bluuebunny/crossref_metadata_2025 huggingface dataset:
Do Smokers’ Perceptions of the Harmfulness of Nicotine Replacement Therapy and Nicotine Vaping Products as Compared to Cigarettes Influence Their Use as an Aid for Smoking Cessation? Findings from the ITC Four Country Smoking and Vaping Surveys
Authors: Yong Hua-Hie , Gravely Shannon , Borland Ron , Gartner Coral , Michael Cummings K , East Katherine , Tagliaferri Scott , Elton-Marshall Tara , Hyland Andrew , Bansal-Travers Maansi , Fong Geoffrey T
Published: April 2022

Introduction

This study examined whether smokers’ harm perceptions of nicotine replacement therapy (NRT) and nicotine vaping products (NVPs) relative to cigarettes predicted their subsequent use as smoking cessation aids during their last quit attempt (LQA).

Aims and Methods

We analyzed data from 1,315 current daily smokers (10+ cigarettes per day) who were recruited at Wave 1 (2016), and who reported making a quit attempt by Wave 2 (2018) of the International Tobacco Control Four Country Smoking and Vaping Surveys in Australia, Canada, England, and the United States. We used multinomial logistic regression models to examine prospective associations between harm perceptions of (a) NRT and (b) NVPs and their use at LQA, controlling for socio-demographic and other potential confounders.

Results

Smokers who perceive that (a) NRT and (b) NVPs are much less harmful than cigarettes were more likely to subsequently use the respective product as an aid than using no aid or other aids during LQA (adjusted relative risk ratio [aRRR] = 3.79, 95%CI = 2.16–6.66; and aRRR = 2.11, 95%CI = 1.29–3.45, respectively) compared to smokers who perceive these products as equally or more harmful. Additionally, those who perceive NVPs as much less harmful than cigarettes were less likely to use NRT as a quit aid (aRRR = 0.34, 95%CI = 0.20–0.60). No country variations for these associations were found.

Conclusions

This study found that smokers’ perceptions of the harmfulness of (a) NRT and (b) NVPs relative to cigarettes predicted the respective product use when trying to quit smoking. Corrective education targeting misperceptions of nicotine products’ relative harmfulness may facilitate their use for smoking cessation.

Implications

Nicotine replacement therapy and nicotine vaping products are two commonly used smoking cessation aids. This study demonstrates that misperceptions of the harms of nicotine products relative to cigarettes influence their use for smoking cessation. Believing that nicotine vaping products are much less harmful than cigarette smoking may lead some smokers to prefer these products over nicotine replacement therapy to aid smoking cessation. Education targeting misperceptions of nicotine products’ harmfulness relative to cigarettes may enable smokers to make informed choices about which are appropriate to aid smoking cessation.
Exposure to Negative News Stories About Vaping, and Harm Perceptions of Vaping, Among Youth in England, Canada, and the United States Before and After the Outbreak of E-cigarette or Vaping-Associated Lung Injury (‘EVALI’)
Authors: East Katherine , Reid Jessica L , Burkhalter Robin , Wackowski Olivia A , Thrasher James F , Tattan-Birch Harry , Boudreau Christian , Bansal-Travers Maansi , Liber Alex C , McNeill Ann , Hammond David
Published: April 2022

Introduction

Little is known about the international impact of E-cigarette or Vaping-Associated Lung Injury (‘EVALI’) on youth perceptions of vaping harms.

Methods

Repeat cross-sectional online surveys of youth aged 16–19 years in England, Canada, and the United States before (2017, 2018), during (2019 August/September), and after (2020 February/March, 2020 August) the ‘EVALI’ outbreak (N = 63380). Logistic regressions assessed trends, country differences, and associations between exposure to negative news stories about vaping and vaping harm perceptions.

Results

Exposure to negative news stories increased between 2017 and February–March 2020 in England (12.6% to 34.2%), Canada (16.7% to 56.9%), and the United States (18.0% to 64.6%), accelerating during (2019) and immediately after (February–March 2020) the outbreak (p < .001) before returning to 2019 levels by August 2020. Similarly, the accurate perception that vaping is less harmful than smoking declined between 2017 and February–March 2020 in England (77.3% to 62.2%), Canada (66.3% to 43.3%), and the United States (61.3% to 34.0%), again accelerating during and immediately after the outbreak (p < .001). The perception that vaping takes less than a year to harm users’ health and worry that vaping will damage health also doubled over this period (p ≤ .001). Time trends were most pronounced in the United States. Exposure to negative news stories predicted the perception that vaping takes less than a year to harm health (Adjusted Odds Ratio = 1.55, 1.48-1.61) and worry that vaping will damage health (Adjusted Odds Ratio = 1.32, 1.18-1.48).

Conclusions

Between 2017 and February–March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after ‘EVALI’. Effects were seen in all countries but were most pronounced in the United States.

Implications

This is the first study examining changes in exposure to news stories about vaping, and perceptions of vaping harms, among youth in England, Canada, and the United States before, during, and after ‘EVALI’. Between 2017 and February–March 2020, youth exposure to negative news stories, and perceptions of vaping harms, increased, and increases were exacerbated during and immediately after ‘EVALI’. By August 2020, exposure to negative news stories returned to 2019 levels, while perceptions of harm were sustained. Exposure to negative news stories also predicted two of the three harm perception measures. Overall, findings suggest that ‘EVALI’ may have exacerbated youth’s perceptions of vaping harms internationally.
Androgen receptor polyQ alleles and COVID-19 severity in men: a replication study
Authors: López-Rodríguez Rosario , Ruiz-Hornillos Javier , Cortón Marta , Almoguera Berta , Minguez Pablo , Pérez-Tomás María Elena , Barreda-Sánchez María , Mancebo Esther , Ondo Lorena , Martinez-Ramas Andrea , Fernández-Caballero Lidia ,   the STOP_Coronavirus Study Group, Paz-Artal Estela , Guillen-Navarro Encarna , Ayuso Carmen
Published: April 2022

Ample evidence indicates a sex-related difference in severity of COVID-19, with less favorable outcomes observed in men. Genetic factors have been proposed as candidates to explain this difference. The polyQ polymorphism in the androgen receptor gene has been recently described as a genetic biomarker of COVID-19 severity. In this study, we analyzed this association in a large cohort of 1136 men classified into three groups according to their degree of COVID-19 severity, finding a similar distribution of polyQ alleles among severity groups. Therefore, our results do not support the role of this polymorphism as a biomarker of COVID-19 severity.
Association of Mass Distribution of Rapid Antigen Tests and SARS-CoV-2 Prevalence: Results from NIH-CDC funded Say Yes! Covid Test program in Michigan
Authors: Soni Apurv , Herbert Carly , Baek Jonggyu , Shi Qiming , Marquez Juan , Harman Emma , Kheterpal Vik , Nowak Chris , Suvarna Thejas , Lin Honghuang , Heetderks William , Zai Adrian , Cohen-Wolkowiez Michael , Corbie-Smith Giselle , Kibbe Warren , Gerber Ben S. , Hafer Nathaniel , Barton Bruce , Broach John , McManus David
Published: April 2022

Importance

Wide-spread distribution of diagnostics is an integral part of the United States’ COVID-19 strategy; however, few studies have assessed the effectiveness of this intervention at reducing transmission of community COVID-19.

Objective

To assess the impact of the Say Yes! Covid Test (SYCT!) Michigan program, a population-based program that distributed 20,000 free rapid antigen tests within Ann Arbor and Ypsilanti, Michigan in June-August 2021, on community prevalence of SARS-CoV-2.

Design

This ecological study analyzed cases of SARS-CoV-2 from March to October 2021 reported to the Washtenaw County Health Department.

Setting

Washtenaw County, Michigan

Participants

All residents of Washtenaw County

Interventions

Community-wide distribution of 500,000 rapid antigen tests for SARS-CoV-2 to residents of Ann Arbor and Ypsilanti, Michigan. Each household was limited to one test kit containing 25 rapid antigen tests.

Main Outcome and Measures

Community prevalence of SARS-CoV-2, as measured through 7-day average cases, in Ann Arbor and Ypsilanti was compared to the rest of Washtenaw County. A generalized additive model was fitted with non-parametric trends for control and relative differences of trends in the pre-intervention, intervention, and post-intervention periods to compare intervention municipalities of Ann Arbor and Ypsilanti to the rest of Washtenaw County. Model results were used to calculate average cases prevented in the post-intervention period.

Results

In the post-intervention period, there were significantly lower standardized average cases in the intervention communities of Ann Arbor/Ypsilanti compared to the rest of Washtenaw County (p<0.001). The estimated standardized relative difference between Ann Arbor/Ypsilanti and the rest of Washtenaw County was -0.016 cases per day (95% CI: -0.020 to -0.013), implying that the intervention prevented 40 average cases per day two months into the post-intervention period if trends were consistent.

Conclusions and Relevance

Mass distribution of rapid antigen tests may be a useful mitigation strategy to combat community transmission of SARS-CoV-2, especially given the recent relaxation of social distancing and masking requirements.
Spatial prediction of COVID-19 pandemic dynamics in the United States
Authors: Ak Cigdem , Chitsazan Alex D. , Gönen Mehmet , Etzioni Ruth , Grossberg Aaron J.
Published: April 2022

Background

The impact of COVID-19 across the United States has been heterogeneous, with some areas demonstrating more rapid spread and greater mortality than others. We used geographically-linked data to test the hypothesis that the risk for COVID-19 is spatially defined and sought to define which features are most closely associated with elevated COVID-19 spread and mortality.

Methods

Leveraging geographically-restricted social, economic, political, and demographic information from U.S. counties, we developed a computational framework using structured Gaussian processing to predict county-level case and death counts during both the initial and the nationwide phases of the pandemic. After identifying the most predictive spatial features, we applied an unsupervised clustering algorithm, topic modelling, to identify groups of features that are most closely associated with COVID-19 spread.

Findings

We found that the inclusion of spatial features modeled case counts very well, with overall Pearson’s correlation coefficient (PCC) and R2of 0.96 and 0.84 during the initial phase and 0.95 and 0.87, respectively, during the nationwide phase. The most frequently selected features were associated with urbanicity and 2020 presidential vote margins. When trained using death counts, models revealed similar performance metrics, with the addition of aging metrics to those most frequently selected. Topic modeling showed that counties with similar socioeconomic and demographic features tended to group together, and some feature sets were associated with COVID-19 dynamics. Unsupervised clustering of counties based on these topics revealed groups of counties that experienced markedly different COVID-19 spread.

Interpretation

Spatial features explained most of the variability in COVID-19 dynamics between counties. Topic modeling can be used to group collinear features and identify counties with similar features in epidemiologic research.
Quickest Way to Less Headache Days: an operational research model and its implementation for Chronic Migraine
Authors: Lo Irene , Zhang Pengfei
Published: April 2022

Structured Abstract

Background

Choosing migraine prevention medications often involves trial and error. Operations research methodologies, however, allow us to derive a mathematically optimum way to conduct such trial and error processes.

Objective

Given probability of success (defined as 50% reduction in headache days) and adverse events as a function of time, we seek to develop and solve an operations research model, applicable to any arbitrary patient, minimizing time until discovery of an effective migraine prevention medication. We then seek to apply our model to real life data for chronic migraine prevention.

Methods

We develop a model as follows: Given a set of D many preventive medications, for drug i in D, we describe the likelihood of reaching 50% headache day reduction over the course of time, (ti,1 ≤ ti,2 ≤ …) by probability (pi,1 ≤ pi,2 ≤ …). We additionally assume a probability of adverse event(qi,1 ≤ qi,2 ≤ …). We then solve for a sequence of prescription trials that minimizes the expected time until an effective drug is identified.

Once we identify the optimal sequence for our model, we estimate p, t and q for topiramate and OnabotulinumtoxinA based on the FORWARD study by Rothrock et al as well as erenumab data published by Barbanti et al. at IHC 2019.

Results

The solution for our model is to order the drugs by probability of efficacy per unit time. When the efficacy of each drug i is known only for one period ti and there are no adverse effects, then the optimum sequence is to administer drug i for ti periods in decreasing order pi/ti. In general, the optimum sequence is to administer drug i for ti,k* periods in decreasing order of the Gittins index σi,k*

Based on the above data, the optimum sequence of chronic migraine prevention medication is a trial of erenumab for 12 weeks, followed by a trial of OnabotulinumtoxinA for 32 weeks, followed by a trial of topiramate for 32 weeks.

Conclusion

We propose an optimal sequence for preventive medication trial for patients with chronic migraine. Since our model makes limited assumptions on the characteristics of disease, it can be readily applied also to episodic migraine, given the appropriate data as input.

Indeed, our model can be applied to other scenarios so long as probability of success/adverse event as a function of time can be estimated. As such, we believe our model may have implications beyond our sub-specialty.

Trial Registration

Not applicable.
Lymphoid Enhancer-Binding Factor 1 (LEF1) immunostaining as a surrogate of β-catenin (CTNNB1)mutations
Authors: Hewer Ekkehard , Fischer Pascal , Vassella Erik , Knabben Laura , Imboden Sara , Mueller Michael D. , Rau Tilman T. , Dettmer Matthias S.
Published: April 2022

Background

Activating mutations affecting exon 3 of the β-catenin (CTNNB1) gene result in constitutive activation of WNT signaling and are a diagnostic hallmark of several tumor entities including desmoid-type fibromatosis. They also define clinically relevant tumor subtypes within certain entities such as endometrioid carcinoma. In diagnostics, β-catenin immunohistochemistry is widely used as a surrogate forCTNNB1mutations, but is often difficult to assess in practice, given that the characteristic nuclear translocation may be focal or hard to distinguish from spillover of the normal membranous staining.

Study design and methods

We therefore examined Lymphoid Enhancer-Binding Factor 1 (LEF1) immunostaining, a nuclear marker of WNT activation that serves as a potential surrogate ofCTNNB1mutations.

Results

In a cohort of endometrial carcinomas (n=255) LEF1 predictedCTNNB1mutations correctly in 85%, while β-catenin was 76% accurate. Across a variety of entities characterized byCTNNB1mutations as putative drivers, we found diffuse and strong expression of LEF1 in 77% of cases. LEF1 immunostaining proved easier to interpret than β-catenin immunostaining in 54% of cases, more difficult in 1% of cases, and comparable in the remaining cases.

Conclusion

We conclude that LEF1 immunostaining is a useful surrogate marker forCTNNB1mutations. It favorably complements β-catenin immunohistochemistry and outperforms the latter as a single marker.
Effectiveness of an Inactivated Covid-19 Vaccine with Homologous and Heterologous Boosters against Omicron in Brazil
Authors: Ranzani Otavio T. , Hitchings Matt D.T. , Leite de Melo Rosana , de França Giovanny V. A. , Fernandes Cássia de Fátima R. , Lind Margaret L , Scaramuzzini Torres Mario Sergio , Tsuha Daniel Henrique , David Leticia C. S. , Said Rodrigo F. C. , Almiron Maria , de Oliveira Roberto D. , Cummings Derek A.T. , Dean Natalie E , Andrews Jason R. , Ko Albert I. , Croda Julio
Published: April 2022

The effectiveness of inactivated vaccines (VE) against symptomatic and severe COVID-19 caused by omicron is unknown. We conducted a nationwide, test-negative, case-control study to estimate VE for homologous and heterologous (BNT162b2) booster doses in adults who received two doses of CoronaVac in Brazil in the Omicron context. Analyzing 1,386,544 matched-pairs, VE against symptomatic disease was 8.6% (95% CI, 5.6-11.5) and 56.8% (95% CI, 56.3-57.3) in the period 8-59 days after receiving a homologous and heterologous booster, respectively. During the same interval, VE against severe Covid-19 was 73.6% (95% CI, 63.9-80.7) and 86.0% (95% CI, 84.5-87.4) after receiving a homologous and heterologous booster, respectively. Waning against severe Covid-19 after 120 days was only observed after a homologous booster. Heterologous booster might be preferable to individuals with completed primary series inactivated vaccine.
COVID-19 vaccination coverage by company size and the effects of socioeconomic factors and workplace vaccination in Japan: a cohort study
Authors: Mori Koji , Mori Takahiro , Nagata Tomohisa , Ando Hajime , Hino Ayako , Tateishi Seiichiro , Tsuji Mayumi , Muramatsu Keiji , Fujino Yoshihisa ,   the CORoNa Work Project
Published: April 2022

Background

Vaccination is considered the most effective control measure against COVID-19. Vaccine hesitancy and equitable vaccine allocation are important challenges to disseminating developed vaccines. To promote COVID-19 vaccination coverage, the government of Japan established the workplace vaccination program. However, while it appears that the program was effective in overcoming vaccine hesitancy, the program may have hindered the equitable allocation of vaccines because it mainly focused on employees of large companies. We investigated the relationship between company size and COVID-19 vaccination completion status of employees and the impact of the workplace vaccination program on this relationship.

Methods

We conducted an internet-based prospective cohort study from December 2020 (baseline) to December 2021. The data were collected using a self-administered questionnaire survey. Briefly, 27,036 workers completed the questionnaire at baseline and 18,560 at follow-up. After excluding ineligible respondents, we finally analyzed the data from 15,829 participants. At baseline, the participants were asked about the size of the company they worked for, and at follow-up they were asked about the month in which they received their second COVID-19 vaccine dose and the availability of a company-arranged vaccination opportunity.

Results

In each month throughout the observation period, the odds of having received a second COVID-19 vaccine dose were significantly lower for small-company employees than for large-company employees in the sex- and age-adjusted model. This difference decreased after adjusting for socioeconomic factors, and there was no significant difference after adjusting for the availability of a company-arranged vaccination opportunity.

Conclusions

The workplace vaccination program implemented in Japan to control the COVID-19 pandemic may have been effective in overcoming vaccine hesitancy in workers; however, it may have caused an inequitable allocation of vaccines between companies of different sizes. Because people who worked for small companies were less likely to be vaccinated, it will be necessary to enhance support of vaccination for this population in the event of future infectious disease outbreaks.

Trial registration

Not applicable.
Risk models based on non-cognitive measures may identify presymptomatic Alzheimer’s disease
Authors: Yang Jingjing , Oveisgharan Shahram , Liu Xizhu , Wilson Robert S , Bennett David A , Buchman Aron S
Published: April 2022

Background

Alzheimer’s disease is a progressive disorder without a cure. Developing risk prediction models for detecting presymptomatic Alzheimer’s disease using non-cognitive measures is necessary to enable early interventions.

Objective

Examine if non-cognitive metrics alone can be used to construct risk models to identify adults at risk for Alzheimer’s dementia and cognitive impairment.

Methods

Clinical data from older adults without dementia from the Memory and Aging Project (MAP, n=1179) and Religious Orders Study (ROS, n=1103) were analyzed using Cox proportional hazard models to develop risk prediction models for Alzheimer’s dementia and cognitive impairment. Models using only non-cognitive covariates were compared to models that added cognitive covariates. All models were trained in MAP, tested in ROS, and evaluated by the AUC of ROC curve.

Results

Models based on non-cognitive covariates alone achieved AUC (0.800,0.785) for predicting Alzheimer’s dementia (3,5) years from baseline. Including additional cognitive covariates improved AUC to (0.916,0.881). A model with a single covariate of composite cognition score achieved AUC (0.905,0.863). Models based on non-cognitive covariates alone achieved AUC (0.717,0.714) for predicting cognitive impairment (3,5) years from baseline. Including additional cognitive covariates improved AUC to (0.783,0.770). A model with a single covariate of composite cognition score achieved AUC (0.754,0.730).

Conclusion

Risk models based on non-cognitive metrics predict both Alzheimer’s dementia and cognitive impairment. However, non-cognitive covariates do not provide incremental predictivity for models that include cognitive metrics in predicting Alzheimer’s dementia, but do in models predicting cognitive impairment. Further improved risk prediction models for cognitive impairment are needed.
An investigation of age-related neuropathophysiology in autism spectrum disorder using fixel-based analysis of corpus callosum white matter micro- and macrostructure
Authors: Kirkovski Melissa , Singh Mervyn , Dhollander Thijs , Fuelscher Ian , Hyde Christian , Albein-Urios Natalia , Donaldson Peter H , Enticott Peter G
Published: April 2022

Background

Corpus callosum anomalies are commonly noted in autism spectrum disorder (ASD). Given the complexity of its microstructural architecture, with crossing fibers projecting throughout, we applied fixel-based analysis to probe white matter micro- and macrostructure within this region. As ASD is a neurodevelopmental condition with noted abnormalities in brain growth, age was also investigated.

Methods

Data for participants with (N=54) and without (N=50) ASD, aged 5-34 years, were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Within each site, indices of fiber density (FD), fiber cross-section (FC), and combined fiber density and cross-section (FDC) were compared between those groups.

Results

Young adolescents with ASD (age = 11.19 ± 7.54) showed reduced macroscopic FC and FDC compared to age-matched neurotypical controls (age = 10.04 ± 4.40). Reduced FD and FDC was noted in a marginally older ASD (age 13.87 ± 3.15) cohort compared to matched controls (age = 13.85 ± 2.90). Among the oldest cohorts, a non-significant trend indicated reduced FD in older adolescents/young adults with ASD (age = 17.07 ± 3.56) compared to controls (age = 16.55 ± 2.95). There was a positive correlation between age and callosal mean FC and FDC in the youngest cohort. When stratified by diagnosis, this finding remained only for the ASD sample.

Conclusion

White matter aberration appears greatest among younger ASD cohorts. In older adolescents and young adults, less of the corpus callosum seems affected. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.
Breast and Cervical Cancer Screening Rates in Student-Run Free Clinics: A Systematic Review
Authors: Xiao Sophia Ying , Major Catherine Kendall , O’Connell Katie A. , Lee David , Lin Christine , Sarino Esther , Chen Kevin
Published: April 2022

Objective

To assess rates of breast and cervical cancer screening at student-run free clinics to better understand challenges and strategies for advancing quality and accessibility of women’s health screening at student-run free clinics.

Data sources

We performed a systematic search of Ovid MEDLINE, PubMed, Web of Science, and Google Scholar databases from database inception to 2020 using keywords related to student-run clinics, breast cancer screening, and cervical cancer screening.

Study eligibility criteria

We included all English-language publications describing screening rates of breast and/or cervical cancer at student-run free clinics within the United States. Five authors screened abstracts and reviewed full texts for inclusion.

Study appraisal and synthesis methods

Two reviewers extracted data independently for each publication using a structured data extraction table. Disagreements were resolved by group consensus. Two reviewers then assessed for risk of bias for each text using a modified Agency for Healthcare Research and Quality checklist for cross-sectional and prevalence studies. Results were synthesized qualitatively due to study heterogeneity.

Results

Of 3634 references identified, 12 references met study inclusion criteria. The proportion of patients up-to-date on breast cancer screening per guidelines ranged from 45% to 94%. The proportion of patients up-to-date on cervical cancer screening per guidelines ranged from 40% to 88%.

Conclusion

Student-run free clinics can match breast and cervical cancer screening rates amongst uninsured populations nationally, though more work is required to bridge the gap in care that exists for the underinsured and uninsured.
Interpretation of non-responders to SARS-CoV-2 vaccines using WHO International Standard
Authors: Zeng Qiang , Yang Xue , Gao Qi , Lin Biao-yang , Li Yong-zhe , Huang Gang , Xu Yang
Published: April 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic with more than 485 millions infected. Questions about non-responders to SARS-CoV-2 vaccines remain unaddressed. Here, we report data from people after administering the complete dose of SARS-CoV-2 vaccines using the World Health Organization International Standard for anti-SARS-CoV-2 immunoglobulin. Our study showed that immune cells such as CD4 cells, CD8 cells, and B cells and anti-spike immunoglobulin G levels were significantly reduced in the elderly. There were 7.5% non-responders among the 18–59 yr group and 11.7% in the ≥60 yr group. A titer of anti-SARS-CoV-2 spike immunoglobulin G is blew 50 BAU/mL to be considered as non-responders at intervals of 30 to 90 days after the last vaccine dose. Booster vaccination may be recommended for non-responders to reduce the disease severity and mortality.
Size matters - the impact of nucleus size on results from spatial transcriptomics
Authors: Mohammadi Elyas , Chojnowska Katarzyna , Bieńkowski Michał , Kostecka Anna , Koczkowska Magdalena , Żmijewski Michał A. , Jąkalski Marcin , Ingelsson Martin , Filipowicz Natalia , Olszewski Paweł , Davies Hanna , Wierzbicka Justyna M. , Hyman Bradley T. , Dumanski Jan P. , Piotrowski Arkadiusz , Mieczkowski Jakub
Published: April 2022

Visium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover novel modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei. Here, we defined the effect of Consecutive Slices Data Integration (CSDI) on results from spatial transcriptomic study of human postmortem brains. CSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.
Metabolic alkalosis and mortality in COVID-19
Authors: Jiang Zhifeng
Published: April 2022

Background

As a new infectious disease affecting the world, COVID-19 has caused a huge impact on countries around the world. At present, its specific pathophysiological mechanism has not been fully clarified. We found in the analysis of the arterial blood gas data of critically ill patients that the incidence of metabolic alkalosis in such patients is high.

Method

We retrospectively analyzed the arterial blood gas analysis results of a total of 16 critically ill patients in the intensive ICU area of Xiaogan Central Hospital and 42 severe patients in the intensive isolation ward, and analyzed metabolic acidosis and respiratory acidosis. Metabolic alkalosis and respiratory alkalosis, and the relationship between metabolic alkalosis and death.

Result

Among the 16 critically ill patients, the incidence of metabolic alkalosis was 100%, while the incidence of metabolic alkalosis in severe patients was 50%; the mortality rate in critically ill patients was 81.3%, and 21.4% in severe patients; The mortality of all patients with metabolic alkalosis is 95.5%,and 4.5% in without metabolic alkalosis.

Conclusion

The incidence of metabolic alkalosis in critically ill COVID-19 patients is high, and it is associated with high mortality.
Changes in Apolipoprotein A1 and B, Glucose Metabolism, and Skeletal Muscle Mass in Peripheral Artery Disease after Endovascular Treatment: A Pilot Study
Authors: Ikeda Takeshi , Komiyama Hidenori , Miyakuni Tomoyo , Takano Masamichi , Matsushita Masato , Kobayashi Nobuaki , Asai Kuniya , Shimizu Wataru , Miyauchi Yasushi
Published: April 2022

Peripheral artery disease impairs walking and physical activity, resulting in further loss of skeletal muscle. However, peripheral artery disease can be treated with endovascular treatment. The thigh muscle has been shown to correlate with systemic skeletal muscle volume. We assessed the changes in the metabolism of apolipoproteins A1 and B, blood glucose, and thigh muscle mass after endovascular treatment in above-the-knee peripheral artery disease where vessels supply the thigh muscle. Mid-thigh muscle volume was measured with computed tomography before and at 6 months after endovascular treatment. Apolipoproteins A1 and B, fasting blood glucose, post-load (75 g oral glucose tolerance test) 2 h-blood glucose, and glycated hemoglobin A1c (HbA1c) levels were measured concomitantly. The relationships between changes in apolipoproteins A1, apolipoproteins B, blood glucose, post-oral glucose tolerance test 2 h-blood glucose, Rutherford classification, and gain or loss of thigh muscle were investigated. Thigh muscle mass did not correlate with changes in apolipoproteins A1, B, fasting glucose, post-oral glucose tolerance test 2 h-blood glucose, HbA1c, and Rutherford classification. Among patients with muscle gain post-endovascular treatment, apolipoproteins A1 increased significantly, while apolipoproteins B levels were similar. Post-oral glucose tolerance test 2 h-blood glucose levels decreased. Preferable metabolic changes were observed in patients with skeletal muscle gain contrasted with muscle loss.
Using genetic information to define idiopathic pulmonary fibrosis in UK Biobank
Authors: Leavy Olivia C , Allen Richard J , Kraven Luke M , Morgan Ann , Tobin Martin D , Quint Jennifer K , Jenkins R Gisli , Wain Louise V
Published: April 2022

Introduction

Idiopathic pulmonary fibrosis (IPF) is a rare lung disease characterised by progressive scarring in the alveoli. IPF can be defined in population studies using electronic healthcare records (EHR) but recent genetic studies of IPF using EHR have shown an attenuation of effect size for known genetic risk factors when compared to clinically-derived datasets, suggesting misclassification of cases.

Methods

We used EHR (ICD-10, Read (2 & 3)) and questionnaire data to define IPF cases in UK Biobank, and evaluated these definitions using association results for the largest genetic risk variant for IPF (rs35705950-T, MUC5B). We further evaluated the impact of exclusions based on co-occurring codes for non-IPF pulmonary fibrosis and restricting codes according to changes in diagnostic practice.

Results

Odds ratio (OR) estimates for rs35705950-T associations with IPF defined using EHR and questionnaire data in UK Biobank were significant and ranged from 2.06 to 3.09 which was lower than those reported using clinically-derived IPF datasets (95% confidence intervals: 3.74, 6.66). Code-based exclusions of cases gave slightly closer effect estimates to those previously reported, but sample sizes were substantially reduced.

Discussion

We show that none of the UK Biobank IPF codes replicate the effect size for the association of rs35705950-T on IPF risk when using clinically-derived IPF datasets. Further code-based exclusions also did not lead to effect estimates closer to those expected. Whilst the apparent increased sample sizes available for IPF from general population cohorts may be of benefit, future studies should take these limitations of the case definition into account.

Key Messages

What is already known on this topic

UK Biobank is a very large prospective cohort that can be utilised to increase sample sizes for studies of rare diseases such as idiopathic pulmonary fibrosis (IPF). However, effect size estimates for genetic risk factors for IPF in UK Biobank and other general population cohorts, when defining cases using electronic healthcare records (EHR), are smaller than those estimated from clinically-derived IPF datasets.

What this study adds

Using Hospital Episode Statistics (HES) data, primary care data, death registry data and self-report data in UK Biobank, we used the association rs35705950-T, the largest genetic risk factor for IPF, to evaluate code-based definitions of IPF. We show that none of the available IPF coding replicates the effect size for rs35705950-T on IPF risk that is observed in clinically-derived IPF datasets.

How this study might affect research, practice or policy

Research using large general population cohorts and datasets for observational studies of IPF should take these limitations of EHR definitions of IPF into consideration.
Single-Molecule Analysis of DNA-binding proteins from Nuclear Extracts (SMADNE)
Authors: Schaich Matthew A. , Schnable Brittani L. , Kumar Namrata , Roginskaya Vera , Jakielski Rachel C. , Urban Roman , Zhong Zhou , Kad Neil M. , Van Houten Bennett
Published: April 2022

Single-molecule characterization of protein-DNA dynamics provides unprecedented mechanistic details about numerous nuclear processes. Here, we describe a new method that rapidly generates single-molecule information for fluorescently tagged proteins isolated from nuclear extracts of human cells. This approach determines binding lifetimes (koff), events per second (∼kon), positional dependence (specificity), and characterizes 1D diffusion along DNA. We demonstrated the wide applicability of this approach on three forms of DNA damage using seven native DNA repair proteins and two structural variants, including: poly(ADP-ribose) polymerase (PARP1), heterodimeric ultraviolet-damaged DNA-binding protein (UV-DDB), xeroderma pigmentosum complementation group C protein (XPC), and 8-oxoguanine glycosylase 1 (OGG1). By measuring multiple fluorescent colors simultaneously, we additionally characterized the assembly and disassembly kinetics of multi-protein complexes on DNA. Thus, Single-Molecule Analysis of DNA-binding proteins from Nuclear Extracts (SMADNE) provides new insights about damage recognition and represents a universal technique that can be used to rapidly characterize numerous protein-DNA interactions.
Highly multiplexed targeted plasma proteomics quantifies several hundred blood proteins in serum from colorectal carcinoma patients
Authors: Lesur Antoine , Bernardin François , Koncina Eric , Letellier Elisabeth , Kruppa Gary , Pierre-Olivier Schmit , Dittmar Gunnar
Published: April 2022

The rapid analysis of human serum and plasma can provide deep insights into changes of the blood proteome in response to different patient treatments or diseases. Targeted proteomics techniques, like SRM and PRM, can be utilized to monitor proteins at high sensitivitym but so far were limited to smaller protein panels, which can be monitored in one experiment. The recently, on a Bruker tims-TOF pro mass spectrometer, developed parallel reaction monitoring-parallel accumulation − serial fragmentation (prm-PASEF) method expands the standard PRM method by using ion-mobility. The use of ion mobility as a fourth separation dimension increases the proteome coverage while reducing the length of the necessary chromatogeaphic separation. By combining an isotope-labeled reference standard, which covers 579 plasma proteins, we were able to quantify 565 proteins in plasma using prm-PASEF, with the least abundant protein being quantified at 7 amol. We continued the analysis by combining the isotype-labeled reference standard with dia-PASEF, which allowed the quantification of 549 proteins. Both methods were used to analyze 20 patient plasma samples from a colorectal cancer (CRC) cohort. The analysis identified 16 differentially regulated proteins between the CRC patient and control individual plasma samples. 15 of the 16 proteins showed a high correlation to the mRNA expression in CRC tumor samples, showing the technique’ s potential for the rapid identification of potential biomarkers in larger cohorts, abolishing the need for preselection of potential biomarker proteins.

Graphical abstract
Clinically-relevant treatment of PDX models reveals patterns of neuroblastoma chemoresistance
Authors: Mañas Adriana , Aaltonen Kristina , Andersson Natalie , Hansson Karin , Adamska Aleksandra , Seger Alexandra , Yasui Hiroaki , van den Bos Hilda , Radke Katarzyna , Esfandyari Javanshir , Bhave Madhura Satish , Karlsson Jenny , Spierings Diana , Foijer Floris , Gisselsson David , Bexell Daniel
Published: April 2022

Chemotherapy resistance and relapses are common in high-risk neuroblastoma (NB), an aggressive pediatric solid tumor of the sympathetic nervous system. Here, we developed a clinically-relevant in vivo treatment protocol mimicking the first line five-chemotherapy treatment regimen of high-risk NB and applied this protocol to mice with MYCN-amplified NB patient-derived xenografts (PDXs). Genomic and transcriptomic analyses were used to reveal the genetic and non-genetic mechanisms involved in NB chemoresistance. We observed convergent and parallel evolution of key NB genetic aberrations over time. Intrinsic resistance to chemotherapy was associated with high genetic diversity and an embryonic phenotype. Relapsed NB PDX tumors with acquired resistance showed an immature mesenchymal-like phenotype resembling multipotent Schwann cell precursors that are found in the adrenal gland. NBs with a successful treatment response presented a lineage-committed adrenergic phenotype similar to normal neuroblasts, reduced cell cycle gene expression, and negative regulation of the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) cascade. NB organoids established from relapsed PDX tumors retained drug resistance, tumorigenicity, and transcriptional cell states ex vivo. This work sheds light on mechanisms involved in NB chemotherapy response in vivo and ex vivo using a clinically-relevant protocol, and emphasizes the importance of transcriptional cell states in treatment response. Detailed characterization of resistance mechanisms is essential for the development of novel treatment strategies in non-responsive or relapsed high-risk NB.

One Sentence Summary

COJEC chemotherapy treatment of neuroblastoma PDX models uncovers patterns of transcriptional plasticity and chemoresistance.
A Locally Activatable Sensor for Robust Quantification of Organellar Glutathione
Authors: Hübner Sarah , Quargnali Gianluca , Thallmair Sebastian , Rivera-Fuentes Pablo
Published: April 2022

Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signaling pathways. Achieving a detailed understanding of intracellular GSH trafficking and regulation depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Herein, we present a new GSH sensing platform, TRaQ-G, for live-cell imaging. This small-molecule/protein hybrid sensor possesses a unique reactivity turn-on mechanism that ensures that the small molecule is only sensitive to GSH in the desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein of choice to give a ratiometric response. Using TRaQ-G-mGold, we demonstrated that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. We also used this sensor, in combination with roGFP, to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.
Characterization of cell-fate decision landscapes by estimating transcription factor dynamics
Authors: Jiménez Sara , Schreiber Valérie , Mercier Reuben , Gradwohl Gérard , Molina Nacho
Published: April 2022

Modulation of gene expression during differentiation by transcription factors promotes cell diversity. Despite their role in cell fate decisions, no experimental assays estimate their regulatory activity in a high-throughput manner and at the single-cell resolution. We present FateCompass for identifying lineage-specific transcription factors across differentiation. It uses single-cell transcriptomics data to infer differentiation trajectories and transcription factor activities. We combined a probabilistic framework with RNA velocities or a differentiation potential to estimate transition probabilities and perform stochastic simulations. Also, we learned transcription factor activities using a linear model of gene regulation. Considering dynamic changes and correlations, we identified lineage-specific regulators. We applied FateCompass to an islet cell formation dataset from the mouse embryo, and we found known and novel potential cell-type drivers. Also, when applied to a differentiation protocol dataset towards beta-like cells, we pinpointed undescribed regulators of an off-target population, which were experimentally validated. Thus, as a framework for identifying lineage-specific transcription factors, FateCompass could have implications on hypothesis generation to increase the understanding of the gene regulatory networks driving cell fate choices.

Highlights

We developed FateCompass, a flexible pipeline to estimate transcription factor activities during cell-fate decision using single-cell RNA seq data.

FateCompass outlines gene expression stochastic trajectories by infusing the direction of differentiation using RNA velocity or a differentiation potential when RNA velocity fails.

Transcription factor dynamics allow the identification of time-specific regulatory interactions.

FateCompass predictions revealed known and novel cell-subtype-specific regulators of mouse pancreatic islet cell development.

Differential motif analysis predicts lineage-specific regulators of stem cell-derived human β- cells and sheds light on the cellular heterogeneity of β-cell differentiation protocols.

Experimental validation supports the proposed GRN controlling SC-EC differentiation predicted by FateCompass.
Evolutionary barriers to horizontal gene transfer in macrophage associated Salmonella
Authors: Bhatia Rama P. , Kirit Hande A. , Lewis Cecil M. , Sankaranarayanan Krithivasan , Bollback Jonathan P.
Published: April 2022

Horizontal gene transfer (HGT) is a powerful evolutionary force facilitating bacterial adaptation and emergence of novel phenotypes. Several factors, including environmental ones, are predicted to restrict HGT, but we lack systematic and experimental data supporting these predictions. Here, we address this gap by measuring the relative fitness of genes horizontally transferred from E. coli to S. enterica in infection relevant environments. We estimated the distribution of fitness effects in each environment and identified dosage-dependent effects across different environments are a significant barrier to HGT. The majority of genes were found to be deleterious. We also found longer genes had stronger negative fitness consequences than shorter ones, showing that gene length can significantly hinder HGT. Furthermore, fitness effects of transferred genes were found to be environmentally dependent. In summary, a substantial fraction of transferred genes had a significant fitness cost on the recipient, with both gene characteristics and the environment acting as evolutionary barriers to HGT.
Potent Human Broadly SARS-CoV-2 Neutralizing IgA and IgG Antibodies Effective Against Omicron BA.1 and BA.2
Authors: Planchais Cyril , Fernández Ignacio , Bruel Timothée , Dias de Melo Guilherme , Prot Matthieu , Beretta Maxime , Guardado-Calvo Pablo , Dufloo Jérémy , Molinos-Albert Luis M. , Backovic Marija , Chiaravalli Jeanne , Giraud Emilie , Vesin Benjamin , Conquet Laurine , Grzelak Ludivine , Planas Delphine , Staropoli Isabelle , Guivel-Benhassine Florence , Boullé Mikaël , Cervantes-Gonzalez Minerva ,   French COVID Cohort Study Group,   CORSER Study Group, Ungeheuer Marie-Noëlle , Charneau Pierre , van der Werf Sylvie , Agou Fabrice , Dimitrov Jordan D. , Simon-Lorière Etienne , Bourhy Hervé , Montagutelli Xavier , Rey Félix A. , Schwartz Olivier , Mouquet Hugo
Published: April 2022

Memory B-cell and antibody responses to the SARS-CoV-2 spike protein contribute to long-term immune protection against severe COVID-19, which can also be prevented by antibody-based interventions. Here, wide SARS-CoV-2 immunoprofiling in COVID-19 convalescents combining serological, cellular and monoclonal antibody explorations, revealed humoral immunity coordination. Detailed characterization of a hundred SARS-CoV-2 spike memory B-cell monoclonal antibodies uncovered diversity in their repertoire and antiviral functions. The latter were influenced by the targeted spike region with strong Fc-dependent effectors to the S2 subunit and potent neutralizers to the receptor binding domain. Amongst those, Cv2.1169 and Cv2.3194 antibodies cross-neutralized SARS-CoV-2 variants of concern including Omicron BA.1 and BA.2. Cv2.1169, isolated from a mucosa-derived IgA memory B cell, demonstrated potency boost as IgA dimers and therapeutic efficacy as IgG antibodies in animal models. Structural data provided mechanistic clues to Cv2.1169 potency and breadth. Thus, potent broadly neutralizing IgA antibodies elicited in mucosal tissues can stem SARS-CoV-2 infection, and Cv2.1169 and Cv2.3194 are prime candidates for COVID-19 prevention and treatment.