bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional Data Analysis: Transition from Daily Observation of COVID-19 Prevalence in France to Functional Curves
Authors: Oshinubi Kayode , Ibrahim Firas , Rachdi Mustapha , Demongeot Jacques
Published: September 2021

In this paper we use the technique of functional data analysis to model daily hospitalized, deceased, ICU cases and return home patient numbers along the COVID-19 outbreak, considered as functional data across different departments in France while our response variables are numbers of vaccinations, deaths, infected, recovered and tests in France. These sets of data were considered before and after vaccination started in France. We used some smoothing techniques to smooth our data set, then analysis based on functional principal components method was performed, clustering using k-means techniques was done to understand the dynamics of the pandemic in different French departments according to their geographical location on France map and we also performed canonical correlations analysis between variables. Finally, we made some predictions to assess the accuracy of the method using functional linear regression models.
Modeling of COVID-19 Transmission Dynamics on US Population: Inter-transfer Infection in Age Groups, Mutant Variants and Vaccination Strategies
Authors: Roy Jyotirmoy , Heath Samuel , Ramkrishna Doraiswami , Wang Shiyan
Published: September 2021

The in-depth understanding of the dynamics of COVID-19 transmission among different age groups is of great interest for governments and health authorities so that strategies can be devised to reduce the pandemic’s detrimental effects. We developed the SIRDV-Virulence epidemiological model based on a population balance equation to study the effect of mutants of the virus and the effect of vaccination strategies on mitigating the transmission among the population in the United States. Based on the available data from the Centers for Disease Control and Prevention (CDC), we obtain the key parameters governing the dynamic evolution of the spread of the COVID-19 pandemic. In the context studied, the results show that a large fraction of infected cases comes from the adult and children populations in the presence of a mutant variant of COVID-19 with high infection rates. We further investigate the optimum vaccine distribution strategy among different age groups. Given the current situation in the United States, the results show that prioritizing children and adult vaccinations over that of seniors can contain the spread of the active cases, thereby preventing the healthcare system from being overwhelmed and minimizing subsequent deaths. The model suggests that the only option to curb the effects of this pandemic is to reduce the population of unvaccinated individuals. A higher fraction of ‘Anti/Non-vaxxers’ can lead to the resurgence of the pandemic.

Author summary

The changing dynamics of the COVID-19 pandemic are primarily due to the mutations of the SARS-CoV-2 virus. It is often seen that these mutants not only have a higher infection rate but also evade the presently administered vaccines. To consider the fact that different age population groups are affected to varied extent by these mutants, we build a mathematical model to account for the inter-transfer infection among age groups, which can predict the overall COVID-19 transmission in the United States. The parameter quantification of our mathematical model is based on the public data for infected cases, deaths and vaccinated from the Centers for Disease Control and Prevention (CDC). Additionally, our study shows that the vaccine distribution strategies should be developed with a priority given to the most infected age groups in order to curb the total infected and death cases. We also show how the ‘Anti/Non-vaxxers’ can be a potential reason for resurgence of the pandemic. These results are of immediate practical application in determining future vaccine distribution regarding to the pandemic and ensuring the health care system is ready to deal with the worst-case scenario with a very high infection rate.
Control of subunit stoichiometry in single-chain MspA nanopores
Authors: Pavlenok Mikhail , Yu Luning , Herrmann Dominik , Wanunu Meni , Niederweis Michael
Published: September 2021

Transmembrane protein channels enable fast and highly sensitive electrical detection of single molecules. Nanopore sequencing of DNA was achieved using an engineered Mycobacterium smegmatis porin A (MspA) in combination with a motor enzyme. Due to its favorable channel geometry, the octameric MspA pore exhibits the highest current level as compared to other pore proteins. To date, MspA is the only protein nanopore with a published record of DNA sequencing. While widely used in commercial devices, nanopore sequencing of DNA suffers from significant base-calling errors due to stochastic events of the complex DNA-motor-pore combination and the contribution of up to five nucleotides to the signal at each position. Asymmetric mutations within subunits of the channel protein offer an enormous potential to improve nucleotide resolution and sequencing accuracy. However, random subunit assembly does not allow control of the channel composition of MspA and other oligomeric protein pores. In this study, we showed that it is feasible to convert octameric MspA into a single-chain pore by connecting eight subunits using peptide linkers. We constructed single-chain MspA trimers, pentamers, hexamers and heptamers to demonstrate that it is feasible to alter the subunit stoichiometry and the MspA pore diameter. All single-chain MspA proteins formed functional channels in lipid bilayer experiments. Importantly, we demonstrated that single-chain MspA discriminated all four nucleotides identical to MspA produced from monomers. Thus, single-chain MspA constitutes a new milestone in its development and adaptation as a biosensor for DNA sequencing and many other applications.

STATEMENT OF SIGNFICANCE

Nanopore sequencing of DNA is a fast and cheap technology that uniquely delivers multi-kilobase reads. It is currently used world-wide in many applications such as genome sequencing, epigenetics, and surveillance of viral and bacterial pathogens and has started to revolutionize human lives in medicine, agriculture and environmental studies. However, the high base-calling error rates prevent nanopore DNA sequencing from reaching its full potential. In this study, we converted octameric MspA into a single-chain pore enabling asymmetric mutations to fine-tune the pore geometry and chemistry and address the shortcomings of nanopores. Thus, single-chain MspA constitutes a new milestone in its development and adaptation as a biosensor for DNA sequencing and many other applications.
In-silico analysis: common biomarkers of NDs
Authors: Sarkar Deepanjan , Chakraborty Souvik , Bhowmick Sushmita , Maiti Tarasankar
Published: September 2021

Neurodegenerative disorders (NDs) are a class of rapidly rising devastating diseases and the reason behind are might be an improper function of related genes or a mutation in a particular gene or even could be autoimmune also. Parkinson’s disease (PD), Multiple sclerosis (MS), Huntington’s disease (HD) are some of the NDs, and still, incurable fully. Apart from the similarities in symptoms, there are common genes that express somehow a differential manner in patients of PDs, MSs, and HDs. A total of 1197 differentially expressed genes (DEGs) are obtained by analyzing the chosen datasets. The protein interactions by STRING online tool and degree sorted hubs obtained through a plug-in in Cytoscape; Cyto-Hubba. Among the sorted hubs KRAS, CREB1, PIK3CA, JAK2 are the ones that are not only common to all the studied datasets of NDs but also in other neurological disorders like Alzheimer’s. The enriched pathways with biological process, molecular function, cellular component, and KEGG pathway details are obtained and analyzed using Enricher. This paper frames that the obtained hub genes could be potential biomarkers also and a need for further drug design for finding a possible cure.
In COVID-19, NLRP3 inflammasome genetic variants are associated with critical disease and these effects are partly mediated by the sickness symptom complex: a nomothetic network approach
Authors: Maes Michael , Del Tedesco Junior Walton Luiz , Lozovoy Marcell Alysson Batisti , Mori Mayara Tiemi Enokida , Danellii Tiago , Delicato de Almeida Elaine Regina , Tejo Alexandre Mestre , Tano Zuleica Naomi , Reiche Edna Maria Vissoci , Simão Andréa Name Colado
Published: September 2021

Background

In COVID-19, the NLRP3 inflammasome is activated in response to SARS-CoV-2 infection. Acute infections are accompanied by a sickness symptom complex (SSC) which is a highly conserved symptom complex that protects against infections and hyperinflammation. Aims: To examine the associations of COVID-19, SSC and the NLPR3 rs10157379 T>C and NLPR3 rs10754558 C>G SNV variants; and the protective role of SSC in severe acute respiratory syndrome (SARS)-CoV-2 infection.

Methods

We recruited COVID-19 patients, 308 with critical, 63 with moderate and 157 with mild disease.

Results

Increased SSC protects against SARS, critical disease, and death due to COVID-19. Increasing age, male sex and rs10754558 CG significantly predict reduced SSC protection. The rs10157379 CT and rs10754558 GG genotypes are positively associated with SARS. Partial Least Squares analysis shows a) that 41.8% of the variance in critical COVID-19 symptoms could be explained by SSC and oxygen saturation (inversely associated), and inflammation, chest computed tomography abnormalities, increased body mass index, SARS and age (positively associated); and b) the effects of the NLRP3 rs10157379 and rs10754558 variants on critical COVID-19 are mediated via SSC (protective) and SARS (detrimental). SSC includes anosmia, dysgeusia and gastrointestinal symptoms.

Conclusions

Intersections among the rs10754558 variant, age, and sex increase risk towards critical COVID-19 by attenuating SSC. NLRP3 variants play an important role in SARS, and severe and critical COVID-19 especially in individuals with reduced SSC, elderly people, and those with increased BMI, hypertension, and diabetes type 2. SSC is a new drug target to combat acute COVID-19.
Non-Pharmaceutical Interventions and COVID-19 Burden in the United States
Authors: Ahlers Michael J. , Aralis Hilary J. , Tang Wilson L. , Sussman Jeremy B. , Fonarow Gregg C. , Ziaeian Boback
Published: September 2021

Background

Non-pharmaceutical interventions (NPIs) are mitigation strategies used to reduce the spread of transmissible diseases. The relative effectiveness of specific NPIs remains uncertain.

Methods

We used state-level Coronavirus disease 2019 (COVID-19) case and mortality data between January 19, 2020 and March 7, 2021 to model NPI policy effectiveness. Empirically derived breakpoints in case and mortality velocities were used to identify periods of stable, decreasing, or increasing COVID-19 burden. The associations between NPI adoption and subsequent decreases in case or death velocities were estimated using generalized linear models accounting for weekly variability shared across states. State-level NPI policies included: stay at home order, indoor public gathering ban (mild >10 or severe ≤10), indoor restaurant dining ban, and public mask mandate.

Results

28,602,830 cases and 511,899 deaths were recorded. The odds of a decrease in COVID-19 case velocity were significantly elevated for stay at home (OR 2.02, 95% CI 1.63-2.52), indoor dining ban (OR 1.62, 95% CI 1.25-2.10), public mask mandate (OR 2.18, 95% CI 1.47-3.23), and severe gathering ban (OR 1.68, 95% CI 1.31-2.16). In mutually adjusted models, odds remained elevated for stay at home (AOR 1.47, 95% CI 1.04-2.07) and public mask mandate (AOR = 2.27, 95% CI 1.51-3.41). Stay at home (OR 2.00, 95% CI 1.53-2.62; AOR 1.89, 95% CI 1.25-2.87) was also associated with greater likelihood of decrease in death velocity in unadjusted and adjusted models.

Conclusions

NPIs employed in the U.S. during the COVID-19 pandemic, most significantly stay at home orders, were associated with decreased COVID-19 burden.
Changes in dispensing of medicines proposed for re-purposing in the first year of the COVID-19 pandemic in Australia
Authors: Schaffer Andrea L , Henry David , Zoega Helga , Elliott Julian H , Pearson Sallie-Anne
Published: September 2021

Objective

We quantified changes in dispensing of common medicines proposed for “re-purposing” due to their perceived benefits as therapeutic or preventive for COVID-19 in Australia, a country with relatively low COVID-19 incidence in the first year of the pandemic.

Methods

We performed an interrupted time series analysis and cross-sectional study using nationwide dispensing claims data (January 2017-November 2020). We focused on six subsidised medicines proposed for re-purposing: hydroxychloroquine, azithromycin, ivermectin, colchicine, corticosteroids, and calcitriol (Vitamin D analogue). We quantified changes in monthly dispensing and initiation trends during COVID-19 (March-November 2020) using autoregressive integrated moving average models (ARIMA) and compared characteristics of initiators in 2020 and 2019.

Results

In March 2020, we observed a 99% (95%CI 96%-103%) increase in hydroxychloroquine dispensing (of which approximately 22% attributable to new use), and a 199% increase (95%CI 184%-213%) in initiation, with a shift towards prescribing by general practitioners (42% in 2020 vs 25% in 2019) rather than specialists. These increases subsided following regulatory restrictions on prescribing to relevant specialties. There was a small but sustained increase in ivermectin dispensing over multiple months, with a 80% (95%CI 42%-118%) increase in initiation in May 2020 following its first identification as potentially disease-modifying in April. Other than increases in March related to stockpiling, we observed no increases in initiation of calcitriol or colchicine during COVID-19. Dispensing of corticosteroids and azithromycin remained lower than expected in April through November 2020.

Conclusions

While most increases in dispensing observed early on during COVID-19 were temporary and appear to be related to stockpiling among existing users, we did observed increases in initiation of hydroxychloroquine and ivermectin and a shift in prescribing patterns which may be related to media hype around these medicines. A quick response by regulators can help limit inappropriate repurposing to lessen the impact on medicine supply and patient harms.
Systematic Transmission Electron Microscopy-Based Identification and 3D Reconstruction of Cellular Degradation Machinery
Authors: Neikirk Kit , Vue Zer , Katti Prasanna , Rodriguez Ben I. , Omer Salem A. , Shao Jianqiang , Christensen Trace , Lopez Edgar Garza , Marshall Andrea , Palavicino-Maggio Caroline B. , Ponce Jessica , Alghanem Ahmad , Vang Larry , Barongan Taylor , Beasley Heather K. , Rodman Taylor , Mungai Margaret , Correia Marcelo , Exil Vernat , Murray Sandra A. , Salisbury Jeffrey L. , Glancy Brian , Pereira Renata O. , Abel E. Dale , Hinton Antentor O.
Published: September 2021

Many interconnected degradation machineries including autophagosomes, lysosomes, and endosomes work in tandem to conduct autophagy, an intracellular degradation system that is crucial for cellular homeostasis. Altered autophagy contributes to the pathophysiology of various diseases, including cancers and metabolic diseases. Although many studies have investigated autophagy to elucidate disease pathogenesis, identification of specific components of the autophagy machinery has been challenging. The goal of this paper is to describe an approach to reproducibly identify and distinguish subcellular structures involved in macro autophagy. We provide methods that help avoid common pitfalls, including a detailed explanation for distinguishing lysosomes and lipid droplets and discuss differences between autophagosomes and inclusion bodies. These methods are based on using transmission electron microscopy (TEM), capable of generating nanometer-scale micrographs of cellular degradation components in a fixed sample. We also utilize serial block face-scanning electron microscopy (SBF-SEM) to offer a protocol for visualizing 3D morphology of degradation machinery. In addition to TEM and 3D reconstruction, we discuss other imaging techniques, such as immunofluorescence and immunogold labeling that can be utilized to reliably and accurately classify cellular organelles. Our results show how these methods may be used to accurately quantify the cellular degradation machinery under various conditions, such as treatment with the endoplasmic reticulum stressor thapsigargin or ablation of the dynamin-related protein 1.
CDK1 and HSP90AA1 appears as novel regulatory gene in Non-Small Cell Lung Cancer: A Bioinformatics Approach
Authors: Bhattacharyya Nirjhar , Gupta Samriddhi , Sharma Shubham , Soni Aman , Bhattacharyya Malini , Mukherjee Atreyee , Ray Ashwini kumar , Malik Md. Zubbair
Published: September 2021

Lung cancer is one of the most invasive cancer affecting over a million of population. Non-small cell lung cancer constitutes up to 85% of all lung cancer cases. Therefore, it is important to identify prognostic biomarkers of NSCLC for therapeutic purpose. The complex behaviour of the NSCLC gene-regulatory network interaction is investigated using a network theoretical approach. We used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, GSE31210 and meta analyse them to find differentially expressed genes (DEGs), construct protein-protein interaction (PPI) network, analysed its topological properties, significant modules using network analyser with MCODE, construct a PPI-MCODE network using the genes of the significant modules. We used topological properties such as Maximal Clique Centrality (MCC) and bottleneck from the PPI-MCODE network. We compare them with hub genes (those with highest degrees) to find key regulator (KR) gene. This result is also validated by finding of common genes among top twenty hub genes, genes with highest betweenness, closeness centrality and eigenvector values. It was found that two genes, CDK1 and HSP90AA1 were common in PPI-MCODE combined analysis, and it was also found that CDK1, HSP90AA1 and HSPA8 were common among hub and bottle neck properties and suggesting significant regulatory role of CDK1 in non-small cell lung cancer. After validation, the common genes among top twenty hubs and centrality values like Betweenness Centrality, Closeness Centrality and eigen vector properties, CDK1 again appeared as the common gene. Our study as a summary suggested CDK1 as key regulator gene in complex NSCLC network interaction using network theoretical approach and described the complex topological properties of the network.
IsMycobacterium aviumsubspeciesparatuberculosis(MAP) associated with Crohn’s Disease?
Authors: Patterson Joshua M. , Winstead Cherese , Milligan Kimberly
Published: September 2021

Objective

This retroactive meta-analysis assesses the relationship betweenMycobacterium aviumsubspeciesparatuberculosis(MAP) and Crohn’s Disease (CD).

Methods

A meta-analysis of PCR– and culture–based studies was conducted to determine if there is a relationship between MAP and Crohn’s Disease. The chi-squared test of independence was also conducted to determine if MAP infection and Crohn’s disease onset are independent events.

Results

The studies analyzed were able to provide evidence thatMycobacterium aviumsubspeciesparatuberculosisis highly associated with Crohn’s disease. It is also shown that, regardless of detection method, MAP can effectively be detected in Crohn’s patients.

Conclusion

MAP is strongly connected with Crohn’s Disease.

This paper examines the incidence of MAP in the tissue of Crohn’s disease patients. We found evidence to support MAP being strongly associated with Crohn’s disease.
Sub-Saharan African Countries’ COVID-19 Research: An analysis of the External and Internal Contributions, Collaboration Patterns and Funding Sources
Authors: Asubiaro Toluwase Victor , Shaik Hafsah
Published: September 2021

This study aims at providing some evidence-based insight into Sub-Saharan Africa’s first eighteen months of COVID-19 research by evaluating its research contributions, patterns of collaboration, and funding sources. Eighteen months (2020 January 1-2021 June 30) COVID-19 publication data of 46 Sub-Saharan African countries was collected from Scopus for analysis. Country of affiliation of the authors and funding agencies data was analyzed to understand country contributions, collaboration pattern and funding sources. USA (23.08%) and the UK (19.63%), the top two external contributors, collaborated with Sub-Saharan African countries about three times more than other countries. Collaborative papers between Sub-Saharan African countries - without contributions from outside the region-made up less than five percent of the sample, whereas over 50% of the papers were written in collaboration with researchers from outside the region. Organizations that are in USA and the UK funded 45% of all the COVID-19 research from Sub-Saharan Africa. 53.44% of all the funding from Sub-Saharan African countries came from South African organizations. This study provides evidence that pan-African COVID-19 research collaboration is low, perhaps due to poor funding and lack of institutional support within Sub-Saharan Africa. This mirrors the collaborative features of science in Sub-Saharan Africa before the COVID-19 pandemic. The high volume of international collaboration during the pandemic is a good development. There is also a strong need to forge more robust pan-African research collaboration networks, through funding from Africa’s national and regional government organizations, with the specific objective of meeting local COVID-19 and other healthcare needs.
Single cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis
Authors: Healey Hope M. , Bassham Susan , Cresko William A.
Published: September 2021

Single cell RNA sequencing (scRNAseq) is a powerful technique that continues to expand across various biological applications. However, incomplete 3′ UTR annotations in less developed or non-model systems can impede single cell analysis resulting in genes that are partially or completely uncounted. Performing scRNAseq with incomplete 3′ UTR annotations can impede the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single cell isoform sequencing (ScISOr-Seq) in tandem with scRNAseq can rapidly improve 3′ UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic ScISOr-Seq dataset retained 26.1% greater scRNAseq reads than gene models from Ensembl alone. Furthermore, pooling our ScISOr-Seq isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the ScISOr-Seq only dataset. In addition, isoforms identified by ScISOr-Seq included thousands of new splicing variants. The improved gene models obtained using ScISOr-Seq lead to successful identification of cell types and increased the reads identified of many genes in our scRNAseq stickleback dataset. Our work illuminates ScISOr-Seq as a cost-effective and efficient mechanism to rapidly annotate genomes for scRNAseq.
Tasselyzer, a machine learning method to quantify maize anther exertion, based on PlantCV
Authors: Teng Chong , Fahlgren Noah , Meyers Blake C.
Published: September 2021

Male fertility in maize involves complex genetic programming affected by environmental factors. Evaluating the presence and proportion of fertile anthers is crucial for agronomic purposes. Anthers in maize emerge from male-only florets, and quantifying anther exertion is a key indicator of male fertility; however, traditional manual scoring methods are subjective. To address this limitation, we developed an automated method,Tasselyzer, for large-scale analysis. This image-based program uses the PlantCV platform to provide a quantitative assessment of anther exertion, capturing regional differences within the tassel based on the distinct color of anthers. We successfully applied this method to diverse maize lines to demonstrate its utility for research and breeding programs.

Significance Statement

Tasselyzer is a novel image-based segmentation tool for automated, large-scale measurement of anther exertion and the impact of genetic and environmental variation on male fertility in maize.
Involvement of non-LTR retrotransposons in mammal cancer incidence and ageing
Authors: Ricci Marco , Peona Valentina , Taccioli Cristian
Published: September 2021

The presence in nature of closely related species showing drastic differences in lifespan and cancer incidence has recently increased the interest of the scientific community on these topics. In particular, the adaptations and genomic characteristics underlying the evolution of cancer-resistant and long-lived species have recently focused on the presence of alterations in the number of non-coding RNAs, on epigenetic regulation and, finally, on the activity of transposable elements (TEs). In this study, we compared the content and dynamics of TE activity in the genomes of four rodent and six bat species exhibiting different lifespans and cancer susceptibility. Mouse, rat and guinea pig (short-lived and cancer-prone organisms) were compared with the naked mole rat (Heterocephalus glaber) which is the rodent with the longest lifespan. The long-lived and cancer-resistant bats of the genera Myotis, Rhinolophus, Pteropus and Rousettus were instead compared with the Molossus, which is instead a short-lived and cancer-resistant organism. Analyzing the patterns of recent accumulations of TEs in the genome in these species, we found a strong suppression or negative selection to accumulation, of non-LTR retrotransposons in long-lived and cancer-resistant organisms. On the other hand, all short-lived and cancer-prone species have shown recent accumulation of this class of TEs. Among bats, the Molossus molossus turned out to be a very particular species and, at the same time, an important model because, despite being susceptible to rapid ageing, it is resistant to cancer. In particular, we found that its genome has the highest density of SINE (non-LTR retrotransposons), but, on the other hand, a total lack of active LINE retrotransposons. Our hypothesis is that the lack of LINEs presumably makes the Molossus cancer resistant due to lack of retrotransposition but, at the same time, the high presence of SINE, may be related to their short life span due to “sterile inflammation” and high mutation load. We suggest that research on ageing and cancer evolution should put particular attention to the involvement of non-LTR retrotransposons in these phenomena.
AlphaFold2: A role for disordered protein prediction?
Authors: Wilson Carter J. , Choy Wing-Yiu , Karttunen Mikko
Published: September 2021

The development of AlphaFold2 was a paradigm-shift in the structural biology community; herein we assess the ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors. We find that a näaive use of Dictionary of Secondary Structure of Proteins (DSSP) to separate ordered from disordered regions leads to a dramatic overestimation in disorder content, and that the predicted Local Distance Difference Test (pLDDT) provides a much more rigorous metric. In addition, we show that even when used for disorder prediction, conventional predictors can outperform the pLDDT in disorder identification, and note an interesting relationship between the pLDDT and secondary structure, that may explain our observations, and hints at a broader application of the pLDDT to IDP dynamics.
The Open Field test as a tool for behavior analysis in pigs - is a standardization of setup necessary? A systematic review
Authors: Schulz M. , Zieglowski L. , Kopaczka M. , Tolba R.H.
Published: September 2021

The Open Field test is a common tool to measure anxiety and behavioral changes in rodents. However, scientific findings of rodent experiments may not translate adequately to humans and it has been shown that larger animal models might perform better in that regard. As a result, the number of published studies involving the Open Field test in domestic pig models is increasing. The aim of our review was to investigate the Open Field set-ups in published studies as well as similarity between performance and parameters published. Following the PRISMA guidelines for reviews we selected 69 studies for data extraction in this systematic review. We were able to determine specific set-up conditions such as size, duration and daytime for most of the included studies and found a high variability within these test specifiers. Results indicate a non-uniform performance of set-up including size, timing, parameters and additional combined tests such as the novel object test. We would like to point out the need for standardization of Open Field test for pigs in order to improve result, comparability and reduce inconsistencies.
Distinct neural representations for prosocial and self-benefitting effort
Authors: Lockwood Patricia L. , Wittmann Marco , Nili Hamed , Matsumoto-Ryan Mona , Abdurahman Ayat , Cutler Jo , Husain Masud , Apps Matthew A. J.
Published: September 2021

Prosocial behaviours – actions that benefit others – are central to individual and societal well-being. Most prosocial acts are effortful. Yet, how the brain encodes effort costs when actions benefit others is unknown. Here, using a combination of multivariate representational similarity analysis and model-based univariate analysis during fMRI, we reveal how the costs of prosocial efforts are processed. Strikingly, we identified a unique neural signature of effort in the anterior cingulate gyrus for prosocial acts both when choosing to help others and when exerting force for their benefit. This pattern was absent for similar self-benefitting behaviour and correlated with individual levels of empathy. In contrast, the ventral tegmental area and the ventral insula signalled subjective value preferentially when choosing whether to exert effort to benefit oneself. These findings demonstrate partially distinct brain areas guide the evaluation and exertion of effort costs when acts are prosocial or self-benefitting.
Overcoming the effect of ASH1L haploinsufficiency on stem cells amenability to genome editing and differentiation into the neuronal lineage – a technical report
Authors: Cheon Seon Hye , Ritchie Foster D. , Vacharasin Janay M. , Marinelli Nicholas , Cheatle Collin , McCord Mikayla M. , Cox Kaitlin , Lizarraga Sofia B.
Published: September 2021

Genome editing and neuronal differentiation protocols have proliferated in the last decade. Mutations in genes that control pluripotency could lead to a potential obstacle with regards to the survival and differentiation potential of the genome-edited cell lines. Here we describe a protocol for the generation, and differentiation, of cell lines containing CRISPR/Cas9 induced mutations in the histone methyl transferase ASH1L. This chromatin modifier was previously implicated in hematopoietic stem cell pluripotency and is a major genetic risk factor for autism spectrum disorders (ASD). We find that haploinsufficiency of ASH1L leads to decreased NANOG gene expression leading to reduce cell survival and increased spontaneous differentiation. We report a method that provides improved single-cell survival with higher colony formation efficiency in ASH1L mutant stem cells. Additionally, we describe a modified dual-SMAD inhibition neuronal induction methodology that permits the successful generation of human neurons with mutations in ASH1L, in a smaller scale than previously reported methods. With our modified CRISPR-genome editing and neuronal differentiation protocols, it is possible to generate genome-edited stem cells containing mutations in genes that impact pluripotency and could affect subsequent cell lineage specific differentiation. Our detailed technical report presents cost-effective strategies that will benefit researchers focusing on both translational and basic science using stem cell experimental systems.
Intraspecific variation stabilizes classic predator-prey dynamics
Authors: Allesina Stefano , Miller Zachary R. , Serván Carlos A.
Published: September 2021

In 1920, Alfred J. Lotka found that, to his “considerable surprise”, the dynamics of a simple predatorprey model he had devised led “to undamped, and hence indefinitely continued, oscillations”1,2— which he thought epitomized the “rhythm of Nature” dear to the Victorians. In 1926, the same model was proposed independently by mathematician Vito Volterra3,4, who was inspired by the work of his son-in-law, fish biologist Umberto D’Ancona5. For over a century, the equations that now bear their names have served as a template for the development of sophisticated models for population dynamics6–10. Coexistence in this classic predator-prey model is fragile—stochasticity or temporal variability in parameter values result in extinctions. The dynamics can be stabilized by intraspecific competition or other forms of self-regulation, but the prevalence of these processes in large food webs has been questioned11,12. Here we show that when we consider populations characterized by intraspecific variability, dynamics are stable—despite the absence of any direct self-regulation. Our results can be generalized further, defining a new class of consumer-resource models8,13. By accounting for intraspecific variation, which is manifest in all biological populations, we obtain dynamics that differ qualitatively and quantitatively from those found for homogeneous populations—challenging a central assumption of many ecological models.
Inflammasome activation in infected macrophages drives COVID-19 pathology
Authors: Sefik Esen , Qu Rihao , Junqueira Caroline , Kaffe Eleanna , Mirza Haris , Zhao Jun , Brewer J. Richard , Han Ailin , Steach Holly R. , Israelow Benjamin , Blackburn Holly N. , Velazquez Sofia , Chen Y. Grace , Halene Stephanie , Iwasaki Akiko , Meffre Eric , Nussenzweig Michel , Lieberman Judy , Wilen Craig B. , Kluger Yuval , Flavell Richard A.
Published: September 2021

Severe COVID-19 is characterized by persistent lung inflammation, inflammatory cytokine production, viral RNA, and sustained interferon (IFN) response all of which are recapitulated and required for pathology in the SARS-CoV-2 infected MISTRG6-hACE2 humanized mouse model of COVID-19 with a human immune system1-20. Blocking either viral replication with Remdesivir21-23 or the downstream IFN stimulated cascade with anti-IFNAR2 in vivo in the chronic stages of disease attenuated the overactive immune-inflammatory response, especially inflammatory macrophages. Here, we show SARS-CoV-2 infection and replication in lung-resident human macrophages is a critical driver of disease. In response to infection mediated by CD16 and ACE2 receptors, human macrophages activate inflammasomes, release IL-1 and IL-18 and undergo pyroptosis thereby contributing to the hyperinflammatory state of the lungs. Inflammasome activation and its accompanying inflammatory response is necessary for lung inflammation, as inhibition of the NLRP3 inflammasome pathway reverses chronic lung pathology. Remarkably, this same blockade of inflammasome activation leads to the release of infectious virus by the infected macrophages. Thus, inflammasomes oppose host infection by SARS-CoV-2 by production of inflammatory cytokines and suicide by pyroptosis to prevent a productive viral cycle.
SIN-like pathway kinases regulate the end of mitosis in the methylotrophic yeast Ogataea polymorpha
Authors: Jiangyan Shen , Takegawa Kaoru , Pereira Gislene , Maekawa Hiromi
Published: September 2021

The Mitotic exit network (MEN) is a conserved signalling pathway essential for termination of mitosis in the budding yeast Saccharomyces cerevisiae. All MEN components are highly conserved in the methylotrophic budding yeast Ogataea polymorpha, except for Cdc15 kinase. Amongst O. polymorpha protein kinases that have some similarity to ScCdc15, only two had no other obvious homologues in S. cerevisiae and these were named OpHCD1 and OpHCD2 for homologue candidate of ScCdc15. A search in other yeast species revealed that OpHcd2 has an armadillo type fold in the C-terminal region as found in SpCdc7 kinases of the fission yeast Schizosaccharomyces pombe, which are homologues of ScCdc15; while OpHcd1 is homologous to SpSid1 kinase, a component of the Septation Initiation Network (SIN) of S. pombe not present in the MEN. Since the deletion of either OpHCD1 or OpHCD2 resulted in lethality under standard growth conditions, conditional mutants were constructed by introducing an ATP analog sensitive mutation. For OpHCD2, we constructed and used new genetic tools for O. polymorpha that combined the Tet promoter and the improved auxin-degron systems. Conditional mutants for OpHCD1 and OpHCD2 exhibited significant delay in late anaphase and defective cell separation, suggesting that both genes have roles in mitotic exit and cytokinesis. These results suggest a SIN-like signalling pathway regulates termination of mitosis in O. polymorpha and that the loss of Sid1/Hcd1 kinase in the MEN occurred relatively recently during the evolution of budding yeast.
Fast and cost-effective age estimation in Bengal tiger and Asiatic lion: applicability of cementum analysis method
Authors: Vipin  , Sharma Chandra P , Sharma Vinita , Goyal Surendra P , Gupta Sandeep K
Published: September 2021

Age estimation methods, through cementum analysis, for wild animals are rarely developed in Southeast Asian Countries. In the present study, we describe the applicability of the cementum analysis technique for developing a fast (±19 hours) and cost-effective age estimation method for Bengal tiger (Panthera tigris tigris) and Asiatic lion (Panthera leo persica) using incisor tooth. The I2and I3incisor teeth from the right mandible of a tiger and I2and I3from the left maxilla of a lion were used in the study. The longitudinal sections of the tooth were made using a low cost hand grinding technique on sand papers followed by decalcification and staining with hematoxylin. The cementum layers were counted under the microscope at 100X or 200X magnifications. Two cementum layers were observed in each of the I2and I3incisor tooth of tiger and six cementum layers were observed in each of the I2and I3incisor teeth of lion. The permanent incisors in tiger and lion erupt between 12-14 months; hence, we added 1 year to the counted number of cementum layers to estimate the final age of tiger and lion incisors. The absolute age of tiger and lion incisors was estimated to be of 2+1 years and 6+1 years, respectively. The same number of cementum layers in both incisors respective to the tiger and lion were observed. Therefore, we suggest (i) undertake the blind test and (ii) collect incisor teeth from naturally died or killed individuals for strengthening the database on the age of the wild population. This optimized method may be suitable for many carnivore species, applicable in wildlife forensic studies and can be used by researchers with minimum expertise, time, and funds requirements throughout the world.
The Synechocystis ORF slr0201 product is involved in succinate dehydrogenase-mediated cyclic electron transfer around PSI
Authors: Xiong Fusheng , Yang Yang , Fu Xiyuan
Published: September 2021

The Synechocystis sp. PCC 6803 open reading frame (ORF) slr0201 was originally annotated as heterodisulfide reductase B subunit (HdrB). The slr0201 encodes a 301-amino acid hypothetical protein with the predicted amino acid sequence significantly homologous to not only the HdrB from methanogenic bacteria, but also some novel succinate dehydrogenase C subunit (SdhC) found in Archaea and Campylobacter. Genetic manipulation via knocking-out approach created a Δslr0201 mutant showing a ΔsdhB-like phenotype that was characterized by impaired succinate-dependent DCPIP reduction activities, reduced SDH-mediated respiratory electron transports, lower cellular contents of succinate and fumarate, slower KCN-induced increases in Chl fluorescence yield in the dark, and weak state 2/strong state 1 transitions, being indicative of a more oxidized PQ pool. In addition, slower re-reductions of the photosystem (PS) I reaction center P700 upon light-off were also monitored in the Δslr0201, indicating functional involvements of Slr0201 in cyclic electron transfer around PSI. Both photoautptrophical and photomixotrophical growth rates of the Δslr0201 strain resembled to those of the wild type, but substantial growth deteriorations occurred when arginine (∼25 mM) or other two urea-cycle relevant amino acids (citrulline and ornithine) were added, which were attributed to generations and accumulations of certain hazardous metabolites. Based on the ΔsdhB-resembling phenotype, in conjunction with its high sequence similarities to some archaeal SdhC, we proposed that the slr0201 encodes a SDH function-relevant protein and is most likely the SdhC, a membrane anchoring subunit, which, while being genetically distinct from those in traditional bacterial SDH, belongs to the C subunit of novel archaeal SDH.
Growing Glycans in Rosetta: Accuratede novoglycan modeling, density fitting, and rational sequon design
Authors: Adolf-Bryfogle Jared , Labonte Jason W. , Kraft John C. , Shapovalov Maxim , Raemisch Sebastian , Lütteke Thomas , DiMaio Frank , Bahl Christopher D. , Pallesen Jesper , King Neil P. , Gray Jeffrey J. , Kulp Daniel W. , Schief William R.
Published: September 2021

Carbohydrates and glycoproteins modulate key biological functions. Computational approaches inform function to aid in carbohydrate structure prediction, structure determination, and design. However, experimental structure determination of sugar polymers is notoriously difficult as glycans can sample a wide range of low energy conformations, thus limiting the study of glycan-mediated molecular interactions. In this work, we expanded theRosettaCarbohydrateframework, developed and benchmarked effective tools for glycan modeling and design, and extended the Rosetta software suite to better aid in structural analysis and benchmarking tasks through the SimpleMetrics framework. We developed a glycan-modeling algorithm,GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. After a rigorous optimization of kinematic and energetic considerations to improve near-native sampling enrichment and decoy discrimination,GlycanTreeModelerwas benchmarked on a test set of diverse glycan structures, or “trees”. Structures predicted byGlycanTreeModeleragreed with native structures at high accuracy for bothde novomodeling and experimental density-guided building.GlycanTreeModeleralgorithms and associated tools were employed to designde novoglycan trees into a protein nanoparticle vaccine that are able to direct the immune response by shielding regions of the scaffold from antibody recognition. This work will inform glycoprotein model prediction, aid in both X-ray and electron microscopy density solutions and refinement, and help lead the way towards a new era of computational glycobiology.
Integration of a radiofrequency coil and commercial field camera for ultra-high-field MRI
Authors: Gilbert Kyle M. , Dubovan Paul , Gati Joseph S. , Menon Ravi S. , Baron Corey A.
Published: September 2021

Purpose

To develop an RF coil with an integrated commercial field camera for ultra-high field (7 T) neuroimaging. The RF coil will operate within a head-only gradient coil and be subject to the corresponding design constraints. The RF coil can thereafter be used for subject-specific correction of k-space trajectories—notably in gradient-sensitive sequences such as single-shot spiral imaging.

Methods

The transmit and receive performance was evaluated before and after the integration of field probes, while field probes were evaluated when in an optimal configuration external to the coil and after their integration. Diffusion-weighted EPI and single-shot spiral acquisitions were employed to evaluate the efficacy of correcting higher order field perturbations and the consequent effect on image quality.

Results

Field probes had a negligible effect on RF-coil performance, including the transmit efficiency, transmit uniformity, and mean SNR over the brain. Modest reductions in field-probe signal lifetimes were observed, caused primarily by non-idealities in the gradient and shim fields of the head-only gradient coil at the probe positions. The field monitoring system could correct up to second-order field perturbations in single-shot spiral imaging.

Conclusion

The integrated RF coil and field camera was capable of concurrent field monitoring within a 7T head-only scanner and facilitated the subsequent correction of k-space trajectories during spiral imaging.
Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior
Authors: Kaniuth Philipp , Hebart Martin N.
Published: September 2021

Representational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational (dis-)similarity matrices (RDM or RSM), which characterize the pairwise (dis-)similarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This ‘equal weights’ assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, in case of model comparison, may lead them to select an inferior model. The aim of this work is twofold: First, we sought to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RSM correspondence and affects model selection. Previous work suggested that reweighting can improve model selection in RSA but it has remained unclear to what extent these results generalize across datasets and data modalities. To draw more general conclusions, we utilized a range of publicly available datasets and three popular deep neural networks (DNNs). Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We found that reweighting individual model units markedly improved the fit between model RSMs and target RSMs derived from several fMRI and behavioral datasets and affected model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RSM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally show that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain, and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the correspondence between representational spaces.