bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of intraocular lens power formulas according to axial length after myopic corneal laser refractive surgery
Authors: Whang Woong-Joo , Hoffer Kenneth J. , Kim Seon-Ju , Chung So-Hyang , Savini Giacomo 
Published: September 2020

Purpose:
To assess the predictive accuracy of 4 no-history intraocular lens (IOL) power formulas in eyes with prior myopic excimer laser surgery, classified in 4 groups according to their axial length (AL), and investigate the relationship between AL and predictive accuracy.

Setting:
Seoul St. Mary's Hospital, Republic of Korea.

Design:
Retrospective case series.

Methods:
IOL power was calculated with the Barrett True-K, Haigis-L, Shammas-PL, and Triple-S formulas in 4 groups classified according to AL. Primary outcomes were the median absolute error (MedAE) and percentage of eyes with a prediction error (PE) within ±0.50 diopter (D).

Results:
This study included 107 eyes of 107 patients. The Barrett True-K had the lowest MedAE when AL was <26.0 mm (0.30 D) and between 26.0 and 28.0 mm (0.54 D); in these subgroups, it had the highest percentages with a PE within ±0.50 D (71.4% and 46.2%). For AL between 28.0 and 30.0 mm, the Triple-S method showed the lowest MedAE (0.43 D) and highest percentage with a PE within ±0.50 D (58.3%). For AL ≥30.0 mm, the Shammas-PL formula produced the lowest MedAE (0.41 D) and highest percentage with a PE within ±0.50 D (58.3%). The Barrett True-K was the only formula with a correlation between AL and PE (r = −0.219/P = .023).

Conclusions:
The predictive accuracy of no-history IOL formulas depends on the AL. The Barrett True-K had the highest accuracy when AL was < 28.0 mm and the Triple-S when it ranged from 28.0 mm to 30.0 mm, whereas the Shammas-PL was more accurate when AL was ≥30.0 mm.
Resistance profile of HIV-1 quasispecies in patients under treatment failure using single molecule, real-time sequencing
Authors: Monaco Daniela C. , Zapata Lucas , Hunter Eric , Salomon Horacio , Dilernia Dario A. 
Published: September 2020

Objective:
Short-read next-generation sequencing (NGS) has been implemented to study the resistance profile of HIV as it provides a higher sensitivity than Sanger sequencing. However, short-reads only generates a consensus view of the viral population rather than a reconstruction of the viral haplotypes. In this study, we evaluated the resistance profile of HIV quasispecies in patients undergoing treatment failure using SMRT sequencing.

Design:
Whole-pol RT-PCR was performed on viral RNA extracted from plasma samples of 38 HIV-positive individuals undergoing treatment failure, and sequenced in the RSII instrument. Error correction and viral haplotype phasing was performed with the Multilayer Directed Phasing and Sequencing (MDPSeq) algorithm. Presence of resistance mutations reported by the IAS-USA in 2017 was assessed using an in-house script.

Results:
The SMRT sequencing-based test detected 131/134 resistance mutations previously detected using a Sanger sequencing-based test. However, the SMRT test also identified seven additional mutations present at an estimated frequency lower than 30%. The intra-host phylogenetic analysis showed that seven samples harbored at least one resistance variant at 20--80% frequency. The haplotype-resolved sequencing revealed viral diversification and selection of new resistance during suboptimal treatment, an overall trend toward selection and accumulation of new resistance mutations, as well as the co-existence of resistant and susceptible variants.

Conclusion:
Our results validate the SMRT sequencing-based test for detection of HIV drug resistance. In addition, this method unraveled the complex dynamic of HIV quasispecies during treatment failure, which might have several implications on clinical management.
Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults
Authors: Mohammed Akram , Van Wyk Franco , Chinthala Lokesh K. , Khojandi Anahita , Davis Robert L. , Coopersmith Craig M. , Kamaleswaran Rishikesan 
Published: September 2020

ABSTRACT

Background:
Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our primary objective was to develop artificial intelligence capable of predicting sepsis earlier using a minimal set of streaming physiological data in real time.

Methods and Findings:
A total of 29,552 adult patients were admitted to the intensive care unit across five regional hospitals in Memphis, Tenn, over 18 months from January 2017 to July 2018. From these, 5,958 patients were selected after filtering for continuous (minute-by-minute) physiological data availability. A total of 617 (10.4%) patients were identified as sepsis cases, using the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria. Physiomarkers, a set of signal processing features, were derived from five physiological data streams including heart rate, respiratory rate, and blood pressure (systolic, diastolic, and mean), captured every minute from the bedside monitors. A support vector machine classifier was used for classification. The model accurately predicted sepsis up to a mean and 95% confidence interval of 17.4 ± 0.22 h before sepsis onset, with an average test accuracy of 83.0% (average sensitivity, specificity, and area under the receiver operating characteristics curve of 0.757, 0.902, and 0.781, respectively).

Conclusions:
This study demonstrates that salient physiomarkers derived from continuous bedside monitoring are temporally and differentially expressed in septic patients. Using this information, minimalistic artificial intelligence models can be developed to predict sepsis earlier in critically ill patients.
Understanding the compositional changes in LB Lennox medium during growth ofEscherichia coliDH5α in a 1L bioreactor
Authors: Ng Wenfa 
Published: September 2020

AbstractCompositional changes in growth medium represents dynamic interplay between cell growth, biomass formation, and energy maintenance, with concomitant decrease in nutrients and increase in secreted metabolites and metabolic byproducts. Such information is important for quantifying microbial physiological response both at the population and cellular level, with respect to understanding subtle differences in microbial growth response, as well as supporting model building efforts in metabolic engineering. With the desire to understand molecular weight changes in components of LB Lennox medium as well as broth fractions present during cultivation ofEscherichia coliDH5α (ATCC 53868) at 37 °C, 400 rpm stirring and 1 VVM aeration in a 1 L bioreactor, this study used a combination of gel filtration chromatography (GFC) and reversed phase high performance liquid chromatography (RP-HPLC) for determining changes to molecular weight of different fractions of the growth medium. Experiment results revealed the difficulty of fractionating the culture broth with RP-HPLC, where no distinct peaks of narrow retention time width were obtained. More importantly, the column used for GFC was unable to differentiate small molecular weight changes on the order of a few tens to few hundred Da through a refractive index detector. Together, GFC and RP-HPLC highlighted the difficulty of fractionating LB Lennox culture broth into different distinct fractions. Finally, the study validated the use of 194 nm as detection wavelength for visualizing the chromatogram of LB Lennox medium eluted from a C-18 reversed phase column during liquid chromatography. Collectively, GFC and RP-HPLC could not fractionate LB Lennox broth ofE. coliDH5α into distinct fractions for further analysis by identification techniques such as mass spectrometry. Given the inherent complexity of complex medium such as LB Lennox, clean separation of the medium into every component with high purity may be impossible.Graphical abstractShort descriptionBroad elution profile and lack of distinct peaks in chromatogram of LB Lennox broth at 6 hours post inoculation withEscherichia coliDH5α (ATCC 53868), after attempted fractionation by C-18 reversed phase high performance liquid chromatography (RP-HPLC), revealed that separation could not be achieved with a complex mixture such as a microbiology broth. Specifically, while the objective of understanding compositional changes to culture medium during growth presents tremendous opportunities for determining the dynamic conversion of nutrients into metabolites and byproducts, difficulty of profiling all chemical constituents in a complex broth mixture meant that current model building efforts for metabolic engineering remains primitive with respect to the consortia of metabolic reactions occurringin situat the cellular level.Subject areasbiotechnology, biochemistry, cell biology, microbiology, analytical chemistry
Studying the Interplay Between Apolipoprotein E and Education on Cognitive Decline in Centenarians Using Bayesian Beta Regression
Authors: Xiang Qingyan , Andersen Stacy , Perls Thomas T , Sebastiani Paola 
Published: September 2020

AbstractApolipoprotein E (APOE) is an important risk factor for cognitive decline and Alzheimer’s disease in aging individuals. Among the 3 known alleles of this gene: e2, e3, and e4, the e4 allele is associated with faster cognitive decline and increased risk for Alzheimer’s and dementia, while the e2 allele has a positive effect on longevity, and possibly on preservation of cognitive function. Education also has an important effect on cognition and longevity but the interplay betweenAPOEand education is not well characterized. Previous studies of the effect ofAPOEon cognitive decline often used linear regression with the normality assumption, which may not be appropriate for analyzing bounded and skewed cognitive test scores. In this paper, we applied Bayesian beta regression to assess the association betweenAPOEalleles and cognitive decline in a cohort of centenarians with longitudinal assessment of their cognitive function. The analysis confirmed the negative association between older age and cognition and the beneficial effect of education that persists even at the extreme of human lifespan in carriers of the e3 allele. In addition, the analysis showed an association betweenAPOEand cognition that is modified by education. Surprisingly, an antagonistic interaction existed between higher education andAPOEalleles, suggesting that education may reduce both positive and negative effects of this gene.
Measuring functional connectivity with wearable MEG
Authors: Boto Elena , Hill Ryan M. , Rea Molly , Holmes Niall , Seedat Zelekha A. , Leggett James , Shah Vishal , Osborne James , Bowtell Richard , Brookes Matthew J. 
Published: September 2020

AbstractOptically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that: provide improved data quality; accommodate any subject group; allow data capture during movement and offer a reduction in costs. However, OPM-MEG is still a nascent technology and, to realise its potential, it must be shown to facilitate key neuroscientific measurements, such as the characterisation of human brain networks. Networks, and the connectivities that underlie them, have become a core area of neuroscientific investigation, and their importance is underscored by many demonstrations of their perturbation in brain disorders. Consequently, a demonstration of network measurements via OPM-MEG would be a significant step forward. Here, we aimed to show that a wearable 50-channel OPM-MEG system enables characterisation of the electrophysiological connectome. To this end, we characterise connectivity in the resting state and during a simple visuo-motor task, using both OPM-MEG and a state-of-the-art 275-channel cryogenic MEG device. Our results show that connectome matrices from OPM and cryogenic systems exhibit an extremely high degree of similarity, with correlation values >70 %. This value is not measurably different to the correlation observed between connectomes measured in different subject groups, on a single scanner. In addition, similar differences in connectivity between individuals (scanned multiple times) were observed in cryogenic and OPM-MEG data, again demonstrating the fidelity of OPM-MEG data. This demonstration shows that a nascent OPM-MEG system offers results similar to a cryogenic device, even despite having ∼5 times fewer sensors. This adds weight to the argument that OPMs will ultimately supersede cryogenic sensors for MEG measurement.
Manipulating phloem transport affects wood formation but not nonstructural carbon concentrations in an evergreen conifer
Authors: Rademacher Tim , Fonti Patrick , LeMoine James M. , Fonti Marina V. , Basler David , Chen Yizhao , Friend Andrew D. , Seyednasrollah Bijan , Eckes-Shephard Annemarie H. , Richardson Andrew D. 
Published: September 2020

AbstractWood formation is a crucial process for carbon sequestration, yet how variations in carbon supply affect wood formation and carbon dynamics in trees more generally remains poorly understood.To better understand the role of carbon supply in wood formation, we restricted phloem transport using girdling and compression around the stem of mature white pines and monitored the effects on local wood formation and stem CO2efflux, as well as nonstructural carbon concentrations in needles, stems, and roots.Growth and stem CO2efflux varied with location relative to treatment (i.e., above or below on the stem). We observed up to a two-fold difference in the number of tracheids formed above versus below the manipulations over the remaining growing season. In contrast, the treatments did not affect mean cell size noticeably and mean cell-wall area decreased only slightly below them. Surprisingly, nonstructural carbon pools and concentrations in the xylem, needles, and roots remained largely unchanged, although starch reserves declined and increased marginally below and above the girdle, respectively.Our results suggest that phloem transport strongly affects cell proliferation and respiration in the cambial zone of mature white pine, but has little impact on nonstructural carbon concentrations. These findings contribute to our understanding of how wood formation is controlled.HighlightRestrictions in phloem transport designed to affect carbon supply, lead to changes in wood formation and stem respiration of mature white pines without substantially changing local nonstructural carbon concentrations.
Defining the Syrian hamster as a highly susceptible preclinical model for SARS-CoV-2 infection
Authors: Rosenke Kyle , Meade-White Kimberly , Letko Michael , Clancy Chad , Hansen Frederick , Liu Yanan , Okumura Atsushi , Tang-Huau Tsing-Lee , Li Rong , Saturday Greg , Feldmann Friederike , Scott Dana , Wang Zhongde , Munster Vincent , Jarvis Michael A. , Feldmann Heinz 
Published: September 2020

AbstractFollowing emergence in late 2019, SARS-CoV-2 rapidly became pandemic and is presently responsible for millions of infections and hundreds of thousands of deaths worldwide. There is currently no approved vaccine to halt the spread of SARS-CoV-2 and only very few treatment options are available to manage COVID-19 patients. For development of preclinical countermeasures, reliable and well-characterized small animal disease models will be of paramount importance. Here we show that intranasal inoculation of SARS-CoV-2 into Syrian hamsters consistently caused moderate broncho-interstitial pneumonia, with high viral lung loads and extensive virus shedding, but animals only displayed transient mild disease. We determined the infectious dose 50 to be only five infectious particles, making the Syrian hamster a highly susceptible model for SARS-CoV-2 infection. Neither hamster age nor sex had any impact on the severity of disease or course of infection. Finally, prolonged viral persistence in interleukin 2 receptor gamma chain knockout hamsters revealed susceptibility of SARS-CoV-2 to adaptive immune control. In conclusion, the Syrian hamster is highly susceptible to SARS-CoV-2 making it a very suitable infection model for COVID-19 countermeasure development.One Sentence SummaryThe Syrian hamster is highly susceptible to SARS-CoV-2 making it an ideal infection model for COVID-19 countermeasure development.
Detecting and phasing minor single-nucleotide variants from long-read sequencing data
Authors: Feng Zhixing , Clemente Jose , Wong Brandon , Schadt Eric E. 
Published: September 2020

AbstractCellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, co-infection of multiple pathogens. Detecting and phasing minor variants, which is to determine whether multiple variants are from the same haplotype, play an instrumental role in deciphering cellular genetic heterogeneity, but are still difficult because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, have provided an unprecedented opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrated that iGDA can accurately reconstruct haplotypes in closely-related strains of the same species (divergence≥0.011%) from long-read metagenomic data. Our approach, therefore, presents a significant advance towards the complete deciphering of cellular genetic heterogeneity.
Comparison of mental health service activity before and shortly after UK social distancing responses to the COVID-19 pandemic: February-March 2020
Authors: Stewart Robert , Martin Evangelia , Bakolis Ioannis , Broadbent Matthew , Byrne Nicola , Landau Sabine 
Published: September 2020

ABSTRACTThis study sought to provide an early description of mental health service activity before and after national implementation of social distancing for COVID-19. A time series analysis was carried out of daily service-level activity on data from a large mental healthcare provider in southeast London, from 01.02.2020 to 31.03.2020, comparing activity before and after 16.03.2020: i) inpatient admissions, discharges and numbers, ii) contact numbers and daily caseloads (Liaison, Home Treatment Teams, Community Mental Health Teams); iii) numbers of deaths for past and present patients. Daily face-to-face contact numbers fell for liaison, home treatment and community services with incomplete compensatory rises in non-face-to-face contacts. Daily caseloads fell for all services, apart from working age and child/adolescent community teams. Inpatient numbers fell 13.6% after 16th March, and daily numbers of deaths increased by 61.8%.
An optimal control policy for COVID-19 pandemic until a vaccine deployment
Authors: Sayarshad Hamid R. 
Published: September 2020

AbstractWhen an outbreak starts spreading, policy makers have to make decisions that affects health of their citizens and the economic. Some might induce harsh measures, such as lockdown. Following a long harsh lockdown, economical declines force policy makers to rethink reopening. But what is the most effective reopening strategy? In order to provide an effective strategy, here we propose a control strategy model. Our model assesses the trade-off between social performance and limited medical resources by determining individuals’ propensities. The proposed strategy also helps decision makers to find optimal lockdown and exit strategy for each region. Moreover, the financial loss is minimized. In addition, a study of a COVID-19 dataset for Los Angeles County is performed to validate our model and its results.
Immuno-Phenotyping of High-Grade Glioma Infiltrating Immune Cells Reveals Grade Specific Differences in Cells of Myeloid Origin
Authors: Ganesh Raksha A. , Raghavan Jayashree V. , Sonpatki Pranali , Naik Divya , Arunachalam Priyanka , Shah Darshat , Lakshmikantha Akhila , Pillai Shibu , Chandrachari Komal Prasad , Mariswamappa Kiran , Sathyanarayana L. D. , Shah Nameeta , Jhunjhunwala Siddharth 
Published: September 2020

AbstractGliomas are heavily infiltrated with immune cells of myeloid origin. Past studies have shown that high-grade gliomas have a higher proportion of alternatively activated and suppressive myeloid cells when compared to low-grade gliomas, which correlate with poor prognosis. However, the differences in immune cell phenotypes within high-grade gliomas (between grade III and IV) are relatively less explored, and a correlation of phenotypic characteristics between immune cells in the blood and high grade tumors has not been performed. Additionally, myeloid cells of granulocytic origin present in gliomas remain poorly characterized. Herein, we address these questions through phenotypic characterizations of monocytes and neutrophils present in blood and tumors of individuals with glioblastoma (GBM, grade IV) or grade III gliomas. Our data show that CD163 expressing M2 monocytes are present in greater proportions in GBM tissue when compared to grade III glioma tissue. In addition, we observe that neutrophils are highly heterogeneous among individuals with glioma, and a greater proportion of granulocytic myeloid-derived suppressor cells are present in grade III gliomas when compared to GBM. Finally, we show that the expression levels of CD86 and CD63 showed a high correlation between blood and tumor, and suggest that these may be used as possible markers for prognosis.
Contrasting effects of land cover on nesting habitat use and reproductive output for bumble bees
Authors: Pugesek Genevieve , Crone Elizabeth E. 
Published: September 2020

AbstractUnderstanding habitat quality is central to understanding the distributions of species on the landscape, as well as to conserving and restoring at-risk species. Although it is well-known that many species require different resources throughout their life cycles, pollinator conservation efforts focus almost exclusively on forage resources.Here, we evaluate nesting habitat for bumble bees by locating nests directly on the landscape. We compared colony density and colony reproductive output forBombus impatiens, the common eastern bumble bee, across three different land cover types (hay fields, meadows, and forests). We also recorded nest site characteristics, e.g., the position of each nest site, for allBombusnests located during surveys to tease apart species-specific patterns of habitat use.We found thatB. impatiensnests exclusively underground in two natural land cover types, forests and meadows, but not in hay fields.B. impatiensnested at similar densities in both in meadows and forests, but colonies in forests had much higher reproductive output.In contrast toB. impatiens, B. griseocollisfrequently nested on the surface of the ground and was almost always found in meadows.B. bimaculatisnests were primarily below ground in meadows.B. perplexisnested below ground in all three habitat types, including hay fields.For some bumble bee species in this system, e.g.,B. griseocollisandB. bimaculatis, meadows, the habitat type with abundant forage resources, may be sufficient to maintain them throughout their life cycles. However,B. impatiensmight benefit from heterogeneous landscapes with forests and meadows. Further research would be needed to evaluate whether hay fields are high-quality nesting sites for the one species that used them,B. perplexis.Synthesis and applications. In the past,Bombusnesting studies have been perceived as prohibitively labor-intensive. This example shows that it is possible to directly measure nesting habitat use and quality for bumble bee species. Applying these methods to more areas, especially areas where at-riskBombusspp. are abundant, is an important next step for identifying bumble bee habitat needs throughout their life cycles.