bluuebunny/crossref_metadata_2025_split huggingface dataset:
More severe pneumonitis in children predicts the need for admission and elevation of some but not all markers of severe Covid-19
Authors: Walsh Paul , Hankins Andrea , Bang Heejung 
Published: March 2022

AbstractUnlike most other viral pneumonitis, SARS-CoV-2 often causes hyperferritinemia, elevations in D-dimer, lactate dehydrogenase (LDH), transaminases, troponin, CRP, and other inflammatory markers. We questioned (1) if the severity of pneumonitis observed on lung ultrasound was associated with hospitalization and (2) could lung ultrasound be used to stratify which children needed blood tests?MethodsWe did a retrospective cross-sectional review of children aged between 14 days and 21 years of age being evaluated for Covid-19 in our pediatric emergency department from 30/November/2019 to 14/August/2021 who had had a point-of-care lung ultrasound. Lung ultrasounds were categorized using a 6-point ordinal scale. We used logistic regression to estimate the adjusted effect of lung ultrasound on hospital admission. We performed ordinary least square regression for the association between lung ultrasound severity and laboratory abnormalities. We adjusted these using propensity score derived inverse probability weighting to account for the non-random decision to obtain laboratory investigations.ResultsWe identified 500 point-of-care lung ultrasounds of which 427 could be assigned a severity category. Increasing lung ultrasound severity was associated with increased hospital admission OR 1.36(95% CI 1.08, 1.72.) Ferritin, LDH, transaminases, and D-dimer, but not CRP or troponin were significantly associated with more than moderately severe lung ultrasounds. D-Dimer, CRP, and troponin were sometimes elevated even when lung ultrasound was normal.ConclusionSeverity of pneumonitis was associated with hospital admission. Ferritin, LDH, transaminases, and D-dimer were increased in more than moderately severe pneumonitis but lung ultrasound did not predict elevation of other markers.
Electrocardiography-Based Prediction of Sudden Cardiac Death in Heart Failure Patients: Application of Artificial Intelligence
Authors: Shiraishi Yasuyuki , Goto Shinichi , Niimi Nozomi , Katsumata Yoshinori , Goda Ayumi , Takei Makoto , Saji Mike , Nishihata Yosuke , Sano Motoaki , Fukuda Keiichi , Kohno Takashi , Yoshikawa Tsutomu , Kohsaka Shun 
Published: March 2022

ABSTRACTBackgroundAlthough predicting sudden cardiac death (SCD) in patients with heart failure (HF) is critical, the current predictive model is suboptimal. Electrocardiography-based artificial intelligence (ECG-AI) algorithms may better stratify risk. We assessed whether the ECG-AI index established here could better predict SCD in HF and whether the ECG-AI index and conventional predictors of SCD can improve SCD stratification.MethodsIn a prospective observational study, four tertiary care hospitals in metropolitan Tokyo that enrolled 2,559 patients hospitalized with HF who were successfully discharged after acute decompensation. ECG data collected during the index hospitalization were extracted from the hospitals’ electronic medical record systems. The ECG-AI index is the output from an AI model that was trained to predict the risk of SCD based on ECG input. The association between ECG-AI index and SCD was evaluated with adjustment for left ventricular ejection fraction (LVEF), New York Heart Association (NYHA) class, and competing risk of non-SCD. The outcome measure was a composite of SCD and implantable cardioverter-defibrillator activation. The ECG-AI index was established using a derivation (hospital A) and validation cohort (hospital B), and its ability was evaluated in a test cohort (hospitals C and D).ResultsThe ECG-AI index plus classical predictive guidelines (i.e., LVEF ≤ 35%, NYHA class II–III) significantly improved the discriminative value of SCD (area under the receiver operating characteristic curve, 0.66 vs. 0.59; p=0.017; Delong’s test) with good calibration (p=0.11; Hosmer–Lemeshow test) and improved net reclassification (36%; 95% confidence interval, 9%–64%; p=0.009). The Fine-Gray model considering the competing risk of non-SCD demonstrated that the ECG-AI index was independently associated with SCD (adjusted sub-distributional hazard ratio, 1.25; 95% confidence interval, 1.04–1.49; p=0.015). An increased proportional risk of SCD vs. non-SCD with increasing ECG-AI index was also observed (low, 16.7%; intermediate, 18.5%; high, 28.7% risk; p for trend = 0.023). Similar findings were observed in patients aged ≤75 years with a non-ischemic etiology and an LVEF >35%.ConclusionsAmong patients with HF, ECG-based AI significantly improved the SCD risk stratification compared to the conventional indication for implantable cardioverter-defibrillators inclusive of LVEF and NYHA class.
An umbrella review and meta-analysis of the use of renin-angiotensin system drugs and COVID-19 outcomes: what do we know so far?
Authors: Kurdi Amanj , Weir Natalie , Mueller Tanja 
Published: March 2022

AbstractBackgroundsEvidence from several meta-analyses are still controversial about the effects of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin-receptor blockers (ARBs) on COVID-19 outcomes.PurposeUmbrella review of systematic reviews/meta-analysis to provide comprehensive assessment of the effect of ACEIs/ARBs on COVID-19 related outcomes by summarising the currently available evidence.Data SourceMedline (OVID), Embase, Scopus, Cochrane library and medRxiv from inception to 1stFebruary 2021.Study SelectionSystematic reviews with meta-analysis that evaluated the effect of ACEIs/ARBs on COVID-19 related clinical outcomesData ExtractionTwo reviewers independently extracted the data and assessed studies’ risk of bias using AMSTAR 2 Critical Appraisal Tool.Data SynthesisPooled estimates were combined using the random-effects meta-analyses model including several sub-group analyses. Overall, 47 reviews were eligible for inclusion. Out of the nine COVID-19 outcomes evaluated, there was significant associations between ACEIs/ARBs use and each of death (OR=0.80, 95%CI=0.75-0.86; I2=51.9%), death/ICU admission as composite outcome (OR=0.86, 95%CI=0.80-0.92; I2=43.9%), severe COVID-19 (OR=0.86, 95%CI=0.78-0.95; I2=68%), and hospitalisation (OR=1.23, 95%CI=1.04-1.46; I2= 76.4%). The significant reduction in death/ICU admission, however, was higher among studies which presented adjusted measure of effects (OR=0.63, 95%CI=0.47-0.84) and were of moderate quality (OR=0.74, 95%CI=0.63-0.85).LimitationsThe effect of unmeasured confounding could not be ruled out. Only 21.3% (n=10) of the studies were of ‘moderate’ quality.ConclusionCollective evidence from observational studies indicate a good quality evidence on the significant association between ACEIs/ARBs use and reduction in death and death/ICU admission, but poor-quality evidence on both reducing severe COVID-19 and increasing hospitalisation. Our findings further support the current recommendations of not discontinuing ACEIs/ARBs therapy in patients with COVID-19.RegistrationThe study protocol was registered in PROSPERO (CRD42021233398).Funding SourceNone
A Sliding Window Approach to Optimize the Time-varying Parameters of a Spatially-explicit and Stochastic Model of COVID-19
Authors: Ratnavale Saikanth , Hepp Crystal , Doerry Eck , Mihaljevic Joseph R 
Published: March 2022

AbstractThe implementation of non-pharmaceutical public health interventions can have simultaneous impacts on pathogen transmission rates as well as host mobility rates. For instance, with SARS-CoV-2, masking can influence host-to-host transmission, while stay-at-home orders can influence mobility. Importantly, variations in transmission rates and mobility patterns can influence pathogen-induced hospitalization rates. This poses a significant challenge for the use of mathematical models of disease dynamics in forecasting the spread of a pathogen; to create accurate forecasts in spatial models of disease spread, we must simultaneously account for time-varying rates of transmission and host movement. In this study, we develop a statistical model-fitting algorithm to estimate dynamic rates of SARS-CoV-2 transmission and host movement from geo-referenced hospitalization data. Using simulated data sets, we then test whether our method can accurately estimate these time-varying rates simultaneously, and how this accuracy is influenced by the spatial population structure. Our model-fitting method relies on a highly parallelized process of grid search and a sliding window technique that allows us to estimate time-varying transmission rates with high accuracy and precision, as well as movement rates with somewhat lower precision. Estimated parameters also had lower precision in more rural data sets, due to lower hospitalization rates (i.e., these areas are less data-rich). This model-fitting routine could easily be generalized to any stochastic, spatially-explicit modeling framework, offering a flexible and efficient method to estimate time-varying parameters from geo-referenced data sets.
Developing and piloting a preterm birth registry prioritizing social determinants of health and patient-reported data
Authors: Joudeh Layla , Stookey Jodi , Burch Johanna , Kaplan Rachel L. , Guendelman Sylvia , Armstrong Aline , Jackson Rebecca 
Published: March 2022

AbstractBiomedical factors and social determinants of health (SDH) affect preterm birth (PTB). Given the complexity of PTB and the increasing rates in the United States, public datasets involving multicomponent variables—from biomedical to structural—can motivate novel interventions to address PTB in the US. The primary aim of this study was to develop a PTB registry based on multi-modal data collection tools that prioritize biomedical and SDH data and identify PTB phenotype (i.e. spontaneous labor, preterm premature rupture of membrane, or medically indicated). The secondary aim of this study was to execute a pilot study to assess feasibility. This study aimed to describe recruitment practices, assess data accessibility and concordance, and to provide an example of how the registry can be used to generate hypothesis and analyze data. We designed the registry through a conceptual model provided by the Dahlgren and Whitehead model of SDH using validated questionnaires and literature on PTB. The registry included a survey, interview, and medical and birth certificate abstraction. To pilot the registry, we recruited 92 participants who delivered preterm, were admitted for risk of preterm delivery, or delivered at term at an urban public hospital. Enrollment was most effective in-person and in the postpartum period. Consent to different parts of the registry was similar regardless of when participants were recruited. There was also a range of data concordance depending on the data source and chosen variable. The registry’s PTB phenotype algorithm identified the correct PTB phenotype 100% of the time. The example analysis demonstrated six unique SDH domains. Participants who delivered preterm reported an average of 11 total stressors and 19.7 protective items and 66% had a significant medical or obstetric comorbidity. Results of this study demonstrate that a PTB registry is feasible and could help advance research to prevent PTB.
Lipid Accumulation Induced by APOE4 Impairs Microglial Surveillance of Neuronal-Network Activity
Authors: Victor Matheus B. , Leary Noelle , Luna Xochitl , Meharena Hiruy S. , Bozzelli P. Lorenzo , Samaan George , Murdock Mitchell H. , von Maydell Djuna , Effenberger Audrey H. , Cerit Oyku , Wen Hsin-Lan , Liu Liwang , Welch Gwyneth , Bonner Maeve , Tsai Li-Huei 
Published: March 2022

SummaryApolipoprotein E4 (APOE4) is the greatest known genetic risk factor for developing late- onset Alzheimer’s disease and its expression in microglia is associated with pro- inflammatory states. How the interaction of APOE4 microglia with neurons differs from microglia expressing the disease-neutral allele APOE3 is currently unknown. Here, we employ CRISPR-edited induced pluripotent stem cells (iPSCs) to dissect the impact of APOE4 in neuron-microglia communication. Our results reveal that APOE4 induces a distinct metabolic program in microglia that is marked by the accumulation of intracellular neutral lipid stores through impaired lipid catabolism. Importantly, this altered lipid-accumulated state shifts microglia away from homeostatic surveillance and renders APOE4 microglia weakly responsive to neuronal activity. By examining the transcriptional signatures of APOE3 versus APOE4 microglia before and after exposure to neuronal conditioned media, we further established that neuronal soluble cues differentially induce a lipogenic program in APOE4 microglia that exacerbates pro- inflammatory signals. Pharmacological blockade of lipogenesis in APOE4 microglia is sufficient to diminish intracellular lipid accumulation and restore microglial homeostasis. Remarkably, unlike APOE3 microglia that support neuronal network activity, co-culture of APOE4 microglia with neurons disrupts the coordinated activity of neuronal ensembles. We identified that through decreased uptake of extracellular fatty acids and lipoproteins, APOE4 microglia disrupts the net flux of lipids which results in decreased neuronal activity via the potentiation of the lipid-gated K+ channel, GIRK3. These findings suggest that neurological diseases that exhibit abnormal neuronal network-level disturbances may in part be triggered by impairment in lipid homeostasis in non-neuronal cells, underscoring a novel therapeutic route to restore circuit function in the diseased brain.Abstract Figure
Fe3O4nanoparticles to optimize the co-digestion of vinasse, filter cake, and deacetylation liquor: operational aspects and microbiological routes
Authors: Volpi Maria Paula. C. , Mockaitis Gustavo , Moraes Bruna S. 
Published: March 2022

ABSTRACTThe co-digestion of residues from the sugarcane industry has already proven to be a highly attractive process for biogas production through anaerobic digestion (AD). The use of residues such as vinasse (1G) filter cake (1G) and deacetylation liquor (2G) in CSTR operation showed the potential for integrating 1G and 2G ethanol biorefineries through AD in previous work by our research group. The use of nanoparticles (NP) is a favorable way to optimize AD processes, as these additives allow the introduction of nutrients to the process more assertively concerning the distribution and interaction with microorganisms. The present work proposed the optimization of the co-digestion of vinasse, filter cake, and deacetylation liquor in a continuous reactor by adding Fe3O4NP, comparing the results with a previous reactor operation without NP. Initially, tests were carried out in batches with different NP concentrations, resulting in 5 mg L-1as the best concentration to be added in the continuous reactor along the increments of the applied organic rate load (ORL). CH4production reached a maximum value of 2.8 ± 0.1 NLCH4gVS-1and the organic matter removal reached 71 ± 0.9%, in phase VI (ORL of 5.5 gVS L-1day-1). This production was 90% higher than the reactor co-digestion operation without NP. The pH and alkalinity results indicated the methanogenesis stabilization within 60 days of operation: 30 days before when there was no NP added. The AD development was stable, presenting low variations in the oxidation-reduction potential (ORP) and stable organic acid (OA) concentrations, which indicated the propionic acid route to produce CH4was predominant. The main methanogenicArcheaeidentified wasMethanoculleus, indicating that the predominant metabolic route was that of acetate (SAO) coupled with hydrogenotrophic methanogenesis. The use of Fe3O4NP managed to improve the AD from the 1G2G ethanol production residues and stimulated the microbial community growth, not modifying the preferable metabolic pathways.
Exon7 Targeted CRISPR-Prime Editing Approaches for SMN2 Gene Editing in Spinal Muscular Atrophy (SMA) Disease Can Increase In Vitro SMN Expression
Authors: Odabas Sibel Pinar , Bal Enes , Yelgen Gamze , Metin Ayse Simay , Karakaya Ebrar , Gulden Gamze , Sert Berranur , Teymur Tarik , Ay Yasin , Tiryaki Nulifer Neslihan , Araz Hasret , Cavrar Ilayda , Tastan Cihan 
Published: March 2022

AbstractSpinal Muscular Atrophy (SMA) is a fatal neuromuscular disease characterized by motor neuron loss and advanced muscle weakness, which occurs in functional SMN (Survival Motor Neuron) protein deficiency with SMN1 gene-induced deletions and mutations. The incidence of SMA, which is an autosomal recessive disease, is 1/10,000 in the world. The SMN protein acts as a molecular chaperone in the formation of the spliceosome complex, which catalyzes the splicing of pre-mRNA, enabling mRNAs and non-coding RNAs to mature. Since the current SMN1-encoding Adeno-associated virus (AAV) or SMN2 gene targeting antisense oligonucleotide-based strategies cannot provide long-term stable SMN expression in neuron cells, more effective methods need to be developed. CRISPR technology, which adds a new dimension to genetic engineering and gene therapies, makes it possible to treat many genetic diseases. In terms of SMA, some previous studies in the literature prove that it is possible to treat SMA with the CRISPR strategy. Homology Directed Repair (HDR)-based CRISPR technology, which results in a high rate of in-del (insertion-deletion) mutations rather than editing, was shown unsuitable for therapeutic applications. CRISPR-Prime editing (PE) technology is a new generation of gene editing approach that precisely provides various genomic modifications without the need for double-strand breakage or donor DNA sequences. CRISPR-Prime Editing method has also been used in rare diseases such as sickle cell anemia and Tay-Sachs, and their efficiency in editing various pathogenic mutations has been demonstrated. However, CRISPR Prime Editing-mediated gene editing for Spinal Muscular Atrophy (SMA) have not yet been investigated. The c.840 T-C transition and c.859 G-C transformations in the SMN2 gene and the correction of these point mutations with a single pegRNA at the same time were investigated for the first time in this study. Here, we showed that CRISPR-PE systems could increase SMN2 gene activity and SMN protein expression by ensuring exon 7 participation by editing c.840 T-C transition and c.859 G-C transformations. The fact that Prime Editing method showed the efficacy and stability of modifications in SMN2 genes that were investigated in SMN-low Jurkat cells as a proof-of-concept. This study enabled the next step with the CRISPR-Prime Editing approach to be tested ex vivo in primary cell lines from SMA patients and SMN-low neuronal cells.
Three-dimensional structure of the single domain cupredoxin AcoP
Authors: Roger Magali , Leone Philippe , Blackburn Ninan , Horrell Sam , Chicano Tadeo Moreno , Giudici-Orticoni Marie-Thérèse , Abriata Luciano A. , Hura Greg L. , Hough Michael A. , Sciara Giulano , Ilbert Marianne 
Published: March 2022

ABSTRACTCupredoxins are widely occurring copper-binding proteins with a typical Greek-key beta barrel fold. They are generally described as electron carriers that rely on a T1 copper center coordinated by four ligands provided by the folded polypeptide. The discovery of novel cupredoxins demonstrates the high diversity of this family, with variations in term of copper-binding ligands, copper center geometry, redox potential, as well as biological function. AcoP is a periplasmic protein belonging to the iron respiratory chain of the acidophilic bacterium Acidithiobacillus ferrooxidans. AcoP presents original features: highly resistant to acidic pH, it possesses a constrained green-type copper center of high redox potential. To understand the unique properties of AcoP, we undertook structural and biophysical characterization of wild-type AcoP and of two Cu-ligand mutants (H166A and M171A). The crystallographic structure of AcoP at 1.65 Å resolution unveils a typical cupredoxin fold with extended loops, never observed in previously characterized cupredoxins, that might be involved in the interaction of AcoP with its physiological partners. Moreover, the structure shows that the green color of AcoP cannot be attributed to nonclassical copper ligands, its green-colored copper center raising from a long Cu-S (Cys) bond, determined by both X-ray diffraction and EXAFS. The crystal structures of two AcoP mutants confirm that the active center of AcoP is highly constrained. Comparative analysis with other cupredoxins of known structures, suggests that in AcoP the second coordination sphere might be an important determinant of active center rigidity due to the presence of an extensive hydrogen bond network.
Structure of the membrane-bound formate hydrogenlyase complex from Escherichia coli
Authors: Steinhilper Ralf , Höff Gabriele , Heider Johann , Murphy Bonnie J. 
Published: March 2022

AbstractThe prototypical hydrogen-producing enzyme, the membrane-bound formate hydrogen lyase (FHL) complex from Escherichia coli, links formate oxidation at a molybdopterin-containing formate dehydrogenase to proton reduction at a [NiFe] hydrogenase. It is of intense interest due to its ability to efficiently produce H2 during fermentation, its reversibility, allowing H2-dependent CO2 reduction, and its evolutionary link to respiratory complex I. FHL has been studied for over a century, but its atomic structure remains unknown.Here we report cryo-EM structures of FHL in its aerobically- and anaerobically-isolated forms at resolutions reaching 2.6 Å. This includes well-resolved density for conserved loops linking the soluble and membrane arms believed to be essential in coupling enzymatic turnover to ion translocation across the membrane in the complex I superfamily. We describe an unpredicted metal-binding site near the interface of FdhF and HycF subunits that may play a role in preventing reverse activity in vivo, and evaluate possible structural determinants of the bias toward hydrogen production over its oxidation.