bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive and Temporal Surveillance of SARS-CoV-2 in Urban Water Bodies: Early Signal of Second Wave Onset
Authors: Hemalatha Manupati , Tharak Athmakuri , Kopperi Harishankar , Kiran Uday , Gokulan C. G. , Mishra Rakesh K , Mohan S Venkata 
Published: May 2021

AbstractThe possible faecal-oral transmission of SARS-CoV-2 through domestic discharges has emerged as a serious public health concern. Based on persistence of the virus in environment, the wastewater-based epidemiology (WBE) enabled the surveillance of infection in a community. The water bodies connected to the anthropogenic activities have strong possibility of presence of the SARS-CoV-2 genetic material. In this work, we monitored urban, peri-urban and rural lakes in and around Hyderabad as a long-term surveillance study for presence of enteric virus SARS-CoV-2 gene fragments. The study time of seven months coincided with the first and second wave of COVID-19 infection. The study depicted differential viral RNA copies in the urban lake with high viral load observed during the peaks of wave I and wave II. Distinct variability in viral genes detection was observed amongst all five lakes which were in concordance with the human activity of the catchment area. The SARS-CoV-2 genes were not detected in peri-urban and rural lakes, whereas the urban lakes having direct functional attributes from domestic activity, in the community showed presence of viral load. The outcome of the study clearly shows that the urban water streams linked with domestic discharge will function as a proxy for wastewater epidemiological studies. The surge in viral gene load from February 2021 sample suggests the on shoot of the second wave of infection, which correlated well with the prevailing pandemic situation. Implementation of regular WBE based monitoring system for the water bodies/wastewater in the urban and semi-urban areas will help to understand the outbreak and spread of virus in the community.
Impact of vaccination on the COVID-19 pandemic: Evidence from U.S. states
Authors: Chen Xiao , Huang Hanwei , Ju Jiandong , Sun Ruoyan , Zhang Jialiang 
Published: May 2021

AbstractGovernments worldwide are implementing mass vaccination programs in an effort to end the novel coronavirus (COVID-19) pandemic. Although the approved vaccines exhibited high efficacies in randomized controlled trials1,2, their population effectiveness in the real world remains less clear, thus casting uncertainty over the prospects for herd immunity. In this study, we evaluated the effectiveness of the COVID-19 vaccination program and predicted the path to herd immunity in the U.S. Using data from 12 October 2020 to 7 March 2021, we estimated that vaccination reduced the total number of new cases by 4.4 million (from 33.0 to 28.6 million), prevented approximately 0.12 million hospitalizations (from 0.89 to 0.78 million), and decreased the population infection rate by 1.34 percentage points (from 10.10% to 8.76%). We then built a Susceptible-Infected-Recovered (SIR) model with vaccination to predict herd immunity. Our model predicts that if the average vaccination pace between January and early March 2021 (2.08 doses per 100 people per week) is maintained, the U.S. can achieve herd immunity by the last week of July 2021, with a cumulative vaccination coverage of 60.2%. Herd immunity could be achieved earlier with a faster vaccination pace, lower vaccine hesitancy, or higher vaccine effectiveness. These findings improve our understanding of the impact of COVID-19 vaccines and can inform future public health policies regarding vaccination, especially in countries with ongoing vaccination programs.
MASK MANDATES REDUCE COVID-19 MORTALITY: Analysis of 37 States and the District of Columbia, with a further analysis of the impact of demographic and medical factors on efficacy
Authors: Maloney Michael J. 
Published: May 2021

ABSTRACTAs the number of COVID-19 deaths in the US increased, various policies were enacted to slow the spread of the pandemic. While the situation has improved in recent months, determining how best to combat the current pandemic is still essential. Failure to do so invites both further resurgences of the current pandemic, and more pandemics in the years to come. As a result of the widespread failure to contain the spread of COVID-19, enough deaths have occurred that the impact of policy on mortality may be statistically evaluated. This paper uses Optimal Discriminant Analysis (ODA) to evaluate the hypothesized ability of limited mask mandates (MM) to reduce the daily number of COVID-19 deaths in the states analyzed. The mandates were found to reduce mortality in half the states analyzed and did not result in increased mortality in any states. A full range of cofactors were analyzed to determine which, if any, influenced the efficacy of the mandates in the states in which mandates had an effect. Institutional Health Subindex of the Social Capital Index, state health score, population density, portion of the population with nongroup health insurance, state GDP, and the rate of pregnancy related diabetes were all correlated with increased mandate efficacy. In contrast, incarceration rate, overcrowded housing, severely overcrowded housing, portion of the population with military provided insurance, portion of the population uninsured, the portion of the population unable to see a doctor due to cost, and the portion of the population who were American Indian/Native Alaskan were all correlated with reduced mandate efficacy.
The Influence of Coronavirus Disease-2019 (COVID-19) On Parkinson’s Disease: An Updated Systematic Review
Authors: Jaiswal Vikash , Alquraish Danah , Sarfraz Zouina , Nagpal Shavy , Shrestha Prakriti Singh , Mukherjee Dattatreya , Guntipalli Prathima , Sarfraz Azza , Sánchez Velazco Diana F , Bhatnagar Arushee , Savani Saloni , Halilaj Elmjedina , Ruxmohan Samir , Cueva Wilson 
Published: May 2021

AbstractBackgroundCOVID-19 has affected global communities with multiple neurological complications in addition to other critical medical issues. COVID-19 binds to the host’s angiotensin-converting enzyme2 (ACE2) receptors, which are expressed in the neurons and glial cells, acting as an entry port to the central nervous system (CNS). ACE2 receptors are abundantly expressed on dopamine neurons, which may worsen the prognosis of motor symptoms in Parkinson’s disease (PD). SARS-CoV-2 may lead to an indirect response via immune-mediated cytokine storms and propagate through the CNS leading to damage. PD is also been associated with certain post-viral infections apart from COVID-19, such as HSV, Influenzavirus A, Measles virus, Cytomegalovirus, and Mumps.ObjectiveIn this systematic review, we aim to provide a thorough analysis of associations between COVID-19 and neurological outcomes for patients with PD.MethodsUsing PRISMA statement 2020, a systematic review was conducted to isolate confirmed COVID-19 patients and analyze the PD-associated neurological outcomes. A systematic literature search was conducted using the following databases: PubMed, Science Direct, Google Scholar, and Cochrane databases. The following keywords were used “COVID19, SARS-CoV-2, Parkinson’s disease, Pandemic, Mortality.” A modified Delphi process was employed to include the studies and ensure that the clinical outcome measures were addressed.ResultsOf the 355 records located during the initial round of screening, 16 were included in the final synthesis. Of PD patients who tested positive for SARS-CoV-2, worsening motor symptoms and other viral-associated symptoms were reported. These symptoms included bradykinesia, tremors, gait disturbances, delirium and dementia, and severe spasms of arms and legs. Encephalopathy was presented in two of the included studies. Increased mortality rates were identified for hospitalized patients due to COVID-19 and PD as compared to other patient groups, albeit with limited generalizability due to high bias of included studies.ConclusionPatients with PD may experience substantial worsening of motor and non-motor symptoms due to COVID 19. Given the novelty of neurological-viral associations, clinical studies in the future ought to explore the disease severity and neurological outcomes in COVID-19 positive patients with PD as compared to non-PD patients, in addition to understanding the role of ACE2 in increased vulnerability to contracting the infection and as a treatment modality.
Plasmodium infection induces cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein
Authors: Lapidus Sarah , Liu Feimei , Casanovas-Massana Arnau , Dai Yile , Huck John D. , Lucas Carolina , Klein Jon , Filler Renata B. , Strine Madison S. , Sy Mouhamad , Deme Awa B. , Badiane Aida S. , Dieye Baba , Ndiaye Ibrahima Mbaye , Diedhiou Younous , Mbaye Amadou Moctar , Diagne Cheikh Tidiane , Vigan-Womas Inés , Mbengue Alassane , Sadio Bacary D. , Diagne Moussa M. , Moore Adam J. , Mangou Khadidiatou , Diallo Fatoumata , Sene Seynabou D. , Pouye Mariama N. , Faye Rokhaya , Diouf Babacar , Nery Nivison , Costa Federico , Reis Mitermayer , Muenker M. Catherine , Hodson Daniel Z. , Mbarga Yannick , Katz Ben Z. , Andrews Jason R. , Campbell Melissa , Srivathsan Ariktha , Kamath Kathy , Baum-Jones Elisabeth , Faye Ousmane , Sall Amadou Alpha , Vélez Juan Carlos Quintero , Cappello Michael , Wilson Michael , Ben-Mamoun Choukri , Somé Fabrice A. , Dabiré Roch K. , Moukoko Carole Else Eboumbou , Ouédraogo Jean Bosco , Boum Yap , Shon John , Ndiaye Daouda , Wisnewski Adam , Parikh Sunil , Iwasaki Akiko , Wilen Craig B. , Ko Albert I. , Ring Aaron M. , Bei Amy K. 
Published: May 2021

ABSTRACTIndividuals with acute malaria infection generated high levels of antibodies that cross-react with the SARS-CoV-2 Spike protein. Cross-reactive antibodies specifically recognized the sialic acid moiety on N-linked glycans of the Spike protein and do not neutralize in vitro SARS-CoV-2. Sero-surveillance is critical for monitoring and projecting disease burden and risk during the pandemic; however, routine use of Spike protein-based assays may overestimate SARS-CoV-2 exposure and population-level immunity in malaria-endemic countries.
Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classified
Authors: Shibahara Takuma , Wada Chisa , Yamashita Yasuho , Fujita Kazuhiro , Sato Masamichi , Kuwata Junichi , Okamoto Atsushi , Ono Yoshimasa 
Published: May 2021

AbstractDifferentiating the intrinsic subtypes of breast cancer is crucial for deciding the best treatment strategy. Deep learning can predict the subtypes from genetic information more accurately than conventional statistical methods, but to date, deep learning has not been directly utilized to examine which genes are associated with which subtypes. To clarify the mechanisms embedded in the intrinsic subtypes, we developed an explainable deep learning model called a point-wise linear (PWL) model that generates a custom-made logistic regression for each patient. Logistic regression, which is familiar to both physicians and medical informatics researchers, allows us to analyze the importance of the feature variables, and the PWL model harnesses these practical abilities of logistic regression. In this study, we show that analyzing breast cancer subtypes is clinically beneficial for patients and one of the best ways to validate the capability of the PWL model. First, we trained the PWL model with RNA-seq data to predict PAM50 intrinsic subtypes and applied it to the 41/50 genes of PAM50 through the subtype prediction task. Second, we developed a deep enrichment analysis method to reveal the relationships between the PAM50 subtypes and the copy numbers of breast cancer. Our findings showed that the PWL model utilized genes relevant to the cell cycle-related pathways. These preliminary successes in breast cancer subtype analysis demonstrate the potential of our analysis strategy to clarify the mechanisms underlying breast cancer and improve overall clinical outcomes.
Intravital imaging of Candida albicans identifies differential in vitro and in vivo filamentation phenotypes for transcription factor deletion mutants
Authors: Wakade Rohan S. , Huang Manning , Mitchell Aaron P. , Wellington Melanie , Krysan Damian J. 
Published: May 2021

AbstractCandida albicans is an important cause of human fungal infections. A widely studied virulence trait of C. albicans is its ability to undergo filamentation to hyphae and pseudohyphae. Although yeast, pseudohyphae and hyphae are present in pathological samples of infected mammalian tissue, it has been challenging to characterize the role of regulatory networks and specific genes during in vivo filamentation. In addition, the phenotypic heterogeneity of C. albicans clinical isolates is becoming increasingly recognized and correlating this heterogeneity with pathogenesis remains an important goal. Here, we describe the use of an intravital imaging approach to characterize C. albicans filamentation in a mammalian model of infection by taking advantage of the translucence of mouse pinna (ears). Using this model, we have found that the in vitro and in vivo filamentation phenotypes of different C. albicans isolates can vary significantly, particularly when in vivo filamentation is compared to solid agar-based assays. We also show that the well-characterized transcriptional regulators Efg1 and Brg1 appear to play important roles both in vivo and in vitro. In contrast, Ume6 is much more important in vitro than in vivo. Finally, strains that are dependent on Bcr1 for in vitro filamentation are able to form filaments in vivo. This intravital imaging approach provides a new approach to the systematic characterization of this important virulence trait during mammalian infection. Our initial studies provide support for the notion that the regulation and initiation of C. albicans filamentation in vivo is distinct from in vitro induction.ImportanceCandida albicans is one of the most common causes of fungal infections in humans. C. albicans undergoes a transition from a round yeast form to a filamentous form during infection which is critical for its ability to cause disease. Although this transition has been studied in the laboratory for years, methods to do so in an animal model of infection have been limited. We have developed a microscopy method to visualize fluorescently labeled C. albicans undergoing this transition in the subcutaneous tissue of mice. Our studies indicate that the regulation of C. albicans filamentation during infection is distinct from that observed in laboratory conditions.
Prevalence of Macroprolactin in Hyperprolactinemic patients receiving Anti-psychotics
Authors: Al Wasify Loai Ali Al Mortada , Al Maamary Shaikha Said , Al Tobi Mohammed Nasser Rashid 
Published: May 2021

AbstractBackgroundProlactin (PRL) hormone circulates in the blood in three forms, mono-prolactin which constitutes 85 % of prolactin in healthy and hyperprolactinemia conditions, a dimeric prolactin (big PRL) and polymeric PRL (big-big prolactin or Macroprolactin). Macroprolactin in normal conditions is not exceeding 2% of the total serum prolactin and had no biological activity. In some cases, of hyperprolactinemia the dominant form becomes MaPRL and exceeding the 2% percentage of total leading to misdiagnosis of hyperprolactinemia and un-necessary radiological investigations. The aim of this study is to detect the prevalence of MaPRL in Psychiatric patients with hyperprolactinemia due to anti-psychotic medications at Al Masarra hospital.Material and methodsThe study was conducted on 190 samples from patients with high prolactin in Al Masarra Hospital either inpatients or out-patient clinics either male or non-lactating not pregnant female. The measurement of Prolactin level was measured by the automated analyser COBAS e411, Roche Diagnostic. Macroprolactin was precipitated by using Polyethylene glycol (PEG).ResultsPrevalence of Macroprolactin was 10.5 % of hyperprolactinemic patients receiving antipsychotics. There was a statistically significant difference in gender between the symptomatic and asymptomatic group. There was no significant difference in medications used between the symptomatic and asymptomatic group and there was a statistically significant difference in total Prolactin & Macroprolactin between males and females.ConclusionsInvestigation for Macroprolactin should be done in every hyperprolactinemia patient who is receiving antipsychotics more especially the asymptomatic cases to avoid unnecessary radiological imaging and treatment.
Giving patients a voice within healthcare reform: the qualitative VOICE study
Authors: Hoffmann Kathryn , Rumpler Nicole , George Aaron , de Boeckxstaens Pauline 
Published: May 2021

AbstractBackgroundInclusion of patients in healthcare service and system planning is an increasingly important tool to improve healthcare systems worldwide. In 2012, a focused healthcare reform was initiated in Austria to strengthen the primary care sector.ObjectivesThe aim of this study was to assess the perceptions, desires and needs of patients in terms of primary care as a necessary building block of the Austrian healthcare reform.MethodsThis study was designed as an exploratory qualitative study using semi-structured interviews between the years 2013 and 2018. Research questions focused on patients’ positive and negative experiences with regard to GP consultations and the overall primary care system, as well as desires for improvement. Qualitative content analysis by Mayring was used to analyze the material.ResultsAltogether, 41 interviews were conducted with seven main-categories identified. These categories include coordination and time management around consultation, human and professional aspects of consultation including coordination of care, access and availability including opening hours, infrastructure and hygiene of the waiting room, personnel, and overarching healthcare system factors.ConclusionThis study demonstrates the importance of bringing the patients’ voice into ongoing healthcare reform. Without appreciating and responding to patients’ perceptions and needs, healthcare reform in Austria might be challenged to improve in areas such as time, coordination and navigation. Successful health care reform necessitates the inclusion of the patient voice.
Machine learning enabled subgroup analysis with real-world data to inform better clinical trial design
Authors: Xu Jie , Zhang Hao , Zhang Hansi , Bian Jiang , Wang Fei 
Published: May 2021

AbstractRestrictive eligibility criteria for clinical trials may limit the generalizability of treatment effectiveness and safety to real-world patients. In this paper, we propose a machine learning approach to derive patient subgroups from real-world data (RWD), such that the patients within the same subgroup share similar clinical characteristics and safety outcomes. The effectiveness of our approach was validated on two existing clinical trials with the electronic health records (EHRs) from a large clinical research network. One is the donepezil trial for Alzheimer’s disease (AD), and the other is the Bevacizumab trial on colon cancer (CRC). The results show that our proposed algorithm can identify patient subgroups with coherent clinical manifestations and similar risk levels of encountering severe adverse events (SAEs). We further exemplify that potential rules for describing the patient subgroups with less SAEs can be derived to inform the design of clinical trial eligibility criteria.
COVID-19 Pandemic and Prevalence of Self-care Practices among the Future Physicians: A Bangladesh Study
Authors: Johora Fatema , Abbasy Asma Akter , Jeenia Fatiha Tasmin , Bhowmik Mithun Chandro , Aktar Mohsena , Choudhury Nargis Akhter , Moitra Priyanka , Ferdoush Jannatul 
Published: May 2021

AbstractBackgroundSince December 2019, the novel coronavirus, SARS-CoV-2, has garnered global attention due to its rapid transmission, which has infected more than twenty nine million people worldwide. World is facing enormous stress and anxiety as there is no effective medicine or vaccine to treat or prevent COVID-19 till date. Experts are recommending self-care like social distancing, respiratory etiquette, hand washing, using face mask to prevent corona virus infection.Materials and methodsThis descriptive cross-sectional study was designed to assess the prevalence of self-care practice among the undergraduate medical students (4th year) of 14 medical colleges of Bangladesh during COVID-19 pandemic. A structured questionnaire survey linked in the google form was used as study instrument and was distributed among study population through email, messenger, whatsapp and other social media during the month of October 2020. Total 916 students were participated in the study.Results79.8% of students reported self-care practice in study period. 44.98% of students went outside once in a week. 90.5%, 70.96% and 52.62% of respondents always used face mask, followed 20 seconds hand washing principle and maintained social distancing. Face masks (97.8%), sanitizers (76.7%) and gloves (71.9%) are most common items purchased as protective mesures. Most of the students (76.9%) follow their hobbies as a coping strategy to overcome phychological stress, while 6% of students took professional help.ConclusionSuboptimal practice of self-care was found among the undergraduate medical students of Bangladesh.
Linking carbohydrate structure with function in the human gut microbiome using hybrid metagenome assemblies
Authors: Ravi Anuradha , Troncoso-Rey Perla , Ahn-Jarvis Jennifer , Corbin Kendall R. , Harris Suzanne , Harris Hannah , Aydin Alp , Kay Gemma L. , Viet Thanh Le , Gilroy Rachel , Pallen Mark J. , Page Andrew J. , O’Grady Justin , Warren Frederick J. 
Published: May 2021

AbstractBackgroundComplex carbohydrates that escape digestion in the small intestine, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between particular microbes and the host, resulting in metabolic products that influence host gut health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes is not fully understood. Here we take the approach of combining data from long and short read sequencing allowing recovery of large numbers of high quality genomes, from which we can predict carbohydrate degrading functions, and impact of carbohydrate on microbial communities.ResultsIn this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. We found dynamic variations in the microbiome amongst carbohydrate treatments, and over time. Using these data, the MAGs were characterised as primary (0h to 6h) and secondary degraders (12h to 24h). Annotating the MAG’s with the Carbohydrate Active Enzyme (CAZyme) database we are able to identify species which are enriched through time and have the potential to actively degrade carbohydrate substrates.ConclusionsRecent advances in sequencing technology allowed us to identify significant unexplored diversity amongst starch degrading species in the human gut microbiota including CAZyme profiles and complete MAGs. We have identified changes in microbial community composition in response to structurally distinct carbohydrate substrates, which can be directly related to the CAZyme complement of the enriched MAG’s. Through this approach, we have identified a number of species which have not previously been implicated in starch degradation, but which have the potential to play an important role.