bluuebunny/crossref_metadata_2025 huggingface dataset:
Stages of COVID-19 pandemic and paths to herd immunity by vaccination: dynamical model comparing Austria, Luxembourg and Sweden
Authors: Kemp Françoise , Proverbio Daniele , Aalto Atte , Mombaerts Laurent , d’Hérouël Aymeric Fouquier , Husch Andreas , Ley Christophe , Gonçalves Jorge , Skupin Alexander , Magni Stefano
Published: January 2021

Background

Worldwide more than 72 million people have been infected and 1.6 million died with SARS-CoV-2 by 15th December 2020. Non-pharmaceutical interventions which decrease social interaction have been implemented to reduce the spread of SARS-CoV-2 and to mitigate stress on healthcare systems and prevent deaths. The pandemic has been tackled with disparate strategies by distinct countries resulting in different epidemic dynamics. However, with vaccines now becoming available, the current urgent open question is how the interplay between vaccination strategies and social interaction will shape the pandemic in the next months.

Methods

To address this question, we developed an extended Susceptible-Exposed-Infectious-Removed (SEIR) model including social interaction, undetected cases and the progression of patients trough hospitals, intensive care units (ICUs) and death. We calibrated our model to data of Luxem-bourg, Austria and Sweden, until 15th December 2020. We incorporated the effect of vaccination to investigate under which conditions herd immunity would be achievable in 2021.

Results

The model reveals that Sweden has the highest fraction of undetected cases, Luxembourg displays the highest fraction of infected population, and all three countries are far from herd immunity as of December 2020. The model quantifies the level of social interactions, and allows to assess the level which would keep Reff (t) below 1. In December 2020, this level is around 1/3 of what it was before the pandemic for all the three countries. The model allows to estimate the vaccination rate needed for herd immunity and shows that 2700 vaccinations/day are needed in Luxembourg to reach it by mid of April and 45,000 for Austria and Sweden. The model estimates that vaccinating the whole country’s population within 1 year could lead to herd immunity by July in Luxembourg and by August in Austria and Sweden.

Conclusion

The model allows to shed light on the dynamics of the epidemics in different waves and countries. Our results emphasize that vaccination will help considerably but not immediately and therefore social measures will remain important for several months before they can be fully alleviated.
Statistical and machine learning models for classification of human wear and delivery days in accelerometry data
Authors: Moore Ryan , Archer Kristin R. , Choi Leena
Published: January 2021

Purpose

Accelerometers are increasingly utilized in healthcare research to assess human activity. Accelerometry data are often collected by mailing accelerometers to participants, who wear the accelerometers to collect data on their activity. The devices are then mailed back to the laboratory for analysis. We develop models to classify days in accelerometry data as activity from actual human wear or the delivery process. These models can be used to automate the cleaning of accelerometry datasets that are adulterated with activity from delivery.

Methods

For the classification of delivery days in accelerometry data, we developed statistical and machine learning models in a supervised learning context using a large human activity and delivery labeled accelerometry dataset. We extracted several features, which were included to develop random forest, logistic regression, mixed effects regression, and multilayer perceptron models, while convolutional neural network, recurrent neural network, and hybrid convolutional recurrent neural network models were developed without feature extraction. Model performances were assessed using Monte Carlo cross-validation.

Results

We found that a hybrid convolutional recurrent neural network performed best in the classification task with an F1 score of 0.960 but simpler models such as logistic regression and random forest also had excellent performance with F1 scores of 0.951 and 0.957, respectively.

Conclusion

The models developed in this study can be used to classify days in accelerometry data as either human or delivery activity. An analyst can weigh the larger computational cost and greater performance of the convolutional recurrent neural network against the faster but slightly less powerful random forest or logistic regression. The best performing models for classification of delivery data are publicly available on the open source R package,PhysicalActivity.
Canonical features of human antibodies recognizing the influenza hemagglutinin trimer interface
Authors: Zost Seth J. , Dong Jinhui , Gilchuk Iuliia , Gilchuk Pavlo , Thornburg Natalie J. , Bangaru Sandhya , Kose Nurgun , Finn Jessica A. , Bombardi Robin , Soto Cinque , Nargi Rachel , Irving Ryan P. , Suryadevara Naveenchandra , Westover Jonna B. , Carnahan Robert H. , Turner Hannah L. , Li Sheng , Ward Andrew B. , Crowe James E.
Published: January 2021

Broadly reactive antibodies targeting the influenza A hemagglutinin (HA) head domain are thought to be rare and to require extensive somatic mutations or unusual structural features to achieve breadth against divergent HA subtypes. Here we describe common genetic and structural features of diverse human antibodies from several individuals recognizing the trimer interface (TI) of the influenza HA head, a recently identified site of vulnerability1–3. We examined the sequence of TI-reactive antibodies, determined crystal structures for TI antibody-antigen complexes, and analyzed the contact residues of the antibodies on HA to discover common genetic and structural features of TI antibodies. Our data reveal that many TI antibodies are encoded by a light chain variable gene segment incorporating a shared somatic mutation. In addition, these antibodies have a shared acidic residue in the heavy chain despite originating from diverse heavy chain variable gene segments. These studies show that the TI region of influenza HA is a major antigenic site with conserved structural features that are recognized by a common human B cell public clonotype. The canonical nature of this antibody-antigen interaction suggests that the TI epitope might serve as an important new target for structure-based vaccine design.
Estimation of the Acetylcholinesterase activity of honey bees in Nepal
Authors: Pandey Shishir , Gotame Shankar , Sejuwal Sachin , Giri Basant , Giri Susma
Published: January 2021

Decline in honey bee colonies possess a serious threat to biodiversity and agriculture. Prior detection of the stresses with the help of biomarkers and their management ensures honey bee’s survivability. Acetylcholinesterase (AChE) is a promising biomarker to monitor exposure of honey bees towards environmental pollutants. In this preliminary study, we measured AChE activity in forager honey bees collected from six districts of Nepal, Kathmandu, Bhaktapur, Lalitpur, Chitwan, Rupandehi and Pyuthan during autumn and winter seasons. We estimated AChE tissue and specific activities from bee’s heads using commercial kit based on Ellman assay and protein concentration using Lowry assay. In total, we collected 716 foragers belonging toA. cerana, A. melliferaandA. dorsata. A significant increase in all three parameters measured: AChE tissue activity, AChE specific activity and protein concentration was observed in winter samples. Both AChE tissue and specific activities were lower inA. melliferacompared to eitherA. ceranaorA. dorsata. Protein concentration was higher inA. melliferathan inA. dorsataand lower than inA. cerana. We show correlation between both AChE tissue and specific activities and protein concentration across season and species and discuss possible factors contributing to the observations. Our results clearly indicate the presence of stress in the winter which is manifested through overexpression of the AChE. We recommend a detailed study to determine the factors accountable for the stresses for better management of honey bees in Nepal.
Comprehensive profiling of genomic and transcriptomic differences between risk groups of lung adenocarcinoma and lung squamous cell carcinoma
Authors: Zengin Talip , Önal-Süzek Tuğba
Published: January 2021

Lung cancer is the second frequently diagnosed cancer type and responsible for the highest number of cancer deaths worldwide. Lung adenocarcinoma and lung squamous cell carcinoma are subtypes of non-small cell lung cancer which has the highest frequency of lung cancer cases. We aimed to analyze genomic and transcriptomic variations including simple nucleotide variations (SNVs), copy number variations (CNVs) and differential expressed genes (DEGs) in order to find key genes and pathways for diagnostic and prognostic prediction for lung adenocarcinoma and lung squamous cell carcinoma. We performed univariate cox model and then lasso regularized cox model with leave-one-out cross-validation using TCGA gene expression data in tumor samples. We generated a 35-gene signature and a 33-gene signature for prognostic risk prediction based on the overall survival time of the patients with LUAD and LUSC, respectively. When we clustered patients into high-risk and low-risk groups, the survival analysis showed highly significant results with high prediction power for both training and test datasets. Then we characterized the differences including significant SNVs, CNVs, DEGs, active subnetworks, and the pathways. We described the results for the risk groups and cancer subtypes separately to identify specific genomic alterations between both high-risk groups and cancer subtypes. Both LUAD and LUSC high-risk groups have more down-regulated immune pathways and upregulated metabolic pathways. On the other hand, low-risk groups have both upregulated and downregulated genes on cancer-related pathways. Both LUAD and LUSC have important gene alterations such as CDKN2A and CDKN2B deletions with different frequencies. SOX2 amplification occurs in LUSC and PSMD4 amplification in LUAD. EGFR and KRAS mutations are mutually exclusive in LUAD samples. EGFR, MGA, SMARCA4, ATM, RBM10, and KDM5C genes are mutated only in LUAD but not in LUSC. CDKN2A, PTEN, and HRAS genes are mutated only in LUSC samples. Low-risk groups of both LUAD and LUSC, tend to have a higher number of SNVs, CNVs, and DEGs. The signature genes and altered genes have the potential to be used as diagnostic and prognostic biomarkers for personalized oncology.
Comparing instance segmentation methods for analyzing clonal growth of single cells in microfluidic chips
Authors: SoRelle Elliott D. , White Scott , Yellen Benjamin B. , Wood Kris C. , Luftig Micah A. , Chan Cliburn
Published: January 2021

Appropriately tailored segmentation techniques can extract detailed quantitative information from biological image datasets to characterize and better understand sample distributions. Practically, high-resolution characterization of biological samples such as cell populations can provide insights into the sources of variance in biomarker expression, drug resistance, and other phenotypic aspects, but it is still unclear what is the best method for extracting this information from large image-based datasets. We present a software pipeline and comparison of multiple image segmentation methods to extract single-cell morphological and fluorescence quantitation from time lapse images of clonal growth rates using a recently reported microfluidic system. The inputs in all pipelines consist of thousands of unprocessed images and the outputs are the detection of cell counts, chamber identifiers, and individual morphological properties of each clone over time detected through multi-channel fluorescence and bright field imaging. Our conclusion is that unsupervised learning methods for cell segmentation substantially outperform supervised statistical methods with respect to accuracy and have key advantages including individual cell instance detection and flexibility through model training. We expect this system and software to have broad utility for researchers interested in high-throughput single-cell biology.
HOPMA: Boosting protein functional dynamics with colored contact maps
Authors: Laine Elodie , Grudinin Sergei
Published: January 2021

In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches.

We present HOPMA, a novel method to predict protein functional states and transitions using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures.

The method is computationally efficient and available athttps://github.com/elolaine/HOPMAandhttps://team.inria.fr/nano-d/software/nolb-normal-modes.
Distribution of Huntington’s disease Haplogroups in Indian population
Authors: Venkatesh Sowmya Devatha , Ratna Nikhil , Lakshmi.P Swathi , Murari Geetanjali , Kamble Nitish , Yadav Ravi , Viswanath Biju , Varghese Mathew , Pal Pramod Kumar , Jain Sanjeev , Purushottam Meera
Published: January 2021

Huntington’s disease (HD), a rare neurodegenerative disorder, is inherited in an autosomal dominant manner, and caused by a pathological trinucleotide expansion at exon1 of theHTTlocus. Previous studies have described the haplogroups at theHTTlocus that can explain the differences in prevalence of HD. We have selected three informative SNPs (rs762855, rs3856973 and rs4690073) to study these haplogroups in an Indian sample. Our results show that the genotype frequencies are significantly different between cases and controls for these SNPs. More than 90% of both cases and controls belong to Haplogroup A which is the predominant European haplogroup.
metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Authors: Zorrilla Francisco , Patil Kiran R. , Zelezniak Aleksej
Published: January 2021

Advances in genome-resolved metagenomic analysis of complex microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts still tend to rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end highly scalable pipeline enabling metabolic modeling of multi-species communities directly from metagenomic samples. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from metagenome assembled genomes to community level flux balance simulations. To demonstrate the capabilities of the metaGEM pipeline, we analyzed 483 samples spanning lab culture, human gut, plant associated, soil, and ocean metagenomes, to reconstruct over 14 000 prokaryotic GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to the GEMs reconstructed from reference genomes. We further demonstrate that metagenomic GEMs capture intraspecies metabolic diversity by identifying the differences between pathogenicity levels of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, our pipeline enables simulation-ready metabolic model reconstruction directly from individual metagenomes, provides a resource of all reconstructed metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.
A Practical Guide to Sparse K-Means Clustering for Studying Molecular Development of the Human Brain
Authors: Balsor Justin L. , Arbabi Keon , Singh Desmond , Kwan Rachel , Zaslavsky Jonathan , Jeyanesan Ewalina , Murphy Kathryn M.
Published: January 2021

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables (e.g. genes or proteins (p)) for each sample. This leads to a data structure that is high dimensional (p >> n) and introduces thecurse of dimensionality,which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets wherep >> n.Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparseK-means clustering (Robust SparseK-means Clustering (RSKC)) that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.
Survival analysis of all critically ill patients with COVID-19 admitted to the main hospital in Mogadishu, Somalia, 30 March–12 June 2020: what interventions are proving effective?
Authors: Ali Mohamed M. , Rahman Malik Sk Md Mamunur , Ahmed Abdulrazaq Yusuf , Bashir Ahmed Mohamed , Mohamed Abdulmunim , Abdi Abdulkadir , Obtel Majdouline
Published: January 2021

OBJECTIVES

To determine risk factors for death in patients with COVID-19 admitted to the main public sector hospital in Somalia and identify interventions contributing to improved clinical outcome in a low-resource and fragile setting.

SETTING

Main public sector tertiary hospital in Mogadishu, Somalia.

PARTICIPANTS

All 131 laboratory-confirmed COVID-19 patients admitted to the main public tertiary hospital in Somalia between 30 March and 12 June 2020.

MAIN OUTCOME MEASURES

We extracted demographic and clinical data from hospital records of all 131 COVID-19 patients admitted to hospital until their death or recovery. We used Kaplan–Meier statistics to estimate survival probabilities and the log-rank test to assess significant differences in survival between groups. We used the Cox proportional hazard model to estimate likelihood of death and assess the effect of risk factors on survival.

RESULTS

Of the 131 patients, 52 (40%) died in the hospital and 79 (60%) survived to discharge. The factors independently associated with increased risk of in-hospital death were: age ≥ 60 years – survival probability on day 21 in patients < 60 years was 0.789 (95% confidence interval (CI): 0.658–0.874) compared with 0.339 (95% CI: 0.205–0.478) in patients ≥ 60 years; cardiovascular disease (survival probability 0.478 (95% CI: 0.332–0.610) in patients with cardiovascular disease compared with 0.719 (95% CI: 0.601–0.807) in patients without cardiovascular disease); and non-invasive ventilation on admission – patients who were not ventilated were significantly more likely to survive than those who were (P < 0.001).

CONCLUSION

Our study, which includes the largest cohort of COVID-19 patients admitted to a single hospital in a sub-Saharan African country, confirms that underlying conditions and age are associated with increased risk of in-hospital death in patients with COVID-19. Our results show the advantage of medical oxygen over non-invasive ventilation in the treatment of patients with severe COVID-19 symptoms.
Accuracy of the Veterans Health Administration COVID-19 (VACO) Index for predicting short-term mortality among 1,307 Yale New Haven Hospital inpatients and 427,224 Medicare patients
Authors: King Joseph T. , Yoon James S. , Bredl Zachary M. , Habboushe Joseph P. , Walker Graham A. , Rentsch Christopher T. , Tate Janet P. , Kashyap Nitu M. , Hintz Richard C. , Chopra Aneesh P. , Justice Amy C.
Published: January 2021

Background

The Veterans Health Administration COVID-19 (VACO) Index incorporates age, sex, and pre-existing comorbidity diagnoses readily available in the electronic health record (EHR) to predict 30-day all-cause mortality in both inpatients and outpatients infected with SARS-CoV-2. We examined the performance of the Index using data from Yale New Haven Hospital (YNHH) and national Medicare data overall, over time, and within important patient subgroups.

Methods and findings

With measures and weights previously derived and validated in a national Veterans Healthcare Administration (VA) sample, we evaluated the accuracy of the VACO Index for estimating inpatient (YNHH) and both inpatient and outpatient mortality (Medicare) using area under the receiver operating characteristic curve (AUC) and comparisons of predicted versus observed mortality by decile (calibration plots). The VACO Index demonstrated similar discrimination and calibration in both settings, over time, and among important patient subgroups including women, Blacks, Hispanics, Asians, and Native Americans. In sensitivity analyses, we allowed component variables to be re-weighted in the validation datasets and found that weights were largely consistent with those determined in VA data. Supplementing the VACO Index with body mass index and race/ethnicity had no effect on discrimination.

Conclusion

Among COVID-19 positive individuals, the VACO Index accurately estimates risk of short-term mortality among a wide variety of patients. While it modestly over-estimates risk in recent intervals, the Index consistently identifies those at greatest relative risk. The VACO Index could identify individuals who should continue practicing social distancing, help determine who should be prioritized for vaccination, and among outpatients who test positive for SARS-CoV-2, indicate who should receive greater clinical attention or monoclonal antibodies.
FLT3-ITD transduces autonomous growth signals during its biosynthetic trafficking in acute myelogenous leukemia cells
Authors: Yamawaki Kouhei , Shiina Isamu , Murata Takatsugu , Tateyama Satoru , Maekawa Yutarou , Niwa Mariko , Shimonaka Motoyuki , Okamoto Koji , Suzuki Toshihiro , Nishida Toshirou , Abe Ryo , Obata Yuuki
Published: January 2021

FMS-like tyrosine kinase 3 (FLT3) in hematopoietic cells binds to its ligand at the plasma membrane (PM), then transduces growth signals.FLT3gene alterations that lead the kinase to assume its permanently active form, such asinternal tandem duplication (ITD)andD835Ysubstitution, are found in 30~40% of acute myelogenous leukemia (AML) patients. Thus, the drugs for molecular targeting of FLT3 mutants have been developed for the treatment of AML. Several groups have reported that compared with wild-type FLT3 (FLT3-wt), FLT3 mutants are retained in organelles, resulting in low levels of PM localization of the receptor. However, the precise subcellular localization of mutant FLT3 remains unclear, and the relationship between oncogenic signaling and the mislocalization is not completely understood. In this study, we show that in cell lines established from AML patients, endogenous FLT3-ITD but not FLT3-wt clearly accumulates in the perinuclear region. Our co-immunofluorescence assays demonstrate that Golgi markers are co-localized with the perinuclear region, indicating that FLT3-ITD mainly localizes to the Golgi region in AML cells. FLT3-ITD biosynthetically traffics to the Golgi apparatus and remains there in a manner dependent on its tyrosine kinase activity. A tyrosine kinase inhibitor midostaurin (PKC412) markedly decreases in FLT3-ITD retention and increases in the PM levels of the mutant. FLT3-ITD activates downstream in the endoplasmic reticulum (ER) and the Golgi apparatus during its biosynthetic trafficking. Results of our trafficking inhibitor treatment assays show that FLT3-ITD in the ER activates STAT5, whereas that in the Golgi can cause the activation of AKT and ERK. We provide evidence that FLT3-ITD signals from the early secretory compartments before reaching the PM in AML cells.
Characterizing and correcting camera noises in back-illuminated sCMOS cameras
Authors: Zhang Zhaoning , Wang Yujie , Piestun Rafael , Huang Zhen-Li
Published: January 2021

With promising properties of fast imaging speed, large field-of-view, relative low cost and many others, back-illuminated sCMOS cameras have been receiving intensive attentions for low-light imaging in the past several years. However, due to the pixel-to-pixel difference of camera noises (called noise non-uniformity) in sCMOS cameras, researchers may hesitate to use them in some application fields, and sometimes wonder whether they should optimize the noise non-uniformity of their sCMOS cameras before using them in a specific application scenario. In this paper, we systematically characterize the impact of different types of sCMOS noises on image quality and perform corrections to these sCMOS noises. We verify that it is possible to use appropriate correction methods to push the non-uniformity of major camera noises, including readout noise, offset, and photon response, to a satisfactory level for conventional microscopy and single molecule localization microscopy. We further find out that, after these corrections, global read noise becomes a major concern that limits the imaging performance of back-illuminated sCMOS cameras. We believe this study provides new insights into the understanding of camera noises in back-illuminated sCMOS cameras, and also provides useful information for future development of this promising camera technology.
An integrative model of plant gravitropism linking statoliths position and auxin transport
Authors: Levernier Nicolas , Pouliquen Olivier , Forterre Yoël
Published: January 2021

Gravity is a major cue for the proper growth and development of plants. The response of plants to gravity implies starch-filled plastids, the statoliths, which sediments at the bottom of the gravisensing cells, the statocytes. Statoliths are assumed to modify the transport of the growth hormone, auxin, by acting on specific auxin transporters, PIN proteins. However, the complete gravitropic signaling pathway from the intracellular signal associated to statoliths to the plant bending is still not well understood. In this article, we build on recent experimental results showing that statoliths do not act as gravitational force sensor, but as position sensor, to develop a bottom-up theory of plant gravitropism. The main hypothesis of the model is that the presence of statoliths modifies PIN trafficking close to the cell membrane. This basic assumption, coupled with auxin transport and growth in an idealized tissue made of a one-dimensional array of cells, recovers several major features of the gravitropic response of plants. First, the model provides a new interpretation for the response of a plant to a steady stimulus, the so-called sine-law of plant gravitropism. Second, it predicts the existence of a gravity-independent memory process as observed recently in experiments studying the response to transient stimulus. The model suggests that the timescale of this process is associated to PIN turnover, calling for new experimental studies.
Degradation of Photoreceptor Outer Segments by the Retinal Pigment Epithelium Requires Pigment Epithelium-derived Factor Receptor (PEDF-R)
Authors: Bullock Jeanee , Polato Federica , Abu-Asab Mones , Bernardo-Colón Alexandra , Aflaki Elma , Agbaga Martin-Paul , Becerra S. Patricia
Published: January 2021

Purpose

To examine the contribution of PEDF-R to the phagocytosis process. Previously, we identified PEDF-R, the protein encoded by thePNPLA2gene, as a phospholipase A2 in the retinal pigment epithelium (RPE). During phagocytosis, RPE cells ingest abundant phospholipids and protein in the form of photoreceptor outer segment (POS) tips, which are then hydrolyzed. The role of PEDF-R in RPE phagocytosis is not known.

Methods

Mice in whichPNPLA2was conditionally knocked out in the RPE were generated (cKO). Mouse RPE/choroid explants were cultured. Human ARPE-19 cells were transfected with siPNPLA2silencing duplexes. POS were isolated from bovine retinas. The phospholipase A2 inhibitor bromoenol lactone was used. Transmission electron microscopy, immunofluorescence, lipid labeling, pulse-chase experiments, western blots, and free fatty acid and β-hydroxybutyrate assays were performed.

Results

The RPE of the cKO mice accumulated lipids as well as more abundant and larger rhodopsin particles compared to littermate controls. Upon POS exposure, RPE explants from cKO mice released less β-hydroxybutyrate compared to controls. After POS ingestion during phagocytosis, rhodopsin degradation was stalled both in cells treated with bromoenol lactone and inPNPLA2-knocked-down cells relative to their corresponding controls. Phospholipase A2 inhibition lowered β-hydroxybutyrate release from phagocytic RPE cells.PNPLA2knock down also resulted in a decline in fatty acids and β-hydroxybutyrate release from phagocytic RPE cells.

Conclusions

PEDF-R downregulation delayed POS digestion during phagocytosis. The findings imply that efficiency of RPE phagocytosis depends on PEDF-R, thus identifying a novel contribution of this protein to POS degradation in the RPE.
Long term consumption of green tea EGCG enhances healthspan and lifespan in mice by mitigating multiple aspects of cellular senescence in mitotic and post-mitotic tissues, gut dysbiosis and immunosenescence
Authors: Sharma Rohit , Kumar Ravi , Sharma Anamika , Goel Abhishek , Padwad Yogendra
Published: January 2021

Cellular senescence is emerging as the causal nexus of aging, and its potential modulators present an effective strategy to counter age-related morbidity. The current study profiled the extent of cellular senescence in different organs of mice at four different time-points of lifespan, and explored the influence of epigallocatechin gallate (EGCG) consumption in impacting multiple aspects of aging biology. We report that adipose and intestinal tissues are highly vulnerable to cellular senescence as evident by age-associated increase in DNA damage response, activation of cell cycle inhibitors (p53/p21) and induction of SASP (p38MAPK/NF-κB/Cox-2). Further, a distinct modulation of nutrient signaling pathway mediators (AMPK/Akt/SIRT3 and 5), and a decrease in autophagy effectors was also observed in aging animals. Systemic inflamm-aging markers (TNF-α/IL-lβ) and splenic CD4/CD8 ratio increased with age, while NK cell population decreased. Metagenomic analyses revealed age-related decrease in the diversity of microbial species while an increase in the abundance of various pathogenic bacterial genera was also observed. Long term EGCG consumption enhanced lifespan of animals by attenuating markers of DNA damage, cell cycle inhibitors and SASP in adipose, intestine and liver tissue. Mechanistically, EGCG inhibited the activation of AMPK and Akt and enhanced mitochondrial SIRT3 and SIRT5 expression, as well as autophagic response in adipose and intestinal tissues. Systemic presence of inflamm-aging markers decreased while expression of T cell immune response regulator CD69 increased in EGCG fed animals. EGCG also improved age-related decrease in the diversity of microbial species and suppressed the growth of pathogenic microbes. In short, our results provide compelling evidence that post-mitotic adipose tissue is a major site of cellular senescence and SASP activation, and that chronic EGCG consumption can influence several aspects of aging and senescence resulting in improved organismal healthspan and lifespan.
12-Lipoxygenase Governs the Innate Immune Pathogenesis of Islet Inflammation and Autoimmune Diabetes
Authors: Kulkarni Abhishek , Pineros Annie R. , Ibrahim Sara , Hernandez-Perez Marimar , Orr Kara S. , Glenn Lindsey , Walsh Melissa , Nadler Jerry L. , Morris Margaret A. , Tersey Sarah A. , Mirmira Raghavendra G. , Anderson Ryan M.
Published: January 2021

Macrophages and related myeloid cells are innate immune cells that participate in the early islet inflammation of type 1 diabetes (T1D). The inflammatory signals and antigen presentation by these cells may be inducers of the adaptive immune response that is the hallmark of T1D. The enzyme 12-lipoxygenase (12-LOX) catalyzes the formation of pro-inflammatory eicosanoids from membrane-derived phospholipids, but its role and mechanisms in the pathogenesis of islet inflammation have not been elucidated. Leveraging a model of T1D-like islet inflammation in zebrafish, we show here that macrophages contribute significantly to the loss of β-cells and the subsequent development of hyperglycemia. Depletion or inhibition of 12-LOX in this model resulted in significantly reduced macrophage infiltration into islets with preservation of β-cell mass. In mice, we deleted the gene encoding 12-LOX (Alox15) in the myeloid lineage in the non-obese diabetic (NOD) model of T1D. Myeloid cell-specificAlox15knockout NOD mice demonstrated reduced insulitis and T-cell responses, preserved β cell mass, and almost complete protection from the development of T1D. A critical effect of 12-LOX depletion appeared secondary to a defect in myeloid cell migration, a function required for immune surveillance and tissue injury responses. This effect on migration appeared to be secondary to the loss of the chemokine receptor CXCR3. Transgenic expression of the gene encoding CXCR3 rescued the migrator defect in zebrafish 12-LOX morphants. Taken together, our results reveal a formative role for innate immune myeloid cells in the early pathogenesis of T1D and identify 12-LOX as a necessary enzyme to promote their pro-diabetogenic phenotype in the context of autoimmunity.
Transcriptomic profiling uncovers novel players in innate immunity inArabidopsis thaliana
Authors: Safaeizadeh Mehdi , Boller Thomas , Becker Claude
Published: January 2021

In this research a high-throughput RNA sequencing based transcriptome analysis technique (RNA-Seq) was used to evaluate differentially expressed genes (DEGs) in the wild type Arabidopsis seedling in response to flg22, a well-known microbe-associated molecular pattern (MAMP), andAtPep1, a well-known peptide representing an endogenous damage-associated molecular patterns (DAMP). The results of our study revealed that 1895 (1634 up-regulated and 261 down-regulated) and 2271 (1706 up-regulated and 565 down-regulated) significant differentially expressed genes in response to flg22 andAtPep1 treatment, respectively. Among significant DEGs, we observed that a number of hitherto overlooked genes have been found to be induced upon treatment with either flg22 or withAtPep1, indicating their possible involvement in innate immunity. Here, we characterized two of them, namely PP2-B13 and ACLP1.pp2-b13andaclp1mutants showed an increased susceptibility to infection by the virulent pathogenPseudomomas syringae pv tomato mutant hrcC-, as evidenced by an increased growth of the pathogen in planta. Further we present evidence that theaclp1mutant was deficient in ethylene production upon flg22 treatment, while thepp2-b13mutant, was deficient in ROS production. The results from this research provide new information to a better understanding of the immune system in Arabidopsis.
The steroid-inducible pOp6/LhGR gene expression system is fast, sensitive and does NOT cause plant growth defects in rice (Oryza sativa)
Authors: Samalova Marketa , Moore Ian
Published: January 2021

Inducible systems for transgene expression activated by a chemical inducer or an inducer of non-plant origin are desirable tools for both basic plant research and biotechnology. Although, the technology has been widely exploited in model plants, it has not been optimised for use with the major monocotyledonous crop species, namely rice. We have adapted the dexamethasone-inducible pOp6/LhGR system for rice and shown that it is fast, sensitive and tightly regulated, with high levels of induction that remain stable over several generations. Most importantly, we have shown that the system does not cause negative growth defectsin vitroor in soil grown plants. Interestingly in the process of testing, we found that another steroid, triamcinolone acetonide, is a more potent inducer in rice than dexamethasone. We present serious considerations for the construct design to avoid undesirable effects caused by the system in plants, leakiness and possible silencing, as well as simple steps how to maximize translation efficiency of a gene of interest. Finally, we compare the performance of the pOp6/LhGR system with other chemically inducible systems tested in rice in terms of the properties of an ideal inducible system.

Significance statement

The non-monocot codon-optimized version of the dexamethasone inducible pOp6/LhGR system does not cause severe developmental perturbations in rice plants.
Mapping the temporal and spatial dynamics of the human endometriumin vivoandin vitro
Authors: Garcia-Alonso Luz , Handfield Louis-François , Roberts Kenny , Nikolakopoulou Konstantina , Fernando Ridma C. , Gardner Lucy , Woodhams Ben , Arutyunyan Anna , Polanski Krzysztof , Hoo Regina , Sancho-Serra Carmen , Li Tong , Kwakwa Kwasi , Tuck Elizabeth , Kleshchevnikov Vitalii , Tarkowska Aleksandra , Porter Tarryn , Mazzeo Cecilia Icoresi , van Dongen Stijn , Dabrowska Monika , Vaskivskyi Vasyl , Mahbubani Krishna T. , Park Jong-eun , Jimenez-Linan Mercedes , Campos Lia , Kiselev Vladimir , Lindskog Cecilia , Ayuk Paul , Prigmore Elena , Stratton Michael R , Saeb-Parsy Kourosh , Moffett Ashley , Moore Luiza , Bayraktar Omer A. , Teichmann Sarah A. , Turco Margherita Y. , Vento-Tormo Roser
Published: January 2021

The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated single-cell and spatial reference maps of the human uterus and 3D endometrial organoid cultures. We dissect the signalling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids highlights common pathways regulating the differentiation of secretory and ciliated lineagein vivoandin vitro. We showin vitrothat downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. These mechanistic insights provide a platform for future development of treatments for a range of common endometrial disorders including endometriosis and carcinoma.
Measurement of curvature and twist of microtubule bundles in the mitotic spindle
Authors: Ivec Arian , Trupinić Monika , Tolić Iva M. , Pavin Nenad
Published: January 2021

The highly ordered spatial organization of microtubule bundles in the mitotic spindle is crucial for its proper functioning. The recent discovery of twisted shapes of microtubule bundles and spindle chirality suggests that the bundles extend along curved paths in three dimensions, rather than being confined to a plane. This in turn implies that rotational forces exist in the spindle in addition to the widely studied linear forces. However, studies of spindle architecture and forces are impeded by a lack of a robust method for the geometric quantification of microtubule bundles in the spindle. In this paper, we describe a simple method for measuring and evaluating the shapes of microtubule bundles, by characterizing them in terms of their curvature and twist. By using confocal microscopy, we obtain three-dimensional images of spindles, which allow us to trace the entire microtubule bundles. For each traced bundle, we first fit a plane, and then fit a circle lying in that plane. With this easily reproducible method, we extract the curvature and twist, which represent the geometric information characteristic for each bundle. As the bundle shapes reflect the forces within them, this method is valuable for the understanding of forces that act on chromosomes during mitosis.
Massively parallel characterization of engineered transcript isoforms using direct RNA sequencing
Authors: Tarnowski Matthew J. , Gorochowski Thomas E.
Published: January 2021

Transcriptional terminators signal where transcribing RNA polymerases (RNAPs) should halt and disassociate from DNA. However, because termination is stochastic, two different forms of transcript could be produced: one ending at the terminator and the other reading through. An ability to control the abundance of these transcript isoforms would offer bioengineers a mechanism to regulate multi-gene constructs at the level of transcription. Here, we explore this possibility by repurposing terminators as ‘transcriptional valves’ which can tune the proportion of RNAP read-through. Using one-pot combinatorial DNA assembly we construct 1183 transcriptional valves for T7 RNAP and show how nanopore-based direct RNA sequencing (dRNA-seq) can be used to simultaneously characterize the entire pool at a nucleotide resolutionin vitroand unravel genetic design principles to tune and insulate their function using nearby sequence context. This work provides new avenues for controlling transcription and demonstrates the value of long-read sequencing for exploring complex sequence-function landscapes.
The Dorsolateral Prefrontal Cortex Presents Structural Variations Associated with Empathic Capacity in Psychotherapists
Authors: Domínguez-Arriola Marcos E. , Olalde-Mathieu Víctor E. , Garza-Villareal Eduardo A. , Barrios Fernando A.
Published: January 2021

Empathic capacity has been shown to be correlated with brain structural variations, such as cortical thickness. Since psychotherapists have a constant demand to modulate their empathic response, in this study we compared cortical thickness between a group of psychotherapists and a control group at prefrontal and cingulate brain regions, and investigated how this is correlated with their empathic skills. Eighteen psychotherapists and eighteen healthy controls underwent 3-Tesla MRI scanning and completed empathy-related psychometric assessments. Cortical thickness (CT) measures were estimated for each participant. We evaluated how these measures differed between groups, and if they were associated with individual empathy-related scores in a series of regions of interest. Our analysis shows that psychotherapists display a significantly greater CT at a region in the left dorsolateral prefrontal cortex (dlPFC; p < 0.05, FDR corrected). Moreover, psychotherapists’ CT in this region is correlated with the tendency to feel empathically concerned for others (p < 0.01, FDR corrected). This finding is relevant because the dlPFC region participates strongly in the cognitive components of the empathic response, such as emotion regulation and perspective-taking processes. Thus, our findings support the idea that empathic capacity is reflected by brain structural variations while also studying for the first time a sample of subjects for whom empathic responding is crucial in their profession.
Deep learning driven quantification of interstitial fibrosis in kidney biopsies
Authors: Zheng Yi , Cassol Clarissa A. , Jung Saemi , Veerapaneni Divya , Chitalia Vipul C. , Ren Kevin , Bellur Shubha S. , Boor Peter , Barisoni Laura M. , Waikar Sushrut S. , Betke Margrit , Kolachalama Vijaya B.
Published: January 2021

Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA estimation using computational techniques can reduce this variability and provide quantitative assessment by capturing the pathologic features. Using trichrome-stained whole slide images (WSIs) processed from human renal biopsies, we developed a deep learning (DL) framework that captured finer pathological structures at high resolution and overall context at the WSI-level to predict IFTA grade. WSIs (n=67) were obtained from The Ohio State University Wexner Medical Center (OSUWMC). Five nephropathologists independently reviewed them and provided fibrosis scores that were converted to IFTA grades: <=10% (None or minimal), 11-25% (Mild), 26-50% (Moderate), and >50% (Severe). The model was developed by associating the WSIs with the IFTA grade determined by majority voting (reference estimate). Model performance was evaluated on WSIs (n=28) obtained from the Kidney Precision Medicine Project (KPMP). There was good agreement on the IFTA grading between the pathologists and the reference estimate (Kappa=0.622±0.071). The accuracy of the DL model was 71.8±5.3% on OSUWMC and 65.0±4.2% on KPMP datasets, respectively. Identification of salient image regions by combining microscopic and WSI-level pathological features yielded visual representations that were consistent with the pathologist-based IFTA grading. Our approach to analyzing microscopic- and WSI-level changes in renal biopsies attempts to mimic the pathologist and provides a regional and contextual estimation of IFTA. Such methods can assist clinicopathologic diagnosis.

Translational statement

Pathologists rely on interstitial fibrosis and tubular atrophy (IFTA) to indicate chronicity in kidney biopsies and provide a prognostic indicator of renal survival. Although guidelines for evaluation of IFTA exist, there is variability in IFTA estimation among pathologists. In this work, digitized kidney biopsies were independently reviewed by five nephropathologists and majority voting on their ratings was used to determine the IFTA grade. Using this information, a deep learning model was developed that captured microscopic and holistic features on the digitized biopsies and accurately predicted the IFTA grade. The study illustrates that deep learning can be utilized effectively to perform IFTA grading, thus enhancing conventional clinicopathologic diagnosis.