bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maternal vs Fetal Origin of Placental Intervillous Thrombi
Authors: Sukhanova Madina , Mithal Leena B , Otero Sebastian , Azad Hooman A , Miller Emily S , Jennings Lawrence J , Shanes Elisheva D , Goldstein Jeffery A 
Published: July 2021

Abstract

Objectives
To determine maternal vs fetal origin for blood in placental intervillous thrombi (IVTs).

Methods
We used comparative analysis of microsatellites (short tandem repeats [STRs]), sex chromosome fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC) for fetal (ɑ-fetoprotein [AFP]) and maternal (immunoglobulin M [IgM]) serum proteins to distinguish the origin of IVTs. Using an informatics approach, we tested the association between IVTs and fetomaternal hemorrhage (FMH).

Results
In 9 of 10 cases, the preponderance of evidence showed that the thrombus was mostly or entirely maternal in origin. In 1 case, the thrombus was of mixed origins. STR testing was prone to contamination by entrapped fetal villi. FISH was useful but limited only to cases with male fetuses. IgM showed stronger staining than AFP in 9 cases, supporting maternal origin. By informatics, we found no association between IVTs and FMH.

Conclusions
Evidence supports a maternal origin for blood in IVTs. IHC for IgM and AFP may be clinically useful in determining maternal vs fetal contribution to IVTs.
Infection outcome needs two to tango: human host and the pathogen
Authors: Maurya Ranjeet , Kanakan Akshay , Vasudevan Janani Srinivasa , Chattopadhyay Partha , Pandey Rajesh 
Published: July 2021

Abstract
Infectious diseases are potential drivers for human evolution, through a complex, continuous and dynamic interaction between the host and the pathogen/s. It is this dynamic interaction that contributes toward the clinical outcome of a pathogenic disease. These are modulated by contributions from the human genetic variants, transcriptional response (including noncoding RNA) and the pathogen’s genome architecture. Modern genomic tools and techniques have been crucial for the detection and genomic characterization of pathogens with respect to the emerging infectious diseases. Aided by next-generation sequencing (NGS), risk stratification of host population/s allows for the identification of susceptible subgroups and better disease management. Nevertheless, many challenges to a general understanding of host–pathogen interactions remain. In this review, we elucidate how a better understanding of the human host-pathogen interplay can substantially enhance, and in turn benefit from, current and future applications of multi-omics based approaches in infectious and rare diseases. This includes the RNA-level response, which modulates the disease severity and outcome. The need to understand the role of human genetic variants in disease severity and clinical outcome has been further highlighted during the Coronavirus disease 2019 (COVID-19) pandemic. This would enhance and contribute toward our future pandemic preparedness.
Single-cell Hi-C data analysis: safety in numbers
Authors: Galitsyna Aleksandra A , Gelfand Mikhail S 
Published: July 2021

Abstract
Over the past decade, genome-wide assays for chromatin interactions in single cells have enabled the study of individual nuclei at unprecedented resolution and throughput. Current chromosome conformation capture techniques survey contacts for up to tens of thousands of individual cells, improving our understanding of genome function in 3D. However, these methods recover a small fraction of all contacts in single cells, requiring specialised processing of sparse interactome data. In this review, we highlight recent advances in methods for the interpretation of single-cell genomic contacts. After discussing the strengths and limitations of these methods, we outline frontiers for future development in this rapidly moving field.
Mol2Context-vec: learning molecular representation from context awareness for drug discovery
Authors: Lv Qiujie , Chen Guanxing , Zhao Lu , Zhong Weihe , Yu-Chian Chen Calvin 
Published: July 2021

Abstract
With the rapid development of proteomics and the rapid increase of target molecules for drug action, computer-aided drug design (CADD) has become a basic task in drug discovery. One of the key challenges in CADD is molecular representation. High-quality molecular expression with chemical intuition helps to promote many boundary problems of drug discovery. At present, molecular representation still faces several urgent problems, such as the polysemy of substructures and unsmooth information flow between atomic groups. In this research, we propose a deep contextualized Bi-LSTM architecture, Mol2Context-vec, which can integrate different levels of internal states to bring dynamic representations of molecular substructures. And the obtained molecular context representation can capture the interactions between any atomic groups, especially a pair of atomic groups that are topologically distant. Experiments show that Mol2Context-vec achieves state-of-the-art performance on multiple benchmark datasets. In addition, the visual interpretation of Mol2Context-vec is very close to the structural properties of chemical molecules as understood by humans. These advantages indicate that Mol2Context-vec can be used as a reliable and effective tool for molecular expression. Availability: The source code is available for download in https://github.com/lol88/Mol2Context-vec.
Astrocyte–neuron interplay is critical for Alzheimer's disease pathogenesis and is rescued by TRPA1 channel blockade
Authors: Paumier Adrien , Boisseau Sylvie , Jacquier-Sarlin Muriel , Pernet-Gallay Karin , Buisson Alain , Albrieux Mireille 
Published: July 2021

Abstract
The sequence of cellular dysfunctions in preclinical Alzheimer’s disease must be understood if we are to plot new therapeutic routes. Hippocampal neuronal hyperactivity is one of the earliest events occurring during the preclinical stages of Alzheimer’s disease in both humans and mouse models. The most common hypothesis describes amyloid-β accumulation as the triggering factor of the disease but the effects of this accumulation and the cascade of events leading to cognitive decline remain unclear. In mice, we previously showed that amyloid-β-dependent TRPA1 channel activation triggers hippocampal astrocyte hyperactivity, subsequently inducing hyperactivity in nearby neurons. In this work, we investigated the potential protection against Alzheimer's disease progression provided by early chronic pharmacological inhibition of the TRPA1 channel.
A specific inhibitor of TRPA1 channel (HC030031) was administered intraperitoneally from the onset of amyloid-β overproduction in the APP/PS1-21 mouse model of Alzheimer’s disease. Short-, medium- and long-term effects of this chronic pharmacological TRPA1 blockade were characterized on Alzheimer’s disease progression at functional (astrocytic and neuronal activity), structural, biochemical and behavioural levels.
Our results revealed that the first observable disruptions in the Alzheimer’s disease transgenic mouse model used correspond to aberrant hippocampal astrocyte and neuron hyperactivity. We showed that chronic TRPA1 blockade normalizes astrocytic activity, avoids perisynaptic astrocytic process withdrawal, prevents neuronal dysfunction and preserves structural synaptic integrity. These protective effects preserved spatial working memory in this Alzheimer’s disease mouse model.
The toxic effect of amyloid-β on astrocytes triggered by TRPA1 channel activation is pivotal to Alzheimer’s disease progression. TRPA1 blockade prevents irreversible neuronal dysfunction, making this channel a potential therapeutic target to promote neuroprotection.
Somatotopic Specificity of Perceptual and Neurophysiological Changes Associated with Visuo-proprioceptive Realignment
Authors: Mirdamadi Jasmine L , Seigel Courtney R , Husch Stephen D , Block Hannah J 
Published: July 2021

Abstract
When visual and proprioceptive estimates of hand position disagree (e.g., viewing the hand underwater), the brain realigns them to reduce mismatch. This perceptual change is reflected in primary motor cortex (M1) excitability, suggesting potential relevance for hand movement. Here, we asked whether fingertip visuo-proprioceptive misalignment affects only the brain’s representation of that finger (somatotopically focal), or extends to other parts of the limb that would be needed to move the misaligned finger (somatotopically broad). In Experiments 1 and 2, before and after misaligned or veridical visuo-proprioceptive training at the index finger, we used transcranial magnetic stimulation to assess M1 representation of five hand and arm muscles. The index finger representation showed an association between M1 excitability and visuo-proprioceptive realignment, as did the pinkie finger representation to a lesser extent. Forearm flexors, forearm extensors, and biceps did not show any such relationship. In Experiment 3, participants indicated their proprioceptive estimate of the fingertip, knuckle, wrist, and elbow, before and after misalignment at the fingertip. Proprioceptive realignment at the knuckle, but not the wrist or elbow, was correlated with realignment at the fingertip. These results suggest the effects of visuo-proprioceptive mismatch are somatotopically focal in both sensory and motor domains.
Vikela Ekhaya: A Novel, Community-based, Tuberculosis Contact Management Program in a High Burden Setting
Authors: Kay Alexander W , Sandoval Micaela , Mtetwa Godwin , Mkhabela Musa , Ndlovu Banele , Devezin Tara , Sikhondze Welile , Vambe Debrah , Sibanda Joyce , Dube Gloria S , Stevens Robert H , Lukhele Bhekumusa , Mandalakas Anna M 
Published: July 2021

Abstract

Background
The prevention of tuberculosis (TB) in child contacts of TB cases and people living with human immunodeficiency virus (HIV) is a public health priority, but global access to TB preventive therapy (TPT) remains low. In 2019, we implemented Vikela Ekhaya, a novel community-based TB contact management program in Eswatini designed to reduce barriers to accessing TPT.

Methods
Vikela Ekhaya offered differentiated TB and HIV testing for household contacts of TB cases by using mobile contact management teams to screen contacts, assess their TPT eligibility, and initiate and monitor TPT adherence in participants’ homes.

Results
In total, 945 contacts from 244 households were screened for TB symptoms; 72 (8%) contacts reported TB symptoms, and 5 contacts (0.5%) were diagnosed with prevalent TB. A total of 322 of 330 (98%) eligible asymptomatic household contacts initiated TPT. Of 322 contacts initiating TPT, 248 children initiated 3 months of isoniazid and rifampicin and 74 children and adults living with HIV initiated 6 months of isoniazid; 298 (93%) completed TPT. In clustered logistic regression analyses, unknown HIV status (adjusted odds ratio [aOR] 5.7, P = .023), positive HIV status (aOR 21.1, P = .001), urban setting (aOR 5.6, P = .006), and low income (aOR 5.9, P = .001) predicted loss from the cascade of care among TPT-eligible contacts.

Conclusion
Vikela Ekhaya demonstrated that community-based TB household contact management is a feasible, acceptable, and successful strategy for TB screening and TPT delivery. The results of this study support the development of novel, differentiated, community-based interventions for TB prevention and control.
A Collaborative Learning-Based Algorithm for Task Offloading in UAV-Aided Wireless Sensor Networks
Authors: Al-Share Rama , Shurman Mohammad , Alma’aitah Abdallah 
Published: July 2021

Abstract
Recently, unmanned aerial vehicles (UAVs) have emerged to enhance data processing, network monitoring, disaster management and other useful applications in many different networks. Due to their flexibility, cost efficiency and powerful capabilities, combining these UAVs with the existing wireless sensor networks (WSNs) could improve network performance and enhance the network lifetime in such networks. In this research, we propose a task offloading mechanism in UAV-aided WSN by implementing a utility-based learning collaborative algorithm that will enhance the service satisfaction rate, taking into account the delay requirements of the submitted tasks. The proposed learning algorithm predicts the queuing delays of all UAVs instead of having a global overview of the system, which reduces the communication overhead in the network. The simulation results showed the effectiveness of our proposed work in terms of service satisfaction ratio compared with the non-collaborative algorithm that only processes the task locally in the WSN cluster.
Restoration, conservation and phytoplankton hysteresis
Authors: Berthold Maximilian , Campbell Douglas A 
Published: July 2021

AbstractPhytoplankton growth depends not only upon external factors that are not strongly altered by the presence of phytoplankton, such as temperature, but also upon factors that are strongly influenced by activity of phytoplankton, including photosynthetically active radiation, and the availability of the macronutrients carbon, nitrogen, phosphorus and, for some, silicate. Since phytoplankton therefore modify, and to an extent create, their own habitats, established phytoplankton communities can show resistance and resilience to change, including managed changes in nutrient regimes. Phytoplankton blooms and community structures can be predicted from the overall biogeochemical setting and inputs, but restorations may be influenced by the physiological responses of established phytoplankton taxa to nutrient inputs, temperature, second-order changes in illumination and nutrient recycling. In this review we discuss the contributions of phytoplankton ecophysiology to biogeochemical hysteresis and possible effects on community composition in the face of management, conservation or remediation plans.
A Review on Papaya Mealybug Identification and Management Through Plant Essential Oils
Authors: Mwanauta Regina W , Ndakidemi Patrick A , Venkataramana Pavithravani 
Published: July 2021

AbstractPapaya (Carica papaya L.) production suffers from a multitude of abiotic and biotic constraints, among those are insect pests, diseases, and environmental conditions. One of the seriously damaging pests of papaya is invasive papaya mealybug, Paracoccus marginatus, which can inflict heavy yield loss if not contained. Little information on papaya mealybug species has been documented due to challenges in identification approaches to species level. The current approach is based on the morphological features which are restricted to the mealybug life cycle leading to unclear identification. In Sub-Saharan Africa, where a wide diversity of mealybug species exists, it is essential to have a correct identification of these insect species due to the specificity of control measures. Molecular identification could be the best way to identify the mealybug at the species level. Presently, farmers rely heavily on chemical pesticides as their only available option for papaya mealybug control. The overuse of pesticides due to insect waxy covering has led to the development of pesticide resistance and the negative impact on the local ecosystem. Alternatively, the use of plant essential oils (EOs) with adjuvant is suggested as the safe solution to papaya mealybug control as they contain a rich source of natural chemicals that dissolve the insect wax layer, causing the cell membrane to rupture eventually leading to death. This review provides current research knowledge about the papaya mealybug identification approaches and plant EOs from Sweet orange, garlic, castor, and adjuvant (isopropyl alcohol, and paraffin) as sustainable papaya mealybug management.
Microbial retention and resistances in stormwater quality improvement devices treating road runoff
Authors: Liguori Renato , Rommel Steffen H , Bengtsson-Palme Johan , Helmreich Brigitte , Wurzbacher Christian 
Published: July 2021

ABSTRACTCurrent knowledge about the microbial communities that occur in urban road runoff is scarce. Road runoff of trafficked roads can be heavily polluted and is treated by stormwater quality improvement devices (SQIDs). However, microbes may influence the treatment process of these devices or could lead to stress resistant opportunistic microbial strains. In this study, the microbial community in the influent, effluent and the filter materials used to remove dissolved heavy metals from two different SQIDs were analyzed to determine microbial load, retention, composition, and mobile resistance genes. Although the microbes were replaced by new taxa in the effluent, there was no major retention of microbial genera. Further, the bacterial abundance of the SQIDs effluent was relatively stable over time. The heavy metal content correlated with intl1 and with microbial genera. The filter media itself was enriched with Intl1 gene cassettes, carrying several heavy metal and multidrug resistance genes (e.g. czrA, czcA, silP, mexW and mexI), indicating that this is a hot spot for horizontal gene transfer. Overall, the results shed light on road runoff microbial communities, and pointed to distinct bacterial communities within the SQIDs, which subsequently influence the microbial community and the genes released with the treated water.
Early performance of eight broadleaved species grown as short rotation forest in England
Authors: Mc Kay H M , Harrison A J , Connolly T , Forster J , Gregory S , Smith E , Clark J 
Published: July 2021

Abstract
The overall aim of the experiment was to compare the performance of a range of broadleaved species for their biomass production when grown for short rotations on ex-agricultural sites in England. The objectives were to compare over 7 years on four sites the survival, growth and biomass production of eight promising broadleaved species in relation to one another and two conifer species used as controls. Sites were planted in 2010/2011, and by winter 2016/2017 across all species and sites, the mean height, basal diameter (BD) and diameter at 1.3 m (DBH) were 444, 6.4 and 3.7 cm, respectively, despite considerable weed competition on these ex-agricultural sites. There were statistically significant main effects of species and site on all three measures and also significant interactions between sites and species. Totnes, the site with the highest mean annual temperature and the greatest rainfall, had the most uniform growth of the 10 species. At the three more variable sites, there was a general pattern of red alder (Alnus rubra Bong.) with the greatest growth, followed by a group of Italian alder (Alnus cordata (Loisel.) Duby), hybrid aspen (Populus tremula L. x tremuloides Michx.) and common alder (Alnus glutinosa (L.) Gaertner), then silver birch (Betula pendula Roth) with moderate growth. Sycamore (Acer pseudoplatanus L.), sweet chestnut (Castanea sativa Miller) and ash (Fraxinus excelsior L.), which had been infected with ash dieback, had the poorest growth. The estimated total stem volume after seven growing seasons averaged 31 m3 ha−1, with red alder having the greatest volume production, followed by hybrid aspen and Italian alder. Calculated stem biomass (oven dry tonnes per hectare, odt ha−1) after seven growing seasons averaged over all sites and species was 14.1 odt ha−1 (equivalent to 7 tC). The rapid volume growth and intermediate wood density of red alder and Italian alder combined to give the greatest estimated biomass, averaging 34.5 (17 tC) and 24.0 odt ha−1 (12 tC). At three sites, the estimated biomass of red alder was around 40 odt ha−1. Sitka spruce (Picea sitchensis (Bongard) Carrière) and Japanese larch (Larix kaempferi (Lamb.) Carrière) had a standing biomass estimated at 6.3 and 14.0 odt ha−1, respectively.
Mapping tree species ecograms based on soil pH and soil water availability across Denmark
Authors: Roell Yannik E , Nord-Larsen Thomas , Beucher Amélie , Greve Mette B , Greve Mogens H 
Published: July 2021

AbstractA prerequisite for successful afforestation and reforestation is understanding the quality of a site before establishing a specific tree species. Ecograms have been widely applied to determine the suitability of different sites for different species by a simple assessment of nutrient and water availability. Their graphical representation of suitability into classes allows ecograms to be easily understood. However, ecograms have generally been mapped for small areas only and their validity has rarely been documented. The aim of this study is to map ecograms for five tree species across Denmark and validate the maps using forest stand production data. For this purpose, we classified the landscape into six nutrient classes and nine water classes based on four variables to generate the ecogram maps. Based on these classes, the generated maps depict if a tree species is unsuitable, suitable or optimal for a specific site. The absolute average misclassification for nutrient and water supply was 1 and 2 classes, respectively. Stepwise linear regression was implemented to determine if the four variables used to create the ecograms were able to predict production as observed from forest experiment and management planning data obtained from across the country. All five species used the full model to explain variation in production. However, the average production values per ecogram growing condition were not significantly different for all species. The range of $R$2 for the five species was 0.05–0.32, indicating that one ecogram template might not work for all species. The high-resolution national ecogram maps incorporate large-scale variables important for tree growth and will be beneficial when selecting new land for afforestation. The simplicity of ecograms allows for easy interpretation, meaning that foresters can quickly determine which regions of a landscape are suitable, saving time and resources.
Spatiotemporal Invasion Severity of Chinese Tallow (Triadica sebifera) and Invasibility of Forest Types in Southern US Forestlands
Authors: Nepal Sunil , Moser W Keith , Fan Zhaofei 
Published: July 2021

Abstract
Quantifying invasion severity of nonnative invasive plant species is vital for the development of appropriate mitigation and control measures. We examined more than 23,250 Forest Inventory and Analysis (FIA) plots from the southern coastal states of the United States to develop an alternative method to classify and map the invasion severity of Chinese tallow (Triadica sebifera). Remeasured FIA plot-level data were used to examine the spatiotemporal changes in the presence probability and cover percentage of tallow. Four invasion severity classes were identified by using the product of presence probability and cover percentage. Chinese tallow invasion severity increased over time with 90 and 123 counties being classified into the highest severity class for the first and second measurement, respectively. Further, the invasibility of major forest-type groups by severity class was examined using the product of the county-level mean presence probability and mean cover percentage of Chinese tallow as a proxy of invasibility. Longleaf/slash pine (Pinus palustris/P. elliottii) forests were highly resilient to the Chinese tallow invasion. In contrast, elm/ash/cottonwood (Ulmus spp./Fraxinus spp./Populus deltoides) and oak/gum/cypress (Quercus spp./Nyssa spp./Taxodium spp.) forest-type groups were vulnerable to invasion.