bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy
Authors: Inkster Amy M. , Konwar Chaini , Peñaherrera Maria S. , Brain Ursula , Khan Almas , Price E. Magda , Schuetz Johanna M. , Portales-Casamar Élodie , Burt Amber , Marsit Carmen J. , Vaillancourt Cathy , Oberlander Tim F. , Robinson Wendy P. 
Published: June 2022

ABSTRACTBackgroundSelective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.In uteroexposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression.MethodsChorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score >8 to indicate symptomatic depressed mood (“maternally-depressed”), and we further classified cases into SSRI-exposed, maternally-depressed (n=14); SSRI-exposed, not maternally-depressed (n=6); SSRI non-exposed, maternally-depressed (n=20); and SSRI non-exposed, not maternally-depressed (n=24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n=17 SSRI-exposed, n=17 SSRI non-exposed).ResultsNo CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δβ| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n=31; males n=33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off.ConclusionsWe did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.
Fc-modified SARS-CoV-2 neutralizing antibodies with therapeutic effects in two animal models
Authors: Takeshita Masaru , Fukuyama Hidehiro , Kamada Katsuhiko , Matsumoto Takehisa , Makino-Okamura Chieko , Uchikubo-Kamo Tomomi , Tomabechi Yuri , Hanada Kazuharu , Moriyama Saya , Takahashi Yoshimasa , Ishigaki Hirohito , Nakayama Misako , Nguyen Cong Thanh , Kitagawa Yoshinori , Itoh Yasushi , Imai Masaki , Maemura Tadashi , Furusawa Yuri , Ueki Hiroshi , Iwatsuki-Horimoto Kiyoko , Ito Mutsumi , Yamayoshi Seiya , Kawaoka Yoshihiro , Shirouzu Mikako , Ishii Makoto , Saya Hideyuki , Kondo Yasushi , Kaneko Yuko , Suzuki Katsuya , Fukunaga Koichi , Takeuchi Tsutomu ,   the Keio Donner Project
Published: June 2022

SummaryThe use of therapeutic neutralizing antibodies against SARS-CoV-2 infection has been highly effective. However, there remain few practical antibodies against viruses that are acquiring mutations. In this study, we created 494 monoclonal antibodies from COVID-19–convalescent patients, and identified antibodies that exhibited comparable neutralizing ability to clinically used antibodies in the neutralization assay using pseudovirus and authentic virus including variants of concerns. These antibodies have different profiles against various mutations, which were confirmed by cell-based assay and cryo-electron microscopy. To prevent antibody-dependent enhancement, N297A modification was introduced, and showed a reduction of lung viral RNAs by therapeutic administration in a hamster model. In addition, an antibody cocktail consisting of three antibodies was also administered therapeutically to a macaque model, which resulted in reduced viral titers of swabs and lungs and reduced lung tissue damage scores. These results showed that our antibodies have sufficient antiviral activity as therapeutic candidates.
Plant community stability is associated with a decoupling of prokaryote and fungal soil networks
Authors: in ‘t Zandt Dina , Kolaříková Zuzana , Cajthaml Tomáš , Münzbergová Zuzana 
Published: June 2022

AbstractSoil microbial networks play a crucial role in plant community stability. However, we lack knowledge on the network topologies associated with stability and the pathways shaping these networks. In a 13-year mesocosm experiment, we determined links between plant community stability and soil microbial networks. We found that plant communities on soil abandoned from agricultural practices 60 years prior to the experiment promoted destabilising properties and were associated with coupled prokaryote and fungal soil networks. This coupling was mediated by strong interactions of plants and microbiota with soil resource cycling. Conversely, plant communities on natural grassland soil exhibited a high stability, which was associated with decoupled prokaryote and fungal soil networks. This decoupling was mediated by a large variety of past plant community pathways shaping especially fungal networks. We conclude that plant community stability is associated with a decoupling of prokaryote and fungal soil networks and mediated by plant-soil interactions.
Structural polymorphism of amyloid fibrils in cardiac transthyretin amyloidosis revealed by cryo-electron microscopy
Authors: Nguyen Binh An , Afrin Shumaila , Singh Virender , Ahmed Yasmin , Pedretti Rose , del Carmen Fernandez-Ramirez Maria , Benson Merrill Douglas , Sawaya Michael , Singh Preeti , Cao Qin , Boyer David , Pope Alexander , Wydorski Pawel , Kumar Siddharth , Chhapra Farzeen , Eisenberg David , Saelices Lorena 
Published: June 2022

AbstractThe deposition of amyloidogenic transthyretin (ATTR) in ATTR amyloidosis leads to an unexplained variety of clinical phenotypes, including cardiomyopathy. In brain amyloid conditions, there is an apparent association between the clinical phenotype and the amyloid fibril structure. Here, we question this phenotype-structure association in cardiac amyloidoses by determining the cryo-electron microscopy structures of fibrils extracted from the hearts of seven ATTR amyloidosis patients. We found that, in contrast to brain fibrils, cardiac ATTR fibrils display a structural polymorphism that is not genotype-specific, can co-exist within the same individual, and is independent of the cardiac phenotype. This polymorphism challenges the current paradigm of “one disease equals one fibril fold” proposed in tauopathies and synucleinopathies, and questions whether a similar structural heterogeneity occurs in other amyloidoses.One-Sentence SummaryUnlike brain amyloid fibrils, cardiac ATTR fibrils are polymorphic independent of genotype and even within the same patient.
Microbial community dynamics during a harmful Chrysochromulina leadbeateri bloom in northern Norway
Authors: Aalto Nerea J. , Schweitzer Hannah , Grann-Meyer Erlend , Krsmanovic Stina , Svenning Jon B. , Dalheim Lars , Petters Sebastian , Ingebrigtsen Richard , Hulatt Chris J. , Bernstein Hans C. 
Published: June 2022

ABSTRACTA harmful algae bloom occurred in late spring 2019 across multiple, interconnected fjords and bays in northern Norway. The event was caused by the haptophyte Chrysochromulina leadbeateri and led to severe fish mortality at several salmon aquaculture facilities. This study reports on the spatial and temporal succession dynamics of the holistic marine microbiome associated with this bloom by relating all detectable 18S and 16S rRNA gene ASVs to the relative abundance of the C. leadbeateri focal taxon. A k-medoids clustering enabled inferences on how the causative focal taxon co-bloomed with diverse groups of bacteria and microeukaryotes. These co-blooming patterns showed high temporal variability and were distinct between two geographically separated time series stations during the regional harmful algae bloom. The distinct blooming patterns observed with respect to each station were poorly connected to environmental conditions suggesting that other factors, such as biological interactions, may be at least as important in shaping the dynamics of this type of harmful algae bloom. A deeper understanding of microbiome succession patterns during these rare but destructive events will help guide future efforts to forecast deviations from the natural bloom cycles of the northern Norwegian coastal marine ecosystems that are home to intensive aquaculture activities.
MuDoGeR: Multi-Domain Genome Recovery from metagenomes made easy
Authors: Nunes da Rocha Ulisses , Kasmanas Jonas Coelho , Kallies René , Saraiva Joao Pedro , Brizola Toscan Rodolfo , Štefanič Polonca , Bicalho Marcos Fleming , Correa Felipe Borim , Baştürk Merve Nida , Fousekis Efthymios , Barbosa Luiz Miguel Viana , Plewka Julia , Probst Alexander , Baldrian Petr , Stadler Peter ,   CLUE-TERRA consortium
Published: June 2022

AbstractSeveral frameworks that recover genomes from Prokaryotes, Eukaryotes, and viruses from metagenomes exist. For those with little bioinformatics experience, it is difficult to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage from genomes belonging to different domains. MuDoGeR is a user-friendly tool accessible for non-bioinformaticians that make genome recovery from metagenomes of Prokaryotes, Eukaryotes, and viruses alone or in combination easy. By testing MuDoGeR using 574 metagenomes and 24 genomes, we demonstrated users could run it in a few samples or high-throughput. MuDoGeR is an open-source software available at https://github.com/mdsufz/MuDoGeR.
Designing β-hairpin peptide macrocycles for antibiotic potential
Authors: Randall Justin R. , DuPai Cory D. , Cole T. Jeffrey , Davidson Gillian , Groover Kyra E. , Wilke Claus O. , Davies Bryan W. 
Published: June 2022

AbstractPeptide macrocycles are a rapidly emerging new class of therapeutic, yet the design of their structure and activity remains challenging. This is especially true for those with β-hairpin structure due to weak folding properties and a propensity for aggregation. Here we use proteomic analysis and common antimicrobial features to design a large peptide library with macrocyclic β-hairpin structure. Using an activity-driven high-throughput screen we identify dozens of peptides killing bacteria through selective membrane disruption and analyze their biochemical features via machine learning. Active peptides contain a unique constrained structure and are highly enriched for cationic charge with arginine in their turn region. Our results provide a synthetic strategy for structured macrocyclic peptide design and discovery, while also elucidating characteristics important for β-hairpin antimicrobial peptide activity.Brief SummaryWe design, screen, and computationally analyze a synthetic macrocyclic β-hairpin peptide library for antibiotic potential.
Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection
Authors: Farjo Mireille , Koelle Katia , Martin Michael A. , Gibson Laura L. , Walden Kimberly K.O. , Rendon Gloria , Fields Christopher J. , Alnaji Fadi G. , Gallagher Nicholas , Luo Chun Huai , Mostafa Heba H. , Manabe Yukari C. , Pekosz Andrew , Smith Rebecca L. , McManus David D. , Brooke Christopher B. 
Published: June 2022

AbstractThe global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we deep sequenced saliva and nasal samples collected daily from immune and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both naïve and immune individuals appeared largely stochastic; however, we identified clear mutational hotspots within the viral genome, consistent with selection and differing between naïve and immune individuals. In rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of virus between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.
Increased levels of circulating neurotoxic metabolites in patients with mild Covid19
Authors: Santiago-Mujika Estibaliz , Heinrich Kevin , George Sonia , Capan Colt D , Forton Cameron , Madaj Zachary , Burmeister Amanda R , Sims Matthew , Pospisilik J Andrew , Brundin Patrik , Graham Stewart F , Brundin Lena 
Published: June 2022

AbstractSARS-CoV-2 corona virus causes a multi-faceted and poorly defined clinical and pathological phenotype involving hyperinflammation, cytokine release, and long-term cognitive deficits, with an undefined neuropathological mechanism. Inflammation increases the activity of the kynurenine pathway, which is linked to neurodegenerative and psychiatric disorders. We sought to determine whether the kynurenine pathway is impacted in patients with mild COVID-19, leading to elevated neurotoxic metabolites in blood, and whether such changes are associated with pro-inflammatory cytokines. Serum samples were taken from 150 patients and analyzed by ELISA and ultra-high performance liquid chromatography (UHPLC). The data were analyzed using multiple linear regression models adjusted for age and sex. We found increased levels of kynurenine, quinolinic acid and 3-hydroxykynurenine in serum from patients with mild COVID-19, together with increased levels of IL-6, ICAM-1, VCAM-1 and neopterin. The levels of neurotoxic metabolites were significantly associated with key inflammatory cytokines including IL-6 and TNFα. The COVID-19 risk-factor hypertension was associated with the highest levels of neurotoxic metabolites in plasma. These neuroactive metabolites could be part of the pathological mechanisms underlying cognitive impairment during and post-COVID and should be explored as potential biomarkers for long-COVID symptoms.
Does excessive degrees of financial depth push hyper-inflation?
Authors: Subramaniam Yogeeswari , Masron Tajul Ariffin 
Published: June 2022

PurposeUsing an innovative threshold estimation technique, this paper provides new evidence on the relationship between finance and inflation with distinct levels of finance.Design/methodology/approachThe sample consisted of 10 high inflation countries using time series data for the period of 1992–2020. These 10 countries recorded the world's highest inflation rates in 2017.FindingsThe findings demonstrate that there is a threshold effect on the finance–inflation relationship. Whilst the effects of finance are consistently positive for below and above the threshold models, financial depth above the threshold tends to aggravate the inflation level.Practical implicationsThese results disclose that financial depth could be the cause of high inflation in the top 10 countries and thus, is not necessarily welcome as too rapid of a price increase may in turn reverse the prospect of economic growth. Searching and strategizing for the optimal level of financing is crucial in facilitating price stability and economic growth.Originality/valueThe authors believe that the effect of financial depth on inflation is characterised by being desirable to certain extent and undesirable if over-financing is beyond the optimum level. Therefore, in this study, the authors have introduced the threshold modelling as the potential strategy to connect financial depth and inflation.
Prediction of construction accident outcomes based on an imbalanced dataset through integrated resampling techniques and machine learning methods
Authors: Koc Kerim , Ekmekcioğlu Ömer , Gurgun Asli Pelin 
Published: June 2022

PurposeCentral to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.Design/methodology/approachOccupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.FindingsThe results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.Practical implicationsThe proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.Social implicationsPractitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.Originality/valueThe literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.
COVID-19 and the reimaging of compassionate release
Authors: James Jennifer E. , Foe Meghan , Desai Riya , Rangan Apoorva , Price Mary 
Published: June 2022

Purpose
The purpose of this paper is to provide a historical overview of compassionate release policies in the USA and describe how these policies have been used during the COVID-19 pandemic. The authors then describe how these programs have been shaped by COVID-19 and could be reimagined to address the structural conditions that make prisons potentially life limiting for older adults and those with chronic illness.

Design/methodology/approach
This paper is primarily descriptive, offering an overview of the history of compassionate release policies before and during the COVID-19 pandemic. The authors augmented this description by surveying state Departments of Corrections about their utilization of compassionate release during 2019 and 2020. The findings from this survey were combined with data collected via Freedom of Information Act Requests sent to state Departments of Corrections about the same topic.

Findings
The findings demonstrate that while the US federal prison system saw a multifold increase in the number of individuals released under compassionate release policies in 2020 compared to 2019, most US states had modest change, with many states maintaining the same number, or even fewer, releases in 2020 compared with 2019.

Originality/value
This paper provides both new data and new insight into compassionate release utilization during the COVID-19 pandemic and offers new possibilities for how compassionate release might be considered in the future.
Assessing challenges to the mobile wallet usage in India: an interpretive structural modelling approach
Authors: Rana Nripendra P. , Luthra Sunil , Rao H. Raghav 
Published: June 2022

PurposeMobile-based payment is increasing exponentially but in the developing country like India, consumers’ perception is highly positive in daily cash transaction. The purpose of this research is to identify and examine the important challenges for mobile wallet (m-wallet) implementation in India. In the wake of COVID-19, one of the transmission mechanisms of this virus has been the coins and paper money passed between a buyer and a seller. As such m-wallet considered as a convenience of payment has become a necessity in light of the pandemic.Design/methodology/approachThe authors explored 19 unique sets of challenges selected from the literature and collected data from 14 experts from private sector, multinational corporations and mixed private and public partnership who have significant knowledge and experience of mobile payment implementation and use in their respective organisations. Also, the authors have used Interpretive Structural Modelling (ISM) methodology in developing a hierarchal model for the identified challenges. The authors implemented Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis to classify the identified challenges.FindingsThe ISM-based framework is divided into nine different hierarchical levels. “Lack of strong regulatory compliance (Ch6)” has been recognised as the most important challenge, which inhibited the mobile wallet implementation, whereas “Perception of customers about the value of using mobile wallets (Ch11)” is the most dependent critical challenge. There are seven hierarchical layers in between the top and the bottom level with the varied number of challenges based on their driving and dependence power.Originality/valueThis is the first research to the best of our knowledge that has not only comprehensively reviewed the m-wallet literature but also employed a unique ISM-MICMAC-based approach to develop a framework of challenges for the m-wallet implementation.