bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-cell RNA-sequencing reveals predictive features of response to pembrolizumab in Sézary syndrome
Authors: Su Tianying , Ramchurren Nirasha , Fling Steven P. , Kim Youn H. , Khodadoust Michael S. 
Published: April 2022

AbstractThe PD-1 inhibitor pembrolizumab is effective in treating Sézary syndrome, a leukemic variant of cutaneous T-cell lymphoma. Our purpose was to investigate the effects of pembrolizumab on healthy and malignant T cells in Sézary syndrome and to discover characteristics that predict pembrolizumab response. Samples were analyzed before and after 3 weeks of pembrolizumab treatment by single-cell RNA-sequencing of 118,961 peripheral blood T cells isolated from six Sézary syndrome patients. T-cell receptor clonotyping, bulk RNA-seq signatures, and whole exome data were integrated to classify malignant T-cells and their underlying subclonal heterogeneity. We found that responses to pembrolizumab were associated with lower KIR3DL2 expression within Sézary T cells. Pembrolizumab modulated Sézary cell gene expression of T-cell activation associated genes. The CD8 effector populations included clonally expanded populations with a strong cytotoxic profile. Expansions of CD8 terminal effector and CD8 effector memory T-cell populations were observed in responding patients after treatment. We observed intrapatient Sézary cell heterogeneity including subclonal segregation of a coding mutation and copy number variation. Our study reveals differential effects of pembrolizumab in both malignant and healthy T cells. These data support further study of KIR3DL2 expression and CD8 immune populations as predictive biomarkers of pembrolizumab response in Sézary syndrome.
CAR+ and CAR- T cells differentiate into an NK-like subset that is associated with increased inflammatory cytokines following infusion
Authors: Louie Raymond Hall Yip , Cai Curtis , Singh Mandeep , Deveson Ira , Ferguson James , Amos Timothy G. , McGuire Helen Marie , Samir Jerome , Gowrishankar Kavitha , Adikari Thiruni , Balderas Robert , Bishop David , Gottlieb David , Blyth Emily , Micklethwaite Kenneth , Luciani Fabio 
Published: April 2022

AbstractChimeric antigen receptor (CAR) T cells have demonstrable efficacy in treating B-cell malignancies. Factors such as product composition, lymphodepletion and immune reconstitution are known to influence functional persistence of CAR+ T cells. However, little is known about the determinants of differentiation and phenotypic plasticity of CAR+ T and immune cells early post-infusion. We report single cell multi-omics analysis of molecular, clonal, and phenotypic profiles of CAR+ T and other immune cells circulating in patients receiving donor-derived products. We used these data to reconstruct a differentiation trajectory, which explained the observed phenotypic plasticity and identified cell fate of CAR+ and CAR- T cells. Following lympho-depletion, endogenous CAR- CD8+ and γ□ T cells, clonally expand, and differentiate across heterogenous phenotypes, from a dominant resting or proliferating state into precursor of exhausted T cells, and notably into a terminal NK-like phenotype. In parallel, following infusion, CAR+ T cells undergo a similar differentiation trajectory, showing increased proliferation, metabolic activity and exhaustion when compared to circulating CAR- T cells. The subset of NK-like CAR+ T cells was associated with increasing levels of circulating proinflammatory cytokines, including innate-like IL-12 and IL-18. These results demonstrate that differentiation and phenotype of CAR+ T cells are determined by non-CAR induced signals that are shared with endogenous T cells, and condition the patients’ immune-recovery.One Sentence SummaryCAR+ and CAR- CD8+ T cells share a differentiation trajectory terminating in an NK-like phenotype that is associated with increased inflammatory cytokines levels.Graphical Abstract
Identification of novel nutrient-sensitive gene regulatory networks in amniocytes from fetuses with spina bifida
Authors: White Marina , Arif-Pardy Jayden , Connor Kristin L 
Published: April 2022

AbstractNeural tube defects (NTDs) remain among the most common congenital anomalies. Contributing risk factors include genetics and nutrient deficiencies, however, a comprehensive assessment of nutrient-gene interactions in NTDs is lacking. We applied a nutrient-focused gene expression analysis pipeline to identify nutrient-sensitive gene regulatory networks in amniocyte gene expression data (GSE4182) from fetuses with NTDs (cases; n=3) and fetuses with no congenital anomalies (controls; n=5). Differentially expressed genes (DEGs) were screened for having nutrient cofactors. Nutrient-dependent transcriptional regulators (TRs) that regulated DEGs, and nutrient-sensitive miRNAs with a previous link to NTDs, were identified. Of the 880 DEGs in cases, 10% had at least one nutrient cofactor. DEG regulatory network analysis revealed that 39% and 52% of DEGs in cases were regulated by 22 nutrient-sensitive miRNAs and 10 nutrient-dependent TRs, respectively. Zinc- and B vitamin-dependent gene regulatory networks (Zinc: 10 TRs targeting 50.6% of DEGs; B vitamins: 4 TRs targeting 37.7% of DEGs, 9 miRNAs targeting 17.6% of DEGs) were dysregulated in cases. We identified novel, nutrient-sensitive gene regulatory networks not previously linked to NTDs, which may indicate new targets to explore for NTD prevention or to optimise fetal development.
Estimating epidemiological quantities from repeated cross-sectional prevalence measurements
Authors: Abbott Sam , Funk Sebastian 
Published: April 2022

AbstractBackgroundRepeated measurements of cross-sectional prevalence of Polymerase Chain Reaction (PCR) positivity or seropositivity provide rich insight into the dynamics of an infection. The UK Office for National Statistics (ONS) Community Infection Survey publishes such measurements for SARS-CoV-2 on a weekly basis based on testing enrolled households, contributing to situational awareness in the country. Here we present estimates of time-varying and static epidemiological quantities that were derived from the estimates published by ONS.MethodsWe used a gaussian process to model incidence of infections and then estimated observed PCR prevalence by convolving our modelled incidence estimates with a previously published PCR detection curve describing the probability of a positive test as a function of the time since infection. We refined our incidence estimates using time-varying estimates of antibody prevalence combined with a model of antibody positivity and waning that moved individuals between compartments with or without antibodies based on estimates of new infections, vaccination, probability of seroconversion and waning.ResultsWe produced incidence curves of infection describing the UK epidemic from late April 2020 until early 2022. We used these estimates of incidence to estimate the time-varying growth rate of infections, and combined them with estimates of the generation interval to estimate time-varying reproduction numbers. Biological parameters describing seroconversion and waning, while based on a simple model, were broadly in line with plausible ranges from individual-level studies.ConclusionsBeyond informing situational awareness and allowing for estimates using individual-level data, repeated cross-sectional studies make it possible to estimate epidemiological parameters from population-level models. Studies or public health surveillance methods based on similar designs offer opportunities for further improving our understanding of the dynamics of SARS-CoV-2 or other pathogens and their interaction with population-level immunity.
Using DeepLabCut for tracking body landmarks in videos of children with dyskinetic cerebral palsy: a working methodology
Authors: Haberfehlner Helga , van de Ven Shankara S. , van der Burg Sven , Aleo Ignazio , Bonouvrié Laura A. , Harlaar Jaap , Buizer Annemieke I. , van der Krogt Marjolein M. 
Published: April 2022

AbstractMarkerless motion tracking is a promising technique to capture human movements and postures. It could be a clinically feasible tool to objectively assess movement disorders within severe dyskinetic cerebral palsy (CP). Here, we aim to evaluate tracking accuracy on clinically recorded video data.Method94 video recordings of 33 participants (dyskinetic CP, 8-23 years; GMFCS IV-V, i.e. non-ambulatory) from a previous clinical trial were used. Twenty-second clips were cut during lying down as this is a postion for this group of children and young adults allows to freely move. Video image resolution was 0.4 cm per pixel. Tracking was performed in DeepLabCut. We evaluated a model that was pre-trained on a human healthy adult data set with an increasing number of manually labeled frames (0, 1, 2, 6, 10, 15 and 20 frames per video). To assess generalizability, we used 80% of videos for the model development and evaluated the generalizability of the model using the remaining 20%. For evaluation the mean absolute error (MAE) between DeepLabCut’s prediction of the position of body points and manual labels was calculated.ResultsUsing just the pre-trained adult human model yielded a MAE of 121 pixels. An MAE of 4.5 pixels (about 1.5 cm) could be achieved by adding 15-20 manual labels. When applied to unseen video clips (i.e. generalization set), the MAE was 33 pixels with a dedicated model trained on 20 frames per videos.ConclusionAccuracy of tracking with a standard pre-trained model is insufficiently to automatically assess movement disorders in dyskinetic CP. However, manually adding labels improves the model performance substantially. In addition, the methodology proposed within our study is applicable to check the accuracy of DeepLabCut application within other clinical data set.
Birth anthropometry among three Asian ethnic groups in Singapore – new growth charts
Authors: Sensaki Sonoko , Mao Yinan , Biswas Agnihotri , Amutha Chinnadurai , Amin Zubair , Cook Alex R , Lee Jiun 
Published: April 2022

AbstractObjectiveWe analyse birth anthropometry of Asian babies and its socioeconomic exposures, develop gestational age and gender-specific birth anthropometry charts and compare to the widely used Fenton chart.DesignRetrospective observational study.SettingDepartment of Neonatology at the National University Hospital in Singapore.Population or sampleWe report data from 52 220 Chinese, Indian and Malay infants, born from 1991-1997 and from 2010-2017 in Singapore.MethodsThe BW, length and head circumference are each modelled with maternal exposures using general additive model. Anthropometry charts are built using smoothed centile curve and compared with Fenton charts using binomial test.Main outcome measuresBW, head circumference, crown-heel length.ResultsIn contrast to the marked differences in birth anthropometry among these ethnic populations, when exposed to a uniform socioeconomic environment, their intrauterine growth and birth anthropometry were almost identical. From the gestational age specific anthropometric charts, until about late prematurity, Asian growth curves, as derived from our cohort, mirrored that of Fenton’s; thereafter, Asian babies showed a marked reduction in growth velocity.ConclusionsThese findings suggest comparative slowing of intrauterine growth among Asian babies towards term gestation. This phenomenon may be explained by two possible postulations, firstly, restrictive effects of a smaller uterus of shorter Asian women towards term and secondly, early maturation and senescence of fetoplacental unit among Asians. In clinical practice the new birth anthropometry charts will more accurately identify true fetal growth restriction as well as true postnatal growth failure in preterm infants when applied to the appropriate population.FundingSingapore Population Health Improvement Centre (NMRC/CG/C026/2017_NUHS).
Psychosocial and psychological Interventions’ effectiveness among Nurses in Intensive Care Units caring for pediatric patients: A Systematic Review and Meta-Analysis
Authors: Choi Mi-Hyang , Lee Mi-Soon 
Published: April 2022

AbstractPurposeThis review aimed to evaluate the effectiveness of psychosocial and psychological interventions in nurses among intensive care units caring for pediatric patients.MethodsThis study was applied to the Participants, Intervention, Comparisons, Outcomes, Timing of Outcome Measurement, Settings, Study Design and PubMed, EMBASE, CINAHL databases were searched. To estimate the effect size, a meta-analysis of the studies was performed using the RevMan 5.3 program. The effect size used was the standardized mean difference.ResultsOf 1,630 studies identified, 4 met the inclusion criteria, and 3 studies were used to estimate the effect size of psychosocial and psychological interventions. The primary outcome variable of these studies was stress. The effect of the intervention program on stress was also found to have no effect in individual studies, and the overall effect size was not statistically significant (SMD = -0.06; 95% CI: -0.33, 0.20; Z = 0.48, p = 0.630). However, according to the individual literature included in this study, after the stress management program was applied as a group, a significant stress reduction was shown in the experimental group (p = 0.021).ConclusionsThese results show that psychosocial and psychological interventions were effective in stress management by a group approach. Therefore, it is necessary to develop psychosocial support interventions for stress management of nurses among intensive care units caring for pediatric patients more diversely.
Lessons from a pandemic
Authors: Eggli Yves , Rousson Valentin 
Published: April 2022

AbstractObjectivesSeveral interventions have been used around the world trying to contain the SARS-Cov-2 pandemic, such as quarantine, prohibition of mass demonstrations, isolation of sick people, tracing of virus carriers, semi-containment, promotion of barrier gestures, development of rapid auto-tests and vaccines among others. We propose a simple model to evaluate the potential impact of such interventions.MethodsA model for the reproduction number of an infectious disease including three main contexts of infection (indoor mass events, public indoor activities and household) and seven parameters is considered. We illustrate how these parameters could be obtained from the literature or from expert assumptions, and we apply the model to describe 20 scenarios that can typically occur during the different phases of a pandemic.ResultsThis model provides a useful framework for better understanding and communicating the effects of different (combinations of) possible interventions, while encouraging constant updating of expert assumptions to better match reality.ConclusionThis simple approach will bring more transparency and public support to help governments to think, decide, evaluate and adjust what to do during a pandemic.
Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: analysis of an international, multicenter migrants screening study
Authors: Gelaw Sifrash Meseret , Kik Sandra V. , Ruhwald Morten , Ongarello Stefano , Egzertegegne Tesfa Semagne , Gorbacheva Olga , Gilpin Christopher , Marano Nina , Lee Scott , Phares Christina R. , Medina Victoria , Amatya Bhaskar , Denkinger Claudia M. 
Published: April 2022

AbstractThe aim of this study was to independently evaluate the diagnostic accuracy of three artificial intelligence (AI)-based computer aided detection (CAD) systems for detecting pulmonary tuberculosis (TB) on global migrants screening chest x-ray (CXR) cases.Retrospective clinical data and CXR images were collected from the International Organization for Migration (IOM) pre-migration health assessment TB screening global database for US-bound migrants. A total of 2,812 participants were included in the dataset, of which 1,769 (62.9%) had accompanying microbiological test results. All CXRs were interpreted by three CAD systems (CAD4TB v6, Lunit INSIGHT v4.9.0, and qXR v2) offline and re-interpreted by two expert radiologists in a blinded fashion. The performance was evaluated using receiver operating characteristics curve (ROC), estimates of sensitivity and specificity at different CAD thresholds against both microbiological and radiological reference standards (MRS and RadRS, respectively).The area under the curve against MRS was highest for Lunit (0.85; 95% CI 0.83−0.87), followed by qXR (0.75; 95% CI 0.72−0.77) and then CAD4TB (0.71; 95% CI 0.68−0.73). At a set specificity of 70%, Lunit had the highest sensitivity (54.5%; 95% CI 51.7–57.3); at a set sensitivity of 90%, specificity was also highest for Lunit (81.4%; 95% CI 77.9–84.6). The CAD systems performed comparable to sensitivity (98.3%), and except CAD4TB, to specificity (13.7 %) of expert radiologist. Similar trends were observed when using RadRS.In conclusion, the study demonstrated that the three CAD systems had broadly similar diagnostic accuracy with regard to TB screening, and comparable accuracy to expert radiologist. Compared with different reference standards, Lunit performed better than both qXR and CAD4TB against MRS, and better than qXR against RadRS. Overall, these findings suggest that CAD systems could be a useful tool for TB screening programs in remote, high TB prevalent places where access to expert radiologists may be limited.
Decontamination of Geobacillus Stearothermophilus Using the Arca Aerosolized Hydrogen Peroxide Decontamination System
Authors: Mead Loren , Mathison Tanner , Richards Anne Marie 
Published: April 2022

AbstractIntroductionIn response to the limited supply of personal protective equipment during the pandemic caused by SARS-CoV-2, recent studies demonstrate that gaseous H2O2 is an effective decontaminant of N95 filtering facepiece respirators to enable reuse of these items in a clinical setting. This paper evaluates the efficacy of the Arca Aerosolized Hydrogen Peroxide Decontamination System (Arca), a novel aerosolized H2O2 decontamination system, using biologic indicator testing.Materials and MethodsThe Arca produces and circulates H2O2 aerosol inside of a sealed stainless steel chamber. The Arca’s decontamination efficacy was evaluated in 8 decontamination trials with 2 H2O2 concentrations (3% and 12%) and 4 decontamination cycle durations (45, 60, 90, and 120 minutes). Efficacy was evaluated by testing: 1) the concentration in parts per million (ppm) of H2O2 produced inside the chamber and the concentration in ppm of H2O2 vented from the chamber, and 2) the decontamination of Mesa Biologic Indicator filter strips (BI) inoculated with Geobacillus Stearothermophilus. Control tests were conducted by submerging BI strips in 3mL of 3% and 12% H2O2 for 120 minutes (negative controls) and by not exposing one BI strip to H2O2 (positive control).ResultsGreater than 5000 ppm of H2O2 was detected on the concentration strips inside the chamber for each of the eight decontamination trials. No vented H2O2 was detected on the external concentration strips after any decontamination trial. No growth was observed for any of the negative controls after seven days. The positive control was positive for growth.ConclusionThe Arca Aerosolized Hydrogen Peroxide Decontamination System is effective at decontaminating bacterial G. Stearothermophilus at a cycle time of 45 minutes utilizing 6mL of 3% H2O2 solution.
Determinants of mobility decline in nephrology-referred patients with CKD: a longitudinal cohort study
Authors: Bae Se Ri , Goodson David A. , Vargas Chenoa R. , Kim Tae Youn , Begue Gwenaelle , Delgado Cynthia , Robinson-Cohen Cassianne , Gamboa Jorge , Himmelfarb Jonathan , de Boer Ian H. , Kestenbaum Bryan , Roshanravan Baback 
Published: April 2022

AbstractBackground and ObjectiveChronic kidney disease (CKD) is associated with loss of muscle quality leading to mobility limitation and decreased independence. Identifying predictors of gait speed decline may help target rehabilitative therapies to those at highest risk of mobility impairment.Design, setting and participants, and measurementsThe current prospective cohort study recruited ambulatory patients with stage 1-4 CKD (eGFR 15-89 ml/min/1.73m2) from nephrology clinics. Predictors included demographic and clinical variables including GFR estimated using serum cystatin C. Outcomes were average change in gait speed (m/s) per year and inclusion in the top tertile of gait speed decline over 3 years. Linear mixed models and relative risk regression were used to estimate associations with annual gait speed changes and fastest tertile of decline.ResultsAmong 213 participants, 81% were male, 22% were black and 43% had diabetes. Mean age was 57±13 years, median follow-up 3.15 years, mean baseline eGFRcysc 47.9±21ml/min/1.73 m2, and median baseline gait speed 0.95m/s [IQR 0.81, 1.10]. Lower baseline eGFRcysc was associated with more rapid loss of gait speed (−0.029 m/s/year [95% CI -0.042, -0.015] per 30 ml/min/1.73 m2 lower eGFR; p<0.001). Diabetes was associated with -0.024m/s/year faster change (95% CI -0.042, -0.007; p=.007). Lower eGFRcysc was associated with a 49% greater risk of rapid gait speed decline (IRR 1.49; 95% CI 1.11, 2.00, p=.008) after adjustment.Prevalent cardiovascular disease and African American race were associated with a 45% greater (IRR 1.45; 95% CI 1.04, 2.01, p=.03) and 58% greater rate of rapid gait speed decline (IRR 1.58; 95% CI 1.09, 2.29, p=.02), respectively.ConclusionsAmong ambulatory, disability-free patients with CKD, lower eGFRcysc and diabetes status were associated with faster gait speed decline. Lower eGFRcysc, cardiovascular disease, and African American race were associated with rapid gait speed decline.
Visualising Emergency Department Wait Times; Rapid Iterative Testing to Determine Patient Preferences for Displays
Authors: Walker Katie , Potter Eden , Hwang Indae , Dwyer Tim , Egerton-Warburton Diana , Joe Keith , Hutton Jennie , Freeman Sam , Flynn Daphne 
Published: April 2022

AbstractVisualising patient wait times in emergency departments for patients and families is increasingly common, following the development of prediction models using routinely collected patient demographic, urgency and flow data. Consumers of an emergency department wait time display will have culturally and linguistically diverse backgrounds, are more likely to be from under-served populations and will have varied data literacy skills. The wait times are uncertain, the information is presented when people are emotionally and physically challenged, and the predictions may inform high stakes decisions. In such a stressful environment, simplicity is crucial and the visual language must cater to the diverse audience. When wait times are conveyed well, patient experience improves. Designers must ensure the visualisation is patient-centred and that data are consistently and correctly interpreted. In this article, we present the results of a design study at three hospitals in Melbourne, Australia, undertaken in 2021. We used rapid iterative testing and evaluation methodology, with patients and families from diverse backgrounds as participants, to develop and validate a wait time display. We present the design process and the results of this project. Patients, families and staff were eligible to participate if they were awaiting care in the emergency department, or worked in patient reception and waiting areas. The patient-centred approach taken in our design process varies greatly from past work led by hospital administrations, and the resulting visualisations are very distinct. Most currently displayed wait time visualisations could be adapted to better meet end-user needs. Also of note, we found that techniques developed by visualisation researchers for conveying temporal uncertainty tended to overwhelm the diverse audience rather than inform. There is a need to balance precise and comprehensive information presentation against the strong need for simplicity in such a stressful environment.