bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatially regulated designs of incidence surveys can match the precision of classical survey designs whilst requiring smaller sample sizes: the case of snakebite in Sri Lanka
Authors: Ediriweera Dileepa Senajith , de Silva Tiloka , Kasturiratne Anuradhani , de Silva Hithanadura Janaka , Diggle Peter John
Published: April 2022

Background

Snakebite envenoming is a neglected tropical disease. Data from the worst affected countries are limited because conducting epidemiological surveys is challenging. We assessed the utility of inhibitory geostatistical design with close pairs (ICP) to estimate snakebite incidence.

Methods

The National Snakebite Survey (NSS) in Sri Lanka adopted a multistage cluster sampling design, based on population distribution, targeting 1% of the country’s population. Using a simulation-based study, we assessed predictive efficiency of ICP against a classical survey design at different fractions of the original sample size of the NSS. We also assessed travel distance, time taken to complete the survey, and sensitivity and specificity for detecting high-risk areas for snake envenoming, when using these methods.

Results

A classical survey design with 33% of the original NSS sample size was able to yield a similar predictive efficiency. ICP yielded the same at 25% of the NSS sample size, a 25% reduction in sample size compared to a classical survey design. ICP showed >80% sensitivity and specificity for detecting high-risk areas of envenoming when the sampling fraction was >20%. When ICP was adopted with 25% of the original NSS sample size, travel distance was reduced by >40% and time to conduct the survey was reduced by >75%.

Conclusions

This study showed that snakebite envenoming incidence can be estimated by adopting an ICP design with similar precision at a lower sample size than a classical design. This would substantially save resources and time taken to conduct epidemiological surveys and may be suited for low resource settings.

Key messages

Inhibitory geostatistical design with close pairs (ICP) for incidence surveys can match the precision of classical survey designs at lower sample sizes.

The ICP design showed a lower predictive variance than classical design, indicating ICP designs were able to produce more reliable predictions.

The ICP design showed a lower time to complete the survey than the classical sampling method.

Although primary sampling units in the ICP design maintain a minimum distance between two units, ICP did not increase travel distance compared to the classical survey design.

Resource requirements and time to complete surveys can be reduced without increasing the distance to travel by adopting ICP design for epidemiological surveys.
Estimates of Cross-Border Menthol Cigarette Sales Following the Comprehensive Tobacco Flavor Ban in Massachusetts
Authors: Rich Jacob James
Published: April 2022

On June 1, 2020, Massachusetts became the first state in the US to ban all flavored tobacco product sales, including menthol cigarettes. Recent research has estimated the reduction in cigarette sales in Massachusetts following the comprehensive tobacco flavor ban, but noted that missing data on border states was a major limitation of the findings. This letter replicates the procedures of Asare et al. with 1540 state-months and then adds Asare et al.’s missing states with 2420 total observations for the period January 2017 to July 2021. The replication confirms Asare et al.’s adjusted estimate for the reduction in menthol cigarettes, which falls within their 95% confidence interval. However, assigning Massachusetts and its bordering states as a single treatment group leads to an increase of 191.95 (95% CI, 96.82 to 287.09) total cigarette packs sold per 1000 people in the six-state region. In the 12-month period following the comprehensive flavor ban in Massachusetts, the state sold 29.96 million fewer cigarette packs compared to the prior period. However, a total of 33.36 million additional cigarette packs were sold during the same post-ban period in the counties that bordered Massachusetts. Given decreasing rates of smoking in all five bordering states between 2019 and 2020, the increase in border-state cigarette sales following the comprehensive flavor ban should be interpreted as a lower-bound estimate for cigarettes that were ultimately consumed in Massachusetts.
Clinical characteristics and outcome of immunocompromised patients with COVID-19 caused by the Omicron variant: a prospective observational study
Authors: Malahe S. Reshwan K. , Hoek Rogier A.S. , Dalm Virgil A.S.H. , Broers Annoek E.C. , den Hoed Caroline M. , Manintveld Olivier C. , Baan Carla C. , van Deuzen Charlotte M. , Papageorgiou Grigorios , Bax Hannelore I. , Van Kampen Jeroen J. , Hellemons Merel E. , Kho Marcia M.L. , de Vries Rory D. , Molenkamp Richard , Reinders Marlies E.J. , Rijnders Bart J.A.
Published: April 2022

Background

In the general population, illness after infection with the SARS-CoV-2 Omicron variant is less severe compared with previous variants. Data on the disease burden of Omicron in immunocompromised patients are lacking. We investigated the clinical characteristics and outcome of a cohort of immunocompromised patients with COVID-19 caused by Omicron.

Methods

Solid organ transplant recipients, patients on anti-CD20 therapy, and allogenic hematopoietic stem cell transplantation recipients on immunosuppressive therapy infected with the Omicron variant, were included. Patients were contacted regularly until symptom resolution. Clinical characteristics of consenting patients were collected through their electronic patient files. To identify possible risk factors for hospitalization, a univariate logistic analysis was performed.

Results

A total of 114 consecutive immunocompromised patients were enrolled. Eighty-nine percent had previously received three mRNA vaccinations. While only one patient died, 23 (20%) required hospital admission for a median of 11 days. A low SARS-CoV-2 IgG antibody response (<300 BAU/mL) at diagnosis, higher age, being a lung transplant recipient, more comorbidities and a higher frailty were associated with hospital admission (all p<0.01). At the end of follow-up, 25% had still not fully recovered. Of the 23 hospitalized patients, 70% had a negative and 92% a low IgG (<300 BAU/mL) antibody response at admission. Sotrovimab was administered to 17 of them, of which one died.

Conclusions

While the mortality in immunocompromised patients infected with Omicron was low, hospital admission was frequent and the duration of symptoms often prolonged. Besides vaccination, other interventions are needed to limit the morbidity from COVID-19 in immunocompromised patients.

COVID-19-associated morbidity and mortality in immunocompromised patients is unknown for the SARS-CoV-2 Omicron variant. This prospective registry, demonstrated low COVID-19-associated mortality in these vulnerable patients. However, morbidity remained substantial. Other interventions to abate COVID-19 severity are needed.
The prevalence of SARS-CoV-2 antibodies within the community of a private tertiary university in the Philippines: a serial cross sectional study
Authors: Sumpaico-Tanchanco Lourdes Bernadette , Sy Jenica , Dy Angel Belle C. , Levantino Myla , Amit Arianna Maever L , Wong John , Angeles Kirsten , Vergara John Paul
Published: April 2022

The antibody testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was used to detect the presence of antibodies in a private university setting. This serial cross-sectional study determined the seroprevalence of SARS-CoV-2 antibodies using qualitative and quantitative tests. Between June 2021 to December 2021, samples from 1,318 participants were tested, showing 47.80% of the study population yielding IgG antibodies to SARS-CoV-2 virus. A general increase in seroprevalence was observed from June to December 2021. However, a decreasing trend in IgG reactivity was found in vaccinated individuals over time. IgG antibody formation was observed across all brands of vaccines.
Early dosage compensation of zygotically-expressed genes in Drosophila melanogaster is mediated through a post-transcriptional regulatory mechanism
Authors: Blake Victoria M. , Eisen Michael B.
Published: April 2022

Many key regulators of early embryogenesis in Drosophila melanogaster are X-linked. However, the canonical, MSL-mediated dosage compensation, which involves hyper-transcription of the genes on the single X chromosome in males, is not active until the post-syncytial stage of development. A separate MSL-independent dosage compensation system active earlier in development has been described, though the mechanism through which the process functions remain unclear. In this study, we quantified transcription in living embryos at single-locus resolution to determine if early dosage compensation of the X-linked genes buttonhead and giant is sensitive to X chromosome dose. We found no evidence for a transcriptionally regulated mechanism of early dosage compensation, suggesting that the previously observed compensation of mRNA levels for these genes is achieved via a post-transcriptional regulatory mechanism.
Faster SARS-CoV-2 sequence validation and annotation for GenBank using VADR
Authors: Nawrocki Eric P
Published: April 2022

Background

In 2020 and 2021, more than 1.5 million SARS-CoV-2 sequences were submitted to GenBank. The initial version (v1.0) of the VADR (Viral Annotation DefineR) software package that GenBank uses to automatically validate and annotate incoming viral sequences is too slow and memory intensive to process many thousands of SARS-CoV-2 sequences in a reasonable amount of time. Additionally, long stretches of ambiguous N nucleotides, which are common in many SARS-CoV-2 sequences, prevent VADR from accurate validation and annotation.

Results

VADR has been updated to more accurately and rapidly annotate SARS-CoV-2 sequences. Stretches of consecutive Ns are now identified and temporarily replaced with expected nucleotides to facilitate processing, and the slowest steps have been overhauled using blastn and glsearch, increasing speed, reducing the memory requirement from 64Gb to 2Gb per thread, and allowing simple, coarse-grained parallelization on multiple processors per host.

Conclusion

VADR is now nearly 1000 times faster than it was in early 2020 for processing SARS-CoV-2 sequences submitted to GenBank. It has been used to screen and annotate more than 1.5 million SARS-CoV-2 sequences since June 2020, and it is now efficient enough to cope with the current rate of hundreds of thousands of submitted sequences per month. Version 1.4.1 is freely available (https://github.com/ncbi/vadr) for local installation and use.
Detecting epistatic interactions in genomic data using Random Forests
Authors: Al-Mamun Hawlader A. , Dunne Rob , Tellam Ross L. , Verbyla Klara
Published: April 2022

Epistatic interactions can play an important role in the genetic mechanisms that control phenotypic variation. However, identifying these interactions in high dimensional genomic data can be very challenging due to the large computational burden induced by the high volume of combinatorial tests that have to be performed to explore the entire search space. Random Forests Decision Trees are widely used in a variety of disciplines and are often said to detect interactions. However, Random Forests models do not explicitly detect variable interactions. Most Random Forests based methods that claim to detect interactions rely on different forms of variable importance measures that suffer when the interacting variables have very small or no marginal effects. The proposed Random Forests based method detects interactions using a two-stage approach and is computationally efficient. The approach is demonstrated and validated through its application on several simulated datasets representing different data structures with respect to genomic data and trait heritabilities. The method is also applied to two high dimensional genomics data sets to validate the approach. In both cases, the method results were used to identify several genes closely positioned to the interacting markers that showed strong biological potential for contributing to the genetic control for the respective traits tested.

Contact

hawlader.almamun@csiro.au
Discovery of new senolytics using machine learning
Authors: Smer-Barreto Vanessa , Quintanilla Andrea , Elliot Richard J. R. , Dawson John C. , Sun Jiugeng , Carragher Neil O. , Acosta Juan Carlos , Oyarzún Diego A.
Published: April 2022

Cellular senescence is a stress response characterised by a permanent cell cycle arrest and a proinflammatory secretome. In addition to its tumour suppressor role, senescence is involved in ageing and promotes many disease processes such as cancer, type 2 diabetes, osteoarthritis, and SARS-CoV-2 infection. There is a growing interest in therapies based on targeted elimination of senescent cells, yet so far only a few such senolytics are known, partly due to the poor grasp of the molecular mechanisms that control the senescence survival programme. Here we report a highly effective machine learning pipeline for the discovery of senolytic compounds. Using solely published data, we trained machine learning algorithms to classify compounds according to their senolytic action. Models were trained on as few as 58 known senolytics against a background of FDA-approved compounds or in late-stage clinical development (2,523 in total). We computationally screened various chemical libraries and singled out top candidates for validation in human lung fibroblasts (IMR90) and lung adenocarcinoma (A549) cell lines. This led to the discovery of three novel senolytics: ginkgetin, oleandrin and periplocin, with potency comparable to current senolytics and a several hundred-fold reduction in experimental screening costs. Our work demonstrates that machine learning can take maximum advantage of existing drug screening data, paving the way for new open science approaches to drug discovery for senescence-associated diseases.
Antimicrobial wound care in an ant society
Authors: Frank Erik. T. , Kesner Lucie , Liberti Joanito , Helleu Quentin , LeBoeuf Adria C. , Dascalu Andrei , Sponsler Douglas B. , Azuma Fumika , Economo Evan P. , Waridel Patrice , Engel Philipp , Schmitt Thomas , Keller Laurent
Published: April 2022

Infected wounds pose a major mortality risk in animals1,2. Injuries are common in the antMegaponera analis, which raids pugnacious prey3,4. Here we show thatM. analiscan determine when wounds are infected and treat them accordingly. By applying a variety of antimicrobial compounds and proteins secreted from the metapleural gland to infected wounds, workers reduce the mortality of infected individuals by 90%. Chemical analyses showed that wound infection is associated with specific changes in the cuticular hydrocarbon profile, thereby likely allowing nestmates to diagnose the infection state of injured individuals and apply the appropriate antimicrobial treatment. This study demonstrates that the targeted use of antimicrobials to treat infected wounds, previously thought to be a uniquely human behavior, has evolved in insect societies as well.
The double round-robin population unravels the genetic architecture of grain size in barley
Authors: Shrestha Asis , Cosenza Francesco , van Inghelandt Delphine , Wu Po-Ya , Li Jinquan , Casale Federico A. , Weisweiler Marius , Stich Benjamin
Published: April 2022

Grain number, size and weight primarily determine the yield of barley. Although the genes regulating grain number are well studied in barley, the genetic loci and the causal gene for sink capacity are poorly understood. Therefore, the primary objective of our work was to dissect the genetic architecture of grain size and weight in barley. We used a multi-parent population developed from a genetic cross between 23 diverse barley inbreds in a double round-robin design. Seed size-related parameters such as grain length, grain width, grain area and thousand-grain weight were evaluated in the HvDRR population comprising 45 recombinant inbred line sub-populations. We found significant genotypic variation for all seed size characters and observed 84 % or higher heritability across four environments. The results of the quantitative trait locus (QTL) detection indicate that the genetic architecture of grain size is more complex than reported previously. In addition, both cultivars and landraces contributed positive alleles at grain size QTLs. Candidate genes identified using genome-wide variant calling data for all parental inbred lines indicated overlapping and potential novel regulators of grain size in cereals. Furthermore, our results indicated that sink capacity was the primary determinant of grain weight in barley.

Highlight

Multi parent population uncovered the natural allelic series across quantitative loci associated with grain size and weight that will contribute to identifying causal genes and yield improvement in barley.
Dynamic Features of Chromosomal Instability during Culture of Induced Pluripotent Stem Cells
Authors: Dubose Casey O. , Daum John R. , Sansam Christopher L. , Gorbsky Gary J.
Published: April 2022

Induced pluripotent stem cells (iPSCs) hold great potential for regenerative medicine. By reprogramming a patient”s own cells, immunological rejection can be avoided during transplantation. For expansion and gene editing, iPSCs are grown in artificial culture for extended times. Culture affords potential danger for accumulation of genetic aberrations. To study these, two iPS cell lines were cultured and periodically analyzed using advanced optical mapping to detect and classify chromosome numerical and segmental changes that included deletions, insertions, balanced translocations and inversions. In one of the lines, a population trisomic for chromosome 12 gained dominance over a small number of passages. This appearance and dominance of the culture by chromosome 12 trisomic cells was tracked through intermediate passages by analysis of chromosome spreads. Mathematical modeling suggested that the proliferation rates of diploid versus trisomic cells could not account for the rapid dominance of the trisomic population. In addition, optical mapping revealed hundreds of structural variations distinct from those generally found within the human population. Many of these structural variants were detected in samples taken early in the culturing process and were maintained in late passage samples, while others were acquired over the course of culturing.
MycoPhylo experiment reveals how mycorrhiza types and phylogenetic relationships affect soil biodiversity and functioning
Authors: Tedersoo Leho , Loit Kaire , Agan Ahto , Rahimlou Saleh , Vask Annaliisa , Drenkhan Rein
Published: April 2022

Natural forests and abandoned agricultural lands are increasingly replaced by monospecific forest plantations that have poor capacity to support biodiversity and ecosystem services. Natural forests harbour plants belonging to different mycorrhiza types that differ in their microbiome and carbon and nutrient cycling properties.

Here we describe the MycoPhylo field experiment that encompasses 116 woody plant species from three mycorrhiza types and 237 plots, with plant diversity and mycorrhiza type diversity ranging from one to four and one to three per plot, respectively.

The MycoPhylo experiment enables us to test hypotheses about the plant species, species diversity, mycorrhiza type, and mycorrhiza type diversity effects and their phylogenetic context on soil microbial diversity and functioning and soil processes.

Alongside with other experiments in the TreeDivNet consortium, MycoPhylo will contribute to our understanding of the tree diversity effects on soil biodiversity and ecosystem functioning across biomes, especially from the mycorrhiza type and phylogenetic conservatism perspectives.
Extension of PERMANOVA to Testing the Mediation Effect of the Microbiome
Authors: Yue Ye , Hu Yi-Juan
Published: April 2022

Background

Recently, we have seen a growing volume of evidence linking the microbiome and human diseases or clinical outcomes, as well as evidence linking the microbiome and environmental exposures. Now comes the time to assess whether the microbiome mediated the effects of the exposures on the outcomes, which will enable researchers to develop interventions to modulate the outcomes by modifying the microbiome composition. Use of distance matrices is a popular approach to analyzing complex microbiome data that are high-dimensional, sparse, and compositional. However, the existing distance-based methods for mediation analysis of microbiome data, MedTest and MODIMA, only work well in limited scenarios.

Results

PERMANOVA is currently the most commonly used distance-based method for testing microbiome associations. Using the idea of inverse regression, here we extend PER-MANOVA to testing microbiome mediation effects by including both the exposure and the outcome as covariates and basing the test on the product of theirF-statistics. This extension of PERMANOVA, which we call PERMANOVA-med, naturally inherits all the flexible features of PERMANOVA, e.g., allowing adjustment of confounders, accommodating continuous, binary, and multivariate exposure and outcome variables including survival outcomes, and providing an omnibus test that combines the results from analyzing multiple distance matrices. Our extensive simulations indicated that PERMANOVA-med always controlled the type I error and had compelling power over MedTest and MODIMA. Frequently, MedTest had diminished power and MODIMA had inflated type I error. Using real data on melanoma immunotherapy response, we demonstrated the wide applicability of PERMANOVA-med through 16 different mediation analyses, only 6 of which could be performed by MedTest and 4 by MODIMA.

Availability and Implementation

PERMANOVA-med has been added to the existing function “permanovaFL” in our R package LDM, which is available on GitHub athttps://github.com/yijuanhu/LDM.
Optimized Repli-seq: Improved DNA Replication Timing Analysis by Next-Generation Sequencing
Authors: Rivera-Mulia Juan Carlos , Trevilla-Garcia Claudia , Martinez-Cifuentes Santiago
Published: April 2022

The human genome is divided into functional units that replicate at specific times during S-phase. This temporal program is known as replication timing (RT) and is coordinated with the spatial organization of the genome and transcriptional activity. RT is also cell type-specific, dynamically regulated during development, and alterations in RT are observed in multiple diseases. Thus, precise measure of RT is critical to understand the role of RT in gene function regulation. Distinct methods for assaying the RT program exist; however, conventional methods require thousands of cells as input, prohibiting its applicability to samples with limited cell numbers such as those from disease patients or from early developing embryos. Although single-cell analysis of RT has been developed as an alternative, these methods are low throughput and produce low resolution data. Here, we developed an improved method to measure RT genome-wide that enables high resolution analysis of low input samples. This method incorporates direct cell sorting into lysis buffer, as well as DNA fragmentation and library preparation in a single tube, resulting in higher yields, increased quality, and reproducibility with decreased costs. We also performed a systematic data processing analysis to provide standardized parameters for RT measurement. This optimized method facilitates RT analysis and will enable its application to a broad range of studies investigating the role of RT in gene expression, nuclear architecture, and disease.
Toward quantitative metabarcoding
Authors: Shelton Andrew Olaf , Gold Zachary J. , Jensen Alexander J. , D’Agnese Erin , Allan Elizabeth Andruszkiewicz , Van Cise Amy , Gallego Ramón , Ramón-Laca Ana , Garber-Yonts Maya , Parsons Kim , Kelly Ryan P.
Published: April 2022

Amplicon-sequence data from environmental DNA (eDNA) and microbiome studies provides important information for ecology, conservation, management, and health. At present, amplicon-sequencing studies – known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture – struggle to link genetic observations to underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology following decades of microbial and microbiome work using similar techniques, it becomes more important to develop ways ot make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying PCR mechanism explains observed patterns of amplicon data in a general way. By modeling the process through which amplicon-sequence data arises, rather than transforming the data post-hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.
Museomic approaches to genotype historicCinchonabarks
Authors: Canales Nataly Allasi , Gardner Elliot M. , Gress Tobias , Walker Kim , Bieker Vanessa , Martin Michael D. , Nesbitt Mark , Antonelli Alexandre , Rønsted Nina , Barnes Christopher J.
Published: April 2022

Over the last few centuries, millions of plant specimens have been collected and stored within herbaria and biocultural collections. They therefore represent a considerable resource for a broad range of scientific uses. However, collections degrade over time, and it is therefore increasingly difficult to characterise their genetic signatures. Here, we genotyped highly degradedCinchonabarks and leaves from herbaria using two separate high-throughput sequencing methods (HtS) and compared their performance. We subsequently genotyped specimens using genome skimming, the most commonly performed high-throughput sequencing (HtS) technique. We additionally used a recently developed capture bait set (Angiosperm353) for a target enrichment approach. Specifically, phylogenomic analyses of modern leaf and historical barks ofCinchonawere performed, including 23 historical barks and six fresh leaf specimens. We found that samples degraded over time, which directly reduced the quantity and quality of the data produced by both methodologies (in terms of reads mapped to the references). However, we found that both approaches generated enough data to infer phylogenetic relationships, even between highly degraded specimens that are over 230 years old. However, the target capture kit produced data for target nuclear loci and also chloroplast data, which allowed for phylogenies to be inferred from both genomes, whereas it was only possible to use chloroplast data using genome skimming. We therefore find the Angiosperms353 target capture kit a powerful alternative to genome skimming, which can be used to obtain more information from herbarium specimens, and ultimately additional cultural benefits.
Which life history strategy can maintain high genetic diversity in plants?
Authors: Tsuzuki Yoichi , Takada Takenori , Ohara Masashi
Published: April 2022

Classifying a variety of plant life histories is an important step to understand ecological and evolutionary background of life history diversification in plants. Principal component analysis (PCA) of life history traits, as well as elasticity analysis using a ternary diagram, successfully categorized the diverse life histories and clarified their link to various ecological characteristics, such as population dynamics, functional traits, and conservation status. However, the relationships with population genetic properties, including genetic diversity, have not been explored very much. In this study, we overlaid annual change rate of expected heterozygosity η on life history spectrum obtained by PCA and elasticity analysis to examine which life history strategy can maintain high genetic diversity over time. We found that η gradually changed along the fast-slow continuum and that slow-paced life histories maintained high genetic diversity, probably due to generation overlap. Elasticity analysis showed that life histories that highly depend on stasis also maintained genetic diversity. As genetic diversity reflects adaptive potential to environmental changes, our study provides a new genetic perspective on adaptative evolution and population viability to life history study.
High Concentrations of floating life in the North Pacific Garbage Patch
Authors: Chong Fiona , Spencer Matthew , Maximenko Nikolai , Hafner Jan , McWhirter Andrew , Helm Rebecca R.
Published: April 2022

Floating life (obligate neuston) is a core component of the ocean surface food web. However, only one region of high neustonic abundance is known so far, the Sargasso Sea in the Subtropical North Atlantic, where floating life provides critical habitat structure and ecosystem services. Here, we hypothesize that floating life is also concentrated in other gyres with converging surface currents. To test this hypothesis, we collected samples through the eastern North Pacific Subtropical Gyre in the area of the North Pacific “garbage patch” (NPGP) known to accumulate floating anthropogenic debris. We found that densities of floating life were significantly higher inside the central part of NPGP than on its periphery, and there was a significant positive relationship between neuston abundance and plastic abundance. This work has important implications for the ecology and human impact of subtropical oceanic gyre ecosystems.
Mortality among healthcare workers in Indonesia during 18 months of COVID-19
Authors: Ekawati Lenny L. , Arif Ahmad , Hidayana Irma , Nurhasim Ahmad , Munziri M. Zakiyuddin , Lestari Karina D. , Tan Amanda , Ferdiansyah Firdaus , Nashiruddin Fikry , Adnani Qorinah E.S. , Malik Halik , Maharani Tri , Riza Andy , Pasaribu Monalisa , Abidin Khairul , Andrianto Adhi A. , Nursalam  , Sri Suhardiningsih A.V. , Jubaedah Ade , Widodo N.S. , Surendra Henry , Sudoyo Herawati , Smith Adrian D. , Kreager Philip , Baird J. Kevin , Elyazar Iqbal R.F.
Published: April 2022

The impact of SARS-CoV-2 infections upon Indonesian health care workers (HCWs) remains unclear, as mortality data specific to HCWs is not systematically collected or analyzed in this setting. This report describes findings from a systematic collation, abstraction and analysis of HCW fatalities during the first 18 months of COVID-19 in Indonesia. HCW who died during the period of March 2020 to July 2021 across Indonesia were identified on Pusara Digital, a community web-based digital cemetery database dedicated to HCW. We calculated mortality rates and death risk ratio among HCWs and the general population. Qualitative methods explored concerns regarding mortality among HCWs. The analysis suggests that at least 1,545 HCWs died during the study period. The death of males and females HCWs were almost equally distributed (51% vs. 49%). Most were medical doctors and specialists (535, 35%), nurses (428, 28%), and midwives (359, 23%). Deaths most frequently occurred in the age group of 40 to 59 years old with the median age of 50 years (IQR: 39-59). At least 322 (21%) deaths occurred with pre-existing conditions, including 45 who were pregnant. We estimated a minimal HCW mortality rate in Indonesia at 1.707 deaths per 1000 HCW during the first 18 months of COVID-19. Provincial HCW mortality rates ranged from 0.136 (West Sulawesi) to 5.32 HCW deaths per 1000 HCWs (East Java). HCW had a significantly higher mortality rate than the general population (RR = 4.92, 95% CI 4.67 – 5.17). The COVID-19 event in Indonesia resulted in the loss of many hundreds of HCWs, most of them being senior physicians, nurses, and midwives. The HCW death rates is 5-times higher than everyone else. The sheer sparseness of the workforce requires more protective steps and a national systematic surveillance of occupational mortality is urgently needed in this setting.
Utilization of health insurance by patients with diabetes or hypertension in urban hospitals in Mbarara, Uganda
Authors: Kangwagye Peter , Bright Laban Waswa , Atukunda Gershom , Basaza Robert , Bajunirwe Francis
Published: April 2022

Background

Diabetes and hypertension are among the leading contributors to global mortality and require life-long medical care. However, many patients cannot access quality healthcare due to high out-of-pocket expenditures, thus health insurance would help provide relief. This paper examines factors associated with utilization of health insurance by patients with diabetes or hypertension at two urban hospitals in Mbarara, southwestern Uganda.

Methods

We used a cross-sectional survey design to collect data from patients with diabetes or hypertension attending two hospitals located in Mbarara. Logistic regression models were used to examine associations between demographic factors, socio-economic factors and awareness of scheme existence and health insurance utilization.

Results

We enrolled 370 participants, 235 (63.5%) females and 135 (36.5%) males, with diabetes or hypertension. Patients who were not members of a microfinance scheme were 76% less likely to enrol in a health insurance scheme (OR = 0.34, 95% CI: 0.15 – 0.78, p = 0.011). Patients diagnosed with diabetes/hypertension 5 – 9 years ago were more likely to enrol in a health insurance scheme (OR = 2.99, 95% CI: 1.14 – 7.87, p = 0.026) compared to those diagnosed 0 – 4 years ago. Patients who were not aware of the existing schemes in their areas were 99% less likely to take up health insurance (OR = 0.01, 95% CI: 0.0 – 0.02, p < 0.001) compared to those who knew about health insurance schemes operating in the study area. Majority of respondents expressed willingness to join the proposed national health insurance scheme although concerns were raised about high premiums and misuse of funds which may negatively impact decisions to enrol.

Conclusion

Belonging to a microfinance scheme positively influences enrolment by patients with diabetes or hypertension in a health insurance program. Although a small proportion is currently enrolled in health insurance, the vast majority expressed willingness to enrol in the proposed national health insurance scheme. Microfinance schemes could be used as an entry point for health insurance programs for patients in these settings.
Prior Optic Neuritis Detection on Peripapillary Ring Scans using Deep Learning
Authors: Motamedi Seyedamirhosein , Yadav Sunil Kumar , Kenney Rachel C. , Lin Ting-Yi , Kauer-Bonin Josef , Zimmermann Hanna G. , Galetta Steven L. , Balcer Laura J. , Paul Friedemann , Brandt Alexander U.
Published: April 2022

Background

The diagnosis of multiple sclerosis (MS) d requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes with a prior history of acute optic neuritis (ON) and may provide evidence to support a demyelinating attack.

Objective

To investigate whether a deep learning (DL)-based network can distinguish between eyes with prior ON and healthy control (HC) eyes using peripapillary ring scans.

Methods

We included 1,033 OCT scans from 415 healthy eyes (213 HC subjects) and 510 peripapillary ring scans from 164 eyes with prior acute ON (140 patients with MS). Data were split into 70% training (728 HC and 352 ON), 15% validation (152 HC and 79 ON), and 15% test data (153 HC and 79 ON). We included 102 OCT scans from 80 healthy eyes (40 HC) and 61 scans from 40 ON eyes (31 MS patients) from an independent second center. Receiver operating characteristic curve (ROC) analyses with area under the curve (AUC) were used to investigate performance.

Results

We used a dilated residual convolutional neural network with alternating convolutional and max pooling layers for the classification. A final network using 2-factor augmentation had an accuracy of 0.85. The network achieved an area under the curve (AUC) of 0.86, whereas pRNFL only had an AUC of 0.77 in recognizing ON eyes. Using data from a second center, the network achieved an accuracy of 0.77 and an AUC of 0.90 compared to pRNFL, which had an AUC of 0.84.

Conclusion

DL-based disease classification of prior ON is feasible and has the potential to outperform thickness-based classification of eyes with and without history of prior ON.
Purification of mitochondria from skeletal muscle tissue for transcriptomic analyses reveals localisation of nuclear-encoded non-coding RNAs
Authors: Silver Jessica , Trewin Adam J. , Loke Stella , Croft Larry , Ziemann Mark , Soria Megan , Dillon Hayley , Nielsen Søren , Lamon Séverine , Wadley Glenn. D.
Published: April 2022

Mitochondria are central to cellular function, particularly in metabolically active tissues such as skeletal muscle. Nuclear-encoded RNAs typically localise within the nucleus and cytosol but a small population may also translocate to subcellular compartments such as mitochondria. We aimed to investigate the nuclear-encoded RNAs that localise within the mitochondria of skeletal muscle cells and tissue. Intact mitochondria were isolated via immunoprecipitation (IP) followed by enzymatic treatments (RNase-A and proteinase-K) optimised to remove transcripts located exterior to mitochondria, making it amenable for high-throughput transcriptomic sequencing. Small-RNA sequencing libraries were successfully constructed from as little as 1.8 ng mitochondrial RNA input. Small-RNA sequencing of mitochondria from rat myoblasts revealed the enrichment of over 200 miRNAs. Whole-transcriptome RNA sequencing of enzymatically-purified mitochondria isolated by IP from skeletal muscle tissue showed a striking similarity in the degree of purity compared to mitoplast preparations which lack an outer mitochondrial membrane. In summary, we describe a novel, powerful sequencing approach applicable to animal and human tissues and cells that can facilitate the discovery of nuclear-encoded RNA transcripts localised within skeletal muscle mitochondria.
Computationally Guided Design of Novel Angiotensin Converting Enzyme Inhibitors
Authors: Lam Jennifer D. , Riley Mary , Siegel Justin B.
Published: April 2022

Angiotensin-converting enzyme inhibitors (ACEI) such as Moexipril, Trandolapril, Ramipril, and Perindopril are used to treat hypertension. However, these drugs have undesired side effects. Using computational studies, two new novel drug candidates were designed with improved molecular interactions, ADMET properties, and docking scores compared to Moexipril. Homology analysis was done to determine the best animal model for preclinical studies, and it revealed that Pan troglodytes (chim-panzees) and Mus musculus (house mouse) were the best candidates.
Retinotopic organization of feedback projections in primate early visual cortex: implications for active vision
Authors: Wang Mingli , Hou Yujie , Magrou Loïc , Autio Joonas A. , Misery Pierre , Coalson Tim , Reid Erin , Xu Yuanfang , Lamy Camille , Falchier Arnauld , Zhang Qi , Poo Mu-Ming , Dehay Colette , Glasser Matthew F. , Hayashi Takuya , Knoblauch Kenneth , Van Essen David , Shen Zhiming , Kennedy Henry
Published: April 2022

Feedback connections play a major role in many theories of brain function. Previous studies of feedback connections to early visual areas have mainly concentrated on the representation of central visual fields. Here, injections of tracers at different eccentricities in areas V1 and V2 revealed retinotopically organized feedback. Peripheral injections revealed projections from 15 areas that are not labeled by central injections. Connection strengths for the majority of projections vary significantly with eccentricity in a systematic fashion with respect to distance and origin; whereas projections to central and upper visual fields are significantly stronger from ventral stream areas, peripheral and lower field projections are stronger from the dorsal stream. Non-invasive functional connectivity suggests a similar anatomical organization in humans. These features are discussed with respect to the cognitive and perceptual roles of these feedback pathways.
A reverse vaccinology approach identifies putative vaccination targets in the zoonotic nematode Ascaris
Authors: Evangelista Francisco Miguel Dias , van Vliet Arnoud H. M. , Lawton Scott P. , Betson Martha
Published: April 2022

Ascariasis is the most prevalent helminthic disease affecting both humans and pigs and is caused by the roundworms Ascaris lumbricoides and Ascaris suum. While preventive chemotherapy continues to be the most common control method, recent reports of anthelminthic resistance highlight the need for development of a vaccine against ascariasis. The aim of this study was to use a reverse vaccinology approach to identify potential vaccine candidates for Ascaris. Three Ascaris proteomes predicted from whole-genome sequences were analysed. Candidate proteins were identified using open-access bioinformatic tools (e.g. Vacceed, VaxiJen, Bepipred 2.0) which test for different characteristics such as sub-cellular location, T-cell and B-cell molecular binding, antigenicity, allergenicity and phylogenetic relationship with other nematode proteins. From over 100,000 protein sequences analysed, four transmembrane proteins were predicted to be non-allergen antigens and potential vaccine candidates. The four proteins are a Piezo protein, two voltage-dependent calcium channels and a protocadherin-like protein, are all expressed in either the muscle or ovaries of both Ascaris species, and all contained high affinity epitopes for T-cells and B-cells. The use of a reverse vaccinology approach allowed the prediction of four new potential vaccination targets against ascariasis in humans and pigs. These targets can now be further tested in in vitro and in vivo assays to prove efficacy in both pigs and humans.
Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
Authors: Baldazzi Valentina , Ropers Delphine , Gouzé Jean-Luc , Gedeon Tomas , de Jong Hidde
Published: April 2022

Different strains of a microorganism growing in the same environment display a wide variety of growth rates and growth yields. We developed a coarse-grained model to test the hypothesis that different resource allocation strategies, corresponding to different compositions of the proteome, can account for the observed rate-yield variability. The model predictions were verified by means of a database of hundreds of published rate-yield and uptake-secretion phenotypes ofEscherichia colistrains grown in standard laboratory conditions. We found a very good quantitative agreement between the range of predicted and observed growth rates, growth yields, and glucose uptake and acetate secretion rates. These results support the hypothesis that resource allocation is a major explanatory factor of the observed variability of growth rates and growth yields across different bacterial strains. An interesting prediction of our model, supported by the experimental data, is that high growth rates are not necessarily accompanied by low growth yields. The resource allocation strategies enabling high-rate, high-yield growth ofE. colilead to a higher saturation of enzymes and ribosomes, and thus to a more efficient utilization of proteomic resources. Our model thus contributes to a fundamental understanding of the quantitative relationship between rate and yield inE. coliand other microorganisms. It may also be useful for the rapid screening of strains in metabolic engineering and synthetic biology.
Light ‘em up: efficient screening of gold grids in cryo-EM
Authors: Hagen Wim J.H.
Published: April 2022

Transmission electron cryo-microscopy (cryo-EM) allows for obtaining 3D structural information by imaging macromolecules embedded in thin layers of amorphous ice. To obtain high-resolution structural information, samples need to be thin to minimize inelastic scattering which blurs images. During data collection sessions, time spent on finding areas on the cryo-EM grid with optimal ice thickness should be minimized as imaging time on high-end Transmission Electron Microscope TEM systems is costly. Recently, grids covered with thin gold films have become popular due to their stability and reduced beam-induced motion of the sample. Gold foil grids have substantially different densities between the gold foil and ice, effectively resulting in the loss of dynamic range between thin and thick regions of ice, making it challenging to find areas with suitable ice thickness efficiently during grid screening and thus increase expensive imaging time. Here, an energy filter-based plasmon imaging is presented as a fast and easy method for grid screening of the gold grids.
Targeting Neutrophils Extracellular Traps (NETs) reduces multiple organ injury in a COVID-19 mouse model
Authors: Veras Flavio P. , Gomes Giovanni F. , Silva Bruna M. S. , Almeida Cicero J. L. R. , Silva Camila Meirelles S. , Schneider Ayda H. , Corneo Emily S. , Bonilha Caio S. , Batah Sabrina S. , Martins Ronaldo , Arruda Eurico , Fabro Alexandre T. , Alves-Filho José C. , Cunha Thiago M. , Cunha Fernando Q.
Published: April 2022

COVID-19 is characterized by severe acute lung injury, which is associated with neutrophils infiltration and release of neutrophil extracellular traps (NETs). COVID-19 treatment options are scarce. Previous work has shown an increase in NETs release in the lung and plasma of COVID-19 patients suggesting that drugs that prevent NETs formation or release could be potential therapeutic approaches for COVID-19 treatment. Here, we report the efficacy of NET-degrading DNase I treatment in a murine model of COVID-19. DNase I decreased detectable levels of NETs, improved clinical disease, and reduced lung, heart, and kidney injuries in SARS-CoV-2-infected K18-hACE2 mice. Furthermore, our findings indicate a potential deleterious role for NETs lung tissue in vivo and lung epithelial (A549) cells in vitro, which might explain part of the pathophysiology of severe COVID-19. This deleterious effect was diminished by the treatment with DNase I. Together, our results support the role of NETs in COVID-19 immunopathology and highlight NETs disruption pharmacological approaches as a potential strategy to ameliorate COVID-19 clinical outcomes.
Selection of software and database for metagenomics sequence analysis impacts the outcome of microbial profiling and pathogen detection
Authors: Xu Ruijie , Rajeev Sreekumari , Salvador Liliana C. M.
Published: April 2022

Aim

Shotgun metagenomic sequencing analysis is widely used for microbial profiling of biological specimens and pathogen detection. However, very little is known about the technical biases caused by the choice of analysis software and databases. In this study, we evaluated shotgun metagenomics taxonomical profiling software to characterize the microbial compositions of biological samples collected from wild rodents.

Method and Results

Using nine of the most widely used metagenomics software and four different databases, we analyzed shotgun metagenomic sequence data from three sets of wild rodent tissue samples. We demonstrated the discrepancies in results when different databases and software were used, which cause significant variation in microbial community characterizations. Our analysis also showed that these software differed in their ability to detect the presence of Leptospira, a major zoonotic pathogen of one health importance.

Conclusions

Significant differences in compositional profiles for the same dataset while using different databases and software combinations can result in confounding biological conclusions in microbial profiling.

Significance and Impact of Study

This study cautions that the selection of software and databases to analyze metagenomics data can influence the outcome and biological interpretation.