bluuebunny/crossref_metadata_2025 huggingface dataset:
Mannheimia pernigra sp. nov., isolated from bovine respiratory tract
Authors: Kuhnert Peter , Brodard Isabelle , Schönecker Lutz , Akarsu Hatice , Christensen Henrik , Bisgaard Magne
Published: January 2021

Over a period of 1 year, 270 isolates identified as Taxon 39 of Bisgaard were obtained from the nasopharynx of veal calves at 11 epidemiologically independent Swiss fattening farms. Two isolates from each farm and the Australian Taxon 39 reference strain BNO311 were further characterized by genetic and phenotypic methods. Phylogenetic analysis of 16S rRNA and recN gene sequences placed the isolates in a single, distinct cluster within the genus

Mannheimia

. As to the rpoB gene, most isolates clustered together, but four strains formed a separate cluster close to

Mannheimia varigena

. Genome sequence analysis of isolates from both rpoB clusters confirmed their species status, with an average nucleotide identity (ANI) >98.9 % between isolates and <84 % to the closest species,

M. varigena

. Based upon whole genome sequences, the G+C content was determined as 39.1 mol%. Similarly, analysis of MALDI-TOF MS reference spectra clustered the isolates clearly separated from the other

Mannheimia

species, making this the method of choice for identification. In addition, numerous biochemical markers based on classical as well as commercial identification schemes were determined, allowing separation from other

Mannheimia

species and identification of the new taxon. Major fatty acids for strain 17CN0883T are C14 : 0, C16 : 0, C16 : 1 ω7c and C18 : 1 ω7c. Major respiratory quinones are ubiquinone-7 and ubiquinone-8. We propose the name Mannheimia pernigra sp. nov. for former Taxon 39 of Bisgaard. The type strain is 17CN0883T (=CCUG 74657T=DSM 111153T) isolated from a veal calf in Switzerland.
Delayed Interventions, Low Compliance, and Health Disparities Amplified the Early Spread of COVID-19
Authors: Jalali Aliea M. , Khoury Sumaia G. , See JongWon , Gulsvig Alexis M. , Peterson Brent M. , Gunasekera Richard S. , Buzi Gentian , Wilson Jason , Galbadage Thushara
Published: January 2021

The United States (US) public health interventions were rigorous and rapid, yet failed to arrest the spread of the Coronavirus Disease 2019 (COVID-19) pandemic as infections spread throughout the US. Many factors have contributed to the spread of COVID-19, and the success of public health interventions depends on the level of community adherence to preventative measures. Public health professionals must also understand regional demographic variation in health disparities and determinants to target interventions more effectively. In this study, a systematic evaluation of three significant interventions employed in the US, and their effectiveness in slowing the early spread of COVID-19 was conducted. Next, community-level compliance with a state-level stay at home orders was assessed to determine COVID-19 spread behavior. Finally, health disparities that may have contributed to the disproportionate acceleration of early COVID-19 spread between certain counties were characterized. The contribution of these factors for the disproportionate spread of the disease was analyzed using both univariate and multivariate statistical analyses. Results of this investigation show that delayed implementation of public health interventions, a low level of compliance with the stay at home orders, in conjunction with health disparities, significantly contributed to the early spread of the COVID-19 pandemic.
Invasive Mould Disease in Fatal COVID-19: A Systematic Review of Autopsies
Authors: Kula Brittany E. , Clancy Cornelius J. , Nguyen M. Hong , Schwartz Ilan S.
Published: January 2021

Background

Invasive mould disease (IMD) – most commonly pulmonary aspergillosis - is reported to affect up to a third of critically ill COVID-19 patients. Most reported cases are diagnosed with probable/putative COVID-19 associated pulmonary aspergillosis (CAPA) based on a combination of non-specific clinical, radiographic, and mycological findings, but the clinical significance – and whether these cases represent true invasive disease – is unresolved.

Methods

We performed a systematic review of autopsy series of decedents with COVID-19 for evidence of IMD. We searched PubMed, Web of Science, OVID (Embase) and MedRxiv for English- or French-language case series published between January 1, 2019 to September 26, 2020. We included series describing lung histology of ≥3 decedents, and authors were contacted for missing information as necessary.

Findings

We identified 51 case series describing autopsies of 702 decedents. Individual-level data was available for 430 decedents. The median age was 72 (IQR 61 to 80) years. Diabetes mellitus, pre-existing lung disease, and immunocompromising conditions were reported for 129 (32%), 95 (22%), and 25 (6%) decedents, respectively. The median hospitalization length was 10 (IQR 5-22) days. 51.6% of decedents had received mechanical ventilation for a median of nine (IQR 5-20) days. Treatment included immunomodulation in 60 (most often steroids or tocilizumab) and antifungals in 41 decedents. Eleven decedents (1·6%) had autopsy-confirmed IMD (6 with CAPA, 4 with invasive pulmonary mycosis not specified and 1 with disseminated mucormycosis). Among 173 decedents who received mechanical ventilation, 5 had IMD (2·9%).

Interpretation

Autopsy-proven IMD, including CAPA, is uncommon in fatal COVID-19.

Funding

This study is unfunded

Category

Review
Efficient Surveillance and Temporal Calibration of Disease Response
Authors: Najeebullah Kamran , Liebig Jessica , Darbro Jonathan , Jurdak Raja , Paini Dean
Published: January 2021

Abstract

Background

Disease surveillance and response are critical components of epidemic preparedness. The disease response, in most cases, is a set of reactive measures that follow the outcomes of the disease surveillance. Hence, efficient surveillance is a prerequisite for an effective response.

Methodology/Principal Findings

We introduce the principle of epidemiological soundness and utilize it to construct a disease spread network. The network implicitly quantifies the fertility (whether a case leads to secondary cases) and reproduction (number of secondary cases per infectious case) of the cases as well as the size and generations (of the infection chain) of the outbreaks. We empirically confirm that high morbidity relates positively with delay in disease response. Moreover, we identify what constitutes efficient surveillance by applying various thresholds of disease response delay to the network and report their impact on case fertility, reproduction, number of generations and ultimately, outbreak size. Lastly, we identify the components of the disease surveillance system that can be calibrated to achieve the identified efficiency thresholds.

Conclusion

We identify practically achievable, efficient surveillance thresholds (on temporal scale) that lead to an effective response and identify how they can be satisfied. Our approach can be utilized to provide guidelines on spatially and demographically targeted resource allocation for public awareness campaigns as well as to improve diagnostic abilities and turn-around times for the doctors and laboratories involved.

Author Summary

Efficient surveillance and effective response capabilities are pivotal to the prevention and control of the infectious diseases. The disease response is a set of reactive actions that follow the outcomes of the disease surveillance. Ergo, efficient surveillance is a perquisite for the deployment of an effective response. The quantification of the efficiency of a disease surveillance system largely depends on the epidemiological characteristics of the disease. In this paper, we introduce an approach that builds on these characteristics and measures the performance of a disease surveillance system through its impact on the incidence of the disease. Using this approach, we obtain quantitative (on a temporal scale) efficient surveillance thresholds, which if followed by a timely response, lead to a considerable reduction in the disease incidence. Furthermore, we show that these thresholds are practically achievable by identifying the obstacles that lead to less than efficient surveillance outcomes. Our approach can be applied to obtain guidelines on spatially, temporally and demographically targeted resource allocations for public awareness campaigns as well to improve diagnostic ability and turn-around times in treating doctors and pathology labs.
GCH1mutations in hereditary spastic paraplegia
Authors: Varghaei Parizad , Yoon Grace , Estiar Mehrdad A , Veyron Simon , Leveille Etienne , Dupre Nicolas , Trempe Jean-François , Rouleau Guy A , Gan-Or Ziv
Published: January 2021

GCH1mutations have been associated with dopa-responsive dystonia (DRD), Parkinson’s disease (PD) and tetrahydrobiopterin (BH4)-deficient hyperphenylalaninemia B. Recently,GCH1mutations have been reported in five patients with hereditary spastic paraplegia (HSP). Here, we analyzed a total of 400 HSP patients (291 families) from different centers across Canada by whole exome sequencing (WES). Three patients with heterozygousGCH1variants were identified: monozygotic twins with a p.(Ser77_Leu82del) variant, and a patient with a p.(Val205Glu) variant. The former variant is predicted to be likely pathogenic and the latter is pathogenic. The three patients presented with childhood-onset lower limb spasticity, hyperreflexia and abnormal plantar responses. One of the patients had diurnal fluctuations, and none had parkinsonism or dystonia. Phenotypic differences between the monozygotic twins were observed, who responded well to levodopa treatment. Pathway enrichment analysis suggested that GCH1 shares processes and pathways with other HSP-associated genes, and structural analysis of the variants indicated a disruptive effect. In conclusion,GCH1mutations may cause HSP; therefore, we suggest a levodopa trial in HSP patients and includingGCH1in the screening panels of HSP genes. Clinical differences between monozygotic twins suggest that environmental factors, epigenetics, and stochasticity could play a role in the clinical presentation.
Cognitive endophenotypes in racially- and ethnically-diverse middle-aged adult offspring aggregate with parental magnetic resonance imaging biomarkers of Alzheimer’s disease risk
Authors: Lao Patrick J. , Turney Indira C. , Avila-Reiger Justina , Vonk Jet M.J. , Rentería Miguel Arce , Seblova Dominika , Chesebro Anthony G. , Laing Krystal K. , Amarante Erica , Martinez Michelle , Fleurimont Judes , Gutierrez José , Schupf Nicole , Mayeux Richard , Manly Jennifer J. , Brickman Adam M.
Published: January 2021

A family history of Alzheimer’s disease (AD) increases risk for AD in an individual by 1.5-to 3-fold. Heritability of AD risk may be due in part to the aggregation of neurodegeneration and cerebrovascular changes with cognitive endophenotypes within families. The purpose of this study was to determine the extent to which cognitive functioning in middle-aged adults is associated with objectively-measured neurodegenerative and cerebrovascular neuroimaging markers linked to risk for clinical AD in their parents, and the extent to which these associations differ by race/ethnicity and language, as proxy variables for social advantage. Middle-aged children enrolled in the Offspring study (n=356; 53.1±10.1 years old; 13% Non-Hispanic White, 27% Non-Hispanic Black, 26% Latinx tested in English, 34% Latinx tested in Spanish; 65% women; 13.5±3.4 years education) were administered the NIH Toolbox, a computerized neuropsychological battery, in their preferred language. Older adults were a subset of the Washington-Heights Inwood Columbia Aging Project (77.3±6.6 years old; 75% women; 10.0±4.6 years education) who underwent T1w- and T2w-MRI and who had a child enrolled in the Offspring study. We tested the associations of parental MRI measures reflecting neurodegeneration (hippocampal volume, cortical thickness) and cerebrovascular disease (white matter hyperintensity (WMH) volume, presence of infarct) with cognitive tests scores in Offspring participants. We further stratified the models by race/ethnicity. Better offspring cognitive scores aggregated lower parental neurodegeneration and cerebrovascular disease among Non-Hispanic White and Latinx participants, and with lower parental cerebrovascular disease alone among Non-Hispanic Black participants. Associations were generally strongest in Non-Hispanic White participants compared to the other groups. These results suggest a more consistent link between offspring cognitive endophenotype and parental brain health in intergenerational AD transmission among Non-Hispanic White participants compared to racial/ethnic and minority groups in which other social factors may be adding variance.
Simulation of epidemic models with generally distributed sojourn times
Authors: Hernandez-Suarez Carlos , Montesinos-Lopez Osval , Solano-Barajas Ramon
Published: January 2021

Epidemic models are used to analyze the progression or outcome of an epidemic under different control policies like vaccinations, quarantines, lockdowns, use of face-masks, pharmaceutical interventions, etc. When these models accurately represent real-life situations, they may become an important tool in the decision-making process. Among these models, compartmental models are very popular and assume individuals move along a series of compartments that describe their current health status. Nevertheless, these models are mostly Markovian, that is, the time in each compartment follows an exponential distribution. Here, we introduce a novel approach to simulate general stochastic epidemic models that accepts any distribution for the sojourn times.
Inactivation of SARS-CoV-2 virus in saliva using a guanidium based transport medium suitable for RT-PCR diagnostic assays
Authors: Banik Sukalyani , Saibire Kaheerman , Suryavanshi Shraddha , Johns Glenn , Chakravorty Soumitesh , Kwiatkowski Robert , Alland David , Banada Padmapriya
Published: January 2021

Background

Upper respiratory samples used to test for SARS-CoV-2 virus may be infectious and present a hazard during transport and testing. A buffer with the ability to inactivate SARS-CoV-2 at the time of sample collection could simplify and expand testing for COVID-19 to non-conventional settings.

Methods

We evaluated a guanidium thiocyanate-based buffer, eNAT™ (Copan) as a possible transport and inactivation medium for downstream RT-PCR testing to detect SARS-CoV-2. Inactivation of SARS-CoV-2 USA-WA1/2020 in eNAT and in diluted saliva was studied at different incubation times. The stability of viral RNA in eNAT was also evaluated for up to 7 days at room temperature (28°C), refrigerated conditions (4°C) and at 35°C.

Results

SARS-COV-2 virus spiked directly in eNAT could be inactivated at >5.6 log10PFU/ml within a minute of incubation. When saliva was diluted 1:1 in eNAT, no cytopathic effect (CPE) on vero-E6 cell lines was observed, although SARS-CoV-2 RNA could be detected even after 30 min incubation and after two cell culture passages. A 1:2 (saliva:eNAT) dilution abrogated both CPE and detectable viral RNA after as little as 5 min incubation in eNAT. SARS-CoV-2 RNA from virus spiked at 5X the limit of detection remained positive up to 7 days of incubation in all tested conditions.

Conclusion

eNAT and similar guanidinium thiocyanate-based media may be of value for transport, preservation, and processing of clinical samples for RT-PCR based SARS-CoV-2 detection.
COVID-19 propagation by diffusion - a two-dimensional approach for Germany
Authors: Bärwolff Günter
Published: January 2021

Diffusion comes anytime and everywhere. If there is a gradient or a potential difference of a quantity a diffusion process happens and this ends if an equilibrium is reached only. The concentration of a species maybe such quantity, or the voltage. An electric currant will be driven by a voltage difference for example.

In this COVID-19 pandemic one observes both regions with low incidence and other ones with high incidence. The local different people density could be a reason for that. In populous areas like big cities or congested urban areas higher COVID-19 incidences could be observed than in rural regions.

The aim of this paper consists in the application of a diffusion concept to describe one possible issue of the the COVID-19 propagation.

This will be discussed for the German situation based on the quite different incidence data for the different federal states of Germany.

With this ansatz some phenomenoms of the actual development of the pandemic could be confirmed. The model gives a possibility to investigate certain scenarios like border-crossings or local spreading events and their influence on the COVID-19 propagation as well.
Native-like SARS-CoV-2 spike glycoprotein expressed by ChAdOx1 nCoV-19/AZD1222 vaccine
Authors: Watanabe Yasunori , Mendonça Luiza , Allen Elizabeth R. , Howe Andrew , Lee Mercede , Allen Joel D. , Chawla Himanshi , Pulido David , Donnellan Francesca , Davies Hannah , Ulaszewska Marta , Belij-Rammerstorfer Sandra , Morris Susan , Krebs Anna-Sophia , Dejnirattisai Wanwisa , Mongkolsapaya Juthathip , Supasa Piyada , Screaton Gavin R. , Green Catherine M. , Lambe Teresa , Zhang Peijun , Gilbert Sarah C. , Crispin Max
Published: January 2021

Vaccine development against the SARS-CoV-2 virus focuses on the principal target of the neutralizing immune response, the spike (S) glycoprotein. Adenovirus-vectored vaccines offer an effective platform for the delivery of viral antigen, but it is important for the generation of neutralizing antibodies that they produce appropriately processed and assembled viral antigen that mimics that observed on the SARS-CoV-2 virus. Here, we describe the structure, conformation and glycosylation of the S protein derived from the adenovirus-vectored ChAdOx1 nCoV-19/AZD1222 vaccine. We demonstrate native-like post-translational processing and assembly, and reveal the expression of S proteins on the surface of cells adopting the trimeric prefusion conformation. The data presented here confirms the use of ChAdOx1 adenovirus vectors as a leading platform technology for SARS-CoV-2 vaccines.
mRNA vaccine-elicited antibodies to SARS-CoV-2 and circulating variants
Authors: Wang Zijun , Schmidt Fabian , Weisblum Yiska , Muecksch Frauke , Barnes Christopher O. , Finkin Shlomo , Schaefer-Babajew Dennis , Cipolla Melissa , Gaebler Christian , Lieberman Jenna A. , Oliveira Thiago Y. , Yang Zhi , Abernathy Morgan E. , Huey-Tubman Kathryn E. , Hurley Arlene , Turroja Martina , West Kamille A. , Gordon Kristie , Millard Katrina G. , Ramos Victor , Da Silva Justin , Xu Jianliang , Colbert Robert A. , Patel Roshni , Dizon Juan , Unson-O’Brien Cecille , Shimeliovich Irina , Gazumyan Anna , Caskey Marina , Bjorkman Pamela J. , Casellas Rafael , Hatziioannou Theodora , Bieniasz Paul D. , Nussenzweig Michel C.
Published: January 2021

To date severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected over 100 million individuals resulting in over two million deaths. Many vaccines are being deployed to prevent coronavirus disease 2019 (COVID-19) including two novel mRNA-based vaccines1,2. These vaccines elicit neutralizing antibodies and appear to be safe and effective, but the precise nature of the elicited antibodies is not known3–6. Here we report on the antibody and memory B cell responses in a cohort of 20 volunteers who received either the Moderna (mRNA-1273) or Pfizer-BioNTech (BNT162b2) vaccines. Consistent with prior reports, 8 weeks after the second vaccine injection volunteers showed high levels of IgM, and IgG anti-SARS-CoV-2 spike protein (S) and receptor binding domain (RBD) binding titers3,5,6. Moreover, the plasma neutralizing activity, and the relative numbers of RBD-specific memory B cells were equivalent to individuals who recovered from natural infection7,8. However, activity against SARS-CoV-2 variants encoding E484K or N501Y or the K417N:E484K:N501Y combination was reduced by a small but significant margin. Consistent with these findings, vaccine-elicited monoclonal antibodies (mAbs) potently neutralize SARS-CoV-2, targeting a number of different RBD epitopes in common with mAbs isolated from infected donors. Structural analyses of mAbs complexed with S trimer suggest that vaccine- and virus-encoded S adopts similar conformations to induce equivalent anti-RBD antibodies. However, neutralization by 14 of the 17 most potent mAbs tested was reduced or abolished by either K417N, or E484K, or N501Y mutations. Notably, the same mutations were selected when recombinant vesicular stomatitis virus (rVSV)/SARS-CoV-2 S was cultured in the presence of the vaccine elicited mAbs. Taken together the results suggest that the monoclonal antibodies in clinical use should be tested against newly arising variants, and that mRNA vaccines may need to be updated periodically to avoid potential loss of clinical efficacy.
Metabolomics insights into osteoporosis through association with bone mineral density
Authors: Zhang Xiaoyu , Xu Hanfei , Li Gloria H. Y. , Long Michelle T. , Cheung Ching-Lung , Vasan Ramachandran S. , Hsu Yi-Hsiang , Kiel Douglas P. , Liu Ching-Ti
Published: January 2021

Osteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by LC-MS/MS in 1,552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2-10 years later using dual energy x-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified twenty-seven metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (AUC=0.74 for the model with identified metabolites and risk factors vs AUC=0.70 with risk factors alone, p=0.001; Net reclassification index=0.07, p=0.03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (FDR p-value=0.028). Furthermore, three causally related metabolites (glycine, Phosphatidylcholine [PC], and Triacylglycerol [TAG]) were negatively associated with FN-BMD while PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis.
Splenic denervation attenuates repeated social defeat stress-induced T-lymphocyte inflammation
Authors: Elkhatib Safwan K. , Moshfegh Cassandra M. , Watson Gabrielle F. , Schwab Aaron D. , Katsurada Kenichi , Patel Kaushik P. , Case Adam J.
Published: January 2021

Background

Post-traumatic stress disorder (PTSD) is a devastating psychological disorder that significantly increases the risk for inflammatory diseases. While the exact etiology of this predisposition remains unclear, PTSD canonically increases overall sympathetic tone resulting in increased norepinephrine (NE) outflow. Previously, we demonstrated that exogenous NE alters mitochondrial superoxide in T-lymphocytes to produce a pro-inflammatory T-helper 17 (TH17) phenotype. Therefore, we hypothesized sympathetic-driven neuroimmune interactions could mediate psychological trauma-induced T-lymphocyte inflammation.

Methods

Repeated social defeat stress (RSDS) is a preclinical murine model that recapitulates the behavioral, autonomic, and inflammatory aspects of PTSD. Targeted splenic denervation (Dnx) was performed to deduce the contribution of splenic sympathetic nerves to RSDS-induced inflammation. Eighty-five C57BL/6J mice underwent Dnx or sham-operation, followed by RSDS or control paradigms. Animals were assessed for behavioral, autonomic, inflammatory, and redox profiles.

Results

Dnx did not alter the antisocial or anxiety-like behavior induced by RSDS. In circulation, RSDS Dnx animals exhibited diminished levels of T-lymphocyte-specific cytokines (IL-2, IL-17A, and IL-22) compared to intact animals, whereas other non-specific inflammatory cytokines(e.g.,IL-6, TNF-α, and IL-10) were unaffected by Dnx. Importantly, Dnx specifically ameliorated the increases in RSDS-induced T-lymphocyte mitochondrial superoxide, TH17 polarization, and pro-inflammatory gene expression with minimal impact to non-T-lymphocyte immune populations.

Conclusions

Overall, our data suggest that sympathetic nerves regulate RSDS-induced splenic T-lymphocyte inflammation, but play a minimal role in the behavioral and non-T-lymphocyte inflammatory phenotypes induced by this psychological trauma paradigm.
Representation learning for neural population activity with Neural Data Transformers
Authors: Ye Joel , Pandarinath Chethan
Published: January 2021

Neural population activity is theorized to reflect an underlying dynamical structure. This structure can be accurately captured using state space models with explicit dynamics, such as those based on recurrent neural networks (RNNs). However, using recurrence to explicitly model dynamics necessitates sequential processing of data, slowing real-time applications such as brain-computer interfaces. Here we introduce the Neural Data Transformer (NDT), a non-recurrent alternative. We test the NDT’s ability to capture autonomous dynamical systems by applying it to synthetic datasets with known dynamics and data from monkey motor cortex during a reaching task well-modeled by RNNs. The NDT models these datasets as well as state-of-the-art recurrent models. Further, its non-recurrence enables 3.9ms inference, well within the loop time of real-time applications and more than 6 times faster than recurrent baselines on the monkey reaching dataset. These results suggest that an explicit dynamics model is not necessary to model autonomous neural population dynamics.

Code

github.com/snel-repo/neural-data-transformers.
Modelling the probability of detecting mass mortality events
Authors: Brunner Jesse L , Calabrese Justin M
Published: January 2021

While reports of mass mortality events (MMEs) are increasing in the literature, comparing the incidence of MMEs through time, among locations, or taxa is problematic without accounting for detection probabilities. MMEs involving small, cryptic species can be difficult to detect even during the event, and degradation and scavenging of carcasses can make the window for detection very short. As such, the number or occurrence rate of MMEs may often be severely underestimated, especially with infrequent observations. We develop a simple modeling framework to quantify the probability of detecting an MME as a function of the observation frequency relative to the rate at which MMEs become undetectable. This framework facilitates the design of surveillance programs and may be extended to correct estimates of the incidence of MMEs from actual surveillance data for more appropriate analyses of trends through time and among taxa.
A rapid pharmacogenomic assay to detect NAT2 polymorphisms and guide isoniazid dosing for tuberculosis treatment
Authors: Verma Renu , Patil Sunita , Zhang Nan , Moreira Flora M.F. , Vitorio Marize T. , Santos Andrea da S. , Wallace Ellen , Gnanashanmugam Devasena , Persing David , Savic Rada , Croda Julio , Andrews Jason R.
Published: January 2021

Rationale

Standardized weight-based dose of anti-tubercular drugs contributes to a substantial incidence of toxicities, inadequate treatment response, and relapse, in part due to variable drug levels achieved. Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase-2 (NAT2) gene explain the majority of interindividual pharmacokinetic variability of isoniazid (INH). However, an obstacle to implementing pharmacogenomic-guided dosing is the lack of a point-of-care assay.

Objectives

To develop and test a NAT2 classification algorithm, validate its performance in predicting isoniazid clearance, and develop a prototype pharmacogenomic assay.

Methods

We trained random forest models to predict NAT2 acetylation genotype from unphased SNP data using a global collection of 8,561 phased genomes. We enrolled 48 pulmonary TB patients, performed sparse pharmacokinetic sampling, and tested the acetylator prediction algorithm accuracy against estimated INH clearance. We then developed a cartridge-based multiplex qPCR assay on the GeneXpert platform and assessed its analytical sensitivity on whole blood samples from healthy individuals.

Measurements and Main Results

With a 5-SNP model trained on two-thirds of the data (n=5,738), out-of-sample acetylation genotype prediction accuracy on the remaining third (n=2,823) was 100%. Among the 48 TB patients, predicted acetylator types were: 27 (56.2%) slow, 16 (33.3%) intermediate and 5 (10.4%) rapid. INH clearance rates were lowest in predicted slow acetylators (median 19.3 L/hr), moderate in intermediate acetylators (median 41.0 L/hr) and highest in fast acetylators (median 46.7 L/hr). The cartridge-based assay accurately detected all allele patterns directly from 25ul of whole blood.

Conclusions

An automated pharmacogenomic assay on a platform widely used globally for tuberculosis diagnosis could enable personalized dosing of isoniazid.

This manuscript describes the development and validation of point-of-care multiplex pharmacogenomic assay to guide personalized dosing of isoniazid for treatment or prevention of tuberculosis.
Quantifying nanotherapeutics penetration using hydrogel based microsystem as a new 3Din vitroplatform
Authors: Goodarzi Saba , Prunet Audrey , Rossetti Fabien , Bort Guillaume , Tillement Olivier , Porcel Erika , Lacombe Sandrine , Wu Ting-Di , Guerquin-Kern Jean-Luc , Delanoë-Ayari Hélène , Lux François , Rivière Charlotte
Published: January 2021

The huge gap between 2Din vitroassays used for drug screening, and thein vivo3D-physiological environment hampered reliable predictions for the route and accumulation of nanotherapeuticsin vivo.For such nanotherapeutics, Multi-Cellular Tumour Spheroids (MCTS) is emerging as a good alternativein vitromodel. However, the classical approaches to produce MCTS suffer from low yield, slow process, difficulties in MCTS manipulation and compatibility with high-magnification fluorescent optical microscopy. On the other hand, spheroid-on-chip set-ups developed so far require a microfluidic practical knowledge difficult to transfer to a cell biology laboratory.

We present here a simple yet highly flexible 3D-model microsystem consisting of agarose-based microwells. Fully compatible with the multi-well plates format conventionally used in cell biology, our simple process enables the formation of hundreds of reproducible spheroids in a single pipetting. Immunostaining and fluorescent imaging including live high-resolution optical microscopy can be performedin-situ, with no manipulation of spheroids.

As a proof-of-principle of the relevance of suchin vitroplatform for nanotherapeutics evaluation, this study investigates the kinetic and localization of nanoparticles within colorectal cancer MCTS cells (HCT-116). The nanoparticles chosen are sub-5 nm ultrasmall nanoparticles made of polysiloxane and gadolinium chelates that can be visualized in MRI (AGuIX®, currently implicated in clinical trials as effective radiosensitizers for radiotherapy) and confocal microscopy after addition of Cy 5.5. We show that the amount of AGuIX®nanoparticles within cells is largely different in 2D and 3D. Using our flexible agarose-based microsystems, we are able to resolve spatially and temporally the penetration and distribution of AGuIX®nanoparticles within MCTS. The nanoparticles are first found in both extracellular and intracellular space of MCTS. While the extracellular part is washed away after few days, we evidenced intracellular localisation of AGuIX®, mainly within lysosomes compartment, but also occasionally within mitochondria. Our agarose-based microsystem appears hence as a promising 3Din vitrouser-friendly platform for investigation of nanotherapeutics transport, ahead ofin vivostudies.

Abstract Figure

Graphical abstract
Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition
Authors: Nakadai Ryosuke
Published: January 2021

Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data.
FOD-Net: A Deep Learning Method for Fiber Orientation Distribution Angular Super Resolution
Authors: Zeng Rui , Lv Jinglei , Wang He , Zhou Luping , Barnett Michael , Calamante Fernando , Wang Chenyu
Published: January 2021

Mapping the human connectome using fiber-tracking permits the study of brain connectivity and yields new insights into neuroscience. However, reliable connectome reconstruction using diffusion magnetic resonance imaging (dMRI) data acquired by widely available clinical protocols remains challenging, thus limiting the connectome / tractography clinical applications. Here we develop fiber orientation distribution (FOD) network (FOD-Net), a deep-learning-based framework for FOD angular super-resolution. Our method enhances the angular resolution of FOD images computed from common clinical-quality dMRI data, to obtain FODs with quality comparable to those produced from advanced research scanners. Super-resolved FOD images enable superior tractography and structural connectome reconstruction from clinical protocols. The method was trained and tested with high-quality data from the Human Connectome Project (HCP) and further validated with a local clinical 3.0T scanner. Using this method, we improve the angular resolution of FOD images acquired with typical single-shell low-angular-resolution dMRI data (e.g., 32 directions,b= 1000 s/mm2) to approximate the quality of FODs derived from time-consuming, multi-shell high-angular-resolution dMRI research protocols. We also demonstrate tractography improvement, removing spurious connections and bridging missing connections. We further demonstrate that connectomes reconstructed by super-resolved FODs achieve comparable results to those obtained with more advanced dMRI acquisition protocols, on both HCP and clinical 3.0T data. Advances in deep-learning approaches used in FOD-Net facilitate the generation of high quality tractography / connectome analysis from existing clinical MRI environments. Our code is freely available athttps://github.com/ruizengalways/FOD-Net.
Studying the course of Covid-19 by a recursive delay approach
Authors: Kreck Matthias , Scholz Erhard
Published: January 2021

Abstract

In an earlier paper we proposed a recursive model for epidemics; in the present paper we generalize this model to include the asymptomatic or unrecorded symptomatic people, which we call dark people (dark sector). We call this the SEPARd-model. A delay differential equation version of the model is added; it allows a better comparison to other models. We carry this out by a comparison with the classical SIR model and indicate why we believe that the SEPARd model may work better for Covid-19 than other approaches.

In the second part of the paper we explain how to deal with the data provided by the JHU, in particular we explain how to derive central model parameters from the data. Other parameters, like the size of the dark sector, are less accessible and have to be estimated more roughly, at best by results of representative serological studies which are accessible, however, only for a few countries. We start our country studies with Switzerland where such data are available. Then we apply the model to a collection of other countries, three European ones (Germany, France, Sweden), the three most stricken countries from three other continents (USA, Brazil, India). Finally we show that even the aggregated world data can be well represented by our approach.

At the end of the paper we discuss the use of the model. Perhaps the most striking application is that it allows a quantitative analysis of the influence of the time until people are sent to quarantine or hospital. This suggests that imposing means to shorten this time is a powerful tool to flatten the curves.
Impact of Public Health Education Program on the Novel Coronavirus Outbreak in the United States
Authors: Iboi Enahoro A. , Richardson Ariana , Ruffin Rachel , Ingram DeAndrea , Clark Jailyn , Hawkins Jala , McKinney Maati , Horne Nianza , Ponder Reyla , Denton Zoe , Agusto Folashade B. , Oduro Bismark , Akinyemi Lanre
Published: January 2021

The coronavirus outbreak in the United States continues to pose a serious threat to human lives. Public health measures to slow down the spread of the virus involve using a face mask, social-distancing, and frequent hand washing. Since the beginning of the pandemic, there has been a global campaign on the use of non-pharmaceutical interventions (NPIs) to curtail the spread of the virus. However, the number of cases, mortality, and hospitalization continue to rise globally, including in the United States. We developed a mathematical model to assess the impact of a public health education program on the coronavirus outbreak in the US. Our simulation showed the prospect of an effective public health education program in reducing both the cumulative and daily mortality of the novel coronavirus. Finally, our result suggests the need to obey public health measures as loss of willingness would increase the cumulative and daily mortality in the US.
Immune Markers Are Associated with Cognitive Performance in a Multiethnic Cohort: the Northern Manhattan Study
Authors: Elkind Mitchell S. V. , Moon Michelle , Rundek Tatjana , Wright Clinton B. , Cheung Ken , Sacco Ralph L. , Hornig Mady
Published: January 2021

OBJECTIVE

To determine whether immune protein panels add significant information to correlates of cognition.

BACKGROUND

Immune mechanisms in vascular cognitive impairment and dementia are incompletely characterized.

DESIGN/METHODS

A subsample of the prospective Northern Manhattan Study underwent detailed neuropsychological testing. Cognitive scores were converted into Z-scores and categorized into four domains (memory, language, processing speed, and executive function) based on factor analysis. Blood samples were analyzed using a 60-plex immunoassay. We used least absolute shrinkage and selection operator (LASSO) procedures to select markers and their interactions independently associated with cognitive scores. Linear regression models assessed cross-sectional associations of known correlates of cognition with cognitive scores, and assessed model fit before and after addition of LASSO-selected immune markers.

RESULTS

Among 1179 participants (mean age 70±8.9 years, 60% women, 68% Hispanic), inclusion of LASSO-selected immune markers improved model fit above age, education, and other risk factors (p for likelihood ratio test<0.005 for all domains). C-C Motif Chemokine Ligand 11 (CCL 11, eotaxin), C-X-C Motif Chemokine Ligand 9 (CXCL9), hepatocyte growth factor (HGF), and serpin E1 (plasminogen activator inhibitor-1) were associated with each of the domains and with overall cognitive function. Immune marker effects were comparable to conventional risk factors: for executive function, each standard deviation (SD) increase in CCL11 was associated with an effect equivalent to aging three years; for memory, HGF had twice the effect of aging.

CONCLUSIONS

Immune markers associate with cognitive function in a multi-ethnic cohort. Further work is needed to validate these findings and determine optimal treatment targets.
The impacts of COVID-19 vaccine timing, number of doses, and risk prioritization on mortality in the US
Authors: Wang Xutong , Du Zhanwei , Johnson Kaitlyn E. , Pasco Remy F. , Fox Spencer J. , Lachmann Michael , McLellan Jason S. , Meyers Lauren Ancel
Published: January 2021

As COVID-19 vaccination begins worldwide, policymakers face critical trade-offs. Using a mathematical model of COVID-19 transmission, we find that timing of the rollout is expected to have a substantially greater impact on mortality than risk-based prioritization and uptake and that prioritizing first doses over second doses may be life saving.
Loss of C3aR induces immune infiltration and inflammatory microbiota in a new spontaneous model of colon cancer
Authors: Krieg Carsten , Weber Lukas M. , Fosso Bruno , Hardiman Gary , Mileti Erika , Aidy Sahar El , Marzano Marinella , Robinson Mark D. , Guglietta Silvia
Published: January 2021

Several lines of evidence suggest that inflammation plays a pivotal role in the development and progression of colorectal cancer (CRC) and can be unleashed by the loss of innate immunosurveillance. The complement system is a well characterized first line of defense against pathogens and a central component of the immune response. Emerging evidence suggests that complement anaphylatoxin C3a produced upon complement activation and acting via its receptor (C3aR) may play a role in intestinal homeostasis. However, to date, it is unknown whether and how the C3a/C3aR axis can affect CRC. By mining publicly available datasets, we found that CpG island methylation ofc3ar1occurs in CRC patients and is associated with significant downregulation of C3aR. By reverse-translating this finding we were able to shift in APCMin/+mice the tumorigenesis from the small intestine to the colon therefore generating a novel mouse model, which more closely mirrors the CRC in humans. Transcriptomic analysis on colorectal polyps from our newly developed genetic mouse model revealed a significant increase in innate and adaptive immune signatures in absence of C3aR. Furthermore, loss of C3aR significantly impacted the fecal and tumor-associated microbiota and supported the blooming of pro-inflammatory bacterial species as confirmed by experiments of fecal microbiota transplantation.

Future studies will elucidate whether loss of C3aR can be exploited as a biomarker for sub-groups of CRC and whether the C3a/C3aR axis may be exploited for the generation of more effective therapeutic interventions.
Structural and functional characterization of a putativede novogene inDrosophila
Authors: Lange Andreas , Patel Prajal H. , Heames Brennen , Damry Adam M. , Saenger Thorsten , Jackson Colin J. , Findlay Geoffrey D. , Bornberg-Bauer Erich
Published: January 2021

Comparative genomic studies have repeatedly shown that new protein-coding genes can emergede novofrom non-coding DNA. Still unknown is how and when the structures of encodedde novoproteins emerge and evolve. Combining biochemical, genetic and evolutionary analyses, we elucidate the function and structure ofgoddard, a gene which appears to have evolvedde novoat least 50 million years ago within theDrosophilagenus.

Previous studies found thatgoddardis required for male fertility. Here, we show that Goddard protein localizes to elongating sperm axonemes and that in its absence, elongated spermatids fail to undergo individualization. Combining modelling, NMR and CD data, we show that Goddard protein contains a large central α-helix, but is otherwise partially disordered. We find similar results for Goddard’s orthologs from divergent fly species and their reconstructed ancestral sequences. Accordingly, Goddard’s structure appears to have been maintained with only minor changes over millions of years.
The molecular basis of coupling between poly(A)-tail length and translational efficiency
Authors: Xiang Kehui , Bartel David P.
Published: January 2021

In animal oocytes and early embryos, mRNA poly(A)-tail length strongly influences translational efficiency (TE), but later in development this coupling between tail length and TE disappears. Here, we elucidate how this coupling is first established and why it disappears. Overexpressing cytoplasmic poly(A)-binding protein (PABPC) in frog oocytes specifically improved translation of short-tailed mRNAs, thereby diminishing coupling between tail length and TE. Thus, coupling requires limiting PABPC, implying that in coupled systems longer-tail mRNAs better compete for limiting PABPC. In addition to expressing excess PABPC, post-embryonic cells had two other properties that prevented strong coupling: terminal-uridylation-dependent destabilization of mRNAs lacking bound PABPC, and a regulatory regime wherein PABPC contributes minimally to TE. Thus, these results revealed three fundamental mechanistic requirements for coupling and defined the context-dependent functions for PABPC, in which this protein promotes TE but not mRNA stability in coupled systems and mRNA stability but not TE in uncoupled systems.