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Preoperative Narcotic Use, Impaired Ambulation Status, and Increased Intraoperative Blood Loss Are Independent Risk Factors for Complications Following Posterior Cervical Laminectomy and Fusion Surgery.
ObjectiveThis retrospective cohort study seeks to identify risk factors associated with complications following posterior cervical laminectomy and fusion (PCLF) surgery.MethodsAdults undergoing PCLF from 2012 through 2018 at a single center were identified. Demographic and radiographic data, surgical characteristics, and complication rates were compared. Multivariate logistic regression models identified independent predictors of complications following surgery.ResultsA total of 196 patients met the inclusion criteria and were included in the study. The medical, surgical, and overall complication rates were 10.2%, 23.0%, and 29.1% respectively. Risk factors associated with medical complications in multivariate analysis included impaired ambulation status (odds ratio [OR], 2.27; p=0.02) and estimated blood loss over 500 mL (OR, 3.67; p=0.02). Multivariate analysis revealed preoperative narcotic use (OR, 2.43; p=0.02) and operative time (OR, 1.005; p=0.03) as risk factors for surgical complication, whereas antidepressant use was a protective factor (OR, 0.21; p=0.01). Overall complication was associated with preoperative narcotic use (OR, 1.97; p=0.04) and higher intraoperative blood loss (OR, 1.0007; p=0.03).ConclusionPreoperative narcotic use and estimated blood loss predicted the incidence of complications following PCLF for CSM. Ambulation status was a significant predictor of the development of a medical complication specifically. These results may help surgeons in counseling patients who may be at increased risk of complication following surgery
Relevance of Undetectably Rare Resistant Malaria Parasites in Treatment Failure: Experimental Evidence from Plasmodium chabaudi
Resistant malaria parasites are frequently found in mixed
infections with drug-sensitive parasites. Particularly early in
the evolutionary process, the frequency of these resistant
mutants is extremely low and below the level of molecular
detection. We tested whether the rarity of resistance in
infections impacted the health outcomes of treatment failure and
the potential for onward transmission of resistance. Mixed
infections of different ratios of resistant and susceptible
Plasmodium chabaudi parasites were inoculated in laboratory mice
and dynamics tracked during the course of infection using highly
sensitive genotype-specific quantitative polymerase chain
reaction (qPCR). Frequencies of resistant parasites ranged from
10% to 0.003% at the onset of treatment. We found that the rarer
the resistant parasites were, the lower the likelihood of their
onward transmission, but the worse the treatment failure was in
terms of parasite numbers and disease severity. Strikingly, drug
resistant parasites had the biggest impact on health outcomes
when they were too rare to be detected by any molecular methods
currently available for field samples. Indeed, in the field,
these treatment failures would not even have been attributed to
resistance
Breathing FIRE: How Stellar Feedback Drives Radial Migration, Rapid Size Fluctuations, and Population Gradients in Low-Mass Galaxies
We examine the effects of stellar feedback and bursty star formation on
low-mass galaxies ()
using the FIRE (Feedback in Realistic Environments) simulations. While previous
studies emphasized the impact of feedback on dark matter profiles, we
investigate the impact on the stellar component: kinematics, radial migration,
size evolution, and population gradients. Feedback-driven outflows/inflows
drive significant radial stellar migration over both short and long timescales
via two processes: (1) outflowing/infalling gas can remain star-forming,
producing young stars that migrate within their first , and (2) gas outflows/inflows drive strong fluctuations in the
global potential, transferring energy to all stars. These processes produce
several dramatic effects. First, galaxies' effective radii can fluctuate by
factors of over , and these rapid size fluctuations
can account for much of the observed scatter in radius at fixed
Second, the cumulative effects of many outflow/infall episodes steadily heat
stellar orbits, causing old stars to migrate outward most strongly. This
age-dependent radial migration mixes---and even inverts---intrinsic age and
metallicity gradients. Thus, the galactic-archaeology approach of calculating
radial star-formation histories from stellar populations at can be
severely biased. These effects are strongest at , the same regime where feedback most
efficiently cores galaxies. Thus, detailed measurements of stellar kinematics
in low-mass galaxies can strongly constrain feedback models and test baryonic
solutions to small-scale problems in CDM.Comment: Accepted to ApJ (820, 131) with minor revisions from v1. Figure 4 now
includes dark matter. Main results in Figures 7 and 1
Star formation histories of dwarf galaxies in the FIRE simulations: dependence on mass and Local Group environment
We study star formation histories (SFHs) of dwarf galaxies
(stellar mass ) from FIRE-2 cosmological zoom-in
simulations. We compare dwarfs around individual Milky Way (MW)-mass galaxies,
dwarfs in Local Group (LG)-like environments, and true field (i.e. isolated)
dwarf galaxies. We reproduce observed trends wherein higher-mass dwarfs quench
later (if at all), regardless of environment. We also identify differences
between the environments, both in terms of "satellite vs. central" and "LG vs.
individual MWvs. isolated dwarf central." Around the individual MW-mass hosts,
we recover the result expected from environmental quenching: central galaxies
in the "near field" have more extended SFHs than their satellite counterparts,
with the former more closely resemble isolated ("true field") dwarfs (though
near-field centrals are still somewhat earlier forming). However, this
difference is muted in the LG-like environments, where both near-field centrals
and satellites have similar SFHs, which resemble satellites of single MW-mass
hosts. This distinction is strongest for but
exists at other masses. Our results suggest that the paired halo nature of the
LG may regulate star formation in dwarf galaxies even beyond the virial radii
of the MW and Andromeda. Caution is needed when comparing zoom-in simulations
targeting isolated dwarf galaxies against observed dwarf galaxies in the LG.Comment: Main text: 11 pages, 8 figures; appendices: 4 pages, 4 figures.
Submitted to MNRAS; comments welcom
Editorial. Nomenclature - Avoiding Babylonian Speech Confusion in Present Day Immunology
The complexity of the immune system at the gene, protein, cell, and organism levels continues to provide a major challenge. Genomic landscaping, single-cell analysis and mass data acquisition including genome, transcriptome, metabolome, and proteome have now added new levels of complexity. With the rapid progress in these and other fields of immunology, it has become more important than ever to agree on uniform nomenclatures, i.e. to agree on how to name novel genes, proteins, cells, and biological reagents. Names given initially might, in retrospect, not always be logical. For example, tumor necrosis factor (TNF) was named on the basis of the observation of central necrosis in an experimental subcutaneous mouse tumor model (1). It was only after many unsuccessful studies in cancer, that eventually the role of TNF as a master cytokine in inflammation emerged. By that time, it was too late to rename the molecule because that would cause renewed confusion. Another cytokine has been successfully renamed. Interleukin-6 was initially known as B-cell Stimulatory Factor 2, Cytotoxic T lymphocyte Differentiation Factor, Hybridoma Growth Factor, Hepatocyte Stimulating Factor, and Interferon Beta-2. Obviously, such usage of different names for the same item can lead to confusion and may hinder progress in the field. These two examples demonstrate the need for a consensus nomenclature, which is timely applied
Language models show human-like content effects on reasoning
Abstract reasoning is a key ability for an intelligent system. Large language
models achieve above-chance performance on abstract reasoning tasks, but
exhibit many imperfections. However, human abstract reasoning is also
imperfect, and depends on our knowledge and beliefs about the content of the
reasoning problem. For example, humans reason much more reliably about logical
rules that are grounded in everyday situations than arbitrary rules about
abstract attributes. The training experiences of language models similarly
endow them with prior expectations that reflect human knowledge and beliefs. We
therefore hypothesized that language models would show human-like content
effects on abstract reasoning problems. We explored this hypothesis across
three logical reasoning tasks: natural language inference, judging the logical
validity of syllogisms, and the Wason selection task (Wason, 1968). We find
that state of the art large language models (with 7 or 70 billion parameters;
Hoffman et al., 2022) reflect many of the same patterns observed in humans
across these tasks -- like humans, models reason more effectively about
believable situations than unrealistic or abstract ones. Our findings have
implications for understanding both these cognitive effects, and the factors
that contribute to language model performance
Development and Characterization of a Eukaryotic Expression System for Human Type II Procollagen
Background
Triple helical collagens are the most abundant structural protein in vertebrates and are widely used as biomaterials for a variety of applications including drug delivery and cellular and tissue engineering. In these applications, the mechanics of this hierarchically structured protein play a key role, as does its chemical composition. To facilitate investigation into how gene mutations of collagen lead to disease as well as the rational development of tunable mechanical and chemical properties of this full-length protein, production of recombinant expressed protein is required.
Results
Here, we present a human type II procollagen expression system that produces full-length procollagen utilizing a previously characterized human fibrosarcoma cell line for production. The system exploits a non-covalently linked fluorescence readout for gene expression to facilitate screening of cell lines. Biochemical and biophysical characterization of the secreted, purified protein are used to demonstrate the proper formation and function of the protein. Assays to demonstrate fidelity include proteolytic digestion, mass spectrometric sequence and posttranslational composition analysis, circular dichroism spectroscopy, single-molecule stretching with optical tweezers, atomic-force microscopy imaging of fibril assembly, and transmission electron microscopy imaging of self-assembled fibrils.
Conclusions
Using a mammalian expression system, we produced full-length recombinant human type II procollagen. The integrity of the collagen preparation was verified by various structural and degradation assays. This system provides a platform from which to explore new directions in collagen manipulation
Type IIB Solutions with Interpolating Supersymmetries
We study type IIB supergravity solutions with four supersymmetries that
interpolate between two types widely considered in the literature: the dual of
Becker and Becker's compactifications of M-theory to 3 dimensions and the dual
of Strominger's torsion compactifications of heterotic theory to 4 dimensions.
We find that for all intermediate solutions the internal manifold is not
Calabi-Yau, but has SU(3) holonomy in a connection with a torsion given by the
3-form flux. All 3-form and 5-form fluxes, as well as the dilaton, depend on
one function appearing in the supersymmetry spinor, which satisfies a nonlinear
differential equation. We check that the fields corresponding to a flat bound
state of D3/D5-branes lie in our class of solutions. The relations among
supergravity fields that we derive should be useful in studying new gravity
duals of gauge theories, as well as possibly compactifications.Comment: 27pp, v2 REVTeX4, typographical fixes and minor clarifications, v3
added ref, modified discussion of RR axion slightl
Label-free characterization of biochemical changes within human cells under parasite attack using synchrotron based micro-FTIR
© 2019 The Royal Society of Chemistry. The protozoan Toxoplasma gondii is responsible for severe, potentially life-threatening, infection in immunocompromised individuals and when acquired during pregnancy. In the meantime, there is no available vaccine and the anti-T. gondii drug arsenal is limited. An important challenge to improve antiparasitic therapy is to understand chemical changes that occur during infection. Here, we used Fourier transform infrared spectroscopy (FTIR) to investigate the effect of T. gondii infection on the chemical composition of human brain microvascular endothelial cells (hBMECs) at 3, 6, 24 and 48 hours postinfection (hpi). Principal component analysis (PCA) showed that the best separation and largest difference between infected and uninfected hBMECs was detected at 24 hpi and within the 3400-2800 cm-1 region. At 48 hpi, although the difference between samples was obvious within the 3400-2800 cm-1 region, more differences were detected in the fingerprint region. These findings indicate that infected and control cells can be easily distinguished. Although differences between the spectra varied, the separation was most clear at 24 hpi. T. gondii increased signals for lipids (2853 cm-1) and nucleic acids (976 cm-1, 1097 cm-1 and 1245 cm-1), and decreased signals for proteins (3289 cm-1, 2963 cm-1, 2875 cm-1) in infected cells compared to controls. These results, supported by amino acid levels in culture media, and global metabolomic and gene expression analyses of hBMECs, suggest that T. gondii parasite exploits a wide range of host-derived chemical compounds and signaling pathways for its own survival and proliferation within host cells. Our data demonstrate that FTIR combined with chemometric analysis is a valuable approach to elucidate the temporal, infection-specific, chemical alterations in host cells at a single cell resolution
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