bluuebunny/crossref_metadata_2025 huggingface dataset:
Youth Vaping During the Early Stages of the COVID-19 Pandemic Period: Adjusted Annual Changes in Vaping Between the Pre-COVID and Initial COVID-Lockdown Waves of the COMPASS Study
Authors: Leatherdale Scott T , Bélanger Richard E , Gansaonré Rabi Joël , Cole Adam G , Haddad Slim
Published: April 2022

Background

Adolescence is a critical period for vaping onset. The purpose of this article was to examine the effect of the early stages of the COVID-19 pandemic period on youth vaping.

Methods

We used 3-year linked data from the COMPASS study, including 7585 Canadian (Quebec, Ontario) adolescents from which 1949 completed all three survey waves (pre-COVID-19 [2018, 2019] and online [2020] during the early pandemic period [May–July 2020]) and provided vaping data. Structural equation modeling (SEM) and difference-in-difference (DD) models were used to estimate pre-COVID-19 to initial COVID-19 pandemic period change (2019–2020) in vaping (monthly, weekly, daily) compared with 2018–2019 change to adjust for age-related effects. Models were adjusted for age of entry into the cohort and sociodemographic characteristics.

Results

In the SEM and DD models, the proportion of youth who were monthly and weekly vaping increased from 2018 to 2019 but decreased from 2019 to 2020; daily vaping increased across all waves. However, for all vaping outcomes modeled, the expected increases from the pre-COVID-19 wave (2019) to the initial COVID-19 period wave (2020) were lesser relative to the changes seen across the 2018 to 2019 waves.

Conclusion

The early stages of the COVID-19 pandemic period appear to be associated with a reduction in the proportion of youth who were monthly and weekly vapers in our adjusted longitudinal models. While daily vaping increased over this same period of time, the magnitude of the increase in our adjusted longitudinal models appears attenuated by the early stages of the pandemic.

Implications

This large prospective study of youth that included pre-pandemic data is unique in that we were able to identify that the early stages of the COVID-19 pandemic period was associated with a reduction in the proportion of youth who were monthly and weekly vapers in our adjusted longitudinal models. Conversely, the proportion of youth who were daily vaping increased over this same period of time, but the magnitude of the increase appears smaller than expected during the early stages of the pandemic in our adjusted longitudinal models. This study provides novel robust evidence that the patterns of vaping most aligned with onset and progression (i.e., monthly and weekly use) appear attenuated during the initial pandemic period.
Remote Versus In-Person Learning During COVID-19: Comparison of E-Cigarette Susceptibility and Ever Use Among a Diverse Cohort of 6th-Grade Students in Texas
Authors: Mantey Dale S , Omega-Njemnobi Onyinye , Ruiz Felisa A , Chen Baojiang , Springer Andrew E , Kelder Steven H
Published: April 2022

Background

In response to SARS-CoV2 (COVID-19), school districts incorporated remote learning as a mitigation strategy. This study examines the association between classroom setting (ie, on-campus versus remote) and e-cigarette susceptibility or ever use among a sample of Texas public middle school students.

Methods

Data from n = 985 students enrolled in the CATCH My Breath E-Cigarette Prevention Program trial were collected in Spring 2021. Participants were 6th-grade students in urban Texas. E-cigarette use was examined using the “at-risk” definition described by FDA, indicating either: (1) susceptible never user; or (2) experimental ever use. A multilevel, logistic regression model examined the association between classroom setting and e-cigarette susceptibility/ever use. Covariates included sex, race/ethnicity, academic achievement, household e-cigarette use, perceived school connectedness, and school-level economic status. Models account for nesting within school district. Analyses stratified by race/ethnicity were also conducted.

Results

Overall, 36.3% of the sample were susceptible never users or ever e-cigarette users. The sample was comprised of 55.0% on-campus and 45.0% remote learners. On-campus learners had greater odds of reporting e-cigarette susceptibility or ever use (aOR: 1.45; p = .014). These findings were observed among Latino (aOR: 1.77; p = .026) and White (aOR: 2.10; p = .099) but not African American/Black (aOR: 0.86; p = .728) youth.

Conclusions

On-campus learning during the Spring 2021 semester was associated with greater risk for e-cigarette susceptibility or ever use among a diverse sample of 6th-grade students. E-cigarette susceptibility and ever use is a risk factor for progression to long-term e-cigarette use in later adolescence.

Implications

As school districts prepare to return to on-campus learning in 2022, a focused approach to e-cigarette prevention may be needed to prevent widespread e-cigarette initiation and continued use. Further, study findings demonstrate a need for further research on the school environment as a determinant of e-cigarette use.
Delayed Tuberculosis Treatment and Cost of Care in a Low-Incidence Country
Authors: O’Connell James , Reidy Niamh , McNally Cora , de Barra Eoghan , Stanistreet Debbi , McConkey Samuel
Published: April 2022

Background

Tuberculosis (TB) elimination requires high-quality, timely care. In countries with a low incidence of TB, such as Ireland, delayed diagnosis is common. This evaluation aimed to determine the factors that predict patient-related and health care provider–related delays in TB management and to establish how TB care cost is affected by care delays.

Methods

Health care records of patients with signs and symptoms of TB evaluated by a tertiary service in Ireland between July 1, 2018, and December 31, 2019, were reviewed to measure and determine predictors of patient-related delays, health care provider–related delays, and the cost of TB care. Outcomes were compared against benchmarks derived from the literature.

Results

Thirty-seven patients were diagnosed with TB, and 51% (19/37) had pulmonary TB (PTB). The median patient-related delay was 60 days among those with PTB, greater than the benchmark derived from the literature (38 days). The median health care provider–related delay among patients with PTB was 16 days and, although similar to the benchmark (median, 22 days; minimum, 11 days; maximum, 36 days), could be improved. The health care provider–related delay among patients with EPTB was 66 days, greater than the benchmark (42 days). The cost of care was €8298 and, while similar to that reported in the literature (median, €9319; minimum, €6486; maximum, €14 750), could be improved. Patient-related delays among those with PTB predicted care costs.

Conclusions

Patient-related and health care provider–related delays in TB diagnosis in Ireland must be reduced. Initiatives to do so should be resourced.
Relative Effectiveness of MF59 Adjuvanted Trivalent Influenza Vaccine vs Nonadjuvanted Vaccines During the 2019–2020 Influenza Season
Authors: Imran Mahrukh , Puig-Barbera Joan , Ortiz Justin R , Fischer Lauren , O’Brien Dan , Bonafede Machaon , Mansi James A , Boikos Constantina
Published: April 2022

Background

Age-related immunosenescence may impair the immune response to vaccination in older adults. Adjuvanted influenza vaccines are designed to overcome immune senescence in older adults. This study estimated the relative vaccine effectiveness (rVE) of MF59-adjuvanted trivalent inactivated influenza vaccine (aIIV3) vs egg-derived quadrivalent inactivated influenza vaccine (IIV4e) and high-dose trivalent inactivated influenza vaccine (HD-IIV3) in preventing influenza-related medical encounters in the 2019–2020 US season.

Methods

This retrospective cohort study used electronic medical records linked to pharmacy and medical claims data. The study population included adults age ≥65 years with a record of aIIV3, IIV4e, or HD-IIV3 vaccination. A doubly robust inverse probability of treatment weighting model was used to derive adjusted odds ratios (ORs). rVE was calculated by (1 – ORadjusted)*100 and was determined overall and separately for age subgroups. An exploratory analysis evaluated the outcome separately in inpatient and outpatient settings.

Results

Subjects received aIIV3 (n = 936 508), IIV3e (n = 651 034), and HD-IIV3 (n = 1 813 819), and influenza-related medical encounters were recorded in 0.5%, 0.9%, and 0.7% of each cohort, respectively. Overall, the rVE of aIIV3 was 27.5% (95% CI, 24.4% to 30.5%) vs IIV4e and 13.9% (95% CI, 10.7% to 17.0%) vs HD-IIV3. aIIV3 had a more favorable rVE in inpatient and outpatient settings. Findings remained consistent across age subgroups and during alternative seasonal dates.

Conclusions

Adults age ≥65 years vaccinated with aIIV3 had fewer influenza-related medical encounters compared with IIV4e or HD-IIV3 during the 2019–2020 US influenza season.
An evaluation of the validity of an in vitro and an in situ/in vitro procedure for assessing protein digestibility of blood meal, feather meal and a rumen-protected lysine prototype
Authors: Estes Kari A , Yoder Peter S , Stoffel Clayton M , Hanigan Mark D
Published: April 2022

In vitro procedures are commonly used to estimate rumen protein degradability and protein digestibility of feed ingredients. However, it is unclear how well these assays correlate to in vivo data. The objectives of this work were to compare postruminal protein availability estimates from one in vitro procedure and one in situ/in vitro procedure with in vivo observations for blood meal (BM), feather meal (FM), and a rumen-protected lysine prototype (RP-Lys). The FM and BM used for this experiment were subsamples of material assessed in vivo by an isotope-based method and the RP-Lys subsamples were of a prototype tested in two in vivo trials: a lactation trial and by plasma appearance. Subsamples of the BM (n = 14) and the FM (n = 22) were sent to each of three different laboratories for in vitro or in situ/in vitro analysis of crude protein (CP) and determination of rumen undegraded protein (RUP) and digested RUP (dRUP). Subsamples of the RP-Lys (n = 5) were sent to one laboratory for in vitro analysis of CP, RUP, and dRUP. Two diets containing BM or FM were assessed using the Cornell Net Carbohydrate and Protein System (CNCPS) v6.55 with ingredient inputs derived from either the CNCPS feed library, the isotope dilution method, or an average of the in vitro results from the three laboratories to determine how much the differences among estimates affected ingredient values. In vitro dRUP estimates for BM from one laboratory closely matched those determined in vivo (66.7% vs. 61.2%, respectively), but no in vitro estimates for FM matched the in vivo values. Surprisingly, there were significant differences in protein digestibility estimates from the modified three-step procedure across the two laboratories for BM (P < 0.0001) and for FM (P < 0.0001) indicating significant variation among laboratories in application of the method. Within all laboratories, BM estimates were reported in a narrow range (CV values of 2.6 or less). However, when testing multiple samples of FM or the RP-Lys prototype, CV values within a laboratory ranged up to 11 and 34, respectively. For the RP-Lys, dRUP estimates from the in vitro method were roughly half of that determined by the in vivo methods suggesting poor concordance between the in vitro and in vivo procedures for this ingredient. The inconsistencies within and among laboratories accompanied with dissimilarities to in vivo data is problematic for application in nutrition models. Additional refinement to the in vitro techniques is warranted.
Long-Distance Transport of Puccinia striiformis f. sp. tritici by Upper Airflow on the Yunnan–Guizhou Plateau Disrupts the Balance of Agricultural Ecology in Central China
Authors: Huang Liang , Yang Heng , Xia Chongjing , Li Hongfu , Wang Jifeng , Wang Aolin , Zhang Min , Kang Xiaohui , Gao Li , Zhou Yilin , Chen Wanquan , Liu Taiguo
Published: April 2022

Long-distance dispersal of plant pathogens in the air can establish diseases in other areas and lead to an increased risk of large-scale epidemics. Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most destructive diseases of wheat in China. Hubei is an important overwintering region for Pst in China, and this overwintering region is a determinant of stripe rust severity in eastern China. In 2017, stripe rust disease caused a pandemic in the Hubei region and resulted in great yield losses of wheat. To explain the disease pandemic, a total of 595 single-lesion samples of stripe rust were collected in spring, including 204 in five provinces in 2017 and 391 in four provinces in 2018, and genotyped with 13 simple sequence repeat makers. The samples were classified into 12 subpopulations based on the locations and year of collection. Genetic diversity was determined for the collection and each subpopulation. Differentiation and gene flow were determined between subpopulations. STRUCTURE analyses and discriminant analysis of principal components were conducted, and the results were used to infer the relationships between subpopulations. Our study revealed a new route of Pst transmission from the Yunnan–Guizhou Plateau to the Hubei region. The Pst inoculum of northwestern Hubei came from Gansu in the northwest, whereas the inoculum in southern Hubei came from the Yunnan–Guizhou Plateau via upper airflow. After the initial inocula infected wheat plants and multiplied in northern and southern Hubei, urediniospores produced in these regions further spread together along the middle reach of Hanshui Valley and made exchanges there. The finding of the new transmission route of Pst is important for improving integrated stripe rust disease management, which should have a profound impact on the balance of agricultural ecology in China.
Two Main Routes of Spore Migration Contributing to the Occurrence of Wheat Stripe Rust in the Jiangsu and Zhejiang Coastal Sporadic Epidemiological Region in 2019, Based on Phenotyping and Genotyping Analyses
Authors: Ju Meng , Liu Wei , Wang Lin , Sun Mudi , Kang Zhensheng , Zhao Jie
Published: April 2022

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is a destructive disease in many countries. In China, wheat stripe rust generally occurs in northwestern and southwestern China and sporadically in the Jiangsu and Zhejiang coastal epidemiological region (JZER), where an outbreak of the disease occurred in 2019. To understand the population structure and potential inoculum sources of the pathogen in this region, 171 isolates collected from 93 wheat fields of 53 counties in 10 provinces were phenotyped with two sets of wheat differentials and genotyped with 20 pairs of single-nucleotide polymorphism primers. Phenotype tests indicated that identical races (CYR34, CYR33, Su11-139, and Su11-14-1) detected in Jiangsu and Zhejiang were shared with the oversummering regions (Gansu), overwintering regions (Hubei, Henan, and Shaanxi), and Yun-Gui epidemiological regions (Yunnan and Guizhou). In JZER, races CYR32, G22-14, and G22-68 were detected in Jiangsu, but not in Zhejiang, and Su11-208 was identified in Zhejiang, but not in Jiangsu. Genotypic analysis revealed remarkable gene flows among the Jiangsu, Yunnan, Henan, and Anhui populations, as well as those of Zhejiang, Guizhou, and Sichuan, showing that wheat stripe rust in Zhejiang and Jiangsu was from spores that migrated from different routes. Major gene flows were detected between the Jiangsu and Zhejiang populations. P. striiformis f. sp. tritici from both overwintering regions (Yunnan, Sichuan, Guizhou, Henan, Hubei, and Shaanxi) and oversummering regions (Gansu) contributed to the wheat stripe rust epidemic in the JZER region in 2019.
More than a Virulence Factor: Patulin Is a Non-Host-Specific Toxin that Inhibits Postharvest Phytopathogens and Requires Efflux for Penicillium Tolerance
Authors: Bartholomew Holly P. , Bradshaw Michael J. , Macarisin Otilia , Gaskins Verneta L. , Fonseca Jorge M. , Jurick Wayne M.
Published: April 2022

Mycotoxin contamination is a leading cause of food spoilage and waste on a global scale. Patulin, a mycotoxin produced by Penicillium spp. during postharvest pome fruit decay, causes acute and chronic effects in humans, withstands pasteurization, and is not eliminated by fermentation. While much is known about the impact of patulin on human health, there are significant knowledge gaps concerning the effect of patulin during postharvest fruit–pathogen interactions. Application of patulin on six apple cultivars reproduced some blue mold symptoms that were cultivar-independent and dose-dependent. Identical symptoms were also observed in pear and mandarin orange. Six Penicillium isolates exposed to exogenous patulin exhibited delayed germination after 24 h, yet all produced viable colonies in 7 days. However, four common postharvest phytopathogenic fungi were completely inhibited by patulin during conidial germination and growth, suggesting the toxin is important for Penicillium to dominate the postharvest niche. Using clorgyline, a broad-spectrum efflux pump inhibitor, we demonstrated that efflux plays a role in Penicillium auto-resistance to patulin during conidial germination. The work presented here contributes new knowledge of patulin auto-resistance, its mode of action, and inhibitory role in fungal–fungal interactions. Our findings provide a solid foundation to develop toxin and decay mitigation approaches.
Cancer diagnosis in primary care after second pandemic year in Catalonia: a time-series analysis of primary care electronic health records covering about five million people
Authors: Mora Núria , Guiriguet Carolina , Cantenys Roser , Méndez-Boo Leonardo , Marzo-Castillejo Mercè , Benítez Mència , Fina Francesc , Fàbregas Mireia , Hermosilla Eduardo , Mercadé Albert , Medina Manuel , Coma Ermengol
Published: April 2022

Background

During COVID-19 pandemic, incidence of chronic disease had drastically been reduced due to health care interruptions. The aim of this study is to analyze cancer diagnosis during the two years of the COVID-19 pandemic.

Methods

Time-series study of malignant neoplasms, using data from the primary care electronic health records from January 2014 to December 2021. We obtained the expected monthly incidence using a temporary regression adjusted by trend and seasonality. We additionally compared cancer incidence in 2019 with those of 2020 and 2021 using the T-Test. We performed analysis globally, by sex and by type of cancer.

Results

During 2020, the incidence of cancer had reduced by -21% compared to 2019 (p-value <0.05). Greater reductions were observed during lockdown in early 2020 (>40%) and with some types of cancers, especially prostate and skin cancers (−29.6% and -26.9% respectively, p-value<0.05). Lung cancers presented statistically non-significant reductions in both years. Cancer diagnosis returned to expected around March 2021, and incidence in 2021 was similar to that of 2019 (overall difference of 0.21%, p=0.967). However, -11% reduction still was found when comparing pandemic months of 2020-2021 with pre-pandemic months (2019-2020)

Conclusions

Although primary care cancer diagnostic capacity in 2021 has returned to pre-pandemic levels, missing diagnoses during the last two years have not been fully recovered.

Key messages

Cancer diagnoses have dramatically dropped during 2020 worldwide.

We observe a -21% decline in 2020, but a return to pre-pandemic diagnosis capacity in 2021.

A -11% outstanding drop was still found comparing pre-pandemic to pandemic months.

Reductions were greater during the lockdown (>40%).

Lung and breast cancers presented fewer reductions while prostate and skin cancers had greater drops.

Missing diagnoses during the last two years have not been fully recovered
Mechanisms of central brain atrophy in multiple sclerosis
Authors: Klistorner Samuel , Barnett Michael H , Graham Stuart L , Yiannikas Con , Parratt John , Klistorner Alexander
Published: April 2022

Background and objectives

The measurement of longitudinal change in ventricular volume has been suggested as an accurate and reliable surrogate of central brain atrophy (CBA), potentially applicable to the everyday management of patient with multiple sclerosis (MS). To better understand mechanisms underlying central brain atrophy in RRMS patients we investigated the contribution of inflammatory activity in different lesion compartments to the enlargement of ventricular CSF volume. In addition, we investigated the role of the severity of lesional tissue damage in CBA progression.

Methods

Pre- and post-gadolinium 3D-T1, 3D fluid-attenuated inversion recovery (FLAIR) and diffusion tensor images were acquired from 50 patients with relapsing MS. Lesional activity between baseline and 48 months was analysed on FLAIR images using custom-build software, which independently segmented expanding part of the chronic lesions, new confluent lesions and new free-standing lesions. The degree of lesional tissue damage was assessed by change in Mean Diffusivity (MD). Volumetric change of lateral ventricles was used as a measure of central brain atrophy.

Results

During follow-up ventricles expanded on average by 12.6+/-13.7%. There was significant increase of total lesion volume, 69.3% of which was due to expansion of chronic lesions and 30.7%-to new (confluent and free-standing) lesional activity. There was high degree of correlation between volume of combined lesional activity and CBA (r2=0.67), which became considerably stronger when lesion volume was adjusted by the degree of tissue damage severity (r2=0.81). Linear regression analysis explained 90% of CBA variability and revealed that chronic lesion expansion was by far the largest contributor to ventricular enlargement (Standardized Coefficient Beta 0.68 (p<0.001) for expansion of chronic lesions compared to 0.29 (p=<0.001) for confluent lesions and 0.23 (p=0.001) for free-standing new lesions). Age and baseline ventricular volume also provided significant input to the model.

Discussion

Our data suggest that central brain atrophy is almost entirely explained by the combination of the volume and severity of lesional tissue activity. Furthermore, the expansion of chronic lesions plays a central role in this process.
A distinct four-value blood signature of pyrexia under combination therapy of malignant melanoma with BRAF/MEK-inhibitors evidenced by an algorithm-defined pyrexia score
Authors: Schaefer Hannah , Rübben Albert , Esser André , Araujo Arturo , Persa Oana-Diana , Leijs Marike
Published: April 2022

Pyrexia is a frequent adverse event of BRAF/MEK-inhibitor combination therapy in patients with metastasized malignant melanoma (MM). The study’s objective was to identify laboratory changes which might correlate with the appearance of pyrexia. Initially, data of 38 MM (14 with pyrexia) patients treated with dabrafenib plus trametinib were analysed retrospectively. Graphical visualization of time series of laboratory values suggested that a rise in C-reactive-protein, in parallel with a fall of leukocytes and thrombocytes, were indicative of pyrexia. Additionally, statistical analysis showed a significant correlation between lactate dehydrogenase (LDH) and pyrexia. An algorithm based on these observations was designed using a deductive approach in order to calculate a pyrexia score (PS) for each laboratory assessment in treated patients. A second independent data set with 28 MM patients (8 with pyrexia) was used for the validation of the algorithm. PS based on the four parameters CRP, LDH, leukocyte and thrombocyte numbers, were statistically significantly higher in pyrexia patients, differentiated between groups (F=20,8; p=<0,0001) and showed a significant predictive value for the development of pyrexia (F=6,24; p=0,013). We provide first evidence that pyrexia in patients treated with BRAF/MEK-blockade can be identified and predicted by an algorithm that calculates a score.

SUMMARY STATEMENT

Pyrexia is a severe side effect of BRAF/MEK-inhibitor therapy of malignant melanoma. An algorithm based on the four laboratory values, leukocyte and thrombocyte counts, CRP and LDH, was designed for detecting pyrexia. The used heuristic approach might serve as a blueprint for analysing unevenly sampled or even incomplete clinical data.
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

The 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

Chimeric 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 Summary

CAR+ 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

Neural 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

Background

Repeated 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.

Methods

We 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.

Results

We 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.

Conclusions

Beyond 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.
Prediction models with survival data: a comparison between machine learning and the Cox proportional hazards model
Authors: Hazewinkel Audinga-Dea , Gelderblom Hans , Fiocco Marta
Published: April 2022

Recent years have seen increased interest in using machine learning (ML) methods for survival prediction, chiefly using big datasets with mixed datatypes and/or many predictors Model comparisons have frequently been limited to performance measure evaluation, with the chosen measure often suboptimal for assessing survival predictive performance. We investigated ML model performance in an application to osteosarcoma data from the EURAMOS-1 clinical trial (NCT00134030). We compared the performance of survival neural networks (SNN), random survival forests (RSF) and the Cox proportional hazards model. Three performance measures suitable for assessing survival model predictive performance were considered: the C-index, and the time-dependent Brier and Kullback-Leibler scores. Comparisons were also made on predictor importance and patient-specific survival predictions. Additionally, the effect of ML model hyper-parameters on performance was investigated. All three models had comparable performance as assessed by the C-index and Brier and Kullback-Leibler scores, with the Cox model and SNN also comparable in terms of relative predictor importance and patient-specific survival predictions. RSFs showed a tendency for according less importance to predictors with uneven class distributions and predicting clustered survival curves, the latter a result of tuning hyperparameters that influence forest shape through restrictions on terminal node size and tree depth. SNNs were comparatively more sensitive to hyperparameter misspecification, with decreased regularization resulting in inconsistent predicted survival probabilities. We caution against using RSF for predicting patient-specific survival, as standard model tuning practices may result in aggregated predictions, which is not reflected in performance measure values, and recommend performing multiple reruns of SNNs to verify prediction consistency.
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

Markerless 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.

Method

94 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.

Results

Using 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.

Conclusion

Accuracy 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

Objective

We 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.

Design

Retrospective observational study.

Setting

Department of Neonatology at the National University Hospital in Singapore.

Population or sample

We report data from 52 220 Chinese, Indian and Malay infants, born from 1991-1997 and from 2010-2017 in Singapore.

Methods

The 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 measures

BW, head circumference, crown-heel length.

Results

In 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.

Conclusions

These 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.

Funding

Singapore 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

Purpose

This review aimed to evaluate the effectiveness of psychosocial and psychological interventions in nurses among intensive care units caring for pediatric patients.

Methods

This 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.

Results

Of 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).

Conclusions

These 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

Objectives

Several 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.

Methods

A 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.

Results

This 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.

Conclusion

This 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

The 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

Introduction

In 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 Methods

The 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).

Results

Greater 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.

Conclusion

The 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

Background and Objective

Chronic 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 measurements

The 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.

Results

Among 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.

Conclusions

Among 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.