bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness and safety of acupuncture for insulin resistance in women with polycystic ovary syndrome: A systematic review and meta-analysis
Authors: Liu Yu , Fan Hua-ying , Hu Jin-qun , Chen Ming , Chen Jiao 
Published: February 2022

AbstractObjectiveTo perform a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate acupuncture’s clinical effect of on insulin resistance (IR) in women with polycystic ovary syndrome (PCOS).MethodsPubMed, Cochrane Library, Embase databases, and Chinese databases, including China National Knowledge Infrastructure (CNKI), Technology Journal Database (VIP), and Wanfang Database, were searched without language restrictions from inception to 20 December 2021. Only RCTs in which acupuncture had been examined as the sole or adjunctive PCOS-IR treatment were included. Additionally, only studies in Chinese databases that had been published in core journals of Peking University were included. Our primary endpoint was homeostasis model assessment of insulin resistance (HOMA-IR). The secondary outcomes were fasting blood glucose (FBG), 2-h postprandial blood glucose (2h-PBG), fasting insulin (FINS), body mass index (BMI), and adverse events. A random-effects model enabled reporting of differences between groups as mean differences, thus minimizing the effects of uncertainty associated with inter-study variability on the effects of different interventions.ResultsOur analysis included seven eligible RCTs (N=728 participants). Compared with other treatments, acupuncture therapy yielded a greater mean reduction in BMI (−1.21; 95% CI, −2.41 to −0.02; P=0.05). No significant differences existed between acupuncture and other studied treatments for changes in HOMA-IR (−0.33; 95% CI, −0.87 to 0.22; P>0.05), FBG (−0.43; 95% CI, −0.88 to 0.03; P=0.07), 2h-PBG (−0.40;95% CI, −0.90 to 0.10; P>0.05), and FINS (−0.65; 95% CI, −2.18 to 0.89; P>0.05). Furthermore, compared with medication alone, a combination of acupuncture and medication yielded a mean reduction in HOMA-IR of −0.63 (95% CI, −1.12 to −0.14; P=0.01) and BMI of −1.36 (95% CI, −2.07 to −0.66; P<0.01).ConclusionAlthough acupuncture is not more effective than metformin, the former could be an adjuvant strategy for improving PCOS-IR. Further large-scale, long-term RCTs with strict methodological standards are justified.
Predictors of mortality, ICU admission and intubation among hospitalized COVD-19 patients in Jordan
Authors: Al Oweidat Khaled , Albtoosh Asma S. , Toubasi Ahmad A. , Ribie Mona Khaled , Hasuneh Manar M. , Alfaqheri Daniah L. , Alshurafa Abdullah H. , Ribie Mohammad , Obeidat Nathir 
Published: February 2022

AbstractIntroductionSeveral studies characterized COVID-19 patients and revealed the factors associated with COVID-19 mortality and severity. However, few studies were conducted in the Middle East, hence we decided to conduct this study to characterize COVID-19 patients, identify the factors associated with COVID-19 mortality and severity and to compare the patients’ outcomes in the two waves of the pandemic.MethodWe conducted a retrospective single center cohort study among COVID-19 patients admitted to our hospital. The primary outcomes were COVID-19 related death, ICU admission and invasive intubation. Whereas, the secondary outcome was the length of hospital stay. In addition, the patients were divided into two cohorts to represent the two waves of the pandemic, to compare between them based on the outcomes.ResultsThe total number of COVID-19 patients included in our study was 745. The overall rates of COVID-19 related mortality, ICU admission and invasive intubation were 23.0%, 28.3% and 10.8%, respectively. CKD, troponin, LDH and O2 saturation <90% were significant predictors for mortality. Moreover, the significant predictors for ICU admission were HF and remdesivir use. Whereas, O2 saturation<90% and GI symptoms were the only significant predictors for invasive intubation. Additionally, the second wave had significantly higher rates of ICU admission compared to the first one.ConclusionOur study showed that several factors predicted COVID-19 mortality, ICU admission and invasive intubation. Additionally, our study revealed that the second wave of the pandemic had significantly higher rates of ICU admission but not mortality or invasive intubation compared to the first wave.
Clinical Time-to-Event Prediction Enhanced by Incorporating Compatible Related Outcomes
Authors: Gao Yan , Cui Yan 
Published: February 2022

AbstractAccurate time-to-event (TTE) prediction of clinical outcomes from personal biomedical data is essential for precision medicine. It has become increasingly common that clinical datasets contain information for multiple related patient outcomes from comorbid diseases or multifaceted endpoints of a single disease. Various TTE models have been developed to handle competing risks that are related to mutually exclusive events. However, clinical outcomes are often non-competing and can occur at the same time or sequentially. Here we develop TTE prediction models with the capacity of incorporating data of compatible related clinical outcomes. We test our method on real and synthetic data and find that the incorporation of related auxiliary clinical outcomes can: 1) significantly improve the TTE prediction performance of convention Cox model while maintaining its interpretability; 2) further improve the performance of the state-of-the-art deep learning based models. While the auxiliary outcomes are utilized for model training, the model deployment is not limited by the availability of the auxiliary outcome data because the auxiliary outcome information is not required for the prediction of the primary outcome once the model is trained.
DeCalciOn: A hardware system for real-time decoding ofin-vivocalcium imaging data
Authors: Chen Zhe , Blair Garrett J. , Guo Changliang , Zhou Jim , Izquierdo Alicia , Golshani Peyman , Cong Jason , Aharoni Daniel , Blair Hugh T. 
Published: February 2022

AbstractEpifluorescence miniature microscopes (“miniscopes”) are widely used forin vivocalcium imaging of neural population activity. Imaging data is usually collected while subjects are engaged in a task and stored for later offline analysis, but emerging techniques for online imaging offer potential for novel real-time experiments in which closed-loop interventions (such as neurostimulation or sensory feedback) are triggered at short latencies in response to neural population activity. Here we introduceDeCalciOn, a plug-and-play hardware device for online population decoding ofin vivocalcium signals that can trigger closed-loop feedback at millisecond latencies, and is compatible with miniscopes that use the UCLA Data Acquisition (DAQ) interface. In performance tests, the position of rats (n=13) on a linear track was decoded in real time from hippocampal CA1 population activity by 24 linear classifiers. DeCalciOn required <2.5 ms after each end-of-frame to decode up to 1,024 calcium traces and trigger TTL control outputs. Decoding was most efficient using a ‘contour-free’ method of extracting traces from ROIs that were unaligned with neurons in the image, but ‘contour-based’ extraction from neuronal ROIs is also supported. DeCalciOn is an easy-to-use system for real-time decoding of calcium fluorescence that enables closed-loop feedback experiments in behaving animals.
Mesenchymal stem cells support human vascular endothelial cells to form vascular sprouts in human platelet lysate-based matrices
Authors: Rossmanith Eva , Summer Sabrina , Pasztorek Markus , Fiedler Constantin , Gröger Marion , Rauscher Sabine , Weber Viktoria , Fischer Michael B. 
Published: February 2022

AbstractDuring tissue regeneration, mesenchymal stem cells can support endothelial cells in the process of new vessel formation. For a functional interaction of endothelial cells with mesenchymal stem cells a vascular inductive microenvironment is required. Using a cellular model for neo-vessel formation, we could show that newly formed vascular structures emanated from the embedded aggregates, consisting of mesenchymal stem cells co-cultured with human umbilical vein endothelial cells, into the avascular HPL-based matrices bridging distances up to 5 mm to join with adjacent aggregates with the same morphology forming an interconnected network. These newly formed vascular sprouts showed branch points and generated a lumen as sign of mature vascular development. Mesenchymal stem cells in fluid phase could bind to and interact with adherent human umbilical vein endothelial cells when a shear-force of 2 dyne/mm2 was applied in the flow chamber using a Bioflux®200 device. Under these conditions, mesenchymal stem cells bind to human umbilical vein endothelial cells previously damaged by laser beam irradiation to interact and shed particles.In conclusion, we observed that mesenchymal stem cells support human umbilical vein endothelial cells to form new vessels in HPL-based matrices when co-cultured in spherical aggregates to generate complex vascular networks in a primarily avascular scaffold and bind to the damaged cells under shear-force to eventually aid in their regeneration.
QSMRim-Net: Imbalance-Aware Learning for Identification of Chronic Active Multiple Sclerosis Lesions on Quantitative Susceptibility Maps
Authors: Zhang Hang , Nguyen Thanh D. , Zhang Jinwei , Marcille Melanie , Spincemaille Pascal , Wang Yi , Gauthier Susan A. , Sweeney Elizabeth M. 
Published: February 2022

AbstractBackground and PurposeChronic active multiple sclerosis (MS) lesions are characterized by a paramagnetic rim at the edge of the lesion and are associated with increased disability in patients. Quantitative susceptibility mapping (QSM) is an MRI technique that is sensitive to chronic active lesions, termed rim+ lesions on the QSM. We present QSMRim-Net, a data imbalance-aware deep neural network that fuses lesion-level radiomic and convolutional image features for automated identification of rim+ lesions on QSM.MethodsQSM and T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI of the brain were collected at 3T for 172 MS patients. Rim+ lesions were manually annotated by two human experts, followed by consensus from a third expert, for a total of 177 rim+ and 3986 rim negative (rim-) lesions. Our automated rim+ detection algorithm, QSMRim-Net, consists of a two-branch feature extraction network and a synthetic minority oversampling network to classify rim+ lesions. The first network branch is for image feature extraction from the QSM and T2-FLAIR, and the second network branch is a fully connected network for QSM lesion-level radiomic feature extraction. The oversampling network is designed to increase classification performance with imbalanced data.ResultsOn a lesion-level, in a five-fold cross validation framework, the proposed QSMRim-Net detected rim+ lesions with a partial area under the receiver operating characteristic curve (pROC AUC) of 0.760, where clinically relevant false positive rates of less than 0.1 were considered. The method attained an area under the precision recall curve (PR AUC) of 0.704. QSMRim-Net out-performed other state-of-the-art methods applied to the QSM on both pROC AUC and PR AUC. On a subject-level, comparing the predicted rim+ lesion count and the human expert annotated count, QSMRim-Net achieved the lowest mean square error of 0.98 and the highest correlation of 0.89 (95% CI: 0.86, 0.92).ConclusionThis study develops a novel automated deep neural network for rim+ MS lesion identification using T2-FLAIR and QSM images.
Psychedelics and schizophrenia: Distinct alterations to Bayesian inference
Authors: Rajpal Hardik , Mediano Pedro A.M. , Rosas Fernando E. , Timmermann Christopher B. , Brugger Stefan , Muthukumaraswamy Suresh , Seth Anil K. , Bor Daniel , Carhart-Harris Robin L. , Jensen Henrik J. 
Published: February 2022

AbstractSchizophrenia and states induced by certain psychotomimetic drugs may share some physiological and phenomenological properties, but they differ in fundamental ways: one is a crippling chronic mental disease, while the others are temporary, pharmacologically-induced states presently being explored as treatments for mental illnesses. Building towards a deeper understanding of these different alterations of normal consciousness, here we compare the changes in neural dynamics induced by LSD and ketamine (in healthy volunteers) against those associated with schizophrenia, as observed in resting-state M/EEG recordings. While both conditions exhibit increased neural signal diversity, our findings reveal that this is accompanied by an increased transfer entropy from the front to the back of the brain in schizophrenia, versus an overall reduction under the two drugs. Furthermore, we show that these effects can be reproduced via different alterations of standard Bayesian inference applied on a computational model based on the predictive processing framework. In particular, the effects observed under the drugs are modelled as a reduction of the precision of the priors, while the effects of schizophrenia correspond to an increased precision of sensory information. These findings shed new light on the similarities and differences between schizophrenia and two psychotomimetic drug states, and have potential implications for the study of consciousness and future mental health treatments.
Stable Potassium Isotopes (41K/39K) Track Transcellular and Paracellular Potassium Transport in Biological Systems
Authors: Higgins John A. , Ramos Danielle Santiago , Gili Stefania , Spetea Cornelia , Kanoski Scott , Ha Darren , McDonough Alicia A. , Youn Jang H. 
Published: February 2022

AbstractAs the most abundant cation in archaeal, bacterial, and eukaryotic cells, potassium (K+) is an essential element for life. While much is known about the machinery of transcellular and paracellular K transport – channels, pumps, co-transporters, and tight-junction proteins - many quantitative aspects of K homeostasis in biological systems remain poorly constrained. Here we present measurements of the stable isotope ratios of potassium (41K/39K) in three biological systems (algae, fish, and mammals). When considered in the context of our current understanding of potential mechanisms of K isotope fractionation and K+transport in these biological systems, our results provide evidence that the fractionation of K isotopes depends on transport pathway and transmembrane transport machinery. Specifically, we find that passive transport of K+down its electrochemical potential through channels and pores in tight-junctions at favors39K, a result which we attribute to a kinetic isotope effect associated with dehydration and/or size selectivity at the channel/pore entrance. In contrast, we find that transport of K+against its electrochemical gradient via pumps and co-transporters is associated with less/no isotopic fractionation, a result that we attribute to small equilibrium isotope effects that are expressed in pumps/co-transporters due to their slower turnover rate and the relatively long residence time of K+in the ion pocket. These results indicate that stable K isotopes may be able to provide quantitative constraints on transporter-specific K+fluxes (e.g. the fraction of K efflux from a tissue by channels vs. co-transporters) and how these fluxes change under different physiological states. In addition, precise determination of K isotope effects associated with K+transport through channels, pumps, and co-transporters may provide unique constraints on the mechanisms of K transport that could be tested with steered molecular dynamic simulations.
Detection and Interspecies Comparison of SARS-CoV-2 Delta Variant (AY.3) in Feces from a Domestic Cat and Human Samples
Authors: Lenz Olivia C. , Marques Andrew D. , Kelly Brendan J. , Rodino Kyle G. , Cole Stephen D. , Perera Ranawaka A.P.M. , Weiss Susan R. , Bushman Frederic D. , Lennon Elizabeth M. 
Published: February 2022

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have spilled over from humans to companion and wild animals since the inception of the global COVID-19 pandemic. However, whole genome sequencing data of the viral genomes that infect non-human animal species has been scant. Here, we detected and sequenced a SARS-CoV-2 delta variant (AY.3) in fecal samples from an 11-year-old domestic house cat previously exposed to an owner who tested positive for SARS-CoV-2. Molecular testing of two fecal samples collected 7 days apart yielded relatively high levels of viral RNA. Sequencing of the feline-derived viral genomes showed the two to be identical, and differing by between 4 and 14 single nucleotide polymorphisms in pairwise comparisons to human-derived lineage AY.3 sequences collected in the same geographic area and time period. However, several mutations unique to the feline samples reveal their divergence from this cohort on phylogenetic analysis. These results demonstrate continued spillover infections of emerging SARS-CoV-2 variants that threaten human and animal health, as well as highlight the importance of collecting fecal samples when testing for SARS-CoV-2 in animals. To the authors’ knowledge, this is the first published case of a SARS-CoV-2 delta variant in a domestic cat in the United States.
Rapid Carbon Dioxide Capture and Short-Term Biocompatible Sequestration in Aquatic Environments by Monoethanolamine Scrubbing within Calcium Alginate Gel
Authors: Ogundare Simon 
Published: February 2022

AbstractAlginate is a biopolymer extracted from the cell walls of algae, and can crosslink with divalent cations to form an insoluble hydrogel. In this paper, we develop a method to immobilize monoethanolamine, an amine CO2 scrubber, within calcium alginate gel. By mixing monoethanolamine into an alginate solution as the gel was formed, we suspended the compound in the gel, facilitating a means to capture carbon dioxide directly from aquatic environments into the gel, while tethering monoethanolamine and the products formed from CO2 capture to the gel. To delay the eventual diffusion of monoethanolamine out of the gel, we investigated (1) the effect of increasing alginate concentration and (2) the effect of additional alginate layers on the outward diffusion of dye placed in the center of the bead. Using ultraviolet-visible spectroscopy to quantify diffusion rates over time, we determined that increased alginate concentration paired with increased layering significantly decreased the rate of outward diffusion. Finally, we prepared beads using North Atlantic seawater as a solvent and compared the rate of dye leakage in seawater and distilled water to that in beads prepared in distilled water. Expectedly, we concluded that beads prepared with solvents isotonic to their environments would exhibit less leakage as well as greater mechanical stability, resisting swelling, bursting, or splitting behaviors.
The Human “Contaminome”: Bacterial, Viral, and Computational Contamination in Whole Genome Sequences from 1,000 Families
Authors: Chrisman Brianna , He Chloe , Jung Jae-Yoon , Stockham Nate , Paskov Kelley , Washington Peter , Wall Dennis P. 
Published: February 2022

AbstractBackgroundThe unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1,000 families and 5,000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies.ResultsWe present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes.ConclusionBoth experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.genomics WGS contamination
Transmission Dynamics of Human Herpesviruses and Other Blood DNA Viruses from Whole Genome Sequences of Families
Authors: Chrisman Brianna , He Chloe , Jung Jae-Yoon , Stockham Nate , Paskov Kelley , Washington Peter , Wall Dennis P. 
Published: February 2022

1AbstractWhile hundreds of thousands of human whole genome sequences (WGS) have been collected in the effort to better understand genetic determinants of disease, these whole genome sequences have rarely been used to study another major determinant of human health: the human virome. Using the unmapped reads from WGS of 1,000 families, we present insights into the human blood DNA virome. In addition to extensively cataloguing the viruses detected in WGS of human whole blood and lymphoblastoid cell lines, we use the family structure of our dataset to show that household drives transmission of many microbes. We also identify several cases of inherited chromosomally integrated herpes 6A and 6B and locate candidate integration sequences for these cases. We document genetic diversity within exogenous and integrated HHV species and within integration sites of HHV-6. Finally, in the first observation of its kind, we present evidence that suggests widespreadde novoHHV-6B integration and HHV-7 episome replication in lymphoblastoid cell lines. These findings show that the unmapped read space of WGS may be a promising avenue for virology research.
NetMix2: Unifying network propagation and altered subnetworks
Authors: Chitra Uthsav , Park Tae Yoon , Raphael Benjamin J. 
Published: February 2022

AbstractA standard paradigm in computational biology is to use interaction networks to analyze high-throughput biological data. Two common approaches for leveraging interaction networks are: (1)network ranking, where one ranks vertices in the network according to both vertex scores and network topology; (2)altered subnetworkidentification, where one identifies one or more subnetworks in an interaction network using both vertex scores and network topology. The dominant approach in network ranking is network propagation which smooths vertex scores over the network using a random walk or diffusion process, thus utilizing the global structure of the network. For altered subnetwork identification, existing algorithms either restrict solutions to subnetworks insubnetwork familieswith simple topological constraints, such as connected subnetworks, or utilize ad hoc heuristics that lack a rigorous statistical foundation. In this work, we unify the network propagation and altered subnetwork approaches. We derive a subnetwork family which we call thepropagation familythat approximates the subnetworks ranked highly by network propagation. We introduce NetMix2, a principled algorithm for identifying altered subnetworks from a wide range of subnetwork families, including the propagation family, thus combining the advantages of the network propagation and altered subnetwork approaches. We show that NetMix2 outperforms network propagation on data simulated using the propagation family. Furthermore, NetMix2 outperforms other methods at recovering known disease genes in pan-cancer somatic mutation data and in genome-wide association data from multiple human diseases. NetMix2 is publicly available athttps://github.com/raphael-group/netmix2.