bluuebunny/crossref_metadata_2025 huggingface dataset:
The Presence and Significance of A-Waves—A Retrospective Review of 679 Patients
Authors: Zhang WenWen , Roberts Leslie
Published: August 2020

Purpose:

A-waves are late responses that have been reported in healthy individuals and patients with neurologic conditions. The mechanism(s) responsible for their generation and their clinical significance are not fully understood. The aim was to better characterize A-waves.

Methods:

A retrospective study was conducted in a high-volume Neurophysiology Department in a tertiary hospital in Melbourne, Australia. Consecutive neurophysiological tests including F-wave studies performed between July 2017 and September 2018 were reviewed to identify A-waves. Patients' characteristics and neurophysiological diagnoses were recorded.

Results:

A total of 679 patients were included in the analysis and a total of 2,730 nerves were studied. A-waves were most commonly found in tibial nerves, followed by peroneal, median, and ulnar nerves. A-waves were seen in 39.4% of individuals with otherwise normal nerve conduction studies and 39.1% of individuals with entrapment neuropathy. They were most seen in demyelinating neuropathy (85.7%), followed by mixed neuropathy (73.3%), anterior horn cell disease (66.7%), axonal neuropathy (61.2%), and radiculopathy (53.1%). Most patients with demyelinating neuropathy had multiple A-waves (61.9%), but these were also seen in 15.2% of individuals with otherwise normal nerve conduction studies and in 40% of those with other neurologic conditions. A-waves were more often seen in individuals older than 60 years.

Conclusions:

A-waves are commonly seen in symptomatic individuals with otherwise normal nerve conduction studies and individuals with various neurologic conditions but are more commonly found in nerves with otherwise abnormal electrophysiological testing. A-waves are most seen in tibial nerves. Multiple A-waves were more commonly seen in demyelinating neuropathy than other conditions.
Ectoparasite extinction in simplified lizard assemblages during experimental island invasion
Authors: Cox Christian L. , Alexander Sean , Casement Brianna , Chung Albert K. , Curlis John David , Degon Zachariah , Dubois Madeline , Falvey Cleo , Graham Zackary A. , Folfas Edita , Gallegos Koyner Maria A. , Neel Lauren K. , Nicholson Daniel J. , Perez Dylan J. Padilla , Ortiz-Ross Xochitl , Rosso Adam A. , Taylor Quinn , Thurman Timothy J. , Williams Claire E. , McMillan W. Owen , Logan Michael L.
Published: August 2020

Introduced species can become invasive, damaging ecosystems and disrupting economies through explosive population growth. One mechanism underlying population expansion in invasive populations is ‘enemy release’, whereby the invader experiences relaxation of agonistic interactions with other species, including parasites. However, direct observational evidence of release from parasitism during invasion is rare. We mimicked the early stages of invasion by experimentally translocating populations of mite-parasitized slender anole lizards (Anolis apletophallus) to islands that varied in the number of native anoles. Two islands were anole-free prior to the introduction, whereas a third island had a resident population of Gaige's anole (Anolis gaigei). We then characterized changes in trombiculid mite parasitism over multiple generations post-introduction. We found that mites rapidly went extinct on one-species islands, but that lizards introduced to the two-species island retained mites. After three generations, the two-species island had the highest total density and biomass of lizards, but the lowest density of the introduced species, implying that the ‘invasion’ had been less successful. This field-transplant study suggests that native species can be ‘enemy reservoirs’ that facilitate co-colonization of ectoparasites with the invasive host. Broadly, these results indicate that the presence of intact and diverse native communities may help to curb invasiveness.
Ant mazes and astronomy: Harlow Shapley's entomological experiments at Mount Wilson Observatory and Pasadena, California
Authors: Simpson Emily
Published: August 2020

This article explores the entomological research of American astronomer Harlow Shapley (1885–1972). The focus is 1914–1921, the time that Shapley worked as a staff astronomer at Mount Wilson Observatory in the San Gabriel Mountains of California. The years 1919–1920 receive particular attention because they were the most active period for Shapley's ant experiments. During these years, Shapley undertook two primary programmes of study in ant physiology, each centred on a specific species native to Southern California—the velvety tree ant and the California harvester ant. Shapley's ant research was dependent upon the scientific environment of Mount Wilson Observatory because of several benefits and opportunities that the location offered him. The section ‘Observatory ants’ discusses the details of Shapley's research programme as well as the advantages given him by his location. The subsequent section, ‘Indoor ants’, discusses a change in environment for Shapley's ant experiments and how that change, from an outdoor to an indoor setting, changed the scope and nature of his research. This section also discusses the influences that Shapley's work came to have in the disciplines of entomology, ecology, general physiology, and behavioural science. The final section, ‘Living and non-living?’, discusses the impacts that Shapley's ant research came to have on his own later work concerning cosmic evolution and interdisciplinary co-operation among the sciences. In conclusion, we are left with evidence suggesting that Shapley's work in entomology was highly location-dependent while also possessing far-reaching consequences.
Expression of SARS-CoV-2 receptor
ACE2
and the protease
TMPRSS2
suggests susceptibility of the human embryo in the first trimester
Authors: Weatherbee Bailey A. T. , Glover David M. , Zernicka-Goetz Magdalena
Published: August 2020

While initially recognized as causing respiratory disease, the SARS-CoV-2 virus also affects many other organs leading to other complications. It has emerged that advanced age and obesity are risk factors for complications but questions concerning the potential effects on fetal health and successful pregnancy for those infected with SARS-CoV-2 remain largely unanswered. Here, we examine human pre-gastrulation embryos to determine the expression patterns of the genes
ACE2
, encoding the SARS-CoV-2 receptor, and
TMPRSS2
, encoding a protease that cleaves both the viral spike protein and the ACE2 receptor to facilitate infection. We show expression and co-expression of these genes in the trophoblast of the blastocyst and syncytiotrophoblast and hypoblast of the implantation stages, which develop into tissues that interact with the maternal blood supply for nutrient exchange. Expression of
ACE2
and
TMPRSS2
in these tissues raises the possibility for vertical transmission and indicates that further work is required to understand potential risks to implantation, placental health and fetal health that require further study.
Hymenobacter fodinae sp. nov. and Hymenobacter metallicola sp. nov., isolated from abandoned lead–zinc mine
Authors: Feng Guang-Da , Zhang Jun , Chen Wendi , Wang Sheng-Nan , Zhu Honghui
Published: August 2020

Two novel strains, designated 92R-1T and 9PBR-1T, were isolated from abandoned lead–zinc ore collected in Meizhou, Guangdong Province, PR China. Phylogenetic analyses based on 16S rRNA gene sequences showed that they fell into the genus of

Hymenobacte

r and formed two distinct lineages. Strain 92R-1T was most closely related to

Hymenobacter wooponensis

JCM 19491T (98.7 %) and

Hymenobacter gelipurpurascens

LMG 21873T (98.5 %), while strain 9PBR-1T was most closely related to

Hymenobacter chitinivorans

LMG 21951T (99.0 %),

Hymenobacter elongatus

JCM 17223T (98.7 %) and

Hymenobacter aquaticus

JCM 31653T (98.1 %). Strain 92R-1Tshared average nucleotide identity values of 80.0–83.7 % and digital DNA–DNA hybridization values of 23.1–27.1 % with its closely related type strains, respectively, while strain 9PBR-1T shared corresponding values of 80.3–83.2 % and 23.6–26.7 % with its closely related type strains, respectively. The two novel strains could be clearly distinguished from their closely related type strains by enzyme activities and substrates assimilation, respectively. Both of them took iso-C15:0, summed feature 3 (C16:1
ω7c and/or C16:1
ω6c), summed feature 4 (iso-C17:1 I and/or anteiso-C17:1 B) and C16:1
ω5c as major fatty acids, and showed clear differences from their closely relatives in the contents of several components. They contained menaquinone 7 as the major respiratory quinone and phosphatidylethanolamine as the dominant polar lipid. The G+C contents of strains 92R-1T and 9PBR-1T were 56.7 and 59.5 mol%, respectively. The results clearly supported that strains 92R-1T and 9PBR-1T represent two distinct novel species within the genus

Hymenobacter

, for which the names Hymenobacter fodinae sp. nov. (type strain 92R-1T=GDMCC 1.1493T=JCM 32697T) and Hymenobacter metallicola sp. nov. (type strain 9PBR-1T=GDMCC 1.1491T=JCM 32698T) are proposed.
Interim Results of a Phase II/III Multicenter Randomized Clinical Trial of AVIFAVIR in Hospitalized Patients with COVID-19
Authors: Ivashchenko Andrey A. , Dmitriev Kirill A. , Vostokova Natalia V. , Azarova Valeria N. , Blinow Andrew A. , Egorova Alina N. , Gordeev Ivan G. , Ilin Alexey P. , Karapetian Ruben N. , Kravchenko Dmitry V. , Lomakin Nikita V. , Merkulova Elena A. , Papazova Natalia A. , Pavlikova Elena P. , Savchuk Nikolay P. , Simakina Elena N. , Sitdekov Tagir A. , Smolyarchuk Elena A. , Tikhomolova Elena G. , Yakubova Elena V. , Ivachtchenko Alexandre V.
Published: August 2020

In May 2020 the Russian Ministry of Health granted fast-track marketing authorization to RNA polymerase inhibitor AVIFAVIR (favipiravir) for the treatment of COVID-19 patients. In the pilot stage of Phase II/III clinical trial, AVIFAVIR enabled SARS-CoV-2 viral clearance in 62.5% of patients within 4 days, and was safe and well-tolerated.
Therapeutic effectiveness of interferon alpha 2b treatment for COVID-19 patient recovery
Authors: Pereda R , González D , Rivero HB , Rivero JC , Pérez A , López LR , Mezquia N , Venegas R , Betancourt Julio Raul , Domínguez RE
Published: August 2020

Background

Effective antiviral treatments are required to contain the ongoing coronavirus disease 2019 (COVID-19) pandemic. A previous report in 814 patients COVID-19 positive in Cuba provided preliminary therapeutic efficacy evidence with interferon-α2b (IFN-α2b) from March 11 to April 14, 2020. This study, re-evaluates the contribution of IFN-α2b on the evolution of all patients, after 98 days of the epidemic, in a period from March 11 to June 17, 2020.

Method

A prospective observational study was implemented to monitor a therapeutic intervention with IFN-α2b used in the national protocol for COVID-19 attending in Cuba. Were included patients with positive throat swab specimens by real time RT-PCR who gave informed consent and had no contraindications for IFN treatment. Patients received therapy as per the Cuban COVID protocol that included a combination of oral antivirals (lopinavir/ritonavir and chloroquine) with intramuscular or subcutaneous administration of IFN-α2b The primary endpoint was the proportion of patients discharged from hospital, secondary was the case fatality rate and several outcomes related to time variables were also evaluated.

Results

From March 11th until June 17th, 2295 patients had been confirmed SARS-CoV-2 positive in Cuba, 2165 were treated with Heberon® Alpha R and 130 received the approved protocol without IFN. The proportion of fully recovered patients was higher in the IFN-treated compared with non-IFN treated group. Prior IFN treatment decreases the likelihood of intensive care and increases the survival after severe or critical diseases. The benefits of IFN were significantly supported by time variables analyzed.

Conclusions

This second report confirm the preliminary evidences from first for the therapeutic effectiveness of IFNα-2b for SARS-Cov-2 infection and postulated that Heberon® Alpha R is the main component within the antiviral triad used as a therapeutic intervention in the Cuban protocol COVID-19.
Efficacy of Connexin testing in detecting Non-syndromic Sensorineural Hearing Loss in an Indian cohort
Authors: Kurva Jagannath , Bhat Nalini , Shettigar Suresh , Tawade Harshada , Shaikh Shagufta , Ghosh Anu , Cherian Susan
Published: August 2020

Hearing loss is one of the most common sensory disorder and approximately 466 million people have disabling hearing loss worldwide. This study was conducted to identify the mutations in the GJB2, GJB3, and GJB6 genes in an Indian cohort with non-syndromic sensorineural hearing loss and ascertain its use for genetic testing. 31 affected individuals with prelingual bilateral non-syndromic severe to profound sensorineural hearing loss were identified based on clinical evaluation and audiometric assessment. Sanger Sequencing method was used. Six out of 31 affected individuals showed pathogenic nonsense mutations in GJB2 gene, accounting to 19.3%. Of the 6 affected individuals, 5 were homozygous for c.71G>A(p.Trp24Ter) and one was compound heterozygous for c.71G>A and c.370C>T(p.Gln124Ter). Missense mutations [c.380G>A(p.Arg127His) and c.457G>A(p.Val153Ile)], and 3’ UTR variations were also identified in GJB2 gene. GJB3 and GJB6 genes showed only silent mutations and 3’ UTR variations. 19.3% of affected individuals showing pathogenic mutations in GJB2 gene in our cohort is comparable to other Indian studies (approximately 20%) and it is less as compared to Caucasian, Japanese, and Chinese studies (approximately 50%). Lower occurrence of pathogenic mutations in GJB2 gene in our cohort and other Indian studies as compared to other Caucasian, Japanese and Chinese studies, and absence of pathogenic mutations in GJB3 and GJB6 genes indicates that these genes may have a limited role in the Indian population. Hence there is a need to identify genes that play a major role in the Indian population so that they can be used for genetic testing for NHSL to aid in accurate and early diagnosis.
Plasma microRNA profiling for malaria disease: association with severity andP. falciparumbiomass
Authors: Gupta Himanshu , Rubio Mercedes , Sitoe Antonio , Varo Rosauro , Cisteró Pau , Madrid Lola , Cuamba Inocencia , Jimenez Alfons , Martiáñez-Vendrell Xavier , Barrios Diana , Pantano Lorena , Brimacombe Allison , Bustamante Mariona , Bassat Quique , Mayor Alfredo
Published: August 2020

Severe malaria (SM) is a major public health problem in malaria-endemic countries. Sequestration ofPlasmodium falciparum(Pf) infected erythrocytes in vital organs and the associated inflammation leads to organ dysfunction. MicroRNAs (miRNAs), which are rapidly released from damaged tissues into the host fluids, constitute a promising biomarker for the prognosis of SM. This study applied next-generation sequencing to evaluate the differential expression of miRNAs in SM compared to uncomplicated malaria (UM). Six miRNAs were associated within vitro Pfcytoadhesion, severity in Mozambican children andPfbiomass. Relative expression of hsa-miR-4497 quantified by TaqMan-RT-qPCR, was higher in SM children plasmas compared to that of UM (p<0.048), and again correlated withPfbiomass (p=0.033). These findings suggest that different physiopathological processes in SM and UM lead to differential expression of miRNAs and pave the way to future studies aiming to assess the prognostic value of these miRNAs in malaria.
Analytical Model of COVID-19 for lifting non-pharmaceutical interventions
Authors: Jacyna Garry , Thompson James R. , Koehler Matt , Slater David M.
Published: August 2020

In the present work, we outline a set of coarse-grain analytical models that can be used by decision-makers to bound the potential impact of the COVID-19 pandemic on specific communities with known or estimated social contact structure and to assess the effects of various non-pharmaceutical interventions on slowing the progression of disease spread. This work provides a multi-dimensional view of the problem by examining steady-state and dynamic disease spread using a network-based approach. In addition, Bayesian-based estimation procedures are used to provide a realistic assessment of the severity of outbreaks based on estimates of the average and instantaneous basic reproduction number R0.
Atrial fibrillation and kidney function: A bidirectional Mendelian randomization study
Authors: Park Sehoon , Lee Soojin , Kim Yaerim , Lee Yeonhee , Kang Min Woo , Kim Kwangsoo , Kim Yong Chul , Han Seung Seok , Lee Hajeong , Lee Jung Pyo , Joo Kwon Wook , Lim Chun Soo , Kim Yon Su , Kim Dong Ki
Published: August 2020

Aims

To investigate the causal effects between atrial fibrillation (AF) and kidney function.

Methods and Results

We performed a bidirectional Mendelian randomization (MR) analysis implementing the results from large-scale genome-wide association study (GWAS) for estimated glomerular filtration rate (eGFR) by the CKDGen (N = 1,046,070) and for AF (N = 588,190) to determine genetic instruments. A bidirectional two-sample MR based on summary-level data was performed. Inverse variance weighted method was the main MR method. For replication, an allele-score based MR was performed by individual-level data within the UK Biobank cohort of white British ancestry with eGFR values (N= 321,260).

The genetical predisposition to AF was significantly associated with lower eGFR [beta - 0.002 (standard error 0.0005), P < 0.001] and higher risk of chronic kidney disease [beta 0.051 (0.012), P < 0.001], and the significance remained in various MR sensitivity analyses. The causal estimates were consistent when we limited the analysis to individuals of European ancestry. The genetically predicted eGFR did not show significant association with risk of AF [beta −0.189 (0.184), P = 0.305]. The results were similar in allele-score based MR, as allele-score for AF was significantly associated with lower eGFR [beta −0.069 (0.021), P < 0.001] but allele-score for eGFR did not show significant association with risk of AF [beta −0.001 (0.009), P = 0.907].

Conclusions

Our study supports that genetical predisposition to AF is a causal risk factor for kidney function impairment. However, effect from kidney function on AF was not identified in this study.
Understanding signaling and metabolic paths using semantified and harmonized information about biological interactions
Authors: Miller Ryan A , Kutmon Martina , Bohler Anwesha , Waagmeester Andra , Evelo Chris T , Willighagen Egon L
Published: August 2020

Background

To grasp the complexity of biological processes, the biological knowledge is often translated into schematic diagrams of biological pathways, such as signalling and metabolic pathways. These pathway diagrams describe relevant connections between biological entities and incorporate domain knowledge in a visual format that is easier for humans to interpret. It has already been established that these diagrams can be represented in machine readable formats, as done in KEGG, Reactome, and WikiPathways. However, while humans are good at interpreting the message of the creator of such a diagram, algorithms struggle when the diversity in drawing approaches increases. WikiPathways supports multiple drawing styles, and therefore needs to harmonize this to offer semantically enriched access via the Resource Description Framework format. Particularly challenging in the normalization of diagrams are the interactions between the biological entities, so that we can glean information about the connectivity of the entities represented. These interactions include information about the type of interaction (metabolic conversion, inhibition, etc.), the direction, and the participants. Availability of the interactions in a semantic and harmonized format enables searching the full network of biological interactions and integration with the linked data cloud.

Results

We here study how the graphically modelled biological knowledge in diagrams can be semantified and harmonized efficiently, and exemplify how the resulting data can be used to programmatically answer biological questions. We find that we can translate graphically modelled biological knowledge to a sufficient degree into a semantic model of biological knowledge and discuss some of the current limitations. Furthermore, we show how this interaction knowledge base can be used to answer specific biological questions.

Conclusion

This paper demonstrates that most of the graphical biological knowledge from WikiPathways is modelled in the semantic layer of WikiPathways with the semantic information intact and connectivity information preserved. The usability of the WikiPathways pathway and connectivity information has shown to be useful and has been integrated into other platforms. Being able to evaluate how biological elements affect each other is useful and allows, for example, the identification of up or downstream targets that will have a similar effect when modified.
DLDTI: A learning-based framework for identification of drug-target interaction using neural networks and network representation
Authors: Zhao Yihan , Zheng Kai , Guan Baoyi , Guo Mengmeng , Song Lei , Gao Jie , Qu Hua , Wang Yuhui , Zhang Ying , Shi Dazhuo
Published: August 2020

To elucidate novel molecular mechanisms of known drugs, efficient and feasible computational methods for predicting potential drug-target interactions (DTI) would be of great importance. A novel calculation model called DLDTI was generated for predicting DTI based on network representation learning and convolutional neural networks. The proposed approach simultaneously fuses the topology of complex networks and diverse information from heterogeneous data sources and copes with the noisy, incomplete, and high-dimensional nature of large-scale biological data by learning low-dimensional and rich depth features of drugs and proteins. Low-dimensional feature vectors were used to train DLDTI to obtain optimal mapping space and infer new DTIs by ranking DTI candidates based on their proximity to optimal mapping space. DLDTI achieves promising performance under 5-fold cross-validation with AUC values of 0.9172, which was higher than that of the method based on different classifiers or different feature combination technique. Moreover, biomedical experiments were also completed to validate DLDTI’s performance. Consistent with the predicted result, tetramethylpyrazine, a member of pyrazines, reduced atherosclerosis progression and inhibited signal transduction in platelets, via PI3K/Akt, cAMP and calcium signaling pathways. The source code and datasets explored in this work are available athttps://github.com/CUMTzackGit/DLDTI
Computing the daily reproduction number of COVID-19 by inverting the renewal equation using a variational technique
Authors: Alvarez Luis , Colom Miguel , Morel Jean-David , Morel Jean-Michel
Published: August 2020

The COVID-19 pandemic has undergone frequent and rapid changes in its local and global infection rates, driven by governmental measures, or the emergence of new viral variants. The reproduction number Rt indicates the average number of cases generated by an infected person at time t and is a key indicator of the spread of an epidemic. A timely estimation of Rt is a crucial tool to enable governmental organizations to adapt quickly to these changes and assess the consequences of their policies. The EpiEstim method is the most widely accepted method for estimating Rt. But it estimates Rt with a significant temporal delay. Here, we propose a new method, EpiInvert, that shows good agreement with EpiEstim, but that provides estimates of Rt several days in advance. We show that Rt can be estimated by inverting the renewal equation linking Rt with the observed incidence curve of new cases, it. Our signal processing approach to this problem yields both Rt and a restored it corrected for the “weekend effect” by applying a deconvolution + denoising procedure. The implementations of the EpiInvert and EpiEstim methods are fully open-source and can be run in real-time on every country in the world, and every US state through a web interface at www.ipol.im/epiinvert.

Significance Statement

Based on a signal processing approach we propose a method to compute the reproduction number Rt, the transmission potential of an epidemic over time. Rt is estimated by minimizing a functional that enforces: (i) the ability to produce an incidence curve it corrected of the weekly periodic bias produced by the “weekend effect”, obtained from Rt through a renewal equation; (ii) the regularity of Rt. A good agreement is found between our Rt estimate and the one provided by the currently accepted method, EpiEstim, except our method predicts Rt several days closer to present. We provide the mathematical arguments for this shift. Both methods, applied every day on each country, can be compared at www.ipol.im/epiinvert.
Outcome of COVID-19 with co-existing surgical emergencies in children: our initial experiences and recommendations
Authors: Hasan Md Samiul , Ali Md Ayub , Huq Umama
Published: August 2020

Background

COVID-19 has changed the practice of surgery vividly all over the world. Pediatric surgery is not an exception. Prioritization protocols allowing us to provide emergency surgical care to the children in need while controlling the pandemic spread. The aim of this study is to share our experiences with the outcome of children with COVID-19 who had a co-existing surgical emergency.

Methods

This is a retrospective observational study. We reviewed the epidemiological, clinical, and laboratory data of all patients admitted in our surgery department through the emergency department and later diagnosed to have COVID-19 by RT-PCR. The study duration was 3 months (April 2020 – June 2020). A nasopharyngeal swab was taken from all patients irrespective of symptoms to detect SARS CoV 2 by RT-PCR with the purpose of detecting asymptomatic patients and patients with atypical symptoms. Emergency surgical services were provided immediately without delay and patients with positive test results were isolated according to the hospital protocol. We divided the test positive patients into 4 age groups for the convenience of data analysis. Data were retrieved from hospital records and analyzed using SPSS (version 25) software. Ethical permission was taken from the hospital ethical review board.

Results

Total patients were 32. Seven (21.9%) of them were neonates. Twenty-four (75%) patients were male. The predominant diagnosis was acute abdomen followed by infantile hypertrophic pyloric stenosis (IHPS), myelomeningocele, and intussusception. Only two patients had mild respiratory symptoms (dry cough). Fever was present in 13 (40.6%) patients. Fourteen (43.8%) patients required surgical treatment. The mean duration of hospital stay was 5.5 days. One neonate with ARM died in the post-operative ward due to cardiac arrest. No patient had hypoxemia or organ failure. Seven health care workers (5.51%) including doctors & nurses got infected with SARS Co V2 during this period.

Conclusion

Our study has revealed a milder course of COVID-19 in children with minimal infectivity even when present in association with emergency surgical conditions. This might encourage a gradual restart to mitigate the impact of COVID-19 on children’s surgery.
Sensitivity of nasopharyngeal, oropharyngeal and nasal washes specimens for SARS-CoV-2 detection in the setting of sampling device shortage
Authors: Adrien Calame , Léna Mazza , Adriana Renzoni , Laurent Kaiser , Manuel Schibler
Published: August 2020

In the context of an unprecedented shortage of nasopharyngeal swabs (NPS) or sample transport media during the coronavirus disease 2019 (COVID-19) crisis, alternative methods for sample collection are needed. To address this need, we validated a cell culture medium as a viral transport medium, and compared the analytical sensitivity of SARS-CoV-2 real-time RT-PCR in nasal wash (NW), oropharyngeal swab (OPS) and NPS specimens. Both the clinical and analytical sensitivity were comparable in these three sample types. OPS and NW specimens may therefore represent suitable alternatives to NPS for SARS-CoV-2 detection.
Physical activity, BMI and COVID-19: an observational and Mendelian randomisation study
Authors: Zhang Xiaomeng , Li Xue , Sun Ziwen , He Yazhou , Xu Wei , Campbell Harry , Dunlop Malcolm G , Timofeeva Maria , Theodoratou Evropi
Published: August 2020

Physical activity (PA) is known to be a protective lifestyle factor against several non-communicable diseases while its impact on infectious diseases, including Coronavirus Disease 2019 (COVID-19) is not as clear. We performed univariate and multivariate logistic regression to identify associations between body mass index (BMI) and both objectively and subjectively measured PA collected prospectively and COVID-19 related outcomes (Overall COVID-19, inpatient COVID-19, outpatient COVID-19, and COVID-19 death) in the UK Biobank (UKBB) cohort. Subsequently, we tested causality by using two-sample Mendelian randomisation (MR) analysis. In the multivariable model, the increased acceleration vector magnitude PA (AMPA) was associated with a decreased probability of overall and outpatient COVID-19. No association was found between self-reported moderate-to-vigorous PA (MVPA) or BMI and COVID-19 related outcomes. Although no causal association was found by MR analyses, this may be due to limited power and we conclude policies to encourage and facilitate exercise at a population level during the pandemic should be considered.
Mucosal versus systemic antibody responses to SARS-CoV-2 antigens in COVID-19 patients
Authors: Isho Baweleta , Abe Kento T. , Zuo Michelle , Jamal Alainna J. , Rathod Bhavisha , Wang Jenny H. , Li Zhijie , Chao Gary , Rojas Olga L. , Bang Yeo Myong , Pu Annie , Christie-Holmes Natasha , Gervais Christian , Ceccarelli Derek , Samavarchi-Tehrani Payman , Guvenc Furkan , Budylowski Patrick , Li Angel , Paterson Aimee , Yun Yue Feng , Marin Lina M. , Caldwell Lauren , Wrana Jeffrey L. , Colwill Karen , Sicheri Frank , Mubareka Samira , Gray-Owen Scott D. , Drews Steven J. , Siqueira Walter L. , Barrios-Rodiles Miriam , Ostrowski Mario , Rini James M. , Durocher Yves , McGeer Allison J. , Gommerman Jennifer L. , Gingras Anne-Claude
Published: August 2020

While the antibody response to SARS-CoV-2 has been extensively studied in blood, relatively little is known about the mucosal immune response and its relationship to systemic antibody levels. Since SARS-CoV-2 initially replicates in the upper airway, the antibody response in the oral cavity is likely an important parameter that influences the course of infection, but how it correlates to the antibody response in serum is not known. Here, we profile by enzyme linked immunosorbent assays (ELISAs) IgG, IgA and IgM responses to the SARS-CoV-2 spike protein (full length trimer) and its receptor binding domain (RBD) in serum (n=496) and saliva (n=90) of acute and convalescent patients with laboratory-diagnosed COVID-19 ranging from 3–115 days post-symptom onset (PSO), compared to negative controls. Anti-CoV-2 antibody responses were readily detected in serum and saliva, with peak IgG levels attained by 16–30 days PSO. Whereas anti-CoV-2 IgA and IgM antibodies rapidly decayed, IgG antibodies remained relatively stable up to 105 days PSO in both biofluids. In a surrogate neutralization ELISA (snELISA), neutralization activity peaks by 31–45 days PSO and slowly declines, though a clear drop is detected at the last blood draw (105–115 days PSO). Lastly, IgG, IgM and to a lesser extent IgA responses to spike and RBD in the serum positively correlated with matched saliva samples. This study confirms that systemic and mucosal humoral IgG antibodies are maintained in the majority of COVID-19 patients for at least 3 months PSO. Based on their correlation with each other, IgG responses in saliva may serve as a surrogate measure of systemic immunity.

One Sentence Summary

In this manuscript, we report evidence for sustained SARS-CoV-2-specific IgG and transient IgA and IgM responses both at the site of infection (mucosae) and systemically in COVID-19 patients over 3 months and suggest that saliva could be used as an alternative biofluid for monitoring IgG to SARS-CoV-2 spike and RBD antigens.
Low-Cost Enhancement of Facial Mask Filtration to Prevent Transmission of COVID-19
Authors: Bhimaraju Hari , Jain Ramesh , Nag Nitish
Published: August 2020

The use of face masks is recommended worldwide to reduce the spread of COVID-19. A plethora of facial coverings and respirators, both commercial and homemade, pervade the market, but the true filtration capabilities of many homemade measures against the virus are unclear and continue to be unexplored. In this work, we compare the efficacy of the following masks in keeping out particulate matter below 2.5 microns: N95 respirators, surgical masks, cloth masks, cloth masks with activated carbon air filters, cloth masks with HVAC air filters, lightly starch-enhanced cloth masks, and heavily-starched cloth masks. The experiments utilize an inhalation system and aerosol chamber to simulate a masked individual respiring aerosolized air. COVID-19 disproportionately affects people in low-income communities, who often lack the resources to acquire appropriate personal protective equipment and tend to lack the flexibility to shelter in place due to their public-facing occupations. This work tests low-cost enhancements to homemade masks to assist these communities in making better masks to reduce viral transmission. Experimental results demonstrate that the filtration efficacy of cloth masks with either a light or heavy starch can approach the performance of much costlier masks. This discovery supports the idea of low-cost enhancements to reduce transmission and protect individuals from contracting COVID-19.
Effect of Handedness on Learned Controllers and Sensorimotor Noise During Trajectory-Tracking
Authors: Yamagami Momona , Peterson Lauren N. , Howell Darrin , Roth Eatai , Burden Samuel A.
Published: August 2020

In human-in-the-loop control systems, operators can learn to manually control dynamic machines with either hand using a combination of reactive (feedback) and predictive (feed-forward) control. This paper studies the effect of handedness on learned controllers and performance during a trajectory-tracking task. In an experiment with 18 participants, subjects perform an assay of unimanual trajectory-tracking and disturbance-rejection tasks through second-order machine dynamics, first with one hand then the other. To assess how hand preference (or dominance) affects learned controllers, we extend, validate, and apply a non-parametric modeling method to estimate the concurrent feedback and feedforward controllers. We find that performance improves because feedback adapts, regardless of the hand used. We do not detect statistically significant differences in performance or learned controllers between hands. Adaptation to reject disturbances arising exogenously (i.e. applied by the experimenter) and endogenously (i.e. generated by sensorimotor noise) explains observed performance improvements.
Control of aperture closure during reach-to-grasp movements in immersive haptic-free virtual reality
Authors: Mangalam Madhur , Yarossi Mathew , Furmanek Mariusz P. , Tunik Eugene
Published: August 2020

Virtual reality (VR) has garnered much interest as a training environment for motor skill acquisition, including for neurological rehabilitation of upper extremities. While the focus has been on gross upper limb motion, VR applications that involve reaching for, and interacting with, virtual objects are growing. The absence of true haptics in VR when it comes to hand-object interactions raises a fundamentally important question: can haptic-free immersive virtual environments (hf-VEs) support naturalistic coordination of reach-to-grasp movements? This issue has been grossly understudied, and yet is of significant importance in the development and application of VR across a number of sectors. In a previous study (Furmanek et al. 2019), we reported that reach-to-grasp movements are similarly coordinated in both the physical environment (PE) and hf-VE. The most noteworthy difference was that the closure phase—which begins at maximum aperture and lasts through the end of the movement—was longer in hf-VE than in PE, suggesting that different control laws might govern the initiation of closure between the two environments. To do so, we reanalyzed data from Furmanek et al. (2019), in which the participants reached to grasp three differently sized physical objects, and matching 3D virtual object renderings, placed at three different locations. Our analysis revealed two key findings pertaining to the initiation of closure in PE and hf-VE. First, the respective control laws governing the initiation of aperture closure in PE and hf-VE both included state estimates of transport velocity and acceleration, supporting a general unified control policy for implementing reach-to-grasp across physical and virtual environments. Second, aperture was less informative to the control law in hf-VE. We suggest that the latter was likely because transport velocity at closure onset and aperture at closure onset were less independent in hf-VE than in PE, ultimately resulting in aperture at closure onset having a weaker influence on the initiation of closure. In this way, the excess time and muscular effort needed to actively bring the fingers to a stop at the interface of a virtual object was factored into the control law governing the initiation of closure in hf-VE. Critically, this control law remained applicable, albeit with different weights in hf-VE, despite the absence of terminal haptic feedback and potential perceptual differences.
The Kamin Blocking Effect in Sign and Goal Trackers
Authors: Aggarwal Mayank , Wickens Jeffery R.
Published: August 2020

The discovery of the Kamin blocking effect suggested that surprise or prediction errors are necessary for associative learning. This suggestion led to the development of a new theoretical framework for associative learning relying on prediction error rather than just temporal contiguity between events. However, many recent studies have failed to replicate the blocking effect, questioning the central role of blocking in associative learning theory. Here, we test the expression of Kamin blocking in rats that either approach and interact with the conditioned cue (sign trackers) or approach and interact with the reward location (goal trackers) during appetitive classical conditioning. The behavioral task involved three phases: classical conditioning of a lever cue, conditioning of a compound of the lever cue plus an auditory cue, and testing response to presentation of the auditory cue in extinction. The results show that only sign trackers express the blocking effect. Thus, groups that include goal trackers are less likely to be able to replicate the blocking effect. Our findings support the idea that sign and goal tracking responses arise as a result of distinct parallel learning processes. Psychological theories of learning that incorporate these parallel learning processes and their interactions will provide a better framework for understanding the blocking effect and related associative learning phenomena.
Epidemiological characteristics of SARS-COV-2 in Myanmar
Authors: Thway Aung Minn , Teza Htun , Win Tun Tun , Htun Ye Min , Aung Moe Myint , Win Yan Naung , Tun Kyaw Myo
Published: August 2020

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In Myanmar, first COVID-19 reported cases were identified on 23rd March 2020. There were 336 reported confirmed cases, 261 recovered and 6 deaths through 13th July 2020. The study was a retrospective case series and all COVID-19 confirmed cases from 23rd March to 13th July 2020 were included. The data series of COVID-19 cases were extracted from the daily official reports of the Ministry of Health and Sports (MOHS), Myanmar and Centers for Disease Control and Prevention (CDC), Myanmar. Among 336 confirmed cases, there were 169 cases with reported transmission events. The median serial interval was 4 days (IQR 3, 2-5) with the range of 0 - 26 days. The mean of the reproduction number was 1.44 with (95% CI = 1.30-1.60) by exponential growth method and 1.32 with (95% CI = 0.98-1.73) confident interval by maximum likelihood method. This study outlined the epidemiological characteristics and epidemic parameters of COVID-19 in Myanmar. The estimation parameters in this study can be comparable with other studies and variability of these parameters can be considered when implementing disease control strategy in Myanmar.
Dynamics of task-related electrophysiological networks: a benchmarking study
Authors: Tabbal Judie , Kabbara Aya , Khalil Mohamad , Benquet Pascal , Hassan Mahmoud
Published: August 2020

Motor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the random selection of methods and the limited evaluation studies. Using Magnetoencephalography (MEG) combined with Source Separation (SS) methods, we present an integrated framework to track fast dynamics of electrophysiological brain networks. We evaluate nine SS methods applied to three independent MEG databases (N=95) during motor and memory tasks. We report differences between these methods at the group and subject level. We show that the independent component analysis (ICA)-based methods and especially those exploring high order statistics are the most efficient, in terms of spatiotemporal accuracy and subject-level analysis. We seek to help researchers in choosing objectively the appropriate methodology when tracking fast reconfiguration of functional brain networks, due to its enormous benefits in cognitive and clinical neuroscience.
Functional immune mapping with deep-learning enabled phenomics applied to immunomodulatory and COVID-19 drug discovery
Authors: Cuccarese Michael F. , Earnshaw Berton A. , Heiser Katie , Fogelson Ben , Davis Chadwick T. , McLean Peter F. , Gordon Hannah B. , Skelly Kathleen-Rose , Weathersby Fiona L. , Rodic Vlad , Quigley Ian K. , Pastuzyn Elissa D. , Mendivil Brandon M. , Lazar Nathan H. , Brooks Carl A. , Carpenter Joseph , Probst Brandon L. , Jacobson Pamela , Glazier Seth W. , Ford Jes , Jensen James D. , Campbell Nicholas D. , Statnick Michael A. , Low Adeline S. , Thomas Kirk R. , Carpenter Anne E. , Hegde Sharath S. , Alfa Ronald W. , Victors Mason L. , Haque Imran S. , Chong Yolanda T. , Gibson Christopher C.
Published: August 2020

Development of accurate disease models and discovery of immune-modulating drugs is challenged by the immune system’s highly interconnected and context-dependent nature. Here we apply deep-learning-driven analysis of cellular morphology to develop a scalable “phenomics” platform and demonstrate its ability to identify dose-dependent, high-dimensional relationships among and between immunomodulators, toxins, pathogens, genetic perturbations, and small and large molecules at scale. High-throughput screening on this platform demonstrates rapid identification and triage of hits for TGF-β- and TNF-α-driven phenotypes. We deploy the platform to develop phenotypic models of active SARS-CoV-2 infection and of COVID-19-associated cytokine storm, surfacing compounds with demonstrated clinical benefit and identifying several new candidates for drug repurposing. The presented library of images, deep learning features, and compound screening data from immune profiling and COVID-19 screens serves as a deep resource for immune biology and cellular-model drug discovery with immediate impact on the COVID-19 pandemic.
Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancer
Authors: Diao James A. , Chui Wan Fung , Wang Jason K. , Mitchell Richard N. , Rao Sudha K. , Resnick Murray B. , Lahiri Abhik , Maheshwari Chirag , Glass Benjamin , Mountain Victoria , Kerner Jennifer K. , Montalto Michael C. , Khosla Aditya , Wapinski Ilan N. , Beck Andrew H. , Taylor-Weiner Amaro , Elliott Hunter L.
Published: August 2020

While computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction, lack of interpretability remains a significant barrier to clinical integration. In this study, we present a novel approach for predicting clinically-relevant molecular phenotypes from histopathology whole-slide images (WSIs) using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5,700 WSIs to train deep learning models for high-resolution tissue classification and cell detection across entire WSIs in five cancer types. Combining cell- and tissue-type models enables computation of 607 HIFs that comprehensively capture specific and biologically-relevant characteristics of multiple tumors. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment (TME) and can predict diverse molecular signatures, including immune checkpoint protein expression and homologous recombination deficiency (HRD). Our HIF-based approach provides a novel, quantitative, and interpretable window into the composition and spatial architecture of the TME.
Nonlinear delay differential equations and their application to modeling biological network motifs
Authors: Glass David S. , Jin Xiaofan , Riedel-Kruse Ingmar H.
Published: August 2020

Biological regulatory systems, such as transcription factor or kinase networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. “Network motif” models focus on small sub-networks to provide quantitative insight into overall behavior. However, conventional network motif models often ignore time delays either inherent to biological processes or associated with multi-step interactions. Here we systematically examine explicit-delay versions of the most common network motifs via delay differential equations (DDEs), both analytically and numerically. We find many broadly applicable results, such as the reduction in number of parameters compared to canonical descriptions via ordinary differential equations (ODE), criteria for when delays may be ignored, a complete phase space for autoregulation, explicit dependence of feedforward loops on a difference of delays, a unified framework for Hill-function logic, and conditions for oscillations and chaos. We emphasize relevance to biological function throughout our analysis, summarize key points in non-mathematical form, and conclude that explicit-delay modeling simplifies the phenomenological understanding of many biological networks and may aid in discovering new functional motifs.