way. Interestingly, such inhibition by HMOS and 2’-FL was not detected for another C-type lectin, Langerin, evolutionary similar to DC-SIGN. The cell-ligand competition assay using DC-SIGN expressing cells confirmed that 2’-FL inhibits the binding of DC-SIGN to Leb. Molecular dynamics (MD) simulations show that 2’-FL exists in a preorganized bioactive conformation before binding to DC-SIGN and this conformation is retained after binding to DC-SIGN. Lebhas more flexible conformations and utilizes two binding modes, which operate one at a time via its two fucoses to bind to DC-SIGN. 2’-FL may have a reduced entropic penalty due to its preorganized state compared to Leb, and it has lower binding enthalpy, suggesting better binding to DC-SIGN. Thus, due to the better binding to DC-SIGN, 2’-FL may replace Lebfrom its binding pocket in DC-SIGN. MD simulations also showed that 2’-FL does not bind to Langerin. Our studies confirm 2’-FL as a specific ligand for DC-SIGN and suggest that 2’-FL can replace other DC-SIGN ligands from its binding pocket during ligand-receptor interactions in possible immunomodulatory processes.
Single cell transcriptomics of human skin equivalent organoids
Authors: Stabell Adam R. , Wang Shuxiong , Lee Grace E. , Ling Ji , Nguyen Sandrine D. , Sen George L. , Nie Qing , Atwood Scott X. 
Published: July 2022

ABSTRACTSeveral methods for generating human skin equivalent (HSE) organoid cultures are regularly used to study skin biology and test pharmaceuticals, however few studies have thoroughly characterized these systems. To fill this gap, we used single cell-RNA sequencing to compare the cellular states of in vitro HSEs generated from distinct culture methods, HSEs xenografted onto mice, and in vivo epidermis. By combining differential gene expression, pseudotime analyses, splicing kinetics, and spatial localization, we reconstructed HSE keratinocyte differentiation trajectories that recapitulated known in vivo epidermal differentiation pathways and show that HSEs contain many of the major in vivo cellular states. However, HSEs also develop several unique keratinocyte states, an expanded basal stem cell program, and disrupted terminal differentiation. In addition, cell-cell communication modeling showed the presence of EMT-associated signaling pathways not normally active in homeostatic skin and we show that EGF supplementation influences the EMT signature. Lastly, xenografted HSEs at early timepoints post-transplantation significantly rescued many of the observed in vitro deficits, while undergoing a hypoxic response that drove an alternative differentiation lineage. This study highlights the strengths and limitations of organoid cultures and identifies areas for potential innovation.
Investigations on the performance of poly(o-toluidine)/silicon dioxide nanocomposite coatings for the corrosion protection of mild steel
Authors: Rajendran Rajkumar , Muthukrishnan Karuppuraja , Chinnapiyan Vedhi 
Published: July 2022

PurposeThe purpose of this study is to investigate the presence of silicon dioxide (SiO2) nanoparticles in o-toluidine monomer as a reactant and ammonium persulfate as an oxidant to obtain the poly(o-toluidine) (POT)/SiO2nanocomposites by oxidative polymerization method.Design/methodology/approachFourier transformation infrared spectroscopy, X-ray diffraction and field emission scanning electron microscopy were used to characterize the structural properties of the composite. POT/SiO2nanocomposites were mixed with acrylic resin through a solution mixing method and the composites were coated onto the surface of mild steel. Electrochemical measurements were used to determine the corrosion protection efficiency (P.E.%) of polymer composite coatings using 3.5% NaCl solution as corrosion environment.FindingsThe results obtained reveals that the POT/SiO2/acrylic resin composite coatings have got higher corrosion P.E.% than that of POT/acrylic resin coatings.Originality/valueThe formation of uniformly passive layer in the POT/SiO2composite was used to enhance the P.E.% on mild steel surface. The POT/SiO2/acrylic resin nanocomposites showed effective anticorrosive behavior on mild steel in 3.5% NaCl solution.