bluuebunny/crossref_metadata_2025 huggingface dataset:
Clonal transitions and phenotypic evolution in Barrett esophagus
Authors: Evans James A , Carlotti Emanuela , Lin Meng-Lay , Hackett Richard J , Passman Adam , Dunn Lorna , Elia George , Porter Ross J , McClean Mairi H , Hughes Frances , ChinAleong Joanne , Woodland Philip , Preston Sean L , Griffin S Michael , Lovat Laurence , Rodriguez-Justo Manuel , Wright Nicholas A , Jansen Marnix , McDonald Stuart AC
Published: April 2021

Background & Aims

Barrett esophagus (BE) is a risk factor for the development of esophageal adenocarcinoma, however our understanding of how Barrett esophagus evolves is still poorly understood. We demonstrate that dynamic clonal phenotypic changes occur at the gland level, the mechanism by which these changes evolve, and how diversity may play a role in progression.

Methods

We analyzed the distribution and diversity of gland phenotype between and within BE biopsies and the background mucosa of those that had progressed to dysplasia or developed BE post-esophagectomy, using immunohistochemistry and H&E analysis. Clonal relationships between distinct gland types were determined by laser capture microdissection sequencing of the mitochondrial genome.

Results

Five different non-dysplastic gland phenotypes were identified in a cohort of 64 patients biopsies taken at the same physical location in the esophagus; most non-dysplastic patients showed a single gland phenotype per biopsy, but some showed two or three gland types. We reveal a shared common ancestor between parietal cell-containing oxynto-cardiac glands and goblet cell-containing specialized Barrett glands through a shared somatic mtDNA mutation. We also reveal a similar relationship between specialized and cardiac-type glands, and specialized and Paneth cell-containing glands. The diversity of gland types was significantly increased adjacent to dysplasia compared to non-dysplastic BE and patients with post-esophagectomy BE, suggesting that gland diversity evolves in BE patients over time.

Conclusions

We have shown that the range of BE phenotypes represent an evolutionary process and that changes in gland diversity may play a role in progression. Furthermore, we demonstrate common ancestry between gastric and intestinal glands in BE.

Graphic abstract

A) The cardiac gland as the basic unit of Barrett esophagus that can evolve into phenotypes that adapt to the esophageal microenvironment. B) Phenotypic diversity of non-dysplastic glands is associated with the presence of dysplasia or cancer in patients with BE.
Loss of C2orf69 defines a fatal auto-inflammatory mitochondriopathy in Humans and Zebrafish
Authors: Wong Hui Hui , Seet Sze Hwee , Maier Michael , Traspas Ricardo Moreno , Lee Cheryl , Shan Zhang , Loh Abigail Y. T. , Chia Crystal Y. , Teoh Tze Shin , Sng Danielle , Cepni Ece , Nathan Fatima M. , Sirota Fernanda L. , Chao Liang , Tadahiro Mitani , Mbarek Hamdi , Georgiadou Danai , Sotiropoulou Kortessa , Paul Franziska , Pehlivan Davut , Lainé Candice , Chai Guoliang , Ali Nur Ain , Choo Siew Chin , Boisson Bertrand , Xue Shifeng , Kayserili Hulya , Zaki Maha , Isfort Robert J. , Bauer Peter , Rezaei Nima , Seyedpour Simin , Khotaei Ghamar Taj , Bascom Charles C. , Chaabouni Myriam , AlSubhi Afaf , Eyaid Wafaa , Işıkay Sedat , Gleeson Joseph G. , Lupski James R. , Casanova Jean-Laurent , Maurer-Stroh Sebastian , Bertoli-Avella Aida , Mathuru Ajay S. , Ho Lena , Bard Frederic , Reversade Bruno
Published: April 2021

Human C2orf69 is an evolutionary-conserved gene whose function is unknown. Here, we report 9 children from 5 unrelated families with a fatal syndrome consisting of severe auto-inflammation, progredient leukoencephalopathy with recurrent seizures that segregate homozygous loss-of-function C2orf69 variants. C2ORF69 orthologues, which can be found in most eukaryotic genomes including that of unicellular phytoplanktons, bear homology to esterase enzymes. We find that human C2ORF69 is loosely bound to the mitochondrion and its depletion affects mitochondrial membrane potential in human fibroblasts and neurons. Moreover, we show that CRISPR/Cas9-inactivation of zebrafish C2orf69 results in lethality by 8 months of age due to spontaneous epileptic seizures which is accompanied by persistent brain inflammation. Collectively, our results delineate a novel auto-inflammatory Mendelian disorder of C2orf69 deficiency that disrupts the development/homeostasis of the immune and central nervous systems as demonstrated in patients and in a zebrafish model of the disease.

One Sentence Summary

C2orf69 is a putative enzyme whose inactivation in humans and zebrafish causes a hitherto unknown auto-inflammatory syndrome.
Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders
Authors: Wolff Jan , Reißner Pamela , Hefner Gudrun , Normann Claus , Kaier Klaus , Binder Harald , Hiemke Christoph , Toto Sermin , Domschke Katharina , Marschollek Michael , Klimke Ansgar
Published: April 2021

Introduction

The aim of this study was to describe the number and type of drugs used to treat depressive disorders in inpatient psychiatry and to analyse the determinants of potential drug-drug interactions (pDDI) and potentially inappropriate medication (PIM).

Methods

Our study was part of a larger pharmacovigilance project funded by the German Innovation Funds. It included all inpatients with a main diagnosis in the group of depressive episodes (F32, ICD-10) or recurrent depressive disorders (F33) discharged from eight psychiatric hospitals in Germany between 1 October 2017 and 30 September 2018 or between 1 January and 31 December 2019.

Results

The study included 14,418 inpatient cases. The mean number of drugs per day was 3.7 (psychotropic drugs = 1.7; others = 2.0). Thirty-one percent of cases received at least five drugs simultaneously (polypharmacy). Almost one half of all cases received a combination of multiple antidepressant drugs (24.8%, 95% CI 24.1% - 25.5%) or a treatment with antidepressant drugs augmented by antipsychotic drugs (21.9%, 95% CI 21.3% - 22.6%). The most frequently used antidepressants were selective serotonin reuptake inhibitors, followed by serotonin and norepinephrine reuptake inhibitors and tetracyclic antidepressants. In multivariate analyses, cases with recurrent depressive disorders and cases with severe depression were more likely to receive a combination of multiple antidepressant drugs (Odds ratio recurrent depressive disorder: 1.56, 95% CI 1.41 - 1.70, severe depression 1.33, 95% CI 1.18 - 1.48). The risk of any pDDI and PIM in elderly patients increased substantially with each additional drug (Odds Ratio: pDDI 1.32, 95% CI: 1.27 - 1.38, PIM 1.18, 95% CI: 1.14 - 1.22) and severity of disease (Odds Ratio per point on CGI-Scale: pDDI 1.29, 95% CI: 1.11 - 1.46, PIM 1.27, 95% CI: 1.11 - 1.44), respectively.

Conclusion

This study identified potential sources and determinants of safety risks in pharmacotherapy of depressive disorders and provided additional data which were previously unavailable. Most inpatients with depressive disorders receive multiple psychotropic and non-psychotropic drugs and pDDI and PIM are relatively frequent. Patients with a high number of different drugs must be intensively monitored in the management of their individual drug-related risk-benefit profiles.
Predicting Infection-related Consultations on Intensive Care Units - Development of a Machine Learning Prediction Model
Authors: Luz Christian F. , Soudis Dimitrios , Renes Maurits H. , Zwerwer Leslie R. , Giudice Nicoletta , Glasner Corinna , Nijsten Maarten W. N. , Sinha Bhanu
Published: April 2021

Objectives

Infection-related consultations on intensive care units (ICU) build an important cornerstone in the care for critically ill patients with (suspected) infections. The positive impact of consultations on quality of care and clinical outcome has previously been demonstrated. However, timing is essential and to date consultations are typically event-triggered and reactive. Here, we investigate a proactive approach by predicting infection-related consultations using machine learning models and routine electronic health records (EHR).

Methods

We used data from a mixed ICU at a large academic tertiary care hospital including 9684 admissions. EHR data comprised demographics, laboratory results, point-of-care tests, vital signs, line placements, and prescriptions. Consultations were performed by clinical microbiologists. The predicted target outcome (occurrence of a consultation) was modelled using random forest (RF), gradient boosting machines (RF), and long short-term memory neural networks (LSTM).

Results

Overall, 7.8 % of all admission received a consultation. Time-sensitive modelling approaches and increasing numbers of patient features (parameters) performed better than static approaches in predicting infection-related consultations at the ICU. Splitting a patient admission into eight-hour intervals and using LSTM resulted in the accurate prediction of consultations up to eight hours in advance with an area under the receiver operator curve of 0.921 and an area under precision recall curve of 0.673.

Conclusion

We could successfully predict of infection-related consultations on an ICU up to eight hours in advance, even without using classical triggers, such as (interim) microbiology reports. Predicting this key event can potentially streamline ICU and consultant workflows and improve care and outcome for critically ill patients with (suspected) infections.
Efficient Maternal to Neonatal transfer of SARS-CoV-2 and BNT162b2 antibodies
Authors: Beharier Ofer , Mayo Romina Plitman , Raz Tal , Sacks Kira Nahum , Schreiber Letizia , Suissa-Cohen Yael , Chen Rony , Gomez-Tolub Rachel , Hadar Eran , Gabbay-Benziv Rinat , Moshkovich Yuval Jaffe , Biron-Shental Tal , Shechter-Maor Gil , Farladansky-Gershnabel Sivan , Sela Hen Yitzhak , Raischer Hedi Benyamini , Sela Nitzan Dana , Goldman-Wohl Debra , Shulman Ziv , Many Ariel , Barr Haim , Yagel Simcha , Neeman Michal , Kovo Michal
Published: April 2021

Background

The significant risks posed to mothers and fetuses by COVID-19 in pregnancy have sparked a worldwide debate surrounding the pros and cons of antenatal SARS-CoV-2 inoculation, as we lack sufficient evidence regarding vaccine effectiveness in pregnant women and their offspring. We aimed to provide substantial evidence for the effect of BNT162b2 mRNA vaccine versus native infection on maternal humoral, as well as transplacentally acquired fetal immune response, potentially providing newborn protection.

Methods

A multicenter study where parturients presenting for delivery were recruited at 8 medical centers across Israel and assigned to three study groups: vaccinated (n=86); PCR confirmed SARS-CoV-2 infected during pregnancy (n=65), and unvaccinated non-infected controls (n=62). Maternal and fetal blood samples were collected from parturients prior to delivery and from the umbilical cord following delivery, respectively. Sera IgG and IgM titers were measured using Milliplex MAP SARS-CoV-2 Antigen Panel (for S1, S2, RBD and N).

Results

BNT162b2 mRNA vaccine elicits strong maternal humoral IgG response (Anti-S and RBD) that crosses the placenta barrier and approaches maternal titers in the fetus within 15 days following the first dose. Maternal to neonatal anti-COVID-19 antibodies ratio did not differ when comparing sensitization (vaccine vs. infection). IgG transfer rate was significantly lower for third-trimester as compared to second trimester infection. Lastly, fetal IgM response was detected in 5 neonates, all in the infected group.

Conclusions

Antenatal BNT162b2 mRNA vaccination induces a robust maternal humoral response that effectively transfers to the fetus, supporting the role of vaccination during pregnancy.
Fundamental limitations of case isolation
Authors: Hansson Jonas , Govaert Alain , Pates Richard , Tegling Emma , Soltesz Kristian
Published: April 2021

Case isolation is a strategy with the potential to curb infectious disease epidemics. Expressions for the stability boundary of a case isolation scheme defined through the proportion of the infectious population that it isolates with a given delay have recently been established. Here we quantify how this stability boundary moves when heterogeneity of the inter-individual contact network increases, and explain the underlying mechanism through insightful examples.
Immunogenicity of COVID-19 Tozinameran Vaccination in Patients on Chronic Dialysis
Authors: Schrezenmeier Eva , Bergfeld Leon , Hillus David , Lippert Joerg-Detlev , Weber Ulrike , Tober-Lau Pinkus , Landgraf Irmgard , Schwarz Tatjana , Kappert Kai , Stefanski Ana-Luisa , Sattler Arne , Kotsch Katja , Doerner Thomas , Sander Leif Erik , Budde Klemens , Halleck Fabian , Kurth Florian , Corman Victor Max , Choi Mira
Published: April 2021

Objective

Patients with kidney failure have notoriously weak responses to common vaccines. Thus, immunogenicity of novel SARS-CoV-2 vaccines might be impaired in this group. To determine immunogenicity of SARS-CoV-2 vaccination in patients with chronic dialysis, we analyzed the humoral and T-cell response after two doses of mRNA vaccine Tozinameran (BNT162b2 BioNTech/Pfizer).

Design, Settings, and Participants

This observational study included 43 patients on dialysis before vaccination with two doses of Tozinameran 21 days apart. Overall, 36 patients completed the observation period. Serum samples were analyzed by SARS-CoV-2 specific antibodies ∼1 and ∼3-4 weeks after the second vaccination. In addition, SARS-CoV-2-specific T-cell responses were assessed at the later time point by an interferon-gamma release assay (IGRA). Outcomes at later timepoints were compared to a group of 44 elderly patients with no dialysis after immunization with Tozinameran.

Exposures

Blood drawings during regular laboratory routine assessment right before start of dialysis therapy or at the time of vaccination and at follow-up study visits.

Main Outcomes and Measures

Assessment of immunogenicity after vaccination against SARS-CoV-2 in patients on and without dialysis.

Results

Median age of patients on chronic dialysis was 74.0 years (IQR 66.0, 82.0). The proportion of males was higher (69.4%) than females. Only 20/36 patients (55.6%, 95%CI: 38.29-71.67) developed SARS-CoV-2-IgG antibodies at first sampling, whereas 32/36 patients (88.9%, 95%CI:73.00-96.38) demonstrated seropositivity at the second sampling. Seroconversion rates and antibody titers were significantly lower compared to a cohort of vaccinees with similar age but no chronic dialysis (>90% seropositivity). SARS-CoV-2-specific T-cell responses 3 weeks after second vaccination were detected in 21/31 vaccinated dialysis patients (67.7%, 95%CI: 48.53-82.68) compared to 42/44 (93.3%, 95%CI: 76.49-98.84) in controls of similar age.

Conclusion and Relevance

Patients on dialysis demonstrate a delayed, but robust immune response three weeks after the second dose, which indicates effective vaccination of this vulnerable group. However, the lower immunogenicity of Tozinameran in these patients needs further attention to develop potential countermeasures such as an additional booster vaccination.
Impacts of worldwide individual non-pharmaceutical interventions on COVID-19 transmission across waves and space
Authors: Ge Yong , Zhang Wen-Bin , Liu Haiyan , Ruktanonchai Corrine W , Hu Maogui , Wu Xilin , Song Yongze , Ruktanonchai Nick W , Yan Wei , Cleary Eimear , Feng Luzhao , Li Zhongjie , Yang Weizhong , Liu Mengxiao , Tatem Andrew J , Wang Jin-Feng , Lai Shengjie
Published: April 2021

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.
Quantifying Face Mask Comfort
Authors: Koh Esther , Ambatipudi Mythri , Boone DaLoria L. , Luehr Julia B. W. , Blaise Alena , Gonzalez Jose , Sule Nishant , Mooney David J. , He Emily M.
Published: April 2021

Face mask usage is one of the most effective ways to limit SARS-CoV-2 transmission, but a mask is only useful if user compliance is high. Through anonymous surveys, we show that mask discomfort is the primary source of noncompliance in mask wearing. Further, through these surveys, we identify three critical parameters that dictate mask comfort: air resistance, water vapor permeability, and face temperature change. To validate these parameters in a physiological context, we performed experiments to measure the respiratory rate and change in face temperature while wearing different types of commonly used masks. Finally, using values of these parameters from experiments and the literature, and surveys asking users to rate the comfort of various masks, three machine learning algorithms were trained and tested to generate overall comfort scores for those masks. Although all three models tested performed with an accuracy of approximately 70%, the multiple linear regression model also provides a simple analytical expression to predict the comfort scores for any face mask provided the input parameters. As face mask usage is crucial during the COVID-19 pandemic, the ability of this quantitative framework to predict mask comfort is likely to improve user experience and prevent discomfort-induced noncompliance.
Experiences of coping with the first wave of COVID-19 epidemic in Philadelphia, PA: Mixed methods analysis of a cross-sectional survey of worries and symptoms of mood disorders
Authors: Burstyn Igor , Huynh Tran
Published: April 2021

Our objective was to describe how residents of Philadelphia, PA, coped psychologically with the first wave of COVID-19 pandemic. In a cross-sectional design, we aimed to estimate the rates and correlates of anxiety and depression, examine how specific worries correlated with general anxiety and depression, and synthesized themes of “the most difficult experiences” shared by the respondents. We collected data through an on-line survey in a convenience sample of 1,293 adult residents of Philadelphia, PA between April 17 and July 3, 2020, inquiring about symptoms of anxiety and depression (via Hospital Anxiety and Depression Scale), specific worries, open-ended narratives of “the most difficult experiences” (code into themes), demographics, perceived sources of support, and general health. Anxiety was evident among 30 to 40% of participants and depression – about 10%. Factor analysis revealed two distinct, yet inter-related clusters of specific worries related to mood disorders: concern about “hardships” and “fear of infection”. Regression analyses revealed that anxiety, depression, and fear of infection, but not concern about hardships, worsened over the course of the epidemic. “The most difficult experiences” characterized by loss of income, poor health of self or others, uncertainty, death of a relative or a friend, and struggle accessing food were each associated with some of the measures of worries and mood disorders. Respondents who believed they could reply on support of close personal network fared better psychologically than those who reported replying primarily on government and social services organizations. Thematic analysis revealed complex perceptions of the pandemic by the participants, giving clues to both positive and negative experiences that may have affected how they coped with the pandemic. Despite concerns about external validity, our observations are concordant with emerging evidence of psychological toll of the COVID-19 pandemic and measures employed to mitigate risk of infection.
OCT2Hist: Non-Invasive Virtual Biopsy Using Optical Coherence Tomography
Authors: Winetraub Yonatan , Yuan Edwin , Terem Itamar , Yu Caroline , Chan Warren , Do Hanh , Shevidi Saba , Mao Maiya , Yu Jacqueline , Hong Megan , Blankenberg Erick , Rieger Kerri E. , Chu Steven , Aasi Sumaira , Sarin Kavita Y. , de la Zerda Adam
Published: April 2021

Histological haematoxylin and eosin–stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumour margin detection, and disease diagnosis1. Producing H&E sections, however, is invasive and time-consuming. Non-invasive optical imaging modalities, such as optical coherence tomography (OCT), permit label-free, micron-scale 3D imaging of biological tissue microstructure with significant depth (up to 1mm) and large fields-of-view2, but are difficult to interpret and correlate with clinical ground truth without specialized training3. Here we introduce the concept of a virtual biopsy, using generative neural networks to synthesize virtual H&E sections from OCT images. To do so we have developed a novel technique, “optical barcoding”, which has allowed us to repeatedly extract the 2D OCT slice from a 3D OCT volume that corresponds to a given H&E tissue section, with very high alignment precision down to 25 microns. Using 1,005 prospectively collected human skin sections from Mohs surgery operations of 71 patients, we constructed the largest dataset of H&E images and their corresponding precisely aligned OCT images, and trained a conditional generative adversarial network4 on these image pairs. Our results demonstrate the ability to use OCT images to generate high-fidelity virtual H&E sections and entire 3D H&E volumes. Applying this trained neural network to in vivo OCT images should enable physicians to readily incorporate OCT imaging into their clinical practice, reducing the number of unnecessary biopsy procedures.
FINDING STUNTING HOTSPOT AREAS IN SEVEN MAJOR ISLANDS USING SPATIAL ANALYSIS: FOR THE ACCELERATION OF STUNTING PREVENTION IN INDONESIA
Authors: Sipahutar Tiopan , Eryando Tris , Budhiharsana Meiwita Paulina , Siregar Kemal N. , Aidi Muhammad Nur , Minarto  , Utari Diah Mulyawati , Rahmaniati Martya , Hendarwan Harimat
Published: April 2021

Objectives

To find stunting hotspots district/ cities in Indonesia in seven major islands in Indonesia.

Method

This is an ecological study that using aggregate data. We used data from The Basic Health Research Report of Indonesia 2018 and The Poverty Data and Information Report from the Central Bureau of Statistics (BPS) 2018. We analyzed 514 districts/ cities in Indonesia that spread out in 7 major Islands with 34 provinces. We used The Euclidean distance method to determine the neighborhood. Moran’s test was occupied to identify autocorrelation while Moran’s Scatter Plot particularly in the high-high quadrant was used to identify stunting hotspot areas.

Result

It was found that there is autocorrelation among districts/ cities in four major islands namely Sumatera, Java, Sulawesi, and Bali Nusa Tenggara Timur (NTT) Nusa Tenggara Barat (NTB). We identified 135 districts/ cities as stunting hotspot areas that spread in 14 provinces in four islands.

Conclusion

There is autocorrelation among districts/ cities in Sumatera, Java, Sulawesi, and Bali NTT NTB which resulted in 135 districts/ cities identified as stunting hotspots in four major islands in Indonesia

Policy implication

Provide information to the government in prioritizing stunting prevention areas in Indonesia in term of the acceleration of stunting prevention.

Strengths and limitations of this study:

The hypothesis which states that the prevalence of stunting in one area is associated with the prevalence of stunting in the neighboring area is a new method that should be considered to set the policy.

The study results can be used by the government to set priority areas for stunting interventions in Indonesia because so far, the government has made priorities based on stunting prevalence and weighted by poverty. Thus, by setting the priority areas, the funds required will be less compare if it executed in districts of Indonesia simultaneously.

The weakness in this study is the geographical differences of Indonesia regions given the vastness of the Indonesian territory. Some of the districts are separated by oceans and the size of the area is sometimes extremely different. It becomes difficult in determining the neighborhood definition method. Some regions will have no neighbors under certain conditions. Therefore, further research can be carried out with different methods of neighborhood definition.
Mindsets Predict Physical Activity and Relate to Chosen Management Strategies in Individuals with Knee Osteoarthritis
Authors: Boswell Melissa A. , Evans Kris M. , Zion Sean R. , Boles Danielle Z. , Hicks Jennifer L. , Delp Scott L. , Crum Alia J.
Published: April 2021

Objectives

We compared mindsets about physical activity among those with and without knee osteoarthritis and investigated if these mindsets relate to physical activity level and symptom management.

Methods

Participants with (n=150) and without (n=152) knee osteoarthritis completed an online survey at study enrollment (T1). Participants with knee osteoarthritis repeated the survey three weeks later (T2; n=62). The mindset questionnaire, scored from 1-4, assessed the extent to which individuals associate the process of exercising with less appeal-focused qualities (e.g., boring, painful, isolating, and depriving) vs. appeal-focused (e.g., fun, pleasurable, social, and indulgent)versus. Using linear regression, we examined the relationship between mindset and having knee osteoarthritis, and, in the subgroup of participants with knee osteoarthritis, the relationship between mindset at T1 and physical activity (via the Physical Activity Scale for the Elderly) at T2. We also compared mindsets between those who use medication for management and those who use exercise.

Results

A less appeal-focused mindset regarding physical activity was marginally associated with having knee osteoarthritis (β=-0.125,P=0.096). Within the knee osteoarthritis group, a more appeal-focused mindset predicted higher future physical activity (β=20.68,P=0.039), controlling for current physical activity, demographics, and health. Individuals that used exercise with or without pain medication or injections had more appeal-focused process mindsets than those who used medication or injections without exercise (P<0.001). Further, the process mindset inventory demonstrated strong internal consistency (α=0.92 at T1 for n=150 and α=0.92 at T2 for n=62) and test-retest reliability (ICC>0.841,P<0.001) within the knee osteoarthritis population.

Conclusion

In individuals with knee osteoarthritis, mindsets predict future physical activity levels and relate to an individual’s management strategy. Mindsets are a reliable and malleable construct and may be a valuable target for increasing physical activity and improving adherence to rehabilitation strategies involving exercise among individuals with knee osteoarthritis.
Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomization using polygenic risk scores
Authors: Bond Tom A , Richmond Rebecca C , Karhunen Ville , Cuellar-Partida Gabriel , Borges Maria Carolina , Zuber Verena , Alves Alexessander Couto , Mason Dan , Yang Tiffany C , Gunter Marc J , Dehghan Abbas , Tzoulaki Ioanna , Sebert Sylvain , Evans David M , Lewin Alex M , O’Reilly Paul F , Lawlor Deborah A , Järvelin Marjo-Riitta
Published: April 2021

Background

Greater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here we use Mendelian Randomization (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal.

Methods

We undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10–18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs).

Results

MV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (Pdifference = 0.001 for 15 year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size.

Conclusions

Our results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.
Wide application of minimally processed saliva on multiple RT-qPCR kits for SARS-CoV-2 detection in Indonesia
Authors: Mahendra Caroline , Kaisar Maria Mardalena Martini , Vasandani Suraj Rajan , Surja Sem Samuel , Tjoa Enty , Chriestya Febie , Junusmin Kathleen Irena , Widowati Tria Asri , Irwanto Astrid , Ali Soegianto
Published: April 2021

Saliva as a sample matrix has been an attractive alternative for the detection of SARS-CoV-2. However, due to potential variability in collection and processing steps, evaluating a proposed workflow amongst the local population is recommended. Here, we aim to validate the collection and treatment of human saliva as a direct specimen for RT-qPCR-based detection of SARS-CoV-2 in Indonesia. We demonstrated that SARS-CoV-2 target genes were detected in saliva specimens and remained stable for five days refrigerated or room temperature storage. The method of processing saliva specimens described in this report bypasses the need for an RNA-extraction process, thereby reducing the cost, time, and manpower required for processing samples. The developed method was tested across nine commercial kits, including the benchmark, to demonstrate its wide applicability on multiple existing workflows. Our developed method achieved 86% overall agreement rate compared to paired nasopharyngeal and oropharyngeal swab specimens (NPOP). With the assistance of a saliva sampling device, the collection was found to be more convenient for individuals and improved the overall agreement rate to 97%.
Diversity and within-host evolution of parasites from VL and VL/HIV patients in Northern Ethiopia
Authors: Franssen Susanne U. , Takele Yegnasew , Adem Emebet , Sanders Mandy J. , Müller Ingrid , Kropf Pascale , Cotton James A.
Published: April 2021

Visceral leishmaniasis (VL) is a fatal disease and a growing public health problem in East Africa, where Ethiopia has one of the highest VL burdens. The largest focus of VL in Ethiopia is driven by high prevalence in migrant agricultural workers and associated with a high rate of co-infection with HIV. This co-infection makes VL more difficult to treat successfully, and is associated with a high rate of relapse, with VL/HIV patients frequently experiencing many relapses of VL before succumbing to this infection. We present genome-wide data on Leishmania donovani isolates from a longitudinal study of cohorts of VL and VL/HIV patients reporting to a single clinic in Ethiopia. Extensive clinical data allows us to investigate the influence of co-infection and relapse on the populations of parasites infecting these patients. We find that the same parasite population is responsible for both VL and VL/HIV infections, and that in most cases, disease relapse is caused by recrudescence of the population of parasites that caused primary VL. Complex, multi-clonal infections are present in both primary and relapse cases, but the infrapopulation of parasites within a patient loses genetic diversity between primary disease presentation and subsequent relapses, presumably due to a population bottleneck induced by treatment. These data suggest that VL/HIV relapses are not caused by genetically distinct parasite infections, nor by re-infection. Treatment of VL does not lead to sterile cure, and in VL/HIV the infecting parasites are able to re-establish after clinically successful treatment, leading to repeated relapse of VL.

Importance

Visceral leishmaniasis (VL) is the second largest cause of deaths due to parasite infections, and a growing problem in East Africa. In Ethiopia, it is particularly associated with migrant workers moving from non-endemic regions for seasonal agricultural work, and frequently found as a co-infection with HIV, which leads to frequent VL relapse following treatment. Insight into the process of relapsing in these patients is thus key to controlling the VL epidemic in Ethiopia. We show that there is little genetic differentiation between the parasites infecting HIV positive and HIV negative VL patients. Moreover, we provide evidence that relapses are caused by the initially infecting parasite population, and that treatment induces a loss of genetic diversity in this population. We propose that restoring functioning immunity and improving anti-parasitic treatment may be key in breaking the cycle of relapsing VL in VL/HIV patients.
Unsupervised Learning for Large Scale Data: The ATHLOS Project
Authors: Barmpas Petros , Tasoulis Sotiris , Vrahatis Aristidis G. , Anagnostou Panagiotis , Georgakopoulos Spiros , Prina Matthew , Ayuso-Mateos José Luis , Bickenbach Jerome , Bayes Ivet , Bobak Martin , Caballero Francisco Félix , Chatterji Somnath , Egea-Cortés Laia , García-Esquinas Esther , Leonardi Matilde , Koskinen Seppo , Koupil Ilona , Pająk Andrzej , Prince Martin , Sanderson Warren , Scherbov Sergei , Tamosiunas Abdonas , Galas Aleksander , MariaHaro Josep , Sanchez-Niubo Albert , Plagianakos Vassilis P. , Panagiotakos Demosthenes
Published: April 2021

1

Recent technological advancements in various domains, such as the biomedical and health, offer a plethora of big data for analysis. Part of this data pool is the experimental studies that record various and several features for each instance. It creates datasets having very high dimensionality with mixed data types, with both numerical and categorical variables. On the other hand, unsupervised learning has shown to be able to assist in high-dimensional data, allowing the discovery of unknown patterns through clustering, visualization, dimensionality reduction, and in some cases, their combination. This work highlights unsupervised learning methodologies for large-scale, high-dimensional data, providing the potential of a unified framework that combines the knowledge retrieved from clustering and visualization. The main purpose is to uncover hidden patterns in a high-dimensional mixed dataset, which we achieve through our application in a complex, real-world dataset. The experimental analysis indicates the existence of notable information exposing the usefulness of the utilized methodological framework for similar high-dimensional and mixed, real-world applications.
Single Site performance of AI software for stroke detection and Triage
Authors: Paz Dan , Yagoda Daniel , Wein Theodore
Published: April 2021

Background

Recently developed software utilizing artificial intelligence for fast detection and triage of stroke cases has the potential to accelerate stroke care and improve patient outcomes. We performed this analysis to evaluate the performance and time-to-notification of one such software - RAPID LVO.

Methods

We created a database of 151 consecutive acute stroke patients for whom CT scans were processed by the RAPID LVO software over a period of eight months. The LVO notification and time to notification of the software were collected, alongside patient information and the CTA findings.

Results

RAPID LVO achieved a sensitivity of 63.6% and specificity of 85.8% for large vessel occlusion, with an average time to notification of 32.53 minutes.

Conclusions

RAPID LVO has low sensitivity, moderate specificity and high time-to-notification performance. Our study data demonstrated in particular low overall sensitivity (63%) for distal occlusions (M2-3). The disparity between the observed performance and the performance reported in RAPID LVO’s FDA clearance demonstrates the importance of independent, multi-center evaluation. The gap between the performance in this study compared to published records of RAPID AI may be due to differences in imaging hardware, software implementation, connectivity or clinical definitions.
Humoral response to Pfizer mRNA vaccine against SARS CoV2, in patients with autoimmune inflammatory rheumatic diseases and the impact on the rheumatic disease activity
Authors: Braun-Moscovici Yolanda , Kaplan Marielle , Markovits Doron , Giryes Samy , Toledano Kochava , Tavor Yonit , Dolnikov Katya , Balbir-Gurman Alexandra
Published: April 2021

Background

The registration trials of mRNA vaccines against SARS CoV2 did not address patients with autoimmune inflammatory rheumatoid diseases (AIRD).

Aims

To assess the humoral response to mRNA vaccine against SARS CoV2, in AIRD patients treated with immunomodulating drugs and the impact on AIRD activity.

Methods

Consecutive patients treated at the rheumatology institute who received their first SARS-CoV-2 (Pfizer) vaccine were recruited to the study, at their routine visit. The patients were invited for serology test 4-6 weeks after receiving the second dose of vaccine. IgG Antibodies (Ab) against SARS COV2 virus were detected using the SARS-Cov-2 IgG II Quant (Abbott) assay

Results

One hundred fifty-six consecutive patients (76% females) treated at a single rheumatology center (mean age (range) 59.1 (21-83) years), mean (range) disease duration 10.8 (1-55) years), were recruited to the study. Thirty-five percents of patients received conventional synthetic (cs)DMARDs only, 64% biological/targeted synthetic (b/ts) DMARDs, 34% received combined treatment with csDMARDs and b/tsDMARDs and 32% corticosteroids (mean dose(range) 5.8mg(2.5-20mg) prednisone). One hundred thirty-seven patients (88%) were seropositive for IgG Ab against SARS CoV2 virus (median 2832.5 AU/ml, range 58-29499). Nineteen (12%) patients had negative tests, 11/19 were treated with B cell depleting agents. The reported side effects of the vaccine were minor (muscle sore, headache, low grade fever). The rheumatic disease remained stable in all patients.

Conclusions

The vast majority of AIRD patients developed a significant humoral response following the administration of the second dose of the Pfeizer mRNA vaccine against SARS CoV2 virus. Only minor side effects were reported and no apparent impact on AIRD activity was noted.
Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017
Authors: Bationo Cédric S. , Gaudart Jean , Dieng Sokhna , Cissoko Mady , Taconet Paul , Ouedraogo Boukary , Somé Anthony , Zongo Issaka , Soma Dieudonné D. , Tougri Gauthier , Dabiré Roch K. , Koffi Alphonsine , Pennetier Cédric , Moiroux Nicolas
Published: April 2021

Background

Malaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centers (HCs).

Methods

Case data for 27 villages were collected in 13 HCs using continuous passive case detection. Meteorological data were obtained through remote sensing. Two synthetic meteorological indicators (SMIs) were created to summarize meteorological variables. Spatial hotspots were detected using the Kulldorf scanning method. A General Additive Model was used to determine the time lag between cases and SMIs and to evaluate the effect of SMIs and distance to HC on the temporal evolution of malaria cases. The multivariate model was fitted with data from the epidemic year to predict the number of cases in the following outbreak.

Results

Overall, the incidence rate in the area was 429.13 cases per 1,000 person-year with important spatial and temporal heterogeneities. Four spatial hotspots, involving 7 of the 27 villages, were detected, for an incidence rate of 854.02 cases per 1,000 person-year. The hotspot with the highest risk (relative risk = 4.06) consisted of a single village, with an incidence rate of 1,750.75 cases per 1,000 person-years. The multivariate analysis found greater variability in incidence between HCs than between villages linked to the same HC. The epidemic year was characterized by a major peak during the second part of the rainy season and a secondary peak during the dry-hot season. The time lag that generated the better predictions of cases was 9 weeks for SMI1 (positively correlated with precipitation variables and associated with the first peak of cases) and 16 weeks for SMI2 (positively correlated with temperature variables and associated with the secondary peak of cases). Euclidian distance to HC was not found to be a predictor of malaria cases recorded in HC. The prediction followed the overall pattern of the time series of reported cases and predicted the onset of the following outbreak with a precision of less than 3 weeks.

Conclusions

Our spatio-temporal analysis of malaria cases in Diébougou health district, Burkina Faso, provides a powerful prospective method for identifying and predicting high-risk areas and high-transmission periods that could be targeted in future malaria control and prevention campaigns.
Quantitative SARS-CoV-2 viral-load curves in paired saliva and nasal swabs inform appropriate respiratory sampling site and analytical test sensitivity required for earliest viral detection
Authors: Savela Emily S. , Winnett Alexander , Romano Anna E. , Porter Michael K. , Shelby Natasha , Akana Reid , Ji Jenny , Cooper Matthew M. , Schlenker Noah W. , Reyes Jessica A. , Carter Alyssa M. , Barlow Jacob T. , Tognazzini Colten , Feaster Matthew , Goh Ying-Ying , Ismagilov Rustem F.
Published: April 2021

Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and pre-symptomatic transmission, curb the spread of variants by travelers, and maximize treatment efficacy. Low-sensitivity nasal-swab testing (antigen and some nucleic-acid-amplification tests) is commonly used for surveillance and symptomatic testing, but the ability of low-sensitivity nasal-swab tests to detect the earliest stages of infection has not been established. In this case-ascertained study, initially-SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity RT-qPCR and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, high-sensitivity saliva testing detected infection up to 4.5 days before viral loads in nasal swabs reached the limit of detection of low-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva, but were undetectable or at lower loads during the first few days of infection. High-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to design optimal testing strategies in the current pandemic and will be required for responding to future viral pandemics. As new variants and viruses emerge, up-to-date data on viral kinetics are necessary to adjust testing strategies for reliable early detection of infections.
Dysconnectivity of a brain functional network was associated with blood inflammatory markers in depression
Authors: Aruldass Athina R. , Kitzbichler Manfred G. , Morgan Sarah E. , Lim Sol , Lynall Mary-Ellen , Turner Lorinda , Vertes Petra ,   Wellcome Trust Consortium for Neuroimmunology of Mood Disorders and Alzheimer’s Disease (NIMA), Cavanagh Jonathan , Cowen Phil , Pariante Carmine M. , Harrison Neil A. , Bullmore Edward T.
Published: April 2021

Objective

There is increasing evidence for a subgroup of major depressive disorder (MDD) associated with heightened peripheral blood inflammatory markers. In this study, the authors sought to understand the mechanistic brainimmune axis in inflammation-linked depression by investigating associations between functional connectivity (FC) of brain networks and peripheral inflammation in depression.

Methods

Resting-state functional magnetic resonance imaging (fMRI) and peripheral blood immune marker data (C-reactive protein; CRP, interleukin-6; IL-6 and immune cells) were collected on N=46 healthy controls (HC; CRP ≤ 3mg/L) and N=83 cases of MDD, stratified further into low CRP (loCRP MDD; ≤ 3 mg/L; N=50) and high CRP (hiCRP MDD; > 3 mg/L; N=33). In a two-part analysis, network-based statistics (NBS) was firstly performed to ascertain FC differences via HC vs hiCRP MDD comparison. Association between this network of interconnected brain regions and peripheral CRP (N=83), IL-6 (N=72), neutrophils and CD4+ T-cells (N=36) were then examined in MDD cases only.

Results

Case-control NBS testing revealed a single network of abnormally attenuated FC in hiCRP MDD, chiefly comprising default mode network (DMN) and ventral attentional network (VA) coupled regions, anatomically connecting the insula/frontal-operculum and posterior cingulate cortex (PCC). Across all MDD cases, FC within the identified network scaled negatively with CRP, IL-6, and neutrophils.

Conclusions

The findings suggest that inflammation is associated with attenuation of functional connectivity within a brain network deemed critical for interoceptive signalling, e.g. accurate communication of peripheral bodily signals such as immune states to the brain, with implications for the etiology of inflammation-linked depression.